diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000000000000000000000000000000000000..9cce129b687eb307316b4698380312435f4be2a0 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,3 @@ +*venv* +log +log_run \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..729db549683d8cc421a7344c36497b1e42faaded --- /dev/null +++ b/.gitignore @@ -0,0 +1,21 @@ +venv/ +data/ +vncore/ +global/ +cls/ +check.json +test3.py +test2.py +time_test.py +vncorenlp +*venv* +__pycache__/ +req_daily +log* +sample +model +*.json +*test* +docker_venv +core +models \ No newline at end of file diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..299934461ecffe9571a086db2d77251ad43c1316 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,46 @@ +FROM python:3.7 + +WORKDIR /app + + +RUN apt-get update && apt-get install build-essential cmake git -y + +#----------------JRE (for vncorenlp)-------------- +RUN apt-get update && \ + DEBIAN_FRONTEND=noninteractive \ + apt-get -y install default-jre-headless && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +RUN apt-get install unzip +RUN pip install gdown +RUN gdown --id 1MTAPYy9AcYtfiJ6m_pz6MPeA6li8pYp7 +RUN unzip vncorenlp.zip -d /app/ + + +# COPY ./model /app/model + +RUN mkdir -p /app/model +RUN mkdir -p /app/log +RUN mkdir -p /app/log_run + +COPY reqs_cpu.txt /app/ +RUN pip install -r reqs_cpu.txt + +COPY ./load_model.py /app/ +RUN python load_model.py + +COPY ./config /app/config +COPY ./entity /app/entity +COPY ./function /app/function +COPY ./main_cache.py /app/ +COPY ./service_cache.py /app/ +COPY ./summary.py /app/ +COPY ./merge_topic.py /app/ +COPY ./consumer_clustering.py /app/ +COPY ./consumer_merge_clustering.py /app/ +COPY ./run_multi_process.py /app/ + +RUN rm -r ~/.cache/pip/* + +CMD ["python", "run_multi_process.py"] diff --git a/Dockerfile_gpu b/Dockerfile_gpu new file mode 100644 index 0000000000000000000000000000000000000000..58f2f4967907fae08cf182ee73dcfd3311c02b14 --- /dev/null +++ b/Dockerfile_gpu @@ -0,0 +1,33 @@ +FROM python:3.7 + +WORKDIR /app + + +RUN apt-get update && apt-get install build-essential cmake git -y + +#----------------JRE (for vncorenlp)-------------- +RUN apt-get update && \ + DEBIAN_FRONTEND=noninteractive \ + apt-get -y install default-jre-headless && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +COPY ./model /app/model + +RUN pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html +RUN mkdir log +RUN mkdir log_run + +COPY req.txt /app/ +RUN pip install -r req.txt + +COPY ./entity /app/entity +COPY ./function /app/function +COPY ./vncorenlp /app/vncorenlp +COPY ./main_cache.py /app/ +COPY ./service_cache.py /app/ +COPY ./summary.py /app/ + +RUN rm -r ~/.cache/pip/* + +CMD ["python", "main_cache.py"] diff --git a/Dockerfile_gpu_Thien b/Dockerfile_gpu_Thien new file mode 100644 index 0000000000000000000000000000000000000000..3512f94c92a3bc01a576d798c4dc81ea6bc6fe1d --- /dev/null +++ b/Dockerfile_gpu_Thien @@ -0,0 +1,34 @@ +FROM python:3.7.17-slim-bullseye + +WORKDIR /app + + +RUN apt-get update && apt-get install build-essential cmake git -y + +#----------------JRE (for vncorenlp)-------------- +RUN apt-get update && \ + DEBIAN_FRONTEND=noninteractive \ + apt-get -y install default-jre-headless && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +COPY ./model /app/model +COPY ./tensorRT /app/tensorRT + +RUN pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html +RUN mkdir log +RUN mkdir log_run + +COPY req.txt /app/ +RUN pip install -r req.txt + +COPY ./entity /app/entity +COPY ./function /app/function +COPY ./vncorenlp /app/vncorenlp +COPY ./main_cache_Thien.py /app/ +COPY ./service_cache_Thien.py /app/ +COPY ./summary.py /app/ + +RUN rm -r ~/.cache/pip/* + +CMD ["python", "main_cache_Thien.py"] diff --git a/Jenkinsfile b/Jenkinsfile new file mode 100644 index 0000000000000000000000000000000000000000..497b7ab3eab817f514c97c1d4fc2465702e71349 --- /dev/null +++ b/Jenkinsfile @@ -0,0 +1,22 @@ +node { + checkout scm + + env.DOCKER_API_VERSION="1.23" + registry_host = env.registry_host + appName = "clusteringcpu" + + sh "git rev-parse --short HEAD > commit-id" + tag = readFile('commit-id').replace("\n", "").replace("\r", "") + + stage("build"){ + sh "docker build --tag ${registry_host}/${appName}:${tag} --file Dockerfile ." + } + stage("push"){ + sh "docker push ${registry_host}/${appName}:${tag}" + } + stage("deploy"){ + sh "sed -i s/{{tag}}/${tag}/g deployment.yaml \ + && sed -i 's|{{registry_host}}|${registry_host}|g' deployment.yaml \ + && kubectl ${env.token_kube} apply -f deployment.yaml" + } +} \ No newline at end of file diff --git a/README.md b/README.md index 3c136beb708a14b15e8eee5da9d5b1089f3130c5..36ab5af2beb268c6ad41a2c670f1b75bdf3120fa 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,55 @@ ---- -title: Topic Clustering Global Dashboard -emoji: 🏆 -colorFrom: gray -colorTo: red -sdk: gradio -sdk_version: 4.43.0 -app_file: app.py -pinned: false ---- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference +--- +title: topic-clustering-global-dashboard +app_file: service_periodic.py +sdk: gradio +sdk_version: 4.43.0 +--- +## Build docker +``` +docker build -t clustering-dashboard . +docker run -d --restart=always --name clustering-dashboard clustering-dashboard +``` + +## Deploy TRT +``` +scp -r docker/api_trt/Dockerfile ./ +docker build -t api-clustering . +docker run --gpus 1 --dns 8.8.8.8 -it -p 8633:8633 -v /home/dp04/topic-clustering-global-dashboard:/app -t --name api-clustering api-clustering +``` + +### Topic Clustering +1. API clustering port 8633: dùng cho phân cụm NEWS trong các loại báo cáo ( báo cáo nhanh, báo cáo tổng quan, báo cáo template,...) +- Command: + ``` + docker run --gpus all -it --rm -v /home/vietle/topic-clustering:/home/vietle/topic-clustering --name topic_clustering_trt_sb -p 8636:8633 topic-clustering-trt + cd /home/vietle/topic-clustering && CUDA_VISIBLE_DEVICES= python main_cache.py + ``` +- screen: 52097.clustering.trt +2. API clustering social: Phân cụm tin tức social +- Command: cd /home/vietle/topic-clustering/ && source docker_venv/bin/activate && uvicorn service_social:app --host 0.0.0.0 --port 8635 +- Screen: 37529.clustering.social +3. Phân cụm cho global dashboard: +- API: + ``` + CMD: systemctl status bzo_clustering_api_cpu.service (port 8634) + Screen: 21445.clustering.cpu + ``` +- Consumer: + + Phân cụm daily: + ``` + Command: cd /home/vietle/topic-clustering/ && source docker_venv/bin/activate && OMP_NUM_THREADS=16 CUDA_VISIBLE_DEVICES=-1 python consumer_clustering.py + Screen: 16024.bzo.clustering_daily + ``` + + Phân cụm weekly/monthly: + ``` + Command: cd /home/vietle/topic-clustering/ && source docker_venv/bin/activate && OMP_NUM_THREADS=16 CUDA_VISIBLE_DEVICES='-1' python consumer_merge_clustering.py + Screen: 60767.bzo.clustering_monthly + ``` + +4. Phân cụm điểm tin: +- Command: + ``` + docker run --gpus all -it --rm -v /home/vietle/topic-clustering:/home/vietle/topic-clustering --name topic_clustering_trt_sb -p 8636:8633 topic-clustering-trt + cd /home/vietle/topic-clustering/ && python main_cache_Thien.py + ``` + \ No newline at end of file diff --git a/config/__init__.py b/config/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..18acaa1f7e4d9cb3c511038e2d057eda65f869e1 --- /dev/null +++ b/config/__init__.py @@ -0,0 +1 @@ +from .config import get_config, parse_connection_string \ No newline at end of file diff --git a/config/cfg.yaml b/config/cfg.yaml new file mode 100644 index 0000000000000000000000000000000000000000..069c09a9e0bb840dd7b349a387c1ad82498b6696 --- /dev/null +++ b/config/cfg.yaml @@ -0,0 +1,173 @@ +AppSettings: +ConnectionStrings: + facebook_info: Server=10.9.3.141,1433; Database=facebook_info; User Id='facebook_info_read'; Password='dh2uxJny'; Pooling=True; Connect Timeout=45; MultipleActiveResultSets=True; Encrypt=False +GraylogConfig: +ConfigManager: + ChannelConfigs: + MemcachedConfigs: + QueueConfigs: + queue_topic_clustering: + Arguments: {} + AutoAck: false + AutoDelete: false + AutomaticRecoveryEnabled: true + ConsumerMaxRetry: 0 + Durable: true + ErrorCounter: 100 + ErrorCounterTotalSeconds: 60 + Exchange: '' + ExchangeArguments: + ExchangeAutoDelete: false + ExchangeDurable: true + ExchangeType: + Exclusive: false + FailedQueue: + HostName: 10.9.3.251 + HostNames: + - 10.9.3.251 + Servers: + - Host: 10.9.3.251 + Port: 15672 + Key: queue1 + MaxWorkpool: 1 + NetworkRecoveryInterval: 120 + Password: 1 + PrefetchCount: 200 + Queue: topic-clustering + QueueBindArguments: + QueueBindRoutingKey: + RequestedHeartbeat: 120 + TopologyRecoveryEnabled: false + UserName: long.nguyen + VirtualHost: posts-broadcast + MessageDeliveryMode: + IsProducer: true + IsConsumer: true + queue_merge_clustering: + Arguments: {} + AutoAck: false + AutoDelete: false + AutomaticRecoveryEnabled: true + ConsumerMaxRetry: 0 + Durable: true + ErrorCounter: 100 + ErrorCounterTotalSeconds: 60 + Exchange: '' + ExchangeArguments: + ExchangeAutoDelete: false + ExchangeDurable: true + ExchangeType: + Exclusive: false + FailedQueue: + HostName: 10.9.3.251 + HostNames: + - 10.9.3.251 + Servers: + - Host: 10.9.3.251 + Port: 15672 + Key: queue2 + MaxWorkpool: 1 + NetworkRecoveryInterval: 120 + Password: 1 + PrefetchCount: 200 + Queue: merge-clustering + QueueBindArguments: + QueueBindRoutingKey: + RequestedHeartbeat: 120 + TopologyRecoveryEnabled: false + UserName: long.nguyen + VirtualHost: posts-broadcast + MessageDeliveryMode: + IsProducer: true + IsConsumer: true + queue_topic_clustering_mnews: + Arguments: {} + AutoAck: false + AutoDelete: false + AutomaticRecoveryEnabled: true + ConsumerMaxRetry: 0 + Durable: true + ErrorCounter: 100 + ErrorCounterTotalSeconds: 60 + Exchange: '' + ExchangeArguments: + ExchangeAutoDelete: false + ExchangeDurable: true + ExchangeType: + Exclusive: false + FailedQueue: + HostName: 10.9.3.251 + HostNames: + - 10.9.3.251 + Servers: + - Host: 10.9.3.251 + Port: 15672 + Key: queue1 + MaxWorkpool: 1 + NetworkRecoveryInterval: 120 + Password: 1 + PrefetchCount: 200 + Queue: topic-clustering-mnews + QueueBindArguments: + QueueBindRoutingKey: + RequestedHeartbeat: 120 + TopologyRecoveryEnabled: false + UserName: long.nguyen + VirtualHost: posts-broadcast + MessageDeliveryMode: + IsProducer: true + IsConsumer: true + queue_merge_clustering_newscms: + Arguments: {} + AutoAck: false + AutoDelete: false + AutomaticRecoveryEnabled: true + ConsumerMaxRetry: 0 + Durable: true + ErrorCounter: 100 + ErrorCounterTotalSeconds: 60 + Exchange: '' + ExchangeArguments: + ExchangeAutoDelete: false + ExchangeDurable: true + ExchangeType: fanout + Exclusive: false + FailedQueue: + HostName: 10.9.3.251 + HostNames: + - 10.9.3.251 + Servers: + - Host: 10.9.3.251 + Port: 5672 + Key: queue_merge_clustering_newscms + MaxWorkpool: 1 + NetworkRecoveryInterval: 120 + Password: 1 + PrefetchCount: 200 + Queue: newscms-merge-clustering + QueueBindArguments: + QueueBindRoutingKey: + RequestedHeartbeat: 120 + TopologyRecoveryEnabled: false + UserName: long.nguyen + VirtualHost: news-cms + MessageDeliveryMode: + IsProducer: true + IsConsumer: true + AppSettings: + ApiConnects: + api_save_clustering: + BaseUrl: https://staging.pontusinc.com/api/category_management/v1/topic-clustering-dashboard/insert + IsMonitor: true + MonitorUrl: https://staging.pontusinc.com/api/category_management/v1/topic-clustering-dashboard/insert + api_sbert: + BaseUrl: http://10.9.3.240:6789/sbert/encode_list + IsMonitor: true + MonitorUrl: http://10.9.3.240:6789/sbert/encode_list + + api_save_cluster_newscms: + BaseUrl: https://staging.pontusinc.com/api/news_cms/News/update_cluster_result + IsMonitor: true + MonitorUrl: https://staging.pontusinc.com/api/news_cms/News/update_cluster_result + GraylogConfig: +key_test: test \ No newline at end of file diff --git a/config/config.py b/config/config.py new file mode 100644 index 0000000000000000000000000000000000000000..8197d41a4104381ee3fd1f657c5a141ba01b2dd9 --- /dev/null +++ b/config/config.py @@ -0,0 +1,57 @@ +import requests +import json +import os +from yaml import load +try: + from yaml import CLoader as Loader, CDumper as Dumper +except ImportError: + from yaml import Loader, Dumper + + +URL_CFG = "http://icomm-api-configserver/api/configserver/v1/configuration.yaml" +# http://10.9.2.151:31244/api/configserver/v1/configuration.yaml +# cấu hình file hosts ở thư mục C:\Windows\System32\drivers\etc như sau: +# 123.31.42.17 icomm-api-configserver + +AccessToken = "wbecrEfJk8F36y0WojqBQaqT28d6NaBnCLBgkoO2sCg3aNhYACkSxMNvWwlsAj5k" +Environment = "Production" +path_save_cfg = "config/cfg.yaml" + + +def get_config(): + cfg = None + try: + payload = json.dumps({ + "AccessToken": AccessToken, + "Environment": Environment + }) + headers = { + 'accept': 'text/plain', + 'Content-Type': 'application/json-patch+json' + } + + response = requests.request("POST", URL_CFG, headers=headers, data=payload) + # if response.status_code == 200: + # with open(path_save_cfg, "w+") as f: + # f.write(response.text) + except Exception as ve: + print(ve) + if os.path.exists(path_save_cfg): + with open(path_save_cfg) as f: + cfg = load(f, Loader) + return cfg + + +def parse_connection_string(str_cnn): + res = dict() + split_dt = str_cnn.split(";") + for c_sp in split_dt: + k, v = c_sp.split("=") + res[k.strip()] = v.replace("'", "").replace('"', '') + return res + + +if __name__ == '__main__': + cf = get_config() + print(cf) + print(parse_connection_string(cf["ConfigManager"]["ConnectionStrings"]["facebook_info"]["Value"])) \ No newline at end of file diff --git a/config/config.yml b/config/config.yml new file mode 100644 index 0000000000000000000000000000000000000000..587ed162d97f9f6c1a7da106f0623bc8fcfb746c --- /dev/null +++ b/config/config.yml @@ -0,0 +1,38 @@ +queue_topic_clustering: + host: + 10.9.3.251 + virtual_host: + posts-broadcast + queue_name: + topic-clustering + usr_name: + long.nguyen + password: + 1 + +queue_topic_clustering_mnews: + host: + 10.9.3.251 + virtual_host: + posts-broadcast + queue_name: + topic-clustering-mnews + usr_name: + long.nguyen + password: + 1 + +queue_merge_clustering: + host: + 10.9.3.251 + virtual_host: + posts-broadcast + queue_name: + merge-clustering + usr_name: + long.nguyen + password: + 1 + +api_save_clustering: + https://staging.pontusinc.com/api/category_management/v1/topic-clustering-dashboard/insert \ No newline at end of file diff --git a/consumer_clustering.py b/consumer_clustering.py new file mode 100644 index 0000000000000000000000000000000000000000..bca2ef8b9fc84db68067ae2137e3e149bf2b555e --- /dev/null +++ b/consumer_clustering.py @@ -0,0 +1,181 @@ +import pika +import os +# os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +import json +import time +# from get_config import config_params +from config import get_config +from function import topic_clustering_not_summary as tc +from function import topic_clustering_social +import requests + +config_params = get_config() +ConfigManager = config_params['ConfigManager'] + +last_time_check = time.time() +def update_result(result, type='daily', meta = {}): + benchmark_children_id = -1 + benchmark_id = -1 + source_tagids = [] + for id_cluster in result: + for doc in result[id_cluster][:1]: + source_tagids = doc.get('source_tagids',[]) + for key in doc: + if "benchmark_child" in key: + benchmark_children_id = int(key.lstrip('benchmark_child_')) + if "benchmark" in key and 'child' not in key: + benchmark_id = int(key.lstrip('benchmark_')) + break + + if not source_tagids: + source_tagids = [] + + if len(source_tagids) > 0: + benchmark_id = 0 + benchmark_children_id = 0 + + output = { + "benchmark_id": benchmark_id, + "benchmark_children_id": benchmark_children_id, + "source_tagids": source_tagids, + "country_code": meta.get('country_code',''), + "type": type, + "data": json.dumps(result) + } + # with open('test_result.json','w') as f: + # json.dump(output, f, ensure_ascii=False) + + # url = config_params['api_save_clustering'] + url = ConfigManager['ApiConnects']['api_save_clustering']['BaseUrl'] + # with open("/home/vietle/topic-clustering/config/save.json", 'w') as f: + # json.dump(output, f,ensure_ascii=False) + res = requests.post(url, json = output) + print(res.text) + print('Update result !!!!!!!!!') + +def callback_func(ch, method, properties, body): + print("receive done: ") + + + + starttime = time.time() + body = json.loads(body.decode("utf-8")) + + # with open('input_daily.json','w') as f: + # json.dump(body, f, ensure_ascii=False) + + docs = body['docs'] + # threshold = body['threshold'] + threshold = 0.25 + top_cluster = body['top_cluster'] + top_sentence = body['top_sentence'] + topn_summary = body['topn_summary'] + hash_str = body['hash_str'] + st_time = body['st_time'] + meta = body.get('meta',{}) + country_code = meta.get("country_code", "") + delete_message = False if country_code in ["ICOMM-RND","SOCIAL"] else True + + print("country_code: ", country_code, "meta: ", meta) + + is_cache = False + try: + with open("log_run/log.txt") as f: + data_dict = json.load(f) + except Exception as ve: + print(ve) + data_dict = {} + + try: + if hash_str in data_dict: + path_res = data_dict[hash_str]["response_path"] + with open(path_res) as ff: + results = json.load(ff) + print("time analysis (cache): ", time.time() - st_time) + update_result(results,meta=meta) + is_cache = True + except Exception as vee: + print(vee) + + if not is_cache: + if country_code in ["SOCIAL"]: + results = topic_clustering_social.topic_clustering(docs, threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, delete_message=delete_message) + else: + results = tc.topic_clustering(docs, threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, delete_message=delete_message) + update_result(results, meta=meta) + + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, "w+") as ff: + ff.write(json.dumps(results)) + + data_dict[hash_str] = {"time": st_time, "response_path": path_res} + + lst_rm = [] + global last_time_check + if time.time() - last_time_check > 3600: + print("check log to del .....") + last_time_check = time.time() + for dt in data_dict: + if time.time() - data_dict[dt]["time"] > 30 * 24 * 3600: + lst_rm.append(dt) + for dt in lst_rm: + del data_dict[dt] + with open("log_run/log.txt", "w+") as ff: + ff.write(json.dumps(data_dict)) + print("time analysis: ", time.time() - starttime) + ch.basic_ack(delivery_tag=method.delivery_tag) + + +def test(): + with open('req_daily/aus.json') as f: + body = json.load(f) + + docs = body['response']['docs'] + # threshold = body['threshold'] + threshold = 0.25 + top_cluster = body['top_cluster'] + top_sentence = body['top_sentence'] + topn_summary = body['topn_summary'] + # hash_str = body['hash_str'] + # st_time = body['st_time'] + meta = body['response'].get('meta',{}) + results = tc.topic_clustering(docs, threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, delete_message=True) + print(results) + # update_result(results, meta=meta) + # print(123) +if __name__ == '__main__': + # test() + params = ConfigManager['QueueConfigs']['queue_topic_clustering'] + usr_name = params["UserName"] + password = str(params["Password"]) + host = params["HostName"] + virtual_host = params["VirtualHost"] + queue_name = params["Queue"] + + + + # params = config_params['queue_topic_clustering'] + # usr_name = params["usr_name"] + # password = str(params["password"]) + # host = params["host"] + # virtual_host = params["virtual_host"] + # queue_name = params["queue_name"] + + while True: + try: + credentials = pika.PlainCredentials(usr_name, password) + connection = pika.BlockingConnection( + pika.ConnectionParameters(host=host, virtual_host=virtual_host, credentials=credentials, heartbeat=3600, blocked_connection_timeout=3600)) + channel = connection.channel() + channel.queue_declare(queue=queue_name, durable=True, arguments={"x-max-priority": 10}) + print(" * wait message") + channel.basic_qos(prefetch_count=1) + channel.basic_consume(queue=queue_name, on_message_callback=callback_func) + channel.start_consuming() + except Exception as ex: + print(f'[ERROR] ', ex) + # raise ex diff --git a/consumer_clustering_mnews.py b/consumer_clustering_mnews.py new file mode 100644 index 0000000000000000000000000000000000000000..47b17753bfe974cbaf420e37627b463faafb3379 --- /dev/null +++ b/consumer_clustering_mnews.py @@ -0,0 +1,137 @@ +import pika +import os +# os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +import json +import time +# from get_config import config_params +from config import get_config +from function import topic_clustering_mnews as tc +import requests + +config_params = get_config() +ConfigManager = config_params['ConfigManager'] + +last_time_check = time.time() +def update_result(result, type='daily', meta = {}): + command_id = meta["command_id"] + + output = { + "id": command_id, + "status": 2, + "json_result": json.dumps(result) + } + + url = "https://staging.pontusinc.com/api/news_management/v1/quick_search/update-command-result" + # with open("/home/vietle/topic-clustering/config/save_.json", 'w') as f: + # json.dump(output, f,ensure_ascii=False) + res = requests.post(url, json = output) + print(res.text) + print('Update result !!!!!!!!!') + +def callback_func(ch, method, properties, body): + print("receive done: ") + starttime = time.time() + body = json.loads(body.decode("utf-8")) + + # with open('input_daily.json','w') as f: + # json.dump(body, f, ensure_ascii=False) + + docs = body['docs'] + # threshold = body['threshold'] + command_id = body.get("command_id",0) + print(command_id) + threshold = 0.1 + top_cluster = body['top_cluster'] + top_sentence = body['top_sentence'] + topn_summary = body['topn_summary'] + hash_str = body['hash_str'] + st_time = body['st_time'] + meta = body.get('meta',{}) + meta["command_id"] = command_id + + is_cache = False + try: + with open("log_mnews/log/log.txt") as f: + data_dict = json.load(f) + except Exception as ve: + print(ve) + data_dict = {} + + try: + if hash_str in data_dict: + path_res = data_dict[hash_str]["response_path"] + with open(path_res) as ff: + results = json.load(ff) + print("time analysis (cache): ", time.time() - st_time) + update_result(results,meta=meta) + is_cache = True + except Exception as vee: + print(vee) + + if not is_cache: + results = tc.topic_clustering(docs, threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary) + update_result(results, meta=meta) + + path_res = "log_mnews/result_{0}.txt".format(hash_str) + with open(path_res, "w+") as ff: + ff.write(json.dumps(results)) + + data_dict[hash_str] = {"time": st_time, "response_path": path_res} + + lst_rm = [] + global last_time_check + if time.time() - last_time_check > 3600: + print("check log to del .....") + last_time_check = time.time() + for dt in data_dict: + if time.time() - data_dict[dt]["time"] > 30 * 24 * 3600: + lst_rm.append(dt) + for dt in lst_rm: + del data_dict[dt] + with open("log_mnews/log/log.txt", "w+") as ff: + ff.write(json.dumps(data_dict)) + print("time analysis: ", time.time() - starttime) + ch.basic_ack(delivery_tag=method.delivery_tag) + + +def test(): + with open('req_daily/aus.json') as f: + body = json.load(f) + + docs = body['response']['docs'] + # threshold = body['threshold'] + threshold = 0.25 + top_cluster = body['top_cluster'] + top_sentence = body['top_sentence'] + topn_summary = body['topn_summary'] + # hash_str = body['hash_str'] + # st_time = body['st_time'] + meta = body['response'].get('meta',{}) + results = tc.topic_clustering(docs, threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary) + update_result(results, meta=meta) + print(123) +if __name__ == '__main__': + params = ConfigManager['QueueConfigs']['queue_topic_clustering_mnews'] + usr_name = params["UserName"] + password = str(params["Password"]) + host = params["HostName"] + virtual_host = params["VirtualHost"] + queue_name = params["Queue"] + + while True: + try: + credentials = pika.PlainCredentials(usr_name, password) + connection = pika.BlockingConnection( + pika.ConnectionParameters(host=host, virtual_host=virtual_host, credentials=credentials, heartbeat=3600, blocked_connection_timeout=3600)) + channel = connection.channel() + channel.queue_declare(queue=queue_name, durable=True, arguments={"x-max-priority": 10}) + print(" * wait message") + channel.basic_qos(prefetch_count=1) + channel.basic_consume(queue=queue_name, on_message_callback=callback_func) + channel.start_consuming() + except Exception as ex: + print(f'[ERROR] ', ex) + # raise ex diff --git a/consumer_hot_topic_ondemand.py b/consumer_hot_topic_ondemand.py new file mode 100644 index 0000000000000000000000000000000000000000..b805d504ef2248acb2f7cd92879b13021e3c9c90 --- /dev/null +++ b/consumer_hot_topic_ondemand.py @@ -0,0 +1,209 @@ +from fastapi import FastAPI +from fastapi.middleware.cors import CORSMiddleware +from entity import InputHotTopic, ResponseQueue +from threading import Thread +from queue import Queue +import time +import json, requests +from service_cache_Thien import get_data_sorl +import os +from datetime import datetime +from email_validator import push_msg_tele + +import time +import json +import hashlib + + +from pydantic import BaseModel + +class InputHotTopic(BaseModel): + start_time: str = "2024-09-03 23:00:00" + end_time: str = "2024-09-05 23:00:00" + query: str = "Giá nhà chung cư trên Hà Nội" + keywords: list = ["chung cư, Hà Nội", "Hoà Lạc"] + top_cluster: int = 5 + prompt: str = """Trong 300 từ, hãy tổng hợp thành một đoạn văn một cách đầy đủ, chi tiết, và trung thực về các chủ đề xung quanh biến động giá nhà chung cư Hà Nội từ nội dung dưới đây. +Nếu không có thông tin gì liên quan đến giá nhà chung cư Hà Nội trong nội dung cung cấp thì trả lời "không có thông tin". Không đưa quan điểm cá nhân, không lặp lại một phần câu hỏi, loại bỏ phần mở đầu. Không có những câu từ liên kết như: "Sau đây là nội dung tóm tắt", "Nội dung tóm tắt là", "Dưới đây là " ... """ + check_relevent: str = "Hãy đánh giá nội dung dưới đây có thông tin liên quan đến giá cả nhà chung cư Hà Nội hay không? Chỉ trả lời có hoặc không, không đưa thêm thông tin không liên quan" + max_posts: int = 5000 + +def get_hash_id(item: InputHotTopic): + str_hash = "" + if item.id_topic: + str_hash += item.id_topic + str_hash += item.start_time + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + else: + return "" + +class SessionProcess(object): + + def __init__(self): + self.session = dict() + + def hash_session(self, query: InputHotTopic): + hash_dict = query.dict() + hash_dict['time'] = int(time.time()) + return hashlib.sha224(json.dumps(hash_dict).encode("utf-8")).hexdigest() + + def insert_session(self, data_input): + print('data_input: ', data_input) + # if self.mode == "command_center": + # hash_id = hash_session(data_input) + # else: + hash_id = self.hash_session(data_input) + if hash_id not in self.session: + self.session[hash_id] = {"status": 0, "created_time": time.time(), "update_time": time.time(), + "result": {}, "data": data_input} + return hash_id + + def get_info_session(self, hash_id: str): + if hash_id in self.session: + return self.session[hash_id] + return {"status": -2, "result": {}, "meta": {}} + + def update_session(self, hash_id: str, result: dict, status: int): + if hash_id in self.session: + self.session[hash_id]["status"] = status + self.session[hash_id]["result"] = result + self.session[hash_id]["update_time"] = time.time() + return True + return False + + def delete_session(self, hash_id: str): + if hash_id in self.session: + del self.session[hash_id] + return True + return False + +SESSION = SessionProcess() +app = FastAPI(title="Hot Topic") +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +NUM_OF_THREAD = 2 +QQ = Queue(maxsize=0) # don't limit queue + +def process_wc(): + print('Run thr') + global SESSION, QQ + while True: + if not QQ.empty(): + hash_id = QQ.get() + SESSION.update_session(hash_id, {}, 0) + print("update trạng thái status = 0: đang xử lý") + try: + ss_info = SESSION.get_info_session(hash_id) + status = ss_info["status"] + print("trạng thái hiện tại: ", status) + if status == 0: + data_input = SESSION.session[hash_id]["data"] + res_doc = get_data_sorl(data_input.query, data_input.keywords, data_input.start_time, data_input.end_time, max_posts = data_input.max_posts) + print('lenght res_doc: ', len(res_doc)) + if not res_doc: + SESSION.update_session(hash_id, {}, -1) + else: + # start_time: str = "2024-03-03 23:00:00" + current_time = datetime.now() + time_now = current_time.strftime("%Y-%m-%d %H:%M:%S") + d = { + "id_topic": "99999", + "start_time": time_now, + "end_time": data_input.end_time, + "threshold": 0.3, + "top_sentence": -1, + "top_cluster": data_input.top_cluster, + "topn_summary": 10, + "type_cluster": "", + "lang_process": "", + "prompt": data_input.prompt, + "topic_name": data_input.check_relevent, + "responseHeader": {}, + "benchmark_topics": [], + "response": {"docs": res_doc} + } + + str_hash = "" + str_hash += "99999" + str_hash += time_now + hash_id_path = hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + + st_time = time.time() + try: + response = requests.post('http://10.9.3.241:8636/newsanalysis/topic_clustering', json=d, timeout=5) + except: + print("Timeout done") + + print("push done msg") + res_clus = {} + # flag = False + # count = 0 + # while not flag and count < 18000: + # if os.path.exists("/home/vietle/topic-clustering/log/result_{0}.txt".format(hash_id_path)): + # path_res = "/home/vietle/topic-clustering/log/result_{0}.txt".format(hash_id_path) + # with open(path_res, encoding="utf-8") as ff: + # res_clus = json.load(ff) + # res_clus["num_articles"] = len(res_doc) + # message = "Hello" + # push_msg_tele(data_input.bot_token , data_input.chat_id , message) + # print('done processing result') + # flag = True + # time.sleep(1) + # count +=1 + # print('sleep: ', count) + + + print("update done msg") + SESSION.update_session(hash_id_path, res_clus, 1) + except Exception as ve_: + print(ve_) + SESSION.update_session(hash_id_path, {}, -1) + raise ve_ + else: + time.sleep(2) + + +for _ in range(NUM_OF_THREAD): + worker = Thread(target=process_wc, args=()) + worker.setDaemon(True) + worker.start() + + +@app.post("/api/v1/send_message") +def send_requests(item: InputHotTopic): + global SESSION + hash_id = SESSION.insert_session(item) + if SESSION.session[hash_id]["status"] == 0: + QQ.put(hash_id) + + return ResponseQueue(statusCode=1, message="Push to queue done !", result={"hash_id": hash_id}) + +class InputSession(BaseModel): + hash_id: str = "" + +class Response(BaseModel): + statusCode: int = 200 + message: str = "" + result: dict = {} +@app.post("/api/mining/qna/result") +def get_result(item: InputSession): + global SESSION + res = SESSION.get_info_session(item.hash_id) + status = res["status"] + res = res["result"] + if status == -1: + msg = "ERROR" + elif status == 0: + msg = "processing ..." + elif status == 1: + msg = "done" + # SESSION.delete_session(item.hash_id) + else: + msg = "nothing" + return Response(statusCode=status, message=msg, result=res) \ No newline at end of file diff --git a/consumer_merge_clustering.py b/consumer_merge_clustering.py new file mode 100644 index 0000000000000000000000000000000000000000..39dcfe465c4b5e69badc86724646525636b3523e --- /dev/null +++ b/consumer_merge_clustering.py @@ -0,0 +1,96 @@ +# import os +# os.environ["CUDA_VISIBLE_DEVICES"] ="-1" +import pika +import json +import time +import requests + +from merge_topic import main +# from get_config import config_params +from config import get_config + +config_params = get_config() +ConfigManager = config_params['ConfigManager'] + +def update_result(result, type='daily', meta = {}): + benchmark_children_id = -1 + benchmark_id = -1 + source_tagids = [] + for id_cluster in result: + for doc in result[id_cluster][:1]: + source_tagids = doc.get('source_tagids',[]) + for key in doc: + if "benchmark_child" in key: + benchmark_children_id = int(key.lstrip('benchmark_child_')) + if "benchmark" in key and 'child' not in key: + benchmark_id = int(key.lstrip('benchmark_')) + break + + if not source_tagids: + source_tagids = [] + if len(source_tagids) > 0: + benchmark_id = 0 + benchmark_children_id = 0 + + output = { + "benchmark_id": benchmark_id, + "benchmark_children_id": benchmark_children_id, + "source_tagids": source_tagids, + "country_code": meta.get('country_code',''), + "type": type, + "data": json.dumps(result) + } + + # with open('test_result.json','w') as f: + # json.dump(output, f, ensure_ascii=False) + + # url = config_params['api_save_clustering'] + url = ConfigManager['ApiConnects']['api_save_clustering']['BaseUrl'] + + res = requests.post(url, json = output) + print(res.text) + print('Update result !!!!!!!!!') + +def callback_func(ch, method, properties, body): + print("receive done: ") + starttime = time.time() + body = json.loads(body.decode("utf-8")) + + req = body + type = req['type'] + meta = req.get('meta', {}) + res = main(req) + update_result(res, type, meta=meta) + print('Time process:', time.time() - starttime) + ch.basic_ack(delivery_tag=method.delivery_tag) + + +if __name__ == '__main__': + params = ConfigManager['QueueConfigs']['queue_merge_clustering'] + usr_name = params["UserName"] + password = str(params["Password"]) + host = params["HostName"] + virtual_host = params["VirtualHost"] + queue_name = params["Queue"] + + # params = config_params['queue_merge_clustering'] + # usr_name = params["usr_name"] + # password = str(params["password"]) + # host = params["host"] + # virtual_host = params["virtual_host"] + # queue_name = params["queue_name"] + + while True: + try: + credentials = pika.PlainCredentials(usr_name, password) + connection = pika.BlockingConnection( + pika.ConnectionParameters(host=host, virtual_host=virtual_host, credentials=credentials, heartbeat=3600, blocked_connection_timeout=3600)) + channel = connection.channel() + channel.queue_declare(queue=queue_name, durable=True, arguments={"x-max-priority": 10}) + print(" * wait message") + channel.basic_qos(prefetch_count=1) + channel.basic_consume(queue=queue_name, on_message_callback=callback_func) + channel.start_consuming() + except Exception as ex: + print(f'[ERROR] ', ex) + # raise ex diff --git a/consumer_merge_clustering_newscms.py b/consumer_merge_clustering_newscms.py new file mode 100644 index 0000000000000000000000000000000000000000..03df2a6de0b59bde6dbde7be0a10f7c7692486cb --- /dev/null +++ b/consumer_merge_clustering_newscms.py @@ -0,0 +1,109 @@ +# import os +# os.environ['CUDA_VISIBLE_DEVICES'] = "-1" + +import pika +import json +import time +import requests + +from merge_topic import main +# from get_config import config_params +from config import get_config + +config_params = get_config() +ConfigManager = config_params['ConfigManager'] +URL_SAVE_CLUSTERING_CMS = ConfigManager["ApiConnects"]["api_save_cluster_newscms"]["BaseUrl"] + +def update_result(result, id, meta = {}): + print(result) + print("-----") + output = { + "id": id, + "result":json.dumps(result) + } + res = requests.post(url=URL_SAVE_CLUSTERING_CMS, json = output) + print(res.text) + print('Update result !!!!!!!!!') + +def callback_func(ch, method, properties, body): + print("receive done: ") + starttime = time.time() + body = json.loads(body.decode("utf-8")) + with open("/home/vietle/topic-clustering/input_merge1.json", 'w') as f: + json.dump(body,f,ensure_ascii = False) + req = body + req["type"] = "monthly" + id = req["id"] + meta = req.get('meta', {}) + + preprocess_reformat = [] + preprocess = req["preprocess"] + for daily_clusters in preprocess: + + dict_cluster = {} + for i,doc in enumerate(daily_clusters["topic"]): + reps_post = doc + lst_doc = [reps_post] + lst_doc.extend(doc.get("list_posts", [])) + dict_cluster[i] = lst_doc + it = { + "topic": dict_cluster + } + preprocess_reformat.append(it) + req["preprocess"] = preprocess_reformat + + res = main(req) + update_result(res, id, meta=meta) + print('Time process:', time.time() - starttime) + ch.basic_ack(delivery_tag=method.delivery_tag) + + +def test(): + with open("/home/vietle/topic-clustering/input_merge1.json", 'r') as f: + body = json.load(f) + + req = body + req["type"] = "monthly" + id = req["id"] + meta = req.get('meta', {}) + + preprocess_reformat = [] + preprocess = req["preprocess"] + for daily_clusters in preprocess: + + dict_cluster = {} + for i,topic in enumerate(daily_clusters["topic"]): + dict_cluster[i] = topic + it = { + "topic": dict_cluster + } + preprocess_reformat.append(it) + req["preprocess"] = preprocess_reformat + with open("/home/vietle/topic-clustering/input_merge2.json", 'w') as f: + json.dump(req,f,ensure_ascii = False) + res = main(req) + +if __name__ == '__main__': + # test() + params = ConfigManager['QueueConfigs']['queue_merge_clustering_newscms'] + usr_name = params["UserName"] + password = str(params["Password"]) + host = params["HostName"] + virtual_host = params["VirtualHost"] + queue_name = params["Queue"] + + + while True: + try: + credentials = pika.PlainCredentials(usr_name, password) + connection = pika.BlockingConnection( + pika.ConnectionParameters(host=host, virtual_host=virtual_host, credentials=credentials, heartbeat=3600, blocked_connection_timeout=3600)) + channel = connection.channel() + channel.queue_declare(queue=queue_name, durable=True, arguments={"x-max-priority": 10}) + print(" * wait message") + channel.basic_qos(prefetch_count=1) + channel.basic_consume(queue=queue_name, on_message_callback=callback_func) + channel.start_consuming() + except Exception as ex: + print(f'[ERROR] ', ex) + raise ex diff --git a/deployment.yaml b/deployment.yaml new file mode 100644 index 0000000000000000000000000000000000000000..28caed22ca3b530bebbc68f437ddfdd790286be4 --- /dev/null +++ b/deployment.yaml @@ -0,0 +1,28 @@ +apiVersion: apps/v1beta1 +kind: Deployment +metadata: + name: clusteringcpu + labels: + app: clusteringcpu +spec: + strategy: + type: Recreate + template: + metadata: + labels: + app: clusteringcpu + tier: clusteringcpu + spec: + containers: + - image: {{registry_host}}/clusteringcpu:{{tag}} + name: clusteringcpu + resources: + requests: + cpu: 6 + memory: 60000Mi + limits: + cpu: 10 + memory: 100000Mi + ports: + - containerPort: + name: \ No newline at end of file diff --git a/docker/api_trt/Dockerfile b/docker/api_trt/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..f329b6a83f6ede40ce91e2ea5b9e09fe1a35e5d2 --- /dev/null +++ b/docker/api_trt/Dockerfile @@ -0,0 +1,22 @@ +FROM nvcr.io/nvidia/tensorrt:22.07-py3 + +EXPOSE 8633 +WORKDIR /app + +RUN echo "nameserver 8.8.8.8" > /etc/resolv.conf && pip install --upgrade pip + +RUN echo "nameserver 8.8.8.8" > /etc/resolv.conf && apt-get update && \ + DEBIAN_FRONTEND=noninteractive \ + apt-get -y install default-jre-headless && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +COPY req.txt /app/ +RUN echo "nameserver 8.8.8.8" > /etc/resolv.conf && pip install -r req.txt +RUN echo "nameserver 8.8.8.8" > /etc/resolv.conf && pip install --upgrade pip && pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113 + +COPY ./main_cache.py /app/ + + +RUN rm -r ~/.cache/pip/* +CMD ["python3", "main_cache.py"] \ No newline at end of file diff --git a/docker/cpu/Dockerfile b/docker/cpu/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..299934461ecffe9571a086db2d77251ad43c1316 --- /dev/null +++ b/docker/cpu/Dockerfile @@ -0,0 +1,46 @@ +FROM python:3.7 + +WORKDIR /app + + +RUN apt-get update && apt-get install build-essential cmake git -y + +#----------------JRE (for vncorenlp)-------------- +RUN apt-get update && \ + DEBIAN_FRONTEND=noninteractive \ + apt-get -y install default-jre-headless && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +RUN apt-get install unzip +RUN pip install gdown +RUN gdown --id 1MTAPYy9AcYtfiJ6m_pz6MPeA6li8pYp7 +RUN unzip vncorenlp.zip -d /app/ + + +# COPY ./model /app/model + +RUN mkdir -p /app/model +RUN mkdir -p /app/log +RUN mkdir -p /app/log_run + +COPY reqs_cpu.txt /app/ +RUN pip install -r reqs_cpu.txt + +COPY ./load_model.py /app/ +RUN python load_model.py + +COPY ./config /app/config +COPY ./entity /app/entity +COPY ./function /app/function +COPY ./main_cache.py /app/ +COPY ./service_cache.py /app/ +COPY ./summary.py /app/ +COPY ./merge_topic.py /app/ +COPY ./consumer_clustering.py /app/ +COPY ./consumer_merge_clustering.py /app/ +COPY ./run_multi_process.py /app/ + +RUN rm -r ~/.cache/pip/* + +CMD ["python", "run_multi_process.py"] diff --git a/docker/gpu/Dockerfile_gpu b/docker/gpu/Dockerfile_gpu new file mode 100644 index 0000000000000000000000000000000000000000..58f2f4967907fae08cf182ee73dcfd3311c02b14 --- /dev/null +++ b/docker/gpu/Dockerfile_gpu @@ -0,0 +1,33 @@ +FROM python:3.7 + +WORKDIR /app + + +RUN apt-get update && apt-get install build-essential cmake git -y + +#----------------JRE (for vncorenlp)-------------- +RUN apt-get update && \ + DEBIAN_FRONTEND=noninteractive \ + apt-get -y install default-jre-headless && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +COPY ./model /app/model + +RUN pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html +RUN mkdir log +RUN mkdir log_run + +COPY req.txt /app/ +RUN pip install -r req.txt + +COPY ./entity /app/entity +COPY ./function /app/function +COPY ./vncorenlp /app/vncorenlp +COPY ./main_cache.py /app/ +COPY ./service_cache.py /app/ +COPY ./summary.py /app/ + +RUN rm -r ~/.cache/pip/* + +CMD ["python", "main_cache.py"] diff --git a/docker_build.txt b/docker_build.txt new file mode 100644 index 0000000000000000000000000000000000000000..21d41849d62316f6e49a2c53e815b97c0855b159 --- /dev/null +++ b/docker_build.txt @@ -0,0 +1,6 @@ +docker build -t topic_clustering . +docker run -d --restart=always -p8633:8633 --name topic_clustering topic_clustering +/////docker run -p8633:8633 --name topic_clustering topic_clustering + +docker build -t clustering-dashboard . +docker run --name clustering-dashboard clustering-dashboard \ No newline at end of file diff --git a/entity/__init__.py b/entity/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..4192f6a107e7b1760847f3febb9f6d0d236a02f1 --- /dev/null +++ b/entity/__init__.py @@ -0,0 +1 @@ +from .types import * \ No newline at end of file diff --git a/entity/__pycache__/__init__.cpython-37.pyc b/entity/__pycache__/__init__.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f5cbcd9e9c47468e8a71faf51ed8b08fcaf5ff0d Binary files /dev/null and b/entity/__pycache__/__init__.cpython-37.pyc differ diff --git a/entity/__pycache__/__init__.cpython-38.pyc b/entity/__pycache__/__init__.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..596cca3044532f070899d7bcf6cb0b1811723568 Binary files /dev/null and b/entity/__pycache__/__init__.cpython-38.pyc differ diff --git a/entity/__pycache__/types.cpython-37.pyc b/entity/__pycache__/types.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..29e62e9338f1d4567acaf8a670c919fb4123777a Binary files /dev/null and b/entity/__pycache__/types.cpython-37.pyc differ diff --git a/entity/__pycache__/types.cpython-38.pyc b/entity/__pycache__/types.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..496d1ef7855df6551fdb47a8ac05f805a17bf450 Binary files /dev/null and b/entity/__pycache__/types.cpython-38.pyc differ diff --git a/entity/types.py b/entity/types.py new file mode 100644 index 0000000000000000000000000000000000000000..b07cf09a4e712765594364e1a0d58e2b1b5f1db4 --- /dev/null +++ b/entity/types.py @@ -0,0 +1,679 @@ +from pydantic import BaseModel + +class InputHotTopic(BaseModel): + start_time: str = "" + end_time: str = "" + query: str = "" + keywords: list = [] + top_cluster: int = 5 + prompt: str = "" + check_relevent: str = "" + max_posts: int = 5000 + + +class Docs(BaseModel): + threshold: float = 0.2 + top_sentence: int = -1 + top_cluster: int = -1 + topn_summary: int = 5 + responseHeader: dict = {} + response: dict = {} + top_doc: int = 200 + keyword: list = [] + sorted_field: str = '' + max_doc_per_cluster: int = 50 + command_id: int = 0 + delete_message: bool = True + is_check_spam: bool = True + + +class Preprocess(BaseModel): + threshold: float = 0.2 + top_cluster: int = -1 + type: str = 'weekly' + preprocess: list = [] + benchmark_id: int = -1 + benchmark_children_id: int = -1 + source_tagids: list = [] + meta: dict = {} + + +class Cluster(BaseModel): + status: int = 1 + message: str = "" + result: dict = {} + + +class SummaryInput(BaseModel): + text: str + topn: int = 3 + + +class InputCheckReview(BaseModel): + id_topic: str = "" + start_time: str = "2024-01-01 00:00:00" + end_time: str = "2024-01-02 00:00:00" + data: dict + + +class DocsWithSamples(BaseModel): + id_topic: str = "" + start_time: str = "2024-01-01 00:00:00" + end_time: str = "2024-01-02 00:00:00" + threshold: float = 0.3 + top_sentence: int = -1 + top_cluster: int = -1 + topn_summary: int = 10 + type_cluster: str = "" + lang_process: str = "" + prompt: str = "" + topic_name: str = "" + responseHeader: dict = {} + response: dict = { + "docs": [ + { + "categories": [ + "Công nghệ" + ], + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "zingnews.vn", + "id": "112dbb7bc8fcb8d54d3c17468bfef1d5ef0fae9b", + "message": "Sáng 9/8 (giờ Mỹ) Tổng thống Mỹ Joe Biden đã ký đạo luật lưỡng đảng, nhằm tăng cường sức cạnh tranh của Mỹ với Trung Quốc trên thị trường sản xuất chip. Việc này đồng nghĩa với hàng tỷ USD sẽ được đầu tư vào các doanh nghiệp công nghệ nước này. \n “Hôm nay là ngày dành cho những nhà chế tạo. Hôm nay nước Mỹ đang chuyển mình”, ông Biden nói tại buổi lễ bên ngoài Nhà Trắng. Lễ ký kết có sự tham dự của giám đốc điều hành nhiều doanh nghiệp điện tử lớn ở nước này.\n Ông Biden tại buổi ký Đạo luật Khoa học và Chip, đầu tư hàng chục tỷ USD vào ngành bán dẫn. Ảnh: AFP. \n Dự luật có tên gọi Đạo luật Khoa học và Chip, bao gồm 52 tỷ USD tài trợ cho các công ty Mỹ chế tạo vi xử lý. Đồng thời, đây cũng là hàng tỷ USD dành cho những khoản vay khuyến khích đầu tư vào ngành sản xuất bán dẫn. Gói tài trợ cung cấp thêm hàng chục tỷ USD khác cho nghiên cứu và phát triển khoa học, thúc đẩy đổi mới, phát triển nước Mỹ.\n Ngoài ra, chính quyền của ông Biden cho biết văn bản vừa được thông qua sẽ “mở khóa thêm hàng trăm tỷ USD” chi tiêu tư nhân trong ngành. Đồng thời, nhiều công ty thuộc nhóm được hỗ trợ bởi đạo luật đã công bố khoản đầu tư trị giá 44 tỷ USD vào ngành bán dẫn. \n Trong đó, 40 tỷ USD được Micron đầu tư vào sản xuất chip nhớ. Nhà Trắng cho biết sáng kiến của công ty nêu trên đem lại 8.000 việc làm mới và thúc đẩy thị phần chip nhớ của Mỹ tăng từ 2% lên 10%. 4,2 tỷ USD khác được Qualcomm và Globalfoundries dùng để mở rộng nhà máy ở ngoại ô New York. \n Theo CNBC , những người ủng hộ cho rằng đạo luật là cần thiết để nâng cao lợi thế cạnh tranh công nghệ của Mỹ và phục hồi ngành công nghiệp chip đang dần tụt hậu của nước này. Mỹ hiện tạo ra khoảng 10% nguồn cung bán dẫn toàn cầu. Trong khi đó, các nước Đông Á chiếm đến 75%. \n Chất bán dẫn đóng vai trò quan trọng trong sản phẩm điện tử tiêu dùng, ôtô, thiết bị chăm sóc sức khỏe và vũ khí. Các quan chức cho biết việc không đủ chất bán dẫn do Covid-19 tạo ra tình trạng thiếu chip và đứt chuỗi cung ứng. Điều này thể hiện rõ sự phụ thuộc của Mỹ vào vi xử lý từ các nước khác, bộc lộ mối đe dọa an ninh tiềm tàng. \n “Trong 40 năm qua, nền công nghiệp sản xuất bán dẫn của Mỹ dần suy yếu khi các công ty đi theo mức nhân công rẻ ở bên kia bán cầu. Điều này tạo ra lỗ hổng về kinh tế và an ninh quốc gia”, Bộ trưởng Thương mại Mỹ Gina Raimondo nói. \n Tuy vậy, 52 tỷ USD tài trợ cho ngành bán dẫn không phải con số lớn. Trung Quốc đã dành 150 tỷ USD cho sản xuất chip, xác định bán dẫn là ngành công nghiệp chủ chốt của quốc gia này trong kế hoạch kinh tế 5 năm. TSMC cho biết công ty dự định chi 100 tỷ USD trong 3 năm để nâng cao năng lực sản xuất. Liên minh châu Âu cũng đang nghiên cứu luật sản xuất chip trong khu vực. \n Ông Guarav Gupta, nhà phân tích ngành công nghiệp bán dẫn của Gather cho rằng con số tài trợ không phải khổng lồ, nhưng đó là tín hiệu cho thấy Mỹ sẵn sàng đầu tư cho ngành sản xuất vi xử lý.", + "snippet": "Tổng thống Joe Biden đã ký đạo luật tài trợ 52 tỷ USD cho các nhà sản xuất bán dẫn tại Mỹ, tăng cường sức cạnh tranh với Trung Quốc.", + "source_tagids": [ + 136, + 1, + 210 + ], + "source_type": 11, + "tag_phrases": [ + "Joe Biden", + "bán dẫn", + "chip", + "Dự luật cho ngành chip Mỹ được tổng thống thông qua" + ], + "title": "Dự luật 52 tỷ USD cho ngành chip của Mỹ được thông qua", + "url": "https://zingnews.vn/du-luat-52-ty-usd-cho-nganh-chip-cua-my-duoc-thong-qua-post1343998.html", + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://znews-photo.zingcdn.me/Uploaded/ygtmvd/2022_08_09/107101127_1660057423600_gettyimages_1242401644_AFP_32GA2PA.jpeg" + ], + "created_time": 1660082406, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer", + "Icomm.NewsCrawl.SmartReader" + ], + "domain": "ntdvn.net", + "id": "15e70a93010f65bbabf0a769e15c8a9c32971205", + "message": "Tổng thống Joe Biden (ở giữa) ký Đạo luật CHIPS năm 2022, tại Bãi cỏ phía Nam của Nhà Trắng vào ngày 09/8/2022. (Ảnh: Mandel Ngan/AFP/Getty Images)\n Tổng thống Mỹ Joe Biden ký thông qua đạo luật đầu tư 280 tỷ USD vào ngành bán dẫn và các lĩnh vực sản xuất công nghệ cao khác nhằm thúc đẩy sản xuất trong nước, giảm sự lệ thuộc vào các chuỗi cung ứng nước ngoài và tăng cường cạnh tranh với Trung Quốc. \n “Đạo luật Khoa học và CHIPS sẽ thúc đẩy nghiên cứu, phát triển và sản xuất chất bán dẫn của Hoa Kỳ, đảm bảo sự dẫn đầu của Hoa Kỳ trong công nghệ, tạo nền tảng cho mọi thứ từ ô tô, thiết bị gia dụng đến hệ thống phòng thủ”, theo một tờ thông tin của Nhà Trắng về đạo luật. \n “Luật cũng sẽ đảm bảo Hoa Kỳ duy trì và nâng cao lợi thế khoa học và công nghệ của mình\".\n Tổng thống Biden ngày 9/8 tuyên bố trong buổi lễ ký ban hành đạo luật: “Nhiều thập niên tới kể từ bây giờ, người dân sẽ nhìn lại tuần này cùng tất cả những gì chúng ta đã thông qua với tất cả những gì đang thăng tiến, điều đó cho thấy rằng thấy rằng chúng ta đã đón lấy thời cơ tại khúc quanh này trong lịch sử\".\n Đạo luật Khoa học và CHIPS có tổng giá trị 280 tỷ USD được lưỡng viện Hoa Kỳ vừa thông qua vào cuối tháng trước. Trong đó dành 52 tỷ USD nhằm hỗ trợ cho ngành công nghiệp bán dẫn.\n Chất bán dẫn là đấu trường quan trọng giữa Washington và Bắc Kinh. Những con chip nhỏ bé nhưng lại đóng vai trò là bộ não của các thiết bị điện tử, từ điện thoại thông minh, máy tính xách tay đến trung tâm dữ liệu, cho đến các hệ thống vũ khí tinh vi, chẳng hạn như tên lửa chống tăng Javelin mà Mỹ đang cung cấp cho Ukraine.\n Washington cho rằng gói chi tiêu khổng lồ sẽ cải thiện việc làm và an ninh quốc gia bằng cách làm cho Hoa Kỳ ít phụ thuộc hơn vào các chuỗi cung ứng nước ngoài, từ đó xây dựng một lực lượng lao động mạnh mẽ hơn.\n “Hôm nay, tôi ký ban hành đạo luật Khoa học và CHIPS”, ông Biden nói trong một tweet.  “Đó là quy luật có từ lâu đời khi đầu tư vào Mỹ bằng cách tăng cường nỗ lực của chúng ta trong việc sản xuất chất bán dẫn trong nước”. \n Today, I sign into law the CHIPS and Science Act. It's a once-in-a-generation law that invests in America by supercharging our efforts to make semiconductors here at home.\n Today represents a more secure economy, jobs, and a stronger future for our nation.\n America is delivering.\n — President Biden (@POTUS) August 9, 2022 \n Nhà Trắng cho biết việc thông qua đạo luật đã thúc đẩy các khoản đầu tư mới trong lĩnh vực sản xuất chip. Qualcomm hôm 8/8 đã đồng ý mua thêm 4,2 tỷ USD chip bán dẫn từ nhà máy GlobalFoundries ở New York, nâng tổng cam kết mua hàng lên 7,4 tỷ USD cho đến năm 2028.\n Nhà Trắng cũng cho biết hãng Micron đã thông báo khoản đầu tư 40 tỷ USD vào sản xuất chip, giúp thúc đẩy thị phần của Mỹ từ mức 2% lên 10%. Đây là một khoản đầu tư được lên kế hoạch với \"khoản tài trợ dự kiến\" từ đạo luật \"Khoa học và Chip\".\n Chính quyền ông Biden cũng đã nhiều lần mô tả luật này như một phần hệ trọng trong nỗ lực chống lại ảnh hưởng của một nước Trung Quốc đang trỗi dậy và bảo đảm Mỹ có thể duy trì lợi thế cạnh tranh trước Bắc Kinh, đặc biệt là trong lĩnh vực sản xuất chất bán dẫn. Các quan chức chính quyền đã tổ chức nhiều buổi báo cáo cho các nhà lập pháp để phác thảo các tác động an ninh quốc gia của dự luật này, và ông Biden lưu ý trong bài phát biểu hôm 9/8 rằng chính phủ Trung Quốc đã vận động các doanh nghiệp Mỹ chống lại luật này.\n Tuy nhiên, có những chỉ trích coi luật này như một sự tiếp tay của các công ty sẽ làm tăng lạm phát và gây tổn hại cho những người đóng thuế ở Mỹ.\n Thượng nghị sĩ Bernie Sanders (Dân chủ-Vermont) cho biết: “Câu hỏi mà chúng ta nên đặt ra là: Những người đóng thuế Mỹ có nên cung cấp cho ngành công nghiệp vi mạch một tấm séc trị giá hơn 76 tỷ USD vào đúng thời điểm các công ty bán dẫn đang kiếm được hàng chục tỷ USD lợi nhuận và trả cho các CEO của họ những gói bồi thường cắt cổ?”. \n “Ông Bernie Sanders và tôi gần như không bao giờ chung quan điểm, nhưng ông ấy đã nói đúng về cái gọi là đạo luật CHIPS\", Thượng nghị sĩ Chuck Grassley (Cộng hòa-Iowa) viết trên Twitter. “Đó chỉ là một khoản phân phát chính phủ khổng lồ cho các công ty lớn [và] đã có lợi nhuận. Tại sao chúng ta lại chi nhiều tiền thuế hơn cho phúc lợi doanh nghiệp không cần thiết?\".\n Sometimes bipartisan bills are bad for the taxpayer / Bernie Sanders & I almost never agree but he is right about so-called CHIPS bill It’s just a huge govt handout to massive/already-profitable companies Why would we spend MORE TAXPAYER DOLLARS for unnecessary corporate welfare?\n — ChuckGrassley (@ChuckGrassley) July 25, 2022 \n Bạn bình luận gì về tin này?", + "snippet": "Aug 10, 2022 ... “Đạo luật Khoa học và CHIPS sẽ thúc đẩy nghiên cứu, phát triển và sản xuất chất bán dẫn của Hoa Kỳ, đảm bảo sự dẫn đầu của Hoa Kỳ trong công nghệ, ...", + "source_type": 6, + "title": "Tổng thống Biden ký đạo luật 'Khoa học và CHIP' trị giá 280 tỷ USD ...", + "url": "https://www.ntdvn.net/the-gioi/tong-thong-biden-ky-dao-luat-khoa-hoc-va-chip-tri-gia-280-ty-usd-canh-tranh-voi-trung-quoc-364851.html", + "attachment_farm_urls": [], + "attachment_types": [], + "attachment_urls": [], + "created_time": 1660150798, + "lang": "vi" + }, + { + "actor_name": "NGUYÊN HẠNH", + "categories": [ + "Thế giới" + ], + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "tuoitre.vn", + "id": "1a777d18c21208b35583b52f89f06488696172dc", + "message": "0 \r\n \r\n \r\n \r\n \r\n \r\n Lưu \r\n \r\n \r\n \r\n TTO - Ngày 10-8, hai hiệp hội thương mại Trung Quốc chỉ trích Đạo luật chip và khoa học của Mỹ, cho rằng đạo luật này sẽ gây phương hại đến ngành sản xuất chip ở những nơi khác trên thế giới. \r\n \r\n \r\n \r\n Theo báo Nikkei Asia , Hội đồng Xúc tiến thương mại quốc tế Trung Quốc và Phòng Thương mại quốc tế Trung Quốc tuyên bố Đạo luật chip và khoa học của Mỹ sẽ \"tăng cường cạnh tranh địa chính trị trong ngành công nghiệp bán dẫn, đồng thời cản trở sự phục hồi kinh tế toàn cầu và sự phát triển của đổi mới công nghệ\". \n Theo hai hiệp hội trên, mục tiêu của đạo luật mới của Mỹ \"phân biệt đối xử với một số công ty nước ngoài, sử dụng quyền lực nhà nước để cưỡng bức thay đổi sự phân công lao động quốc tế trong ngành bán dẫn và gây tổn hại đến lợi ích của các công ty trên khắp thế giới, bao gồm cả ở Trung Quốc và Mỹ\".\n Các nhóm trên kêu gọi cộng đồng doanh nghiệp quốc tế cùng nhau \"loại bỏ tác động tiêu cực\" của đạo luật này.\n Trước đó, người phát ngôn Bộ Ngoại giao Trung Quốc Uông Văn Bân chỉ trích Đạo luật chip và khoa học là một ví dụ về \"sự ép buộc kinh tế\" của Mỹ.\n Theo Đài CNBC, Đạo luật chip và khoa học, Tổng thống Joe Biden vừa ký thông qua hôm 9-8, hỗ trợ hơn 52 tỉ USD cho các công ty sản xuất chip máy tính của Mỹ, cũng như cung cấp hàng tỉ khoản tín dụng thuế để khuyến khích đầu tư vào sản xuất chất bán dẫn.\n Chính quyền ông Biden cũng cho rằng đạo luật trên sẽ \"mở khóa thêm hàng trăm tỉ\" chi tiêu tư nhân trong ngành này.\n Hôm 9-8, Nhà Trắng cho biết nhiều công ty, được \"thúc đẩy\" bởi đạo luật, đã công bố hơn 44 tỉ USD đầu tư mới vào sản xuất chất bán dẫn.  Trong số đó, 40 tỉ USD đến từ khoản đầu tư của Công ty Micron vào sản xuất chip ghi nhớ.  \n Nhà Trắng cũng cho hay sáng kiến ​​của công ty này sẽ mang lại 8.000 việc làm mới và tăng thị phần sản xuất chip ghi nhớ của Mỹ từ 2% lên 10%. \n Cũng theo Nhà trắng, mới đây hai hãng Qualcomm và GlobalFoundries cũng công bố hợp tác sản xuất chip trị giá 4,2 tỉ USD. Quan hệ đối tác này là một phần trong kế hoạch mở rộng cơ sở GlobalFoundries ở ngoại ô New York.\n Chất bán dẫn là thành phần quan trọng của một loạt sản phẩm bao gồm điện tử tiêu dùng, ôtô, thiết bị chăm sóc sức khỏe và hệ thống vũ khí. Giới quan chức đánh giá đại dịch COVID-19 đã gây ra tình trạng thiếu chip và tạo áp lực lớn đối với chuỗi cung ứng.\n\r\n \r\n \r\n NGUYÊN HẠNH", + "snippet": "TTO - Ngày 10-8, hai hiệp hội thương mại Trung Quốc chỉ trích Đạo luật chip và khoa học của Mỹ, cho rằng đạo luật này sẽ gây phương hại đến ngành sản xuất chip ở những nơi khác trên thế giới.", + "source_tagids": [ + 137, + 1, + 210, + 235 + ], + "source_type": 11, + "tag_phrases": [ + "Nhà Trắng" + ], + "title": "Hiệp hội thương mại Trung Quốc chỉ trích đạo luật chip của Mỹ", + "url": "https://tuoitre.vn/hiep-hoi-thuong-mai-trung-quoc-chi-trich-dao-luat-chip-cua-my-20220810110831316.htm", + "attachment_types": [], + "attachment_urls": [], + "created_time": 1660189080, + "lang": "vi" + }, + { + "actor_name": "Ngọc Vân", + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "laodong.vn", + "id": "3932fc98eccbdadc9eabfe809cfd60d5d994d963", + "message": "Tổng thống Mỹ Joe Biden ký Đạo luật Chip và Khoa học 2022, ngày 9.8 tại Nhà Trắng. Ảnh: AFP \r\n \r\n\r\n\r\n \r\n Đạo luật 280 tỉ USD \n Tờ Washington Post đưa tin, Tổng thống Joe Biden ký đạo luật khổng lồ trị giá 280 tỉ USD để khởi động chương trình phát triển công nghiệp chất bán dẫn lớn nhất mà chính phủ liên bang từng quản lý.\n Đạo luật được theo đuổi từ lâu sẽ thúc đẩy việc xây dựng các cơ sở sản xuất chất bán dẫn lớn ở Mỹ, nhằm mục tiêu đảm bảo nguồn cung cấp an toàn hơn cho các linh kiện nhỏ bé nhưng rất quan trọng đối với thiết bị điện tử hiện đại được coi là thiết yếu đối với an ninh quốc gia.\n Dự luật bao gồm khoản trợ cấp 52 tỉ USD cho hoạt động nghiên cứu và sản xuất chất bán dẫn của liên bang và các công ty khởi nghiệp công nghệ trong khu vực, mà chính quyền hy vọng sẽ dẫn đến những đột phá thương mại trong các lĩnh vực mới như điện toán lượng tử và trí tuệ nhân tạo. Reuters dẫn lời ông Biden phát biểu gọi đạo luật là “khoản đầu tư chỉ có 1 lần trong đời cho nước Mỹ”.\n Ngoài khoản 52 tỉ USD nói trên, đạo luật cũng bao gồm một khoản tín dụng thuế đầu tư 25% cho các nhà máy sản xuất chip, ước tính trị giá 24 tỉ USD; khoản 200 tỉ USD trong 10 năm để thúc đẩy hoạt động nghiên cứu khoa học của Mỹ nhằm cạnh tranh tốt hơn. Trước đó, đạo luật được Thượng viện Mỹ phê chuẩn vào ngày 27.7.\n Các khoản trợ cấp được đưa ra trong bối cảnh toàn cầu thiếu chip trầm trọng, gây khó khăn cho các nhà sản xuất ôtô và các nhà sản xuất khác, buộc họ phải cắt giảm sản lượng. Các quỹ liên bang không giải quyết được những thiếu hụt đó trong ngắn hạn nhưng sẽ khuyến khích các dự án xây dựng lớn của Intel, TSMC, Micron, Samsung, GlobalFoundries và các công ty khác nhằm xây dựng các nhà máy sản xuất chip mới đắt tiền trong những năm tới.\n Micron trở thành người mới nhất trong số đó, thông báo sẽ chi 40 tỉ USD cho các cơ sở sản xuất chip mới ở Mỹ cho đến cuối thập kỷ này. Công ty có trụ sở tại Boise, Idaho, cho biết khoản đầu tư sẽ tạo ra 5.000 việc làm công nghệ cao tại Micron và sẽ thúc đẩy thị phần sản xuất chip nhớ toàn cầu của Mỹ lên 10% từ mức 2% hiện nay.\n Giám đốc điều hành của Micron, Sanjay Mehrotra, nói rằng khoản đầu tư phụ thuộc vào việc công ty nhận được bao nhiêu trong số 52 tỉ USD trợ cấp sẽ có từ Đạo luật Chip và Khoa học mới. “Luật này cho phép chúng tôi thực hiện các khoản đầu tư mà nếu không chúng tôi đã không thực hiện ở Mỹ” - Mehrotra nói và khẳng định các cơ sở mới sẽ sản xuất chip “tiên tiến hàng đầu”. \n Micron hiện có một số nhà máy sản xuất chip ở Manassas, nhưng sản xuất hầu hết các chip và tất cả các chip công nghệ cao nhất ở Nhật Bản, Singapore và Đài Loan (Trung Quốc).\n Những người ủng hộ cho rằng cần phải có kinh phí để nâng cao lợi thế công nghệ của Mỹ và phục hồi ngành công nghiệp chip đang tụt hậu của nước này. Theo Nhà Trắng, Mỹ chỉ sản xuất khoảng 10% nguồn cung chất bán dẫn của thế giới, trong khi Đông Á chiếm 75% sản lượng toàn cầu - bao gồm hầu hết các chip cấp cao nhất.\n Chip máy tính - bộ não vận hành tất cả các thiết bị điện tử hiện đại - đã thiếu hụt nguồn cung gần hai năm trong bối cảnh nhu cầu tăng vọt nhưng khan hiếm nhà máy trên toàn thế giới. Sự thiếu hụt đã làm suy yếu tất cả các loại hình sản xuất phụ thuộc vào chip, nổi bật nhất là sản xuất ôtô, gây ra tình trạng thiếu hụt và giá ôtô tăng vọt. Chip không chỉ là nền tảng cho thiết bị điện tử tiêu dùng mà còn nhiều loại thiết bị quân sự, bao gồm máy bay chiến đấu F-35 và tên lửa Javelin - các loại vũ khí được coi là chìa khóa cho an ninh quốc gia.\n Động thái trước bầu cử giữa kỳ \n Việc ký kết diễn ra khi Tổng thống Biden và các nhà lập pháp Đảng Dân chủ chuyển sự chú ý sang các chiến dịch bầu cử giữa kỳ. Các nghị sĩ Đảng Dân chủ tại Thượng viện hôm 7.8 đã thông qua một dự luật sâu rộng để tài trợ cho các chính sách đầy tham vọng về khí hậu, năng lượng và sức khỏe bằng cách tăng thuế đối với các tập đoàn giàu có và cải cách giá thuốc kê đơn. Dự luật này là một phần chính trong chương trình nghị sự của ông Biden mà các đảng viên Dân chủ đã làm việc trong hơn một năm. Nhờ lá phiếu của Phó Tổng thống Kamala Harris, dự luật đã được thông qua khi số phiếu của Đảng Dân chủ và Đảng Cộng hòa ngang bằng.\n Vào cuối tháng 6, ông Biden cũng đã ký một dự luật lưỡng đảng nhằm tăng cường các quy định về súng, bao gồm cả việc tăng cường các yêu cầu về kiểm tra lý lịch. Và tuần trước, ông Biden tiết lộ rằng Mỹ đã tiêu diệt thủ lĩnh hàng đầu của al-Qaeda Ayman Al-Zawahiri ở Afghanistan - kẻ được coi là chủ mưu đằng sau vụ khủng bố 11.9. Tổng thống Mỹ cũng dự kiến ​​sẽ ký một dự luật khác trong tuần này nhằm tăng cường trợ cấp y tế cho các cựu chiến binh.\n Xếp hạng tín nhiệm vốn ở mức trung bình của ông Biden đã giảm trong những tháng gần đây, do lạm phát toàn cầu và các vấn đề về chuỗi cung ứng ảnh hưởng đến túi tiền của người Mỹ. Điều này làm dấy lên lo ngại giữa các đảng viên Dân chủ rằng họ có thể thua trong cuộc bầu cử giữa kỳ vào tháng 11 tới, dẫn đến việc đảng Cộng hòa nắm quyền kiểm soát một hoặc cả hai viện của Quốc hội.\n Nhưng các cuộc thăm dò mới nhất cho thấy cơ hội giữ Thượng viện của đảng Dân chủ đã được cải thiện và hôm 8.8, ông Biden dự đoán rằng việc thông qua dự luật thuế và khí hậu sẽ \"giúp ích ngay lập tức\" vào giữa nhiệm kỳ.", + "snippet": "Ngày 9.8, Tổng thống Mỹ Joe Biden ký thông qua Đạo luật Chip và Khoa học 2022, khởi động sáng kiến ​​công nghiệp lớn của liên bang nhằm cạnh tranh chip trên toàn cầu.", + "source_tagids": [ + 136, + 1, + 210, + 235 + ], + "source_type": 11, + "title": "Mỹ bước vào cuộc cạnh tranh chip", + "url": "https://laodong.vn/the-gioi/my-buoc-vao-cuoc-canh-tranh-chip-1079547.ldo", + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://media-cdn-v2.laodong.vn/storage/newsportal/2022/8/10/1079547/7.jpg" + ], + "created_time": 1660188720, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer", + "Icomm.NewsCrawl.SmartReader" + ], + "domain": "voatiengviet.com", + "id": "40574acd609ee651b0c4d16b96ab382353c55597", + "message": "Tổng thống Joe Biden ngày 9/8 kí một dự luật được cả hai đảng biểu quyết tán thành trị giá 280 tỉ đô để thúc đẩy sản xuất công nghệ cao trong nước, một phần trong nỗ lực tăng cường khả năng cạnh tranh của Mỹ trước Trung Quốc.\n\n Dự luật là một phần cốt lõi trong chủ trương kinh tế của ông Biden khuyến khích đầu tư vào kĩ nghệ sản xuất chất bán dẫn của Mỹ nhằm giảm bớt sự phụ thuộc của Mỹ vào các chuỗi cung ứng ở nước ngoài đối với những mặt hàng hệ trọng, tối tân.\n\n \"Tương lai của ngành sản xuất chip sẽ được tạo ra ở Mỹ,\" ông Biden nói trong một buổi lễ tại Vườn Hồng ngày 9/8, nhắc đến các thiết bị bé xíu cung cấp năng lượng cho mọi thứ từ điện thoại thông minh, máy tính, đến xe hơi. Luật này dành ngân khoản 52 tỉ đôla để củng cố lĩnh vực chip máy tính của Mỹ.\n\n Dự luật được soạn thảo trong hơn một năm, cuối cùng được cả hai viện của Quốc hội thông qua vào cuối tháng trước với sự ủng hộ lưỡng đảng đáng kể. Thượng viện thông qua với tỉ số 64-33 và Hạ viện nhanh chóng theo bước với tỉ số 243-187.\n\n Nhà Trắng ngày 9/8 bắt đầu quảng bá những tác động tức thời của luật này, lưu ý rằng Micron, hãng sản xuất chip hàng đầu của Mỹ, sẽ công bố kế hoạch 40 tỉ đô để thúc đẩy sản xuất chip bộ nhớ trong nước, trong khi Qualcomm và GlobalFoundries sẽ công bố khoản đầu tư 4,2 tỉ đô mở rộng một nhà máy sản xuất chip ở phía bắc bang New York.\n\n Chính quyền cũng đã nhiều lần mô tả luật này như một phần hệ trọng trong nỗ lực chống lại ảnh hưởng của một nước Trung Quốc đang trỗi dậy và bảo đảm Mỹ có thể duy trì lợi thế cạnh tranh trước Bắc Kinh, đặc biệt là trong lĩnh vực sản xuất chất bán dẫn. Các quan chức chính quyền đã tổ chức nhiều buổi báo cáo cho các nhà lập pháp để phác thảo các tác động an ninh quốc gia của dự luật này, và ông Biden lưu ý trong bài phát biểu hôm 9/8 rằng chính phủ Trung Quốc đã vận động các doanh nghiệp Mỹ chống lại luật này.\n\n Nhiều nhà lập pháp Mỹ cho biết họ thường sẽ không ủng hộ các khoản trợ cấp quá lớn cho các doanh nghiệp tư nhân nhưng lưu ý rằng Trung Quốc và Liên minh Châu Âu đã trao hàng tỉ khoản ưu đãi cho các công ty chip của mình. Họ cũng trích dẫn các rủi ro an ninh quốc gia và các vấn đề lớn của chuỗi cung ứng toàn cầu đã cản trở hoạt động sản xuất toàn cầu.\n\n “Đây là lần đầu tiên chính phủ Mỹ đề ra một viễn kiến lâu dài cho cả đất nước, một chuyện rất là quan trọng vì nó đầu tư cho mấy chục năm tới,” tiến sĩ Đinh Xuân Quân, một chuyên gia kinh tế từng làm việc trong lĩnh vực phát triển quốc tế, nhận định. Ông lưu ý rằng luật này là một trong những ngoại lệ hiếm hoi vì “không bao giờ chính phủ Hoa Kỳ muốn giúp chính sách công nghiệp hết.”\n\n “Các chip của Hoa Kỳ sản xuất tân tiến hơn là chip làm tại Trung Quốc và việc đầu tư thêm sẽ giúp cho kinh tế Hoa Kỳ và các công ty Hoa Kỳ có nhiều sức cạnh tranh và tiến lên vị trí số một,” ông giải thích. “Đây là chuyện quan trọng vì trong bao nhiêu năm không có đầu tư mà đưa qua Trung Quốc và Hoa Kỳ có thể bị bắt chẹt.”\n\n “[Luật này] là bước tiến cần thiết để tái xây dựng công nghiệp chip tại Hoa Kỳ,” tiến sĩ Quân nói thêm.\n\n Tổng thống Biden ngày 9/8 tuyên bố trong buổi lễ kí ban hành luật: “Nhiều thập niên tới kể từ bây giờ, người ta sẽ nhìn lại tuần này và tất cả những gì chúng ta đã thông qua và tất cả những gì chúng ta đã thăng tiến, và thấy rằng chúng ta đã đón lấy thời cơ tại khúc quanh này trong lịch sử.”\n\n Buổi lễ là một trong số các sự kiện công cộng mà ông Biden đã lên lịch tham gia kể từ khi hồi phục sau COVID-19, bao gồm một chuyến thăm Kentucky bị lũ lụt tàn phá vào đầu tuần và một sự kiện kí kết luật hỗ trợ các cựu chiến binh vào ngày 10/8.", + "snippet": "Aug 10, 2022 ... Tổng thống Joe Biden giơ \"Đạo luật Khoa học và CHIPS năm 2022\" lên sau khi kí ban hành nó trong một buổi lễ ở Bãi cỏ phía Nam của Nhà Trắng, ở Washington, ...", + "source_tagids": [ + 6, + 8, + 150, + 179, + 210 + ], + "source_type": 11, + "title": "TT Biden kí luật thúc đẩy ngành sản xuất chip của Mỹ, cạnh tranh ...", + "url": "https://www.voatiengviet.com/a/tong-thong-biden-ki-luat-thuc-day-nganh-san-xuat-chip-cua-my-canh-tranh-voi-trung-quoc/6695051.html", + "attachment_farm_urls": [], + "attachment_types": [], + "attachment_urls": [], + "created_time": 61965449998, + "lang": "vi" + }, + { + "actor_name": "Nguyễn Thanh Yên, Cộng đồng vi mạch Việt Nam", + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "ictvietnam.vn", + "id": "46d3011e515575c3c63e00978ee38969e17f5ef9", + "message": "Đạo luật này đảm bảo gói hỗ trợ tài chính khoảng 52,7 tỷ USD cho việc phát triển các chương trình sản xuất bán dẫn, trong đó:   \n - 39 tỷ USD (bao gồm 2 tỷ USD là cho các công nghệ không phải tiên tiến) hỗ trợ cho việc xây dựng, mở rộng hoặc hiện đại hóa các cơ sở và thiết bị trong nước trong việc: chế tạo, lắp ráp, thử nghiệm, đóng gói tiên tiến chất bán dẫn.\n - 11 tỷ USD (5 tỷ trong năm 2022 còn lại phân bổ cho các năm 2023 - 2026) cho các hoạt động nghiên cứu phát triển và đào tạo nguồn nhân lực. Cũng cần lưu ý là ngân sách dành cho thiết kế chipset mẫu chỉ được giới hạn ở mức 10% và 50% của 11 tỷ USD ở trên là cho các chương trình đóng gói tiên tiến [1]. \n - 2,7 tỷ USD là cho các chương trình khác như 200 triệu USD cho việc góp phần giải quyết bài toán thiếu lao động trong ngắn hạn; 2 tỷ USD là thúc đẩy các nghiên cứu thuộc quốc phòng (chuyển đổi công nghệ bán dẫn từ phòng thí nghiệm ra các cơ sở sản xuất); và 500 triệu USD cho vấn đề an ninh công nghệ (hợp tác quốc tế trong việc phát triển các công nghệ viễn thông an toàn và các loại công nghệ mới nổi khác). \n Ngoài ra, đạo luật này cũng đề cập tới việc phân bổ 1,5 tỷ USD cho việc củng cố chuỗi cung ứng viễn thông toàn cầu và giới hạn phạm vi của sự tham gia toàn cầu từ các công ty viễn thông có quan hệ chặt chẽ với Trung Quốc, ví dụ như Huawei.\n Đặc biệt, đạo luật có các biện pháp bảo vệ để đảm bảo những người nhận tài trợ không thể xây dựng các cơ sở sản xuất bán dẫn tiên tiến ở các quốc gia mà Mỹ đưa vào danh sách các nước ảnh hưởng an ninh quốc gia của Mỹ, lưu ý chỉ giới hạn ở các công nghệ bán dẫn tiên tiến.  \n Cũng vào cuối tháng 7, đối thoại 2+2 giữa bộ trưởng ngoại giao và thương mại Mỹ - Nhật đã thống nhất thành lập trung tâm nghiên cứu chung về bán dẫn thế hệ tiếp theo đặt ở Nhật ngay trong năm nay. Hai bên cùng nhau tiến hành nghiên cứu cho quy trình 2nm với mục tiêu là thương mại hóa vào năm 2025. Lưu ý là cả TSMC của Đài Loan và Samsung của Hàn Quốc cũng đặt mục tiêu thương mại hóa tiến trình công ghệ tiếp theo (2nm) vào năm 2025. Việc này rất đáng chú ý khi nhớ lại vào những năm 1990, Mỹ và Nhật Bản cũng có một hiệp định bất bình đẳng về bán dẫn Mỹ - Nhật, chính điều này được cho là đã làm cho ngành bán dẫn Nhật trì trệ trong suốt 20 năm qua.\n Mới đây, ủy ban đặc biệt về chất bán dẫn Hàn Quốc đã tiết lộ về dự luật Chip của Hàn Quốc trong việc hỗ trợ thuế quy mô lớn đối với các đầu từ vào các cơ sở bán dẫn, theo đó thời hạn tín dụng thuế với các khoản đầu tư vào các cơ sở công nghiệp chiến lược công nghệ cao quốc giá như chất bán dẫn được kéo dài thêm 3 năm từ năm 2027 - 2030. Tỷ lệ khấu trừ thuế đầu tư cơ sở vật chất cũng được tăng lên đáng kể, 20% với các công ty lớn, 25% với các công ty có quy mô vừa và 30% đối với các doanh nghiệp nhỏ. Dự luật này cũng mở rộng phạm vi hỗ trợ thuế, hỗ trợ nghiên cứu phát triển và đào tạo nguồn nhân lực.\n Những động thái quyết liệt từ các chính phủ kể trên được dự báo sẽ khiến cho các nhân lực tài năng quay trở lại với ngành bán dẫn. Việt Nam với nguồn lực khoảng 5000 kỹ sư thiết kế chip rất có thể sẽ có sự dịch chuyển ra nước ngoài trong thời gian tới. Đây vừa là cơ hội cũng vừa là thách thức với lĩnh vực thiết kế chip còn non trẻ của Việt Nam, Việt Nam cần có hành động cụ thể nào để tận dụng được lợi thế từ những đạo luật này đem lại trong việc tập hợp và xây dựng được một đội ngũ kỹ sư thiết kế chip đông đảo cho quốc gia là một câu hỏi mở dành cho các nhà hoạch định chính sách để tránh cho Việt Nam thêm một lần nữa lỡ chuyến tàu bán dẫn vi mạch này.\n Tài liệu tham khảo: \n [1]. https://ictvietnam.vn/tich-hop-khong-dong-nhat-co-hoi-cho-phat-trien-linh-vuc-vi-mach-ban-dan-tai-viet-nam-20211122081527926.htm)", + "snippet": "Ngày 28/7/2022, Quốc hội Mỹ đã thông qua Đạo luật chip và khoa học Chips and Science Act nhằm khuyến khích việc sản xuất chip bán dẫn trong nước.", + "source_tagids": [ + 136, + 1 + ], + "source_type": 11, + "tag_phrases": [ + "chất bán dẫn", + "chuỗi cung ứng", + "chip", + "đạo luật", + "nghiên cứu phát triển", + "lắp ráp", + "nhân lực" + ], + "title": "Thấy gì từ các đạo luật CHIPS và sự ảnh hưởng tới nguồn nhân lực thiết kế chip tại Việt Nam", + "url": "https://ictvietnam.vn/thay-gi-tu-cac-dao-luat-chips-va-su-anh-huong-toi-nguon-nhan-luc-thiet-ke-chip-tai-viet-nam-20220805215753897.htm", + "attachment_types": [], + "attachment_urls": [], + "created_time": 1659742200, + "lang": "vi" + }, + { + "actor_name": "AN CHI", + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "diendandoanhnghiep.vn", + "id": "5e369e7232ea75f443848c03c2681f9a18e4587a", + "message": ">>Thượng viện Hoa Kỳ sẽ sớm thông qua Đạo luật CHIPS trị giá 52 tỷ USD \n Các nhà sản xuất chip đang rất hào hứng trước việc Washington đã thông qua Đạo luật CHIPS giúp cung cấp tài chính cho ngành công nghiệp bán dẫn của Mỹ, nhưng việc này cũng đồng nghĩa với việc trong tương lai, cánh cửa đầu tư vào Trung Quốc của họ đã bị đóng lại.\n Liệu đây có phải là cái giá mà những công ty như Intel, TSMC và Samsung sẽ sẵn sàng trả?\n Đạo luật Khoa học và CHIPS có tổng giá trị 280 tỷ USD được lưỡng viện Hoa Kỳ vừa thông qua, trong đó dành 52 tỷ USD nhằm hỗ trợ cho ngành công nghiệp bán dẫn. Nhưng điều này đồng nghĩa rằng các công ty nhận hỗ trợ từ gói này sẽ bị hạn chế, nếu không muốn nói là không thể thực hiện “các hợp đồng quan trọng” để mở rộng các nhà máy sản xuất ở Trung Quốc hay bất kỳ một quốc gia nào khác trong vòng 10 năm tới.\n Chất bán dẫn là đấu trường quan trọng giữa Washington và Bắc Kinh. Những con chip nhỏ bé nhưng lại đóng vai trò là bộ não của các thiết bị điện tử, từ điện thoại thông minh, máy tính xách tay đến trung tâm dữ liệu, cho đến các hệ thống vũ khí tinh vi, chẳng hạn như tên lửa chống tăng Javelin mà Mỹ đang cung cấp cho Ukraine.\n Mặc dù trên lý thuyết thì các nhà sản xuất chip vẫn có thể duy trì hoạt động kinh doanh hiện tại của họ ở Trung Quốc, nhưng theo các nhà phân tích, các điều khoản của đạo luật tạo ra rất nhiều “bẫy” cho các công ty và trên thực tế, có thể những công ty này buộc phải lựa chọn giữa Mỹ và Trung Quốc.\n Đạo luật CHIPS sẽ cho phép các nhà sản xuất chip tiếp tục đầu tư vào Trung Quốc nếu những khoản đầu tư đó nhằm bảo vệ các lợi ích kinh doanh hiện có và quan trọng ở nước này, nhưng những ngoại lệ này chỉ áp dụng cho việc mở rộng các cơ sở hiện có và chỉ cho \"những loại chất bán dẫn đặc biệt\". Những chất bán dẫn đặc biệt nói trên là các công nghệ chip 28 nanomet trở lên. Công nghệ nanomet được sử dụng để đề cập đến chiều rộng dòng giữa các bóng bán dẫn trên chip. Con số này càng nhỏ thì chip càng cao cấp. Chẳng hạn, bộ vi xử lý lõi 13 của iPhone sử dụng các nút 5nm. Và hiện tại, Intel và Qualcomm là hai doanh nghiệp thống trị trên thị trường bộ vi xử lý lõi cao cấp tại Trung Quốc.\n Theo luật sư Albayrak từ Công ty luật Reed Smith LLP, các ngoại lệ của đạo luật đối với các khoản đầu tư vào Trung Quốc là nhằm tránh sự gián đoạn đột ngột đối với hoạt động kinh doanh của các doanh nghiệp Hoa Kỳ. Ông nói: “Điều này không làm suy yếu hàng rào bảo vệ của Hoa Kỳ, mà là hành động cân bằng cần thiết trong việc theo đuổi mục tiêu chính sách là giữ lợi thế về công nghệ, đồng thời giảm thiểu thiệt hại tài sản thế chấp của Hoa Kỳ.”\n Chủ tịch Hạ viện Hoa Kỳ Nancy Pelosi ký Đạo luật Khoa học và CHIPS tại Washington vào ngày 29 tháng 7. Dự luật được thông qua với sự ủng hộ hiếm hoi của lưỡng đảng \n Có rất nhiều tập đoàn đa quốc gia hiện đang sản xuất chip như vậy ở Trung Quốc. TSMC có nhà máy ở Nam Kinh hiện đang sản xuất chip 16 nm và 28 nm, trong khi Samsung có quy mô sản xuất chip nhớ lớn ở Tây An, tỉnh Thiểm Tây, SK Hynix có các cơ sở chip nhớ ở Vô Tích và Đại Liên, Intel và Micron của Mỹ đều có cơ sở đóng gói và thử nghiệm chip ở Trung Quốc.\n >>TSMC và cuộc cạnh tranh chip Mỹ- Trung \n Các hạn chế của Đạo luật CHIPS  thoạt nhìn dường như không gây khó khăn, hoặc là rất ít nếu bất kỳ một nhà sản xuất chip lớn nào có kế hoạch sản xuất các sản phẩm tiên tiến nhất của họ ở Trung Quốc, ít nhất là trong tương lai gần. Tuy nhiên, các luật sư cảnh báo rằng các công ty nên xem xét các hạn chế đầu tư một cách nghiêm túc. Luật sư Clinton Yu từ Công ty luật Barnes & Thornburg có trụ sở tại Washington nhận định: \"Các hình phạt có thể không chỉ làm mất nguồn tài trợ mà còn các hạn chế khác vì lợi ích quốc gia”\n Trong khi đó, một nguyên nhân gây lo ngại khác, theo ông Martijn Rasser - thành viên cấp cao và là giám đốc tại Trung tâm An ninh mới của Mỹ, là các hạn chế có thể là bước dạo đầu cho việc giám sát nhiều hơn các khoản đầu tư ra nước ngoài của các nhà sản xuất chip. Ông Rasser nhận định: “Những hạn chế này nhấn mạnh rằng các nhà hoạch định chính sách của Mỹ đang ngày càng lo ngại về việc các nguồn tài chính của Mỹ đang gián tiếp hỗ trợ việc củng cố năng lực sản xuất công nghệ ở Trung Quốc”.\n Trên thực tế, các nhà sản xuất chip đã hoan nghênh việc thông qua đạo luật. Sau khi Đạo luật được thông qua, một số “ông lớn” đã cam kết đầu tư vào Mỹ, chẳng hạn TSMC với quy mô ít nhất 12 tỷ USD ở Arizona và 17 tỷ USD của Samsung ở Texas, hay SK Hynix và kế hoạch đầu tư trị giá 15 tỷ USD vào các công ty Mỹ của Mỹ là Intel và Micron.\n Thế nhưng, ngoài các khoản trợ cấp, có một lý do khác khiến các công ty chip có thể muốn mở rộng ở Mỹ có liên quan tới tham vọng chip của riêng Trung Quốc: Bắc Kinh đã lên kế hoạch nâng thị phần chip tự chế của nước này lên 70% vào năm 2025. \"Về lâu dài, tham vọng của Trung Quốc thực sự là thay thế tất cả các chip tiên tiến bằng chip sản xuất trong nước. Vì vậy, sẽ có một câu hỏi là liệu TSMC và Samsung có thể thực sự tiếp tục thống trị ngành sản xuất cao cấp ở Trung Quốc hay không\", Louis Lau, giám đốc đầu tư của Quỹ đầu tư Brandes Investment Partners nhận định.\n Về phía mình, Trung Quốc đã phản ứng trước việc thông qua đạo luật CHIPS bằng cách nói rằng họ kiên quyết chống lại các điều khoản hạn chế sự hợp tác \"bình thường về khoa học công nghệ\" giữa hai nước. Nhưng bất chấp những phản ứng có vẻ mạnh mẽ này, không nhiều người cho rằng Bắc Kinh sẽ trả đũa ngay lập tức, do hiện tại quốc gia này vẫn phụ thuộc vào chất bán dẫn nhập khẩu từ nước ngoài.\n \"Tôi nghĩ rằng hiện nay Trung Quốc chưa có đủ tư cách để trừng phạt các công ty. Có thể sau 5, 10 năm nữa ... nếu tình hình chuyển biến và các công ty Trung Quốc đủ năng lực để cung cấp hầu hết các chất bán dẫn cho nhu cầu nội địa mà không cần phải dựa vào TSMC và Samsung, Bắc Kinh rất có thể áp dụng các lệnh trừng phạt các công ty lấy tiền của chính phủ Mỹ.\n \r\n \r\n \r\n\t \r\n \r\n Từ khóa \r\n \r\n \r\n\t\t\t \r\n \r\n\t\t\t\t\t\t \r\n Mỹ - Trung \r\n \r\n\t\t\t\t\t\t \r\n công nghệ \r\n \r\n\t\t\t\t\t\t \r\n sản xuất chip \r\n \r\n\t\t\t\t\t\t \r\n \r\n\t\t\t \r\n\t \r\n \r\n Đánh giá của bạn: \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n\t\t\t\t\r\n\r\n \r\n \r\n Từ khóa \r\n \r\n \r\n \r\n \r\n \r\n Mỹ - Trung \r\n \r\n \r\n công nghệ \r\n \r\n \r\n sản xuất chip", + "snippet": "Các nhà sản xuất chip đang rất hào hứng trước việc Washington đã thông qua Đạo luật CHIPS giúp cung cấp tài chính cho ngành công nghiệp bán dẫn của Mỹ", + "source_tagids": [ + 136 + ], + "source_type": 11, + "tag_phrases": [ + "Mỹ - Trung", + "công nghệ", + "sản xuất chip" + ], + "title": "Đạo luật CHIPS khiến các nhà sản xuất chip phải đối mặt với sự lựa chọn giữa Mỹ và Trung Quốc | Khoa Học - Công nghệ", + "url": "https://diendandoanhnghiep.vn/dao-luat-chips-khien-cac-nha-san-xuat-chip-phai-doi-mat-voi-su-lua-chon-giua-my-va-trung-quoc-228482.html", + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://diendandoanhnghiep.vn/media/uploaded/466/2022/08/08/E76CD972-7855-4B0A-B13E-4A59651E1F2C.jpeg" + ], + "created_time": 1659987460, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer", + "Icomm.NewsCrawl.SmartReader" + ], + "domain": "vietnamplus.vn", + "id": "5ea15f93af148341cf46a6f3271937673a8d3d63", + "message": "Người phát ngôn Bộ Thương mại Trung Quốc Shu Jueting. (Ảnh: CFP) \n\n Ngày 18/8,  Bộ Thương mại Trung Quốc  đã bày tỏ sự phản đối Đạo luật Khoa học và CHIP của Mỹ, cho rằng văn kiện này có các điều khoản hạn chế các hoạt động kinh tế, thương mại và đầu tư bình thường của các công ty liên quan ở Trung Quốc, cũng như sẽ ảnh hưởng tiêu cực tới chuỗi cung ứng chất bán dẫn toàn cầu và thương mại quốc tế. \n\n Phát biểu tại cuộc họp báo, người phát ngôn Bộ Thương mại Trung Quốc Shu Jueting cho rằng luật trên của Mỹ nên được thực hiện phù hợp với các quy tắc liên quan của Tổ chức Thương mại thế giới (WTO) và các nguyên tắc cởi mở, minh bạch và không phân biệt đối xử, đồng thời có lợi cho việc duy trì an ninh và ổn định của chuỗi cung ứng và công nghiệp toàn cầu.\n\n Bà Shu Jueting cũng cho biết Trung Quốc kiên quyết phản đối đạo luật trên và sẽ tiếp tục theo dõi tiến độ thực hiện, đồng thời sẽ thực hiện các biện pháp mạnh mẽ để bảo vệ các quyền và lợi ích hợp pháp của nước này nếu cần thiết.\n\n [Bloomberg: Mỹ thay đổi chiến lược cạnh tranh công nghệ với Trung Quốc] \n\n Theo Đạo luật Khoa học và CHIP, Mỹ sẽ dành 280 tỷ USD trong 10 năm tới cho lĩnh vực sản xuất chip và nghiên cứu khoa học.\n\n Trong số này, 52 tỷ USD sẽ dành riêng cho ngành sản xuất chip, trong đó 39 tỷ USD sẽ được phân bổ cho \"các ưu đãi trực tiếp nhằm kích thích sản xuất\" để thúc đẩy việc xây dựng và mở rộng các nhà máy sản xuất bán dẫn.\n\n Số tiền này sẽ được phân bổ trong 5 năm, với 19 tỷ USD được giải ngân trong năm nay và 5 tỷ USD mỗi năm tới năm 2026.\n\n Đạo luật này được thông qua đánh dấu sự đồng thuận hiếm hoi của lưỡng viện Quốc hội Mỹ, khi các nghị sỹ thuộc cả hai đảng Dân chủ và Cộng hòa đều đánh giá luật này là cần thiết để giúp Mỹ cạnh trạnh kinh tế với Trung Quốc, cũng như tăng cường an ninh quốc gia./.", + "snippet": "Aug 18, 2022 ... Trung Quoc kien quyet phan doi Dao luat Khoa hoc va CHIP cua My hinh anh ... Theo Đạo luật Khoa học và CHIP, Mỹ sẽ dành 280 tỷ USD trong 10 năm tới cho lĩnh ...", + "source_tagids": [ + 136, + 1, + 235, + 238, + 260 + ], + "source_type": 11, + "title": "Trung Quốc kiên quyết phản đối Đạo luật Khoa học và CHIP của Mỹ ...", + "url": "https://www.vietnamplus.vn/trung-quoc-kien-quyet-phan-doi-dao-luat-khoa-hoc-va-chip-cua-my/811881.vnp", + "attachment_farm_urls": [], + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://cdnimg.vietnamplus.vn/t620/uploaded/bokttj/2022_08_18/shu_jueting.png" + ], + "created_time": 61966141198, + "lang": "vi" + }, + { + "actor_name": "Đăng Khoa", + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "viettimes.vn", + "id": "721e51e15b529fa1472ee22235f56e63a7c38ffd", + "message": "Các nhà sản xuất chip đang hoan nghênh việc Washington thông qua Đạo luật được chờ đợi từ lâu để cung cấp tài chính cho ngành công nghiệp bán dẫn của Mỹ, nhưng việc chấp nhận các khoản trợ cấp đó có thể khiến họ bó tay khi đầu tư vào Trung Quốc trong tương lai.\n Đó có phải là mức giá mà những công ty như Intel, TSMC và Samsung sẽ sẵn sàng trả?\n Đạo luật \"Khoa học và Chip\", với gói tài trợ 280 tỉ USD được cả hai viện của Quốc hội thông qua vào tuần trước , chứa 52 tỉ USD hỗ trợ cho ngành công nghiệp bán dẫn. Nhưng nó cũng chỉ rõ rằng các công ty chấp nhận trợ cấp sẽ bị hạn chế thực hiện bất kỳ \"giao dịch quan trọng\" nào để mở rộng năng lực sản xuất chip của họ ở Trung Quốc hoặc bất kỳ quốc gia nước ngoài nào khác mà họ quan tâm trong 10 năm.\n Mặc dù dường như các nhà sản xuất chip có thể bảo vệ hoạt động kinh doanh hiện tại của họ ở Trung Quốc, nhưng các nhà phân tích và luật sư nói với phóng viên Nikkei Asia rằng các điều khoản của đạo luật tạo ra một \"bãi mìn\" cho các công ty, và trên thực tế có thể buộc họ phải lựa chọn giữa Mỹ và Trung Quốc.\n Chip bán dẫn là chiến trường quan trọng giữa Washington và Bắc Kinh. Chúng đóng vai trò là bộ não của các thiết bị điện tử, từ điện thoại thông minh, máy tính xách tay đến trung tâm dữ liệu, và chúng cũng đóng vai trò quan trọng trong các hệ thống vũ khí tinh vi, chẳng hạn như tên lửa chống tăng Javelin mà Mỹ đang cung cấp cho Ukraine.\n Chủ tịch Hạ viện Hoa Kỳ Nancy Pelosi ký Đạo luật Khoa học và Chip tại Washington vào ngày 29.7. Đây là một dự luật hiếm hoi được cả hai đảng ủng hộ (ảnh: AP)\n Đạo luật \"Khoa học và Chip\" vẫn có những ngoại lệ, cho phép các nhà sản xuất tiếp tục đầu tư vào Trung Quốc nếu các khoản đầu tư đó nhằm bảo vệ các lợi ích kinh doanh hiện có và quan trọng ở quốc gia này. Nhưng những ngoại lệ này chỉ áp dụng cho việc mở rộng các cơ sở hiện có và chỉ cho \"các loại chip cấp thấp\".\n Theo luật sư Tan Albayrak của công ty Reed Smith LLP, các loại chip cấp thấp ám chỉ chip được sản xuất với tiến trình 28 nanomet trở lên.\n Kích thước nanomet đề cập đến chiều rộng dòng giữa các bóng bán dẫn trên chip. Nói chung con số càng nhỏ thì chip càng cao cấp ( chip cao cấp nhất hiện nay được sản xuất trên tiến trình 5 nanomet, và chỉ có 2 công ty là TSMC và Samsung Electronics làm được - PV ).\n Tan Albayrak nói rằng các ngoại lệ nói trên nhằm giúp các công ty Mỹ tránh sự gián đoạn đột ngột trong hoạt động kinh doanh tại Trung Quốc.\n \"Điều này không làm suy yếu hàng rào bảo vệ của Hoa Kỳ, mà là hành động cân bằng cần thiết trong việc theo đuổi mục tiêu giữ lợi thế về công nghệ, đồng thời giảm thiểu thiệt hại cho các công ty Hoa Kỳ\", ông Tan nói.\n Các chip cấp thấp thường được sử dụng trong nhiều loại thiết bị điện tử, từ điện thoại thông minh, máy tính đến thiết bị gia dụng và ô tô. Chúng thường được coi là những con chip cơ bản và nhu cầu về loại chip này lớn hơn nhiều so với chip cao cấp.\n Nhiều \"ông lớn\" toàn cầu đang sản xuất những con chip như vậy ở Trung Quốc. Công ty TSMC của Đài Loan có nhà máy ở Nam Kinh hiện đang sản xuất chip 16 nanomet và 28 nanomet, trong khi Samsung có nhà máy sản xuất chip nhớ (memory chip) ở thành phố Tây An, tỉnh Thiểm Tây. SK Hynix có các cơ sở sản xuất chip nhớ ở Vô Tích và Đại Liên. Intel và Micron của Mỹ đều có cơ sở đóng gói và thử nghiệm chip ở Trung Quốc.\n Các hạn chế của Đạo luật \"Khoa học và Chip\" thoạt nhìn có thể không gây nhiều khó khăn cho các công ty lớn muốn sản xuất dòng chip tiến tiến nhất của họ ở Trung Quốc, ít nhất không phải trong tương lai gần. Bởi nếu họ không nhận khoản tài trợ từ chính phủ Mỹ, họ vẫn có thể tự do sản xuất chip cao cấp ở Trung Quốc.\n Khi được phóng viên Nikkei Asia hỏi về vấn đề này, đại diện TSMC và Intel đã không đưa ra bình luận cụ thể nào, mặc dù Intel nói rằng khi thông qua đạo luật, lưỡng viện đã công nhận rằng Mỹ đang cạnh tranh với các quốc gia khác về vị trí dẫn đầu ngành công nghệ.\n SK Hynix nói với Nikkei Asia: \"Công ty chúng tôi tuân thủ các quy định tại các quốc gia nơi chúng tôi kinh doanh. Chúng tôi sẽ ứng phó linh hoạt với hoàn cảnh thị trường trong kế hoạch đầu tư và sản xuất của mình.\"\n Còn Samsung thì từ chối bình luận về ảnh hưởng của Đạo luật.\n Tuy nhiên, một số luật sư cảnh báo rằng các công ty nên xem xét các điều khoản hạn chế trong Đạo luật một cách nghiêm túc. Ông Clinton Yu, chuyên gia về thương mại quốc tế và kiểm soát xuất khẩu của hãng luật thương mại Barnes & Thornburg cho biết: \"Các hạn chế không những khiến các công ty mất nguồn tài trợ, mà còn có các hình phạt khác dựa trên lợi ích quốc gia. \" \n Một yếu tố khác gây lo ngại, theo ông Martijn Rasser - Giám đốc Trung tâm New American Security, là các hạn chế có thể là bước dạo đầu cho việc giám sát kỹ hơn các khoản đầu tư ra nước ngoài của các nhà sản xuất chip.\n Ông Rasser nói với Nikkei Asia: “Những hạn chế này nhấn mạnh rằng các nhà hoạch định chính sách của Mỹ đang ngày càng lo ngại về việc tiền của Mỹ lại hỗ trợ xây dựng năng lực cho Trung Quốc.\"\n Một cách công khai, các nhà sản xuất chip đã hoan nghênh hai viện quốc hội Mỹ thông qua Đạo luật. Một số đã cam kết đầu tư vào Mỹ: TSMC sẽ đầu tư 12 tỉ USD xây dựng một nhà máy ở Arizona và Samsung sẽ xây dựng một nhà máy trị giá 17 tỉ USD ở Texas . Hynix tuần trước đã công bố kế hoạch đầu tư trị giá 15 tỷ USD vào Mỹ. Hai công ty của Mỹ là Intel và Micron cũng đang tăng cường đầu tư.\n Trước đó, một số nhà sản xuất chip đã cảnh báo rằng nếu Đạo luật \"Khoa học và Chip\" không được thông qua thì sẽ ảnh hưởng đến các kế hoạch đầu tư của họ. Ông Morris Chang, nhà sáng lập TSMC cũng than phiền về \"sự hỗ trợ ở quy mô nhỏ\" mà Hoa Kỳ dành cho công ty.\n Một công nhân tại nhà máy sản xuất chip của TSMC ở Đài Loan (ảnh: TSMC)\n Nhưng ngoài tiền tài trợ, có một lý do khác khiến các công ty sản xuất chip muốn mở rộng sản xuất ở Mỹ - đó là tham vọng tự sản xuất chip của Trung Quốc. Bắc Kinh đã đặt mục tiêu thị phần chip tự sản xuất của mình lên 70% vào năm 2025.\n \"Về lâu dài, tham vọng của Trung Quốc là thay thế tất cả các chip tiên tiến bằng chip sản xuất trong nước. Vì vậy, sẽ có một câu hỏi là liệu TSMC và Samsung còn có thể tiếp tục thống trị ngành sản xuất chip cao cấp ở Trung Quốc hay không,\" ông Louis Lau, Giám đốc đầu tư của Brandes Investment Partners nhận định. \"Tôi nghĩ Mỹ là một khách hàng tiềm năng hơn vì các nhà sản xuất chip trong nước rất yếu và họ từ lâu đã mất lợi thế trong lĩnh vực sản xuất.\"\n Trung Quốc đã phản ứng trước việc Hoa Kỳ thông qua Đạo luật \"Khoa học và Chip\". Nước này tuyên bố họ kiên quyết chống lại các điều khoản hạn chế sự hợp tác \"bình thường về khoa học công nghệ\" giữa hai nước. Nhưng bất chấp những lời phản đối mạnh mẽ của Trung Quốc, nước này ít khả năng sẽ đưa ra các biện pháp trả đũa ngay lập tức, do phụ thuộc vào chất bán dẫn nước ngoài.\n \"Tôi nghĩ rằng Trung Quốc chưa có đủ tư cách để trừng phạt các công ty nước ngoài. Có thể sau 5, 10 năm nữa... nếu các công ty Trung Quốc cung cấp hầu hết các chất bán dẫn cho nhu cầu nội địa, và họ không cần phải dựa vào TSMC và Samsung. Lúc đó Bắc Kinh có thể trừng phạt các công ty đã nhận tiền tài trợ của chính phủ Mỹ,\" ông Louis Lau nói.\n Trong khi đó, các nhà sản xuất chip phải đối mặt với một câu hỏi trực tiếp hơn: Trong một ngành công nghiệp mà các khoản đầu tư thường được tính bằng tỉ USD, liệu 52 tỉ USD có đủ không?\n Chỉ 39 tỉ USD tài trợ của Đạo luật \"Khoa học và Chip\" sẽ dành cho lĩnh vực sản xuất chip, trong khi 13 tỉ USD sẽ được phân bổ cho nghiên cứu phát triển và đổi mới sáng tạo. Tuy nhiên, việc xây dựng các nhà máy sản xuất chất bán dẫn không chỉ đơn giản là một cơ sở sản xuất, nó còn liên quan đến một mạng lưới cung cấp khổng lồ: hàng trăm loại hóa chất và vật liệu, cũng như thiết bị sản xuất chip và các bộ phận tiêu hao.\n Trong khi đó, hãng Consultancy Bain ước tính rằng việc tăng sản lượng chip của Mỹ từ 5% đến 10% sẽ cần khoảng 40 tỉ USD. Việc tài trợ cho 10 năm tiếp theo để phát triển các công nghệ mới sẽ còn đắt hơn, trị giá khoảng 110 tỉ USD.\n Ông Peter Hanbury, chuyên gia đối tác của Consultancy Bain nhận định: “52 tỉ USD chắc chắn sẽ là nguồn tài trợ cho cả hai nỗ lực này ( tăng sản lượng chip và phát triển các công nghệ mới - PV ), nhưng nó không hề đủ cho cả hai.\" \n “Xây dựng lại hệ sinh thái bán dẫn là một công việc đắt giá,\" ông nói.\n Đạo luật \"Khoa học và Chip\" cho thấy nền kinh tế Mỹ có sự định hướng của chính phủ", + "snippet": "VietTimes – Đạo luật \"Khoa học và Chip\" được hai viện Quốc hội Mỹ thông qua vào tuần trước cho phép các công ty sản xuất chip nhận tài trợ từ chính phủ Mỹ, nhưng đổi lại họ không được phép mở rộng sản xuất tại Trung Quốc.", + "source_tagids": [ + 1 + ], + "source_type": 11, + "tag_phrases": [ + "Đạo luật Khoa học và Chip", + "dự luật Khoa học và Chip", + "chip bán dẫn", + "Hoa Kỳ", + "Trung Quốc", + "cuộc chiến công nghệ Mỹ - Trung", + "sản xuất chip bán dẫn" + ], + "title": "Đạo luật \"Khoa học và Chip\" khiến các nhà sản xuất chip phải lựa chọn giữa Mỹ và Trung Quốc", + "url": "https://viettimes.vn/dao-luat-khoa-hoc-va-chip-khien-cac-nha-san-xuat-chip-phai-lua-chon-giua-my-va-trung-quoc-post159304.html", + "attachment_types": [ + "image", + "image", + "image", + "image", + "image" + ], + "attachment_urls": [ + "https://photo-cms-viettimes.zadn.vn/w666/Uploaded/2022/livospwi/2022_08_05/nancy-pelosi-ky-dao-luat-chip-220.jpg", + "https://photo-cms-viettimes.zadn.vn/Uploaded/2022/livospwi/2022_08_05/nancy-pelosi-ky-dao-luat-chip-220.jpg", + "https://photo-cms-viettimes.zadn.vn/w666/Uploaded/2022/livospwi/2022_08_05/cong-nhan-nha-may-tsmc-4609.jpg", + "https://photo-cms-viettimes.zadn.vn/Uploaded/2022/livospwi/2022_08_05/cong-nhan-nha-may-tsmc-4609.jpg", + "https://photo-cms-viettimes.zadn.vn/160x120/Uploaded/2022/livospwi/2022_08_04/nha-may-san-xuat-chip-tai-my-9255.jpg" + ], + "created_time": 1659660600, + "lang": "vi" + }, + { + "actor_name": "An Nguyễn (P/v TTXVN tại Kuala Lumpur)", + "categories": [ + "Trang chủ", + "Xe & Công nghệ", + "Công nghệ" + ], + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "bnews.vn", + "id": "72c1e6ee416f2a62681b99ef681892964bd8362d", + "message": "BNEWS \r\n Ngành bán dẫn Malaysia vốn chiếm 13% thị phần lắp ráp và thử nghiệm chip toàn cầu sẽ được hưởng lợi từ Đạo luật Khoa học và Chip của Mỹ đã được Tổng thống Joe Biden ký ngày 9/8.\r\n \r\n\r\n\r\n  Trong tương lai, tổng doanh số bán dẫn toàn cầu dự kiến sẽ tăng với tốc độ tăng trưởng kép hàng năm là 7,1% trong 5 năm tới. Ảnh minh họa: ais.gov.vn Trong đó, có 52,7 tỷ USD hỗ trợ sản xuất và nghiên cứu chất bán dẫn tại Mỹ. Chủ tịch Hiệp hội Công nghiệp Bán dẫn Malaysia (MSIA) Datuk Seri Wong Siew Hai cho rằng, với đạo luật này, nền kinh tế lớn nhất thế giới dự kiến sẽ xây dựng các nhà máy chế tạo chip (fab) hiện đại với quy trình công nghệ từ 7 nanomet trở xuống. \n   Theo ông Wong, việc xây dựng thêm các nhà máy hàng đầu như vậy sẽ đòi hỏi Mỹ cần thêm nhiều dịch vụ lắp ráp và thử nghiệm, do công suất hiện tại sẽ không đủ đáp ứng cho công suất của chế tạo chip mới. Từ góc độ đó, Malaysia sẽ được hưởng lợi do là một trong những địa điểm đầu tư hấp dẫn và cạnh tranh nhất so với các nước Đông Nam Á khác. Chia sẻ với báo giới, ông nhận định điều này có được là nhờ Malaysia với 50 năm kinh nghiệm trong ngành, chính phủ thân thiện với doanh nghiệp, cơ sở hạ tầng tốt và nhân tài, cũng như lực lượng lao động nói có khả năng sử dụng tiếng Anh. \n Ông cũng bác bỏ những lo ngại về việc đạo luật có thể ảnh hưởng đến khả năng cạnh tranh của ngành chế tạo chíp của Malaysia, vì cho rằng Malaysia hiện không có các nhà máy tiên tiến để có thể cạnh tranh trong lĩnh vực này. Trong khi công nghệ mới dự kiến sẽ được chuyển sang phân khúc lắp ráp và thử nghiệm sau khi thành lập các trung tâm mới ở Mỹ, Chủ tịch MSIA kỳ vọng chính phủ có thể khuyến khích các công ty ở Malaysia phát triển để cạnh tranh với các công ty cùng ngành ở Đông Nam Á. Ông cũng cho rằng thay vì liên tục tập trung vào các công nghệ lắp ráp và thử nghiệm cũng như các lĩnh vực thiết bị và giải pháp tự động hóa, chính phủ nên nỗ lực thu hút nhiều đầu tư lớn hơn vào Malaysia, do hiện nay nhiều công ty đã bắt đầu thiết kế mạch tích hợp. \n Tuy nhiên, khi đề cập đến khả năng cạnh tranh, ông Wong bày tỏ lo ngại về quy định áp thuế doanh nghiệp tối thiểu 15%, dự kiến sẽ được thực hiện trên toàn cầu vào năm 2023 nhằm đảm bảo các công ty đa quốc gia (MNC) nộp đúng số thuế mà không tính đến địa điểm hoạt động. Ông Wong cho biết Malaysia mới đây đã đồng ý về nguyên tắc thực hiện chế độ thuế này đối với một số MNC. Điều này sẽ đặt ra nhiều thách thức đối với Malaysia trong thu hút đầu tư nước ngoài khi mọi quốc gia đều đưa ra mức thuế doanh nghiệp 15%. Trích dẫn dự báo thị trường công nghiệp, ông cho rằng trong tương lai tổng doanh số bán dẫn toàn cầu dự kiến sẽ tăng với tốc độ tăng trưởng kép hàng năm là 7,1% trong 5 năm tới. Điều này có thể được thúc đẩy bởi nhu cầu cao hơn từ các ngành như ô tô, điện toán đám mây, 5G, hàng không vũ trụ, thiết bị y tế và trí tuệ nhân tạo./.\n Xem thêm:\n >> Mỹ kỳ vọng đạo luật 280 tỷ USD sẽ thúc đẩy lĩnh vực bán dẫn", + "snippet": "Ngành bán dẫn Malaysia vốn chiếm 13% thị phần lắp ráp và thử nghiệm chip toàn cầu sẽ được hưởng lợi từ Đạo luật Khoa học và Chip của Mỹ đã được Tổng thống Joe Biden ký ngày 9/8.", + "source_type": 11, + "tag_phrases": [ + "Ngành bán dẫn", + "Malaysia", + "chip", + "Đạo luật Khoa học và Chip", + "Mỹ", + "Tổng thống Joe Biden" + ], + "title": "Ngành bán dẫn Malaysia hưởng lợi từ Đạo luật Khoa học và Chip của Mỹ", + "url": "https://bnews.vn/nganh-ban-dan-malaysia-huong-loi-tu-dao-luat-khoa-hoc-va-chip-cua-my/254940.html", + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://image.bnews.vn/MediaUpload/Org/2022/03/31/dam-may-281021-20220331094021.jpg" + ], + "created_time": 1660615140, + "lang": "vi" + }, + { + "actor_name": "H.Hà (Theo Reuters, CNBC)", + "categories": [ + "Trang chủ", + "Thế giới", + "Tin tức" + ], + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "dangcongsan.vn", + "id": "756a018f73a0ba2f8fb9fbde367f57893a9c7209", + "message": "');this.closest('table').remove();\"> \r\n \r\n \r\n \r\n \r\n \r\n Tổng thống Mỹ Joe Biden ký thông qua dự luật lưỡng đảng thúc đẩy sản xuất chất bán dẫn tại \r\n Nhà Trắng. (Ảnh: AFP/Getty Images) \r\n \r\n \r\n \r\n \r\nĐạo luật mang tên \"Chip và Khoa học\" bao gồm khoản trợ cấp trị giá 52,7 tỷ USD cho hoạt động sản xuất chất bán dẫn - vốn được sử dụng trong mọi sản phẩm điện tử, từ ô tô và vũ khí công nghệ cao đến các thiết bị công nghệ và trò chơi điện tử. Đạo luật cũng sẽ bao gồm khoản tín dụng thuế đầu tư 25% cho các nhà máy chip, ước tính trị giá 24 tỷ USD.\r\n\n\r\n Ngoài ra, đạo luật cũng cho phép chi 200 tỷ USD trong 10 năm để thúc đẩy hoạt động nghiên cứu khoa học của Mỹ nhằm cạnh tranh tốt hơn với Trung Quốc trong lĩnh vực khoa học công nghệ.\n\r\n Tại lễ ký kết, Tổng thống Joe Biden đã thông báo về các khoản đầu tư vào các công ty chip đang thực hiện mặc dù vẫn chưa rõ khi nào Bộ Thương mại nước này sẽ thông báo về các quy tắc để xem xét các gói tài trợ và thời gian bảo lãnh các dự án.\n\r\n Đạo luật được thông qua nhằm giải quyết tình trạng thiếu hụt chip, vốn đang ảnh hưởng đến các ngành sản xuất. Đạo luật trên được xem là một bước đột phá lớn hiếm hoi trong chính sách công nghiệp của Mỹ.\n\r\n “Hôm nay là một ngày dành cho những nhà xây dựng. Hôm nay nước Mỹ đang chuyển giao”, Tổng thống Joe Biden nói tại lễ ký kết bên ngoài Nhà Trắng. Lễ ký kết có sự tham dự của hàng trăm người, bao gồm các giám đốc điều hành các công ty công nghệ hàng đầu nước Mỹ như, giám đốc điều hành của Micron, Intel, Lockheed Martin, HP và Advanced Micro Devices, các thống đốc và thị trưởng thành phố, cùng các nhà lập pháp lưỡng đảng.\n\r\n “Tương lai sẽ được tạo ra ở Mỹ”, ông Joe Biden nói, đồng thời gọi đạo luật này là “khoản đầu tư duy nhất trong một thế hệ vào chính nước Mỹ”. Phát biểu tại Nhà Trắng, Tổng thống Joe Biden cho biết “đạo luật này sẽ giúp nước Mỹ giành thắng lợi trong cuộc cạnh tranh về kinh tế trong thế kỷ 21”.\n\r\n Sau khi dự luật được thông qua, Nhà Trắng đề cập việc Micron, một nhà sản xuất chip lớn của Mỹ, sẽ công bố kế hoạch 40 tỷ USD để tăng sản lượng chip trong nước, việc này sẽ mang lại 8.000 việc làm mới và góp phần tăng thị phần sản xuất chip tại Mỹ từ mức 2% lên 10%. Trong khi Qualcomm và Global Foundries sẽ công bố kế hoạch 4,2 tỷ USD mở rộng nhà máy sản xuất chip ở New York.\n\r\n Lãnh đạo phe đa số tại Thượng viện Chuck Schumer gọi đạo luật là \"khoản đầu tư lớn nhất vào khoa học sản xuất và đổi mới trong nhiều thập kỷ\".\n\r\n Theo Nhà Trắng, hiện, Mỹ chỉ sản xuất khoảng 10% nguồn cung chất bán dẫn của thế giới, trong khi Đông Á chiếm tới 75% sản lượng chip toàn cầu./.\n H.Hà (Theo Reuters, CNBC)", + "snippet": "(ĐCSVN) – Ngày 9 8, Tổng thống Joe Biden đã ký thông qua dự luật lưỡng đảng, cung cấp hàng tỷ USD cho việc nghiên cứu và sản xuất chất bán dẫn nhằm thúc đẩy ngành bán dẫn của Mỹ cạnh tranh với các sáng kiến khoa học và công nghệ của Trung Quốc.", + "source_tagids": [ + 136, + 1 + ], + "source_type": 11, + "title": "Tổng thống Mỹ ký dự luật thúc đẩy sản xuất chất bán dẫn", + "url": "https://dangcongsan.vn/the-gioi/tin-tuc/tong-thong-my-ky-du-luat-thuc-day-san-xuat-chat-ban-dan-617132.html", + "attachment_types": [ + "image", + "image", + "image", + "image", + "image" + ], + "attachment_urls": [ + "https://dangcongsan.vn/image/images/left.png", + "https://dangcongsan.vn/image/images/center.png", + "https://dangcongsan.vn/image/images/right.png", + "https://dangcongsan.vn/images/red-error_16px.gif", + "https://file1.dangcongsan.vn/data/0/images/2022/08/10/hanhts/107101127-1660057423600-getty-1242401644-afp-32ga2pa.jpeg?dpi=150&quality=100&w=780" + ], + "created_time": 1660123260, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "congnghe.tuoitre.vn", + "id": "7e6fd57312ec97ca004d3bf007315b3c97550b45", + "message": "Tổng thống Mỹ ký thông qua Đạo luật chip và khoa học 2022 tại Nhà Trắng ngày 9-8 - Ảnh: REUTERS\n \"Tương lai sẽ được tạo ra ở nước Mỹ\", Hãng tin Reuters dẫn lời ông Biden nói và gọi đạo luật là \"khoản đầu tư chỉ có 1 lần trong đời cho nước Mỹ\".\n Theo đó, Đạo luật chip và khoa học 2022, bao gồm khoản trợ cấp 52 tỉ USD cho hoạt động nghiên cứu và sản xuất chất bán dẫn , vốn được sử dụng trong mọi sản phẩm điện tử, từ ôtô và vũ khí công nghệ cao đến các thiết bị công nghệ và trò chơi điện tử. \n Đạo luật cũng bao gồm một khoản tín dụng thuế đầu tư 25% cho các nhà máy sản xuất chip ước tính trị giá 24 tỉ USD.\n Ngoài ra, đạo luật cũng sẽ rót 200 tỉ USD trong 10 năm để thúc đẩy hoạt động nghiên cứu khoa học của Mỹ nhằm cạnh tranh tốt hơn với Trung Quốc.\n Phát biểu tại Nhà Trắng, Tổng thống Biden cho biết đạo luật này sẽ giúp nước Mỹ giành thắng lợi trong cuộc cạnh tranh về kinh tế trong thế kỷ 21.\n Trước đó, đạo luật với mức chi khổng lồ 280 tỉ USD được Thượng viện Mỹ phê chuẩn vào ngày 27-7.\n \"Điều đó có nghĩa các chuỗi cung ứng của Mỹ sẽ bền vững hơn, do đó chúng ta sẽ không bao giờ còn lệ thuộc vào các nước bên ngoài về những công nghiệp thiết yếu mà chúng ta cần\", Tổng thống Joe Biden - người ủng hộ mạnh mẽ dự luật - nói.\n Ông Biden nói rằng Mỹ cần chip cho các hệ thống vũ khí quan trọng như tên lửa Javelin. \"Không có gì lạ khi Trung Quốc tích cực vận động các doanh nghiệp Mỹ chống lại dự luật này\", ông cho biết.\n Nhiều nhà lập pháp Mỹ cho biết họ thường sẽ không ủng hộ các khoản hỗ trợ quá lớn cho các doanh nghiệp tư nhân, nhưng nói rằng Trung Quốc và Liên minh châu Âu cũng đang rót hàng tỉ USD ưu đãi cho các công ty chip của họ. Ngoài ra, các chính trị gia Mỹ cho biết vấn đề này còn liên quan đến nguy cơ an ninh quốc gia và các vấn đề lớn trong chuỗi cung ứng đã cản trở hoạt động sản xuất trên toàn cầu.\n Con chip, cuộc sinh - tử trong khủng hoảng thế giới - Kỳ 3: Con chip và cuộc đua giữa 3 châu lục TTO - Dù Mỹ, châu Âu có những công ty hàng đầu phát triển công nghệ bán dẫn, phần lớn các nhà sản xuất chip lớn nhất hiện nay lại đang ở Đông Á, bao gồm vùng lãnh thổ Đài Loan.", + "snippet": "TTO - Tổng thống Mỹ Joe Biden ký thông qua đạo luật đầu tư hàng tỉ USD vào ngành bán dẫn và các lĩnh vực sản xuất công nghệ cao khác mà chính quyền nước này lo ngại đang bị Trung Quốc thống trị.", + "source_tagids": [ + 1 + ], + "source_type": 11, + "tag_phrases": [ + "chip", + "bán dẫn", + "mỹ", + "trung quốc", + "joe biden" + ], + "title": "Tổng thống Joe Biden ký luật cạnh tranh chip với Trung Quốc", + "url": "https://congnghe.tuoitre.vn/tong-thong-joe-biden-ky-luat-canh-tranh-chip-voi-trung-quoc-20220809233913183.htm", + "attachment_types": [ + "image", + "image", + "image" + ], + "attachment_urls": [ + "https://cdn.tuoitre.vn/thumb_w/586/2022/8/9/2022-08-09t150438z235113998rc2wsv9khwnfrtrmadp3usa-china-chips-1660062905725191627856.jpg", + "https://cdn.tuoitre.vn/2022/8/9/2022-08-09t150438z235113998rc2wsv9khwnfrtrmadp3usa-china-chips-1660062905725191627856.jpg", + "https://cdn.tuoitre.vn/zoom/150_120/2022/8/9/cong-nghiep-chip-o-nhat-ban-16600112855761900980610-crop-1660011387021900317450.jpg" + ], + "created_time": 1660064110, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer", + "Icomm.NewsCrawl.SmartReader" + ], + "domain": "trithucvn.org", + "id": "803a3a3282640da09176d5c52a9c7c6faf0b3e67", + "message": "Ngày 9/8, Tổng thống Mỹ Biden đã ký một đạo luật lưỡng đảng để cung cấp các động lực lớn cho ngành công nghiệp bán dẫn trong nước và tài trợ cho nghiên cứu khoa học. Những người ủng hộ nói rằng đạo luật sẽ giúp thúc đẩy sản xuất chất bán dẫn trong nước ở (Mỹ) để đối kháng Trung Quốc trong cuộc chiến công nghệ Mỹ – Trung và giải quyết các thách thức trong chuỗi cung ứng. \n Tổng thống Joe Biden. (Nguồn: Adam Schultz/ Nhà Trắng) Đạo luật CHIPS và Khoa học (CHIPS and Science Act) trị giá 280 tỷ USD, được thông qua sau hơn một năm làm việc và nhiều lần sửa đổi của quốc hội, đánh dấu sự hợp tác lưỡng đảng hiếm có ở Mỹ. Cả hai đảng đều tin rằng dự luật này rất quan trọng để chống lại sự cưỡng bức kinh tế của ĐCSTQ, để giành chiến thắng trong cạnh tranh kinh tế với ĐCSTQ, và củng cố an ninh quốc gia. \n Theo Đạo luật về Chips và Khoa học, chính quyền Biden đã sử dụng các biện pháp kiểm soát xuất khẩu, giám sát đầu tư và trợ cấp hào phóng cho các công ty không phải của Trung Quốc nhằm tăng cường sản xuất chip trong nước, khiến Trung Quốc khó có được công nghệ bán dẫn tiên tiến hơn. \n Đạo luật chấn hưng sản xuất chất bán dẫn trong nước của Mỹ, giảm sự phụ thuộc vào nước ngoài Đạo luật bao gồm 52 tỷ USD khuyến khích cho các nhà sản xuất chất bán dẫn hoặc chip xây dựng các nhà máy sản xuất chất bán dẫn trong nước, cũng như hơn 80 tỷ USD dùng cho Quỹ Khoa học Quốc gia ủy quyền để hỗ trợ đổi mới và nghiên cứu trong 5 năm. \n Nhà Trắng gọi đạo luật này là giải pháp cho những thách thức chuỗi cung ứng do đại dịch COVID-19. Trong thời gian đại dịch, sự thiếu hụt chip trên toàn cầu đã làm trì hoãn việc sản xuất ô tô và thiết bị điện tử, bao gồm các mặt hàng từ ô tô đến điện thoại di động, đến vũ khí. \n Trong số 52 tỷ USD, 39 tỷ USD được dành trực tiếp cho “khuyến khích sản xuất” để xây dựng và mở rộng các nhà máy sản xuất chất bán dẫn hoặc nhà máy chế tạo bán dẫn. Số tiền sẽ được phân phối trong 5 năm, trong đó gồm 19 tỷ USD trong năm nay và 5 tỷ USD khác mỗi năm cho đến năm 2026. Dự luật cũng dành 200 tỷ USD cho nghiên cứu trong các lĩnh vực như trí tuệ nhân tạo và điện toán lượng tử. \n Khoản tiền này cũng bao gồm hàng tỷ USD cho nghiên cứu chất bán dẫn và phát triển tài năng để xây dựng đội ngũ nhân tài cho ngành công nghiệp trong nước Mỹ; dự luật cũng bao gồm các khoản khấu trừ thuế cho các khoản đầu tư vào Mỹ. \n Ông Biden: Đạo luật bao gồm các hàng rào bảo vệ quan trọng Đạo luật mới nhằm mục đích gia tăng sản xuất chất bán dẫn nội địa của Mỹ trong dài hạn, để giảm sự phụ thuộc của Mỹ vào các nhà cung cấp nước ngoài. Những người ủng hộ cũng nói rằng điều này sẽ giúp Mỹ cạnh tranh với Trung Quốc. \n “Bằng cách sản xuất nhiều chất bán dẫn hơn ở Hoa Kỳ, dự luật này sẽ tăng sản xuất trong nước và giảm chi phí hộ gia đình.” Ông Biden hoan nghênh việc thông qua dự luật trong một tuyên bố hôm thứ Năm tuần trước (ngày 4/8). \n Ông Biden nói: “Hơn nữa, nó (dự luật) sẽ củng cố an ninh quốc gia của chúng ta bằng cách giảm sự phụ thuộc của chúng ta vào các nguồn bán dẫn nước ngoài” , “Dự luật bao gồm các hàng rào bảo vệ quan trọng để đảm bảo rằng các công ty nhận tiền thuế đầu tư vào Mỹ, đồng thời đảm bảo công nhân công đoàn đang xây dựng các nhà máy sản xuất mới trên khắp đất nước.” \n Nhiều kênh truyền thông trước đó đã đưa tin, văn bản của đạo luật này chỉ ra rằng các công ty chip đặt nhà máy ở Mỹ sẽ không thể mở rộng sản xuất chip ở Trung Quốc hoặc các quốc gia có liên quan khác (chẳng hạn như Nga) trong 10 năm tới nếu họ nhận được trợ cấp từ Chính phủ Mỹ. \n Bloomberg đưa tin rằng đạo luật đặt ra giới hạn tĩnh là 28 nanomet, có nghĩa là những người nhận trợ cấp không thể sản xuất bất kỳ con chip nào nhỏ hơn và cao cấp hơn kích thước đó tại Trung Quốc. Các công nghệ chip 28 nanomet ra đời trước rất nhiều so với công nghệ bán dẫn tiên tiến, nhưng chúng vẫn được sử dụng rộng rãi trong các sản phẩm bao gồm ô tô và điện thoại thông minh. Lệnh cấm của dự luật cũng bao gồm các chip logic và bộ nhớ. \n Các biện pháp này là một phần trong nỗ lực rộng lớn hơn của chính quyền Biden nhằm bảo vệ chuỗi cung ứng của Mỹ và chống lại chiến lược của Trung Quốc nhằm làm chậm quá trình hội nhập quân sự – dân sự của Trung Quốc (Đảng Cộng sản Trung Quốc) và ngăn chặn quá trình hiện đại hóa quân sự của Bắc Kinh. \n Nhà phân tích: Đạo luật đưa ra tín hiệu quan trọng Thượng viện đã thông qua dự luật bằng một cuộc bỏ phiếu lưỡng đảng với tỷ lệ 64-33 vào ngày 27/7. Lãnh đạo phe thiểu số Thượng viện Mitch McConnell và 16 đảng viên Cộng hòa khác bỏ phiếu ủng hộ. \n Ông Guarav Gupta, một nhà phân tích ngành công nghiệp bán dẫn tại công ty nghiên cứu Gartner của Mỹ, nói với Nikkei Asian Review rằng mặc dù số liệu (tiền tài trợ) thô có thể không thay đổi đáng kể, nhưng việc Mỹ đang trợ cấp cho ngành công nghiệp chip nội địa của mình lại là một tín hiệu rất quan trọng. \n Ông nói: “Có thể nói rằng Mỹ đã sẵn sàng ủng hộ chính sách của mình và cho rằng chất bán dẫn là quan trọng.”, “Tôi nghĩ đó là thông điệp chính ở đây. Nhưng để có tác động có ý nghĩa, đó phải là một chính sách nhất quán hơn nữa.” \n Ông Brian Deese, Giám đốc Hội đồng Kinh tế Quốc gia của Nhà Trắng, nói với các phóng viên tại một cuộc họp báo gần đây rằng đạo luật này sẽ có tác động gần như trực tiếp đến quyết định kinh doanh của các công ty tại Mỹ. Tuy nhiên ông thừa nhận tác động đối với chuỗi cung ứng trong nước sẽ lâu dài. \n “Đây là một dự án dài hạn, một dự án quốc gia dài hạn, có ý nghĩa quan trọng về kinh tế và an ninh quốc gia, tác động cuối cùng của nó sẽ được cảm nhận trong vài năm”, ông Brian Deese nói. \n Ngày 9/8, Nhà Trắng cho biết, các công ty bị “kích thích” bởi đạo luật chip đã công bố hơn 44 tỷ USD đầu tư vào sản xuất chất bán dẫn mới. Trong đó, 40 tỷ USD đến từ các khoản đầu tư vào sản xuất chip nhớ. Nhà Trắng cho biết động thái của các công ty sẽ tạo ra 8.000 việc làm mới và thúc đẩy thị phần sản xuất chip nhớ của Mỹ từ 2% lên 10%. \n Nhà phân tích: Đạo luật có thể buộc các công ty chip phải chọn đứng về phía Mỹ hay Trung Quốc Các nhà phân tích và luật sư nói với Nikkei Asian Review rằng các điều khoản (hàng rào bảo vệ) của dự luật đã tạo ra một “bãi mìn” cho các công ty, thực tế có thể buộc họ phải lựa chọn giữa Mỹ và Trung Quốc. \n Chất bán dẫn là chiến trường quan trọng trong cuộc chiến công nghệ Mỹ – Trung. Chip là bộ não của các thiết bị điện tử, từ điện thoại thông minh, máy tính xách tay đến trung tâm dữ liệu. Chip cũng đóng một vai trò quan trọng các hệ thống vũ khí tiên tiến, chẳng hạn như hệ thống tên lửa chống tăng mà Mỹ cung cấp cho Ukraine, v.v. \n Đạo luật này có một số trường hợp được phép đầu tư vào Trung Quốc nếu các khoản đầu tư của họ nhằm bảo vệ các lợi ích kinh doanh hiện có và quan trọng ở Trung Quốc, nhưng chỉ giới hạn ở những con chip truyền thống. \n Ông Tan Albayrak, luật sư kiểm soát xuất khẩu và trừng phạt tại Reed Smith LLP, nói với Nikkei rằng chất bán dẫn truyền thống bao gồm công nghệ chip 28 nanomet hoặc thế hệ cũ hơn. \n Tờ Nikkei đưa tin, các luật sư đã cảnh báo rằng các công ty nên thực hiện các biện pháp hạn chế đầu tư một cách nghiêm túc. “Các hình phạt không chỉ bao gồm các khoản tiền bị mất, mà còn các hình phạt khác ‘vì lợi ích quốc gia’ với cách giải thích ngôn ngữ khá rộng. Và tất nhiên, có tác động về danh tiếng nếu các công ty lạm dụng những khoản tiền đó”, Barnes & Thornburg, một công ty luật tại Washington chuyên về thương mại quốc tế và các quy định kiểm soát xuất khẩu, đối tác Clinton Yu, nói với Nikkei. \n Ông Martijn Rasser, một thành viên cấp cao và là giám đốc của Trung tâm An ninh mới của Mỹ, cho biết các hạn chế có thể là bước dạo đầu cho việc giám sát đầu tư nước ngoài khắt khe hơn đối với các nhà sản xuất chip. \n Ông nói với Nikkei: “Những hạn chế này nhấn mạnh mối quan tâm ngày càng tăng của các nhà hoạch định chính sách Mỹ rằng nguồn tài trợ của Mỹ đang giúp Trung Quốc xây dựng năng lực. Những hạn chế này là bản phác thảo ban đầu về những gì bạn có thể mong đợi trong khuôn khổ đánh giá đầu tư ra nước ngoài.” \n Ngày 3/8, tờ Financial Times đưa tin ông Yeo Han-koo, một cựu quan chức kinh tế Hàn Quốc, từng giữ chức Bộ trưởng Thương mại Hàn Quốc cho đến tháng Năm năm nay, việc “điều chỉnh lại chiến lược” của các nhà sản xuất chip Hàn Quốc đối với Mỹ và Trung Quốc đã bắt đầu. \n Báo cáo cho biết các điều khoản trong dự luật chip đã khiến Samsung và SK Hynix phải xem xét lại hoạt động của họ tại Trung Quốc, theo những người quen thuộc với quan điểm của 2 công ty cho biết. \n Một quan chức cấp cao của Hàn Quốc cho biết thêm, theo thời gian, một số khoản đầu tư của Hàn Quốc vào sản xuất chip của Trung Quốc có thể bị “ vứt bỏ”.", + "snippet": "Aug 11, 2022 ... Tổng thống Mỹ Biden đã ký đạo luật CHIPS cung cấp các động lực lớn cho ngành công nghiệp bán dẫn trong nước và tài trợ nghiên cứu khoa học.", + "source_type": 6, + "title": "Những ảnh hưởng của Đạo luật CHIPS đến cuộc chiến khoa học ...", + "url": "https://trithucvn.org/the-gioi/nhung-anh-huong-cua-dao-luat-chips-den-cuoc-chien-khoa-hoc-cong-nghe-my-trung.html", + "attachment_farm_urls": [], + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://trithucvn.org/wp-content/uploads/2022/08/52264822998_be761773c4_b.jpg" + ], + "created_time": 61965536398, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "doanhnghiephoinhap.vn", + "id": "89f6a612383703cdda0b395ceeb375031336dd93", + "message": "DNHN - Các nhà phân tích và luật sư nói với trang tin Nikkei Asia rằng, các điều khoản của luật sẽ tạo ra khó khăn cho các công ty và trên thực tế, có thể buộc họ phải lựa chọn giữa Mỹ và Trung Quốc. \n \n Tổng thống Joe Biden chuẩn bị ký ban hành  Đạo luật  \" Chips  and Science\" (tạm dịch: Chip điện tử và khoa học)  trị giá 280 tỷ USD , cung cấp khoản hỗ trợ cho các công ty chip đầu tư vào ngành công nghiệp bán dẫn của Mỹ. Ảnh: AP. Các nhà sản xuất chip đang ủng hộ việc Washington thông qua dự luật được chờ đợi từ lâu để cung cấp vốn cho ngành công nghiệp bán dẫn của Mỹ, nhưng việc chấp nhận các khoản trợ cấp đó có thể khiến họ khó khăn hơn khi đầu tư vào Trung Quốc trong tương lai. \n Đó liệu có phải là mức giá phải trả mà những công ty như Intel, TSMC và Samsung sẵn sàng đánh đổi?  \n Đạo luật  \" Chips  and Science\" (tạm dịch: Chip điện tử và khoa học)  trị giá 280 tỷ USD được thông qua vào tuần trước sẽ bao gồm 52 tỷ đô la hỗ trợ cho s ản xuất vật liệu bán dẫn của Mỹ .  Nhưng luật này cũng yêu cầu các công ty nếu chấp nhận trợ cấp liên bang sẽ bị hạn chế thực hiện bất kỳ \"giao dịch quan trọng\" nào trong việc mở rộng năng lực sản xuất chip của họ ở Trung Quốc hoặc bất kỳ quốc gia nước ngoài nào khác mà họ quan tâm trong vòng 10 năm. \n Mặc dù dường như các nhà sản xuất chip có thể bảo vệ hoạt động kinh doanh hiện tại của họ ở Trung Quốc, các nhà phân tích và luật sư nói với trang tin Nikkei Asia rằng các điều khoản của luật sẽ tạo ra khó khăn cho các công ty và trên thực tế, có thể buộc họ phải lựa chọn giữa Mỹ và Trung Quốc. \n Chất bán dẫn là lĩnh vực quan trọng trong cuộc đua cạnh tranh giữa Mỹ và Trung Quốc.  Chúng đóng vai trò là bộ não của các thiết bị điện tử, từ điện thoại thông minh, máy tính xách tay đến trung tâm dữ liệu, và chúng cũng đóng vai trò quan trọng trong các hệ thống vũ khí tinh vi.  \n Đạo luật CHIPS có các ngoại lệ như việc cho phép các nhà sản xuất chip có thể tiếp tục đầu tư vào Trung Quốc nếu những khoản đầu tư đó nhằm bảo vệ các lợi ích kinh doanh hiện có và quan trọng ở nước này.  Nhưng những ngoại lệ này chỉ áp dụng cho việc mở rộng các cơ sở hiện có  chỉ cho \"chất bán dẫn truyền thống\" \n Theo Tan Albayrak - Luật sư của  Công ty luật toàn cầu  Reed Smith LLP, các chất bán dẫn truyền thống bao gồm các công nghệ chip 28 nanomet trở lên. \n Kích thước nanomet đề cập đến chiều rộng dòng giữa các bóng bán dẫn trên chip.  Nói chung, con số càng nhỏ thì chip càng cao cấp.  \n Albayrak cho biết, các ngoại lệ của đạo luật đối với các khoản đầu tư vào Trung Quốc là nhằm tránh sự gián đoạn đột ngột cho hoạt động kinh doanh của Mỹ. \n Ông nói: “Điều này không làm suy yếu hàng rào bảo vệ của Hoa Kỳ, mà là hành động cân bằng cần thiết trong việc theo đuổi mục tiêu chính sách là giữ lợi thế về công nghệ, đồng thời giảm thiểu thiệt hại tài sản thế chấp cho khu vực Hoa Kỳ. \n Chủ tịch Hạ viện Hoa Kỳ Nancy Pelosi ký    Đạo luật  \" Chips  and Science\" tại Washington vào ngày 29 tháng 7. Ảnh:AP. Các chip truyền thống được sử dụng trong nhiều loại thiết bị điện tử, từ điện thoại thông minh, máy tính đến thiết bị gia dụng và ô tô được kết nối.  Chúng thường được xem như những con chip đồng hành và thường cần với số lượng lớn hơn nhiều so với những con chip xử lý có kích thước nhỏ. \n Nhiều gã khổng lồ về chip toàn cầu đang hoạt động tích cực ở Trung Quốc.  Công ty sản xuất chất bán dẫn Đài Loan (TSMC) có nhà máy ở Nam Kinh hiện đang sản xuất chip 16 nm và 28 nm, trong khi Samsung có quy mô sản xuất chip nhớ lớn ở Tây An, tỉnh Thiểm Tây.  SK Hynix có các cơ sở chip nhớ ở Vô Tích và Đại Liên.  Intel và Micron của Mỹ đều có cơ sở đóng gói và thử nghiệm chip ở Trung Quốc. \n Các hạn chế của Đạo luật CHIPS sẽ khiến bất kỳ nhà sản xuất chip lớn nào đều phải dừng kế hoạch sản xuất các sản phẩm tiên tiến nhất của họ ở Trung Quốc, ít nhất là trong tương lai gần. \n Tuy nhiên, các luật sư cảnh báo rằng, các công ty nên xem xét các hạn chế đầu tư một cách nghiêm túc.  \n Một nguyên nhân khác gây lo ngại, theo Martijn Rasser, một thành viên cấp cao và là giám đốc tại Trung tâm An ninh Mỹ mới, là các hạn chế có thể là bước dạo đầu cho việc giám sát kỹ hơn các khoản đầu tư ra nước ngoài của các nhà sản xuất chip. \n Rasser nói với Nikkei Asia: “Những hạn chế này nhấn mạnh rằng các nhà hoạch định chính sách của Mỹ đang ngày càng lo ngại về việc tiền của Mỹ sẽ lại chuyển sang hỗ trợ việc xây dựng năng lực ở Trung Quốc.  \n Các nhà sản xuất chip đã hoan nghênh việc thông qua đạo luật.  Một số đã cam kết đầu tư vào Mỹ đã được đưa ra, điển hình như TSMC sẽ đầu tư với quy mô ít nhất 12 tỷ USD ở Arizona, và Samsung với 17 tỷ USD ở Texas,... \n Một số nhà sản xuất chip cảnh báo rằng nếu không thông qua Đạo luật CHIPS sẽ  ảnh hưởng đến các kế hoạch đầu tư  của họ \n Nhưng ngoài trợ cấp, có một lý do khác khiến các công ty chip muốn mở rộng ở Mỹ: Tham vọng chip của riêng Trung Quốc. Bắc Kinh đã lên kế hoạch nâng thị phần chip tự sản xuất trong nước lên 70% vào năm 2025.\n Về lâu dài, tham vọng của Trung Quốc sẽ là thay thế tất cả các chip tiên tiến bằng chip sản xuất trong nước. Vì vậy, sẽ có một câu hỏi là liệu các nhà sản xuất nước ngoài như TSMC và Samsung có thể thực sự tiếp tục thống trị ngành sản xuất chip cao cấp ở Trung Quốc hay không.  \n Các nhà sản xuất chip cũng sẽ phải đối mặt với một câu hỏi trực tiếp rằng: Trong một ngành công nghiệp mà các khoản đầu tư thường được tính bằng tỷ đô la, liệu 52 tỷ đô la có đủ không? \n Chỉ 39 tỷ USD tài trợ của Đạo luật CHIPS sẽ dành cho lĩnh vực sản xuất chip, trong khi 13 tỷ USD sẽ được phân bổ cho nghiên cứu phát triển và đổi mới.  Tuy nhiên, việc xây dựng các nhà máy sản xuất chất bán dẫn không chỉ là về các cơ sở sản xuất chip, nó còn liên quan đến một  mạng lưới cung cấp khổng lồ bao gồm  hàng trăm loại hóa chất và vật liệu, cũng như thiết bị sản xuất chip. \n Trong khi đó, C ông ty tư vấn quản  trị  toàn cầu  Bain & Company  ước tính, việc tăng công suất chip của Mỹ chỉ từ 5% đến 10% sẽ cần khoảng 40 tỷ USD.  Việc tài trợ cho 10 năm tiếp theo để phát triển các công nghệ mới sẽ còn đắt hơn, trị giá khoảng 110 tỷ đô la. \n Peter Hanbury, một đối tác của công ty tư vấn chuyên về chip và các ngành sản xuất cho biết: “52 tỷ USD chắc chắn sẽ giúp tài trợ cho cả hai nỗ lực này, nhưng không là sẽ cung cấp chi phí đầy đủ cho cả hai. Việc x ây dựng lại hệ sinh thái bán dẫn là một đề xuất đắt đỏ\".\n Lyly", + "snippet": "DNHN - Các nhà phân tích và luật sư nói với trang tin Nikkei Asia rằng, các điều khoản của luật sẽ tạo ra khó khăn cho các công ty và trên thực tế, có thể buộc họ phải lựa chọn giữa Mỹ và Trung Quốc.", + "source_type": 11, + "tag_phrases": [ + "#Đạo luật Chips", + "#sản xuất chip", + "#chất bán dẫn" + ], + "title": "Đạo luật CHIPS khiến các nhà sản xuất phải đối mặt với sự lựa chọn giữa Mỹ và Trung Quốc", + "url": "https://doanhnghiephoinhap.vn/dao-luat-chips.html", + "attachment_types": [ + "image", + "image" + ], + "attachment_urls": [ + "https://media.doanhnghiephoinhap.vn/uploads/2022/08/03/https-s3-ap-northeast-1-1659469060.jpeg", + "https://media.doanhnghiephoinhap.vn/uploads/2022/08/03/https-s3-ap-northeast-1-1659469259.jpeg" + ], + "created_time": 1659437040, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer", + "Icomm.NewsCrawl.SmartReader" + ], + "domain": "epochtimesviet.com", + "id": "a115058763a7e66ed37047a6705a6384d952f89e", + "message": "Hôm 09/08, Tổng thống Joe Biden đã ký Đạo luật CHIPS và Khoa học, phân bổ gói tài trợ trị giá 280 tỷ USD để thúc đẩy sản xuất chất bán dẫn trong nước và các nỗ lực nghiên cứu khác nhau. \n\n Tờ thông tin của Tòa Bạch Ốc về đạo luật này cho biết, “Đạo luật CHIPS và Khoa học sẽ thúc đẩy nghiên cứu, phát triển, và sản xuất chất bán dẫn của Mỹ, bảo đảm sự dẫn đầu của Hoa Kỳ trong công nghệ tạo nền tảng cho mọi thứ, từ xe hơi đến thiết bị gia dụng, và cho đến cả hệ thống phòng thủ.” \n\n “Luật này cũng sẽ bảo đảm việc Hoa Kỳ duy trì và nâng cao lợi thế khoa học và công nghệ của mình.” \n\n Chính phủ cho rằng gói chi tiêu khổng lồ này sẽ cải thiện việc làm và an ninh quốc gia bằng cách làm cho Hoa Kỳ ít phụ thuộc hơn vào các chuỗi cung ứng của ngoại quốc và xây dựng một lực lượng lao động mạnh mẽ hơn. \n\n Chất bán dẫn được sử dụng trong nhiều công nghệ, từ xe hơi đến hỏa tiễn siêu thanh. Gói tài trợ này cũng nhận được nhiều lời ca ngợi như một phương tiện để cải thiện khả năng cạnh tranh của quốc gia trước một Trung Quốc cộng sản ngày càng thù địch. \n\n Đạo luật CHIPS và Khoa học \n “Hôm nay, tôi ký thành luật Đạo luật CHIPS và Khoa học,” ông Biden nói trong một tweet. “Đây là đạo luật đầu tiên nhằm đầu tư vào Mỹ bằng cách tăng cường nỗ lực của chúng ta trong việc sản xuất chất bán dẫn tại quê nhà.” \n\n “Ngày hôm nay đại diện cho một nền kinh tế an toàn hơn, công ăn việc làm bảo đảm hơn, và một tương lai vững chắc hơn cho quốc gia của chúng ta. Nước Mỹ đang trở thành nhà cung cấp.” \n\n Khoảng 52 tỷ USD sẽ được chi cho sản xuất và các chi phí liên quan. Phần lớn số tiền còn lại sẽ dành cho việc giảm thuế cho các tập đoàn công nghệ lớn, các sáng kiến ​​năng lượng xanh và tài trợ nghiên cứu cho các dự án công bằng xã hội khác nhau của chính phủ. \n\n Đáng chú ý, luật sẽ cấp hàng tỷ dollar cho các khoản đầu tư vào “các cộng đồng chịu thiệt thòi” để bảo đảm rằng các nhà sản xuất chất bán dẫn “hỗ trợ tăng trưởng và phát triển kinh tế công bằng”. \n\n Cụ thể, Tòa Bạch Ốc cho biết luật sẽ dành nguồn kinh phí đáng kể để thực hiện nghiên cứu tại các trường đại học/cao đẳng truyền thống của người Mỹ gốc Phi Châu và cũng để chống “sách nhiễu về giới trong khoa học.” \n\n Những lời chỉ trích từ cả hai đảng đã phê phán luật này như một sự cho không các công ty mà sẽ làm tăng lạm phát và làm phương hại đến những người đóng thuế ở Hoa Kỳ. \n\n “Câu hỏi mà chúng ta nên hỏi là thế này,” Thượng nghị sĩ Bernie Sanders (Độc Lập-Vermont) nói khi tranh luận về dự luật. “Những người đóng thuế Mỹ có nên cung cấp cho ngành công nghiệp vi mạch một tấm séc trắng hơn 76 tỷ USD vào đúng thời điểm khi các công ty bán dẫn đang kiếm được hàng chục tỷ USD lợi nhuận và trả cho các CEO của họ những mức lương cao ngất ngưởng?” \n\n “Tôi nghĩ câu trả lời cho điều đó là một từ không dõng dạc.” \n\n “Ông Bernie Sanders và tôi gần như chưa bao giờ đồng ý nhưng ông ấy nói đúng về cái gọi là dự luật CHIPS,” Thượng nghị sĩ Chuck Grassley (Cộng Hòa-Iowa) viết trên Twitter. “Đó chỉ là một khoản trợ cấp chính phủ khổng lồ cho các công ty lớn [và] đã có lợi nhuận. Tại sao chúng ta lại chi nhiều tiền thuế hơn cho hoạt động phúc lợi doanh nghiệp không cần thiết?” \n\n Quốc hội đã thông qua Đạo luật Tạo ra Những ưu đãi Hữu ích để Sản xuất Chất bán dẫn (CHIPS) hồi tháng 01/2021. Tuy nhiên, các nhà lập pháp sau đó đã không thông qua dự luật phân bổ ngân sách thích hợp cho dự luật này. \n\n Thượng viện đã thông qua một phiên bản của dự luật hồi tháng 06/2021, có nhan đề là Đạo luật Đổi mới và Cạnh tranh (USICA). Dự luật đó bao gồm 39 tỷ USD để xây dựng ngành bán dẫn trong vòng năm năm, 11.2 tỷ USD cho các hoạt động nghiên cứu và phát triển theo Đạo luật CHIPS, và khoảng 200 tỷ USD để thúc đẩy đổi mới khoa học và công nghệ thông qua các khoản tín thuế cho các công ty sản xuất vi mạch. \n\n Mặc dù Thượng viện đã thông qua USICA với số phiếu 68-32, nhưng các thành viên Đảng Dân Chủ tại Hạ viện đã không ủng hộ đề nghị tài trợ tín thuế cho các công ty sản xuất vi mạch. Hồi tháng 02/2022, Hạ viện đã thông qua phiên bản Hạ viện của dự luật, Đạo luật CẠNH TRANH của Mỹ, bao gồm 52 tỷ USD cho sản xuất chất bán dẫn nhưng đã cắt giảm 200 tỷ USD cho các chương trình khác. \n\n Dự luật này của Hạ viện cũng bao gồm một khoản tài trợ rộng rãi hơn cho các dự án không liên quan, chẳng hạn như tài trợ cho sinh viên học hóa học “xanh”, điều này đã thu hút sự chỉ trích từ các thành viên Đảng Cộng Hòa. \n\n Phiên bản cuối cùng của gói tài trợ do TT Biden ký hôm thứ Ba dường như đã bao gồm hầu hết các yêu cầu từ cả Đảng Dân Chủ và Đảng Cộng Hòa. \n\n Ông Andrew Thornebrooke là một phóng viên của The Epoch Times, chuyên đưa tin về các vấn đề liên quan đến Trung Quốc với trọng tâm là quốc phòng, các vấn đề quân sự, và an ninh quốc gia. Ông có bằng Thạc sĩ lịch sử quân sự tại Đại học Norwich. \n\n\n Xem thêm:", + "snippet": "Aug 10, 2022 ... Hôm 09/08, Tổng thống Joe Biden đã ký Đạo luật CHIPS và Khoa học, phân bổ gói tài trợ trị giá 280 tỷ USD để thúc đẩy sản xuất chất bán dẫn trong nước và các ...", + "source_type": 6, + "title": "TT Biden ký thành luật Dự luật CHIPS và Khoa học trị giá 280 tỷ ...", + "url": "https://www.epochtimesviet.com/tt-biden-ky-thanh-luat-du-luat-chips-va-khoa-hoc-tri-gia-280-ty-usd_310392.html", + "attachment_farm_urls": [], + "attachment_types": [ + "image", + "image", + "image", + "image", + "image" + ], + "attachment_urls": [ + "https://www.epochtimesviet.com/wp-content/uploads/2022/07/2021-10-14T093729Z_1_LYNXMPEH9D0IC_RTROPTP_4_TAIWAN-EU-1-e1637841842542-700x420-1-160x106.jpg", + "https://www.epochtimesviet.com/wp-content/uploads/2022/06/Semiconductor-chips-700x420-1-160x106.jpg", + "https://www.epochtimesviet.com/wp-content/uploads/2022/03/sermiconductors-700x420-1-160x106.jpeg", + "https://www.epochtimesviet.com/wp-content/uploads/2022/08/GettyImages-1241871378-700x420-1-160x106.jpg", + "https://www.epochtimesviet.com/wp-content/uploads/2022/08/schumer-democrats-700x420-1-160x106.jpeg" + ], + "created_time": 64395363598, + "lang": "vi" + }, + { + "actor_name": "Huỳnh Dũng", + "categories": [ + "Chuyển động số" + ], + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "danviet.vn", + "id": "dac82328e1fbdfddde2f06b1722fdb61ffdd16b7", + "message": "Hai hiệp hội thương mại Trung Quốc đã lên án Đạo luật Khoa học và CHIPS, cho rằng luật mới được ký kết của Hoa Kỳ nhằm thúc đẩy sản xuất chip trong nước sẽ làm tổn hại đến ngành công nghiệp ở những nơi khác trên thế giới. \n Theo các nhóm, Hội đồng Xúc tiến Thương mại Quốc tế Trung Quốc và Phòng Thương mại Quốc tế Trung Quốc, đạo luật này sẽ \"tăng cường cạnh tranh địa chính trị trong ngành công nghiệp bán dẫn và cản trở sự phục hồi kinh tế toàn cầu và sự phát triển của đổi mới công nghệ\".\n Trung Quốc kêu gọi tẩy chay Đạo luật CHIPS của Mỹ vì nó sẽ \"tăng cường cạnh tranh địa chính trị trong ngành công nghiệp bán dẫn\". Ảnh: @AFP.\n Mục tiêu của luật khuyến khích xây dựng các nhà máy mới ở Mỹ \"phân biệt đối xử với một số công ty nước ngoài, sử dụng quyền lực nhà nước để cưỡng bức thay đổi sự phân công lao động quốc tế trong ngành bán dẫn và gây tổn hại đến lợi ích của các công ty trên khắp thế giới, kể cả ở Trung Quốc và Mỹ\", các hiệp hội đồng cho biết.\n Các nhôm cũng kêu gọi cộng đồng doanh nghiệp quốc tế cùng nhau \"loại bỏ tác động tiêu cực\" của luật này.\n Người phát ngôn Bộ Ngoại giao Trung Quốc Wang Wenbin đã chỉ trích luật pháp Hoa Kỳ là một ví dụ về \"sự ép buộc kinh tế\" của Hoa Kỳ.\n Wang nói: \"Không có sự hạn chế hay đàn áp nào sẽ kìm hãm sự phát triển khoa học và công nghệ cũng như tiến bộ công nghiệp của Trung Quốc.\n Đạo luật CHIPS, được Tổng thống Joe Biden ký thành luật hôm 10/8, dành 52,7 tỷ đô la trợ cấp cho sản xuất và phát triển chất bán dẫn của Hoa Kỳ. Nó cấm các công ty nhận các khoản tiền này đầu tư vào sản xuất chip tiên tiến ở Trung Quốc. Vốn dĩ, Bắc Kinh đã đầu tư rất nhiều vào ngành công nghiệp bán dẫn của riêng mình thông qua một quỹ do nhà nước hậu thuẫn.\n Trung Quốc kêu gọi tẩy chay Đạo luật CHIPS của Mỹ: \"Một ví dụ về sự ép buộc kinh tế của Hoa Kỳ\". Ảnh: @AFP.\n Việc thông qua Đạo luật Khoa học và CHIPS cũng đánh dấu sự thể hiện thống nhất lưỡng đảng hiếm có ở Washington, với các chính trị gia ở cả hai phía đều coi bộ luật là điều cần thiết để giành chiến thắng trong cuộc cạnh tranh kinh tế với Trung Quốc cũng như tăng cường an ninh quốc gia.\n \"Mỹ đã phát minh ra chất bán dẫn ... và luật này đưa nó trở lại quê hương\", Biden nói. \"Làm như vậy là vì lợi ích kinh tế và lợi ích an ninh quốc gia của chúng ta\".\n Tầm quan trọng của bộ luật trong cuộc cạnh tranh Mỹ-Trung đã được Biden và các nhà lãnh đạo chính trị khác vạch ra, vì chúng không chỉ được quảng cáo về lợi ích kinh tế mà còn đề cập đến việc sản xuất chip tiên tiến trong các hệ thống vũ khí.\n \"Trung Quốc đang cố gắng đi trước chúng tôi và cũng sản xuất những con chip tinh vi này\", Biden nói. \"Không có gì lạ khi Đảng Cộng sản Trung Quốc tích cực vận động các doanh nghiệp Mỹ chống lại dự luật này\".\n Lãnh đạo Đa số Thượng viện Chuck Schumer cho rằng đạo luật này hỗ trợ làn sóng tiến bộ khoa học và công nghiệp của Mỹ tương tự như những gì Mỹ đã đạt được sau Thế chiến thứ hai.\n Schumer nói: \"Những người độc đoán đang cổ vũ chúng tôi thua cuộc, hy vọng chúng tôi ngồi trên tay và thất bại trong việc thích nghi trong thế kỷ 21. Tất nhiên, chúng tôi không dám từ bỏ lớp áo lãnh đạo toàn cầu trong thế kỷ này\".\n Kể từ năm 1990, tỷ trọng năng lực sản xuất chất bán dẫn của Hoa Kỳ đã giảm từ 37% xuống còn 12%, theo Hiệp hội Công nghiệp Chất bán dẫn. Nhóm vận động hành lang cho biết, khoảng 75% tổng công suất của thế giới là ở châu Á.\n \"Bộ luật này không chỉ là về chip, mà còn là về khoa học\", Biden nói. \"Chúng tôi từng đứng số 1 trên thế giới [về] nghiên cứu và phát triển. Bây giờ chúng tôi xếp hạng 9. Trung Quốc đứng số 8 trước đây 8 thập kỷ. Bây giờ họ đứng số 2\".\n Bộ Ngoại giao Trung Quốc cáo buộc Mỹ 'ép buộc kinh tế' bằng luật pháp, trợ cấp khi cuộc chạy đua vũ trang công nghệ với Trung Quốc đang nông dần lên. Ảnh: @AFP.\n Mặc dù đạo luật đánh dấu sự đầu tư mang tính bước ngoặt của chính phủ Hoa Kỳ vào ngành sản xuất chip trong nước, nhưng 52 tỷ đô la trợ cấp là một khoản tiền tương đối nhỏ trong thế giới sản xuất chất bán dẫn, vốn đòi hỏi số lượng đầu tư lớn.\n Trung Quốc đã dành 150 tỷ đô la cho ngành công nghiệp chip của mình, xác định chất bán dẫn là một ngành công nghiệp chủ chốt trong kế hoạch kinh tế 5 năm mới nhất của mình. Taiwan Semiconductor Manufacturing Co., nhà sản xuất chip theo hợp đồng lớn nhất thế giới, cho biết vào năm 2021 rằng họ có kế hoạch chi 100 tỷ USD trong vòng 3 năm để mở rộng năng lực sản xuất. Liên minh châu Âu đang nghiên cứu luật sản xuất chip của riêng mình.\n Guarav Gupta, một nhà phân tích ngành công nghiệp bán dẫn của Gartner, nói rằng mặc dù các số liệu thô có thể không phải là một sự thay đổi địa chấn, nhưng tín hiệu cho thấy Mỹ đang trợ cấp cho ngành công nghiệp chip nội địa của họ là rất quan trọng.\n Ông nói: \"Việc Hoa Kỳ sẵn sàng ủng hộ các chính sách của mình và coi chất bán dẫn là điều có ý nghĩa quan trọng. \"Tôi nghĩ đó là thông điệp chính ở đây. Nhưng để có tác động có ý nghĩa, đây sẽ phải là một loại chính sách nhất quán hơn.\"", + "snippet": "Bộ Ngoại giao Trung Quốc cáo buộc Mỹ 'ép buộc kinh tế' bằng luật pháp, trợ cấp khi cuộc chạy đua vũ trang công nghệ với Trung Quốc đang nóng dần lên.", + "source_tagids": [ + 136, + 1 + ], + "source_type": 11, + "tag_phrases": [ + "Đạo luật CHIPS", + "Đạo luật CHIPS Của mỹ", + "cuộc đua vũ trang công nghệ", + "công nghiệp bán dẫn", + "cuộc đua vũ trang công nghệ mỹ trung", + "cuộc đua vũ trang công nghệ Mỹ - Trung Quốc" + ], + "title": "Đạo luật CHIPS và cuộc đua vũ trang công nghệ Mỹ - Trung Quốc đang nóng rực", + "url": "https://danviet.vn/dao-luat-chips-va-cuoc-dua-vu-trang-cong-nghe-my-trung-quoc-dang-nong-ruc-20220812084751081.htm", + "attachment_types": [ + "image", + "image", + "image" + ], + "attachment_urls": [ + "https://danviet.mediacdn.vn/296231569849192448/2022/8/12/1-1660268560597567651464.jpg", + "https://danviet.mediacdn.vn/296231569849192448/2022/8/12/4-1660268560477654005019.jpg", + "https://danviet.mediacdn.vn/296231569849192448/2022/8/12/2-16602685605751075514517.jpg" + ], + "created_time": 1660527720, + "lang": "vi" + }, + { + "crawlers": [ + "Icomm.Crawl.GoogleRss", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "khoahocdoisong.vn", + "id": "e084af86c7f8020a55aa0737ea22f0e983ba9a78", + "message": "Hỏi: Hộ chiếu của tôi bị mất, vì vậy tôi muốn xin cấp lại. Xin hỏi, hồ sơ xin cấp lại hộ chiếu như thế nào? \n\r\n Nguyễn Thị Hoan (Bắc Giang) \n\r\n Hồ sơ làm hộ chiếu công dân. \r\n Trả lời: \r\nTừ 1/7/2022, công dân Việt Nam ở trong nước và công dân Việt Nam đang ở nước ngoài sẽ bắt đầu được cấp hộ chiếu phổ thông không gắn chip điện tử theo mẫu mới.\n\r\n Công dân đã được cấp hộ chiếu mẫu cũ trước ngày 1/7/2022 sẽ tiếp tục sử dụng đến hết thời hạn ghi trong hộ chiếu.\n\r\n Công dân Việt Nam được xem xét cấp hộ chiếu phổ thông trừ trường hợp quy định tại Điều 21 Luật Xuất cảnh, nhập cảnh của công dân Việt Nam 2019.\n\r\n Hồ sơ cấp hộ chiếu phổ thông ở trong nước gồm những giấy tờ sau:\n\r\n - Người đề nghị cấp hộ chiếu nộp tờ khai theo mẫu đã điền đầy đủ thông tin.\n\r\n - 02 ảnh chân dung.\n\r\n - Giấy tờ liên quan theo xuất trình Chứng minh nhân dân, Thẻ căn cước công dân hoặc hộ chiếu còn giá trị sử dụng.\n\r\n - Tờ khai theo mẫu đã điền đầy đủ thông tin.\n\r\n - Bản sao giấy khai sinh hoặc trích lục khai sinh đối với người chưa đủ 14 tuổi.\n\r\n - Hộ chiếu phổ thông cấp lần gần nhất đối với người đã được cấp hộ chiếu.\n\r\n Trường hợp hộ chiếu bị mất phải kèm đơn báo mất hoặc thông báo về việc đã tiếp nhận đơn của cơ quan có thẩm quyền quy định tại Điều 28 Luật Xuất cảnh, nhập cảnh của công dân Việt Nam 2019.\n\r\n - Bản chụp Chứng minh nhân dân hoặc Thẻ căn cước công dân đối với trường hợp có sự thay đổi thông tin về nhân thân so với thông tin trong hộ chiếu đã cấp lần gần nhất.\n\r\n - Bản chụp có chứng thực giấy tờ do cơ quan có thẩm quyền của Việt Nam cấp chứng minh người đại diện hợp pháp đối với người mất năng lực hành vi dân sự, người có khó khăn trong nhận thức, làm chủ hành vi theo quy định của Bộ luật Dân sự, người chưa đủ 14 tuổi.\n\r\n Trường hợp bản chụp không có chứng thực thì xuất trình bản chính để kiểm tra, đối chiếu.\n\r\n Để tránh thời gian chờ đợi của công dân, Cục Quản lý xuất nhập cảnh, Bộ Công an, khuyến khích công dân chủ động khai tờ khai đề nghị cấp hộ chiếu qua Cổng dịch vụ công Bộ Công an: https://dichvucong.bocongan.go... . Việc này sẽ giúp tiết kiệm thời gian, chi phí đi lại của công dân.", + "snippet": "Từ 1/7/2022, công dân Việt Nam ở trong nước và công dân Việt Nam đang ở nước ngoài sẽ bắt đầu được cấp hộ chiếu phổ thông không gắn chip điện tử theo mẫu mới.", + "source_tagids": [ + 135 + ], + "source_type": 11, + "tag_phrases": [ + "Cơ hội nào cho hộ chiếu mới của Việt Nam?", + "Hồ sơ làm hộ chiếu công dân", + "Cải xoăn, cải ngọt tốt cho sức khỏe đường ruột", + "Cảnh báo lừa đảo qua điện thoại" + ], + "title": "Hồ sơ làm hộ chiếu công dân", + "url": "https://khoahocdoisong.vn/ho-so-lam-ho-chieu-cong-dan-196117.html", + "attachment_types": [ + "image" + ], + "attachment_urls": [ + "https://khds.1cdn.vn/2022/09/05/thu-tuc-cap-ho-chieu.jpg" + ], + "created_time": 1662420480, + "lang": "vi" + }, + { + "categories": [ + "Tuần Việt Nam" + ], + "crawlers": [ + "Icomm.Crawl.GoogleCSE", + "Icomm.Crawl.DownloadHtmlService", + "Icomm.NewsCrawl.LinkToDetailConsumer" + ], + "domain": "vietnamnet.vn", + "id": "f47f7ed7f2739e40155a2200b659c8164884cfea", + "message": "Tuy nhiên, trong khi Quốc hội Mỹ mất tận 13 tháng để thông qua đạo luật trị giá 280 tỷ USD, trong đó có 52 tỷ USD cho ngành chip, thì Trung Quốc đã có những bước nhảy vọt về công nghệ bán dẫn.\n\n Hiện tại, các chuyên gia vẫn phân tích làm thế nào Trung Quốc có thể sản xuất các chất bán dẫn có kích thước siêu nhỏ, mỏng hơn sợi tóc người khoảng 10.000 lần, ngang với các sản phẩm tốt nhất mà Đài Loan (Trung Quốc) cung cấp cho Mỹ. Với việc công nghệ bán dẫn được coi là một thước đo tiềm lực quốc gia, giống với vũ khí hạt nhân và tên lửa đạn đạo, điều này không thể khiến Washington hài lòng.\n\n Cuộc vượt mặt về công nghệ chip bán dẫn \n\n Vẫn chưa có thông tin rõ ràng nào về việc Trung Quốc có thể ứng dụng các đột phá công nghệ bán dẫn trên quy mô lớn hay không, vì đây là một quá trình tốn nhiều thời gian. Nhưng có một sự thật rõ ràng, khi mà Quốc hội Mỹ tốn quá nhiều thời gian để tranh cãi, Bắc Kinh đã vượt mặt Washington về công nghệ chip bán dẫn, pin năng lượng, robot và điện toán lượng tử.\n\n Cựu CEO của Google, Eric Schmidt, hiện điều hành Ủy ban an ninh quốc gia về trí tuệ nhân tạo, đã cảnh báo vào năm 2020 về nguy cơ tụt hậu trong công nghệ \"lõi\" của Mỹ. Một sự thật khó chấp nhận, nhưng ngành công nghiệp bán dẫn của Mỹ đã khô héo, đến mức không có con chip tiên tiến nhất nào được sản xuất ở nước này, mặc dù công nghệ được phát minh tại đây và mang lại tên tuổi cho thung lũng Silicon.\n\n \n Tổng thống Mỹ Joe Biden ký ban hành ký Đạo luật Khoa học và Chip. Ảnh: Reuters \n \n Tình cảnh này giống với Nhật Bản những năm 1980 đầu 1990, khi các gã khổng lồ công nghệ tại châu Á đã chậm chạp trong việc phát triển công nghệ di động và hệ điều hành máy tính. Nhưng không có nghĩa là Mỹ không thể bắt kịp Trung Quốc, song mọi việc không hề dễ dàng.\n\n Để so sánh, trong số 52 tỷ USD dành cho ngành chip, 39 tỷ USD sẽ được phân bổ cho \"các ưu đãi trực tiếp nhằm kích thích sản xuất” để thúc đẩy việc xây dựng và mở rộng các nhà máy sản xuất bán dẫn. Số tiền này sẽ được phân bổ trong 5 năm, với 19 tỷ USD được giải ngân trong năm nay và 5 tỷ USD mỗi năm tới năm 2026. Trong khi đó, Trung Quốc đã dành 150 tỷ USD cho ngành công nghiệp chip và xác định chất bán dẫn là ngành công nghiệp chủ chốt trong kế hoạch kinh tế 5 năm mới nhất. \n\n Tuy nhiên, theo Bộ trưởng Thương mại Mỹ Gina Raimondo, 52 tỷ USD trợ cấp liên bang sẽ được hỗ trợ bởi tiền tư nhân và biến thành \"hàng trăm tỷ\" trong các khoản đầu tư. Phần lớn số tiền này được cho là sẽ tới từ các doanh nghiệp quốc phòng, bởi họ cần những con chip tiên tiến nhất, đồng thời muốn giảm thiểu những rủi ro vào việc phụ thuộc nguồn cung nước ngoài. Đây cũng là điều các nhà lập pháp muốn, bởi các công nghệ hỗ trợ quốc phòng dễ được Quốc hội thông qua hơn.\n\n Tự chủ nguồn cung \n\n Bắc Kinh dường như cũng nhận ra những nguy cơ khi Mỹ quyết định thay đổi, khi Hội đồng xúc tiến thương mại quốc tế và Phòng Thương mại quốc tế Trung Quốc nói rằng, đạo luật mới sẽ \"tăng cạnh tranh địa chính trị trong ngành công nghiệp bán dẫn, đồng thời cản trở sự phục hồi kinh tế toàn cầu và sự phát triển của đổi mới công nghệ\". Người phát ngôn Bộ Ngoại giao Trung Quốc Uông Văn Bân cũng chỉ trích đạo luật Khoa học và Chip là một ví dụ về \"sự ép buộc kinh tế\" của Mỹ.\n\n Theo thượng nghị sĩ Todd Young, dù các bước tiến của Trung Quốc là không thể xem nhẹ, nhưng không quốc gia nào có thể vượt qua Mỹ \"nếu sử dụng tất cả nguồn lực đang có\". Một lợi thế khác là Mỹ có các mối quan hệ với nhiều đồng minh trên thế giới, điều này giúp quá trình nghiên cứu công nghệ mới có thể diễn ra nhanh hơn. \n\n \n Hình ảnh bên trong nhà máy sản xuất chip bán dẫn của TSMC. Ảnh: Time \n \n Thực tế, việc thông qua đạo luật Khoa học và Chip đánh dấu sự đồng thuận hiếm hoi của lưỡng đảng trong Quốc hội Mỹ, khi các nghị sĩ thuộc cả hai đảng đều đánh giá nó là cần thiết để giúp Mỹ cạnh tranh kinh tế với Trung Quốc cũng như tăng cường an ninh quốc gia.\n\n Nghe có vẻ kỳ lạ, nhưng chính Trung Quốc là nguyên nhân khiến cho lưỡng đảng trong Quốc hội Mỹ có thể ngưng tranh luận. Việc con chip 7 nanomet được Bắc Kinh tạo ra cho mục đích khai thác tiền điện tử đã khiến Mỹ không thể tiếp tục đứng ngoài cuộc. Ngay cả khi một số thông tin cho rằng, công nghệ này bị đánh cắp từ Đài Loan, nhưng không có nghĩa là Trung Quốc không thể tạo ra những bước đột phá từ việc sao chép. \n\n Hiện tại, Taiwan Semiconductor vẫn là nhà sản xuất chip bán dẫn lớn nhất trên thế giới, nhưng các nguy cơ bất ổn quanh eo biển Đài Loan khiến cho Mỹ buộc phải lên kế hoạch tự chủ nguồn cung. \n\n Lãnh đạo phe đa số tại Thượng viện Chuck Schumer cho rằng đạo luật Khoa học và Chip sẽ hỗ trợ làn sóng tiến bộ khoa học và công nghiệp của Mỹ, tương tự như những gì nước này đạt được sau Thế chiến thứ hai.\n\n “Nhiều kẻ đang muốn chúng ta thua cuộc, hy vọng chúng ta tự dẫm vào chân mình và không thể thích nghi trong thế kỷ 21. Chúng ta sẽ không nhường vai trò dẫn dắt của mình trong thế này”, ông Schumer nói.\n\n Việt Dũng (Theo New York Times) \n\n \n Công nghệ bán dẫn: Chiến trường mới giữa Mỹ và Trung Quốc Cuộc chiến công nghệ giữa Mỹ và Trung Quốc đã bước vào thời kỳ mới, chạy đua cho việc phát triển chip bán dẫn. \n \n \n \r\n\n Tuy nhiên, trong khi Quốc hội Mỹ mất tận 13 tháng để thông qua đạo luật trị giá 280 tỷ USD, trong đó có 52 tỷ USD cho ngành chip, thì Trung Quốc đã có những bước nhảy vọt về công nghệ bán dẫn.\n\n Hiện tại, các chuyên gia vẫn phân tích làm thế nào Trung Quốc có thể sản xuất các chất bán dẫn có kích thước siêu nhỏ, mỏng hơn sợi tóc người khoảng 10.000 lần, ngang với các sản phẩm tốt nhất mà Đài Loan (Trung Quốc) cung cấp cho Mỹ. Với việc công nghệ bán dẫn được coi là một thước đo tiềm lực quốc gia, giống với vũ khí hạt nhân và tên lửa đạn đạo, điều này không thể khiến Washington hài lòng.\n\n Cuộc vượt mặt về công nghệ chip bán dẫn \n\n Vẫn chưa có thông tin rõ ràng nào về việc Trung Quốc có thể ứng dụng các đột phá công nghệ bán dẫn trên quy mô lớn hay không, vì đây là một quá trình tốn nhiều thời gian. Nhưng có một sự thật rõ ràng, khi mà Quốc hội Mỹ tốn quá nhiều thời gian để tranh cãi, Bắc Kinh đã vượt mặt Washington về công nghệ chip bán dẫn, pin năng lượng, robot và điện toán lượng tử.\n\n Cựu CEO của Google, Eric Schmidt, hiện điều hành Ủy ban an ninh quốc gia về trí tuệ nhân tạo, đã cảnh báo vào năm 2020 về nguy cơ tụt hậu trong công nghệ \"lõi\" của Mỹ. Một sự thật khó chấp nhận, nhưng ngành công nghiệp bán dẫn của Mỹ đã khô héo, đến mức không có con chip tiên tiến nhất nào được sản xuất ở nước này, mặc dù công nghệ được phát minh tại đây và mang lại tên tuổi cho thung lũng Silicon.\n\n \n Tổng thống Mỹ Joe Biden ký ban hành ký Đạo luật Khoa học và Chip. Ảnh: Reuters \n \n Tình cảnh này giống với Nhật Bản những năm 1980 đầu 1990, khi các gã khổng lồ công nghệ tại châu Á đã chậm chạp trong việc phát triển công nghệ di động và hệ điều hành máy tính. Nhưng không có nghĩa là Mỹ không thể bắt kịp Trung Quốc, song mọi việc không hề dễ dàng.\n\n Để so sánh, trong số 52 tỷ USD dành cho ngành chip, 39 tỷ USD sẽ được phân bổ cho \"các ưu đãi trực tiếp nhằm kích thích sản xuất” để thúc đẩy việc xây dựng và mở rộng các nhà máy sản xuất bán dẫn. Số tiền này sẽ được phân bổ trong 5 năm, với 19 tỷ USD được giải ngân trong năm nay và 5 tỷ USD mỗi năm tới năm 2026. Trong khi đó, Trung Quốc đã dành 150 tỷ USD cho ngành công nghiệp chip và xác định chất bán dẫn là ngành công nghiệp chủ chốt trong kế hoạch kinh tế 5 năm mới nhất. \n\n Tuy nhiên, theo Bộ trưởng Thương mại Mỹ Gina Raimondo, 52 tỷ USD trợ cấp liên bang sẽ được hỗ trợ bởi tiền tư nhân và biến thành \"hàng trăm tỷ\" trong các khoản đầu tư. Phần lớn số tiền này được cho là sẽ tới từ các doanh nghiệp quốc phòng, bởi họ cần những con chip tiên tiến nhất, đồng thời muốn giảm thiểu những rủi ro vào việc phụ thuộc nguồn cung nước ngoài. Đây cũng là điều các nhà lập pháp muốn, bởi các công nghệ hỗ trợ quốc phòng dễ được Quốc hội thông qua hơn.\n\n Tự chủ nguồn cung \n\n Bắc Kinh dường như cũng nhận ra những nguy cơ khi Mỹ quyết định thay đổi, khi Hội đồng xúc tiến thương mại quốc tế và Phòng Thương mại quốc tế Trung Quốc nói rằng, đạo luật mới sẽ \"tăng cạnh tranh địa chính trị trong ngành công nghiệp bán dẫn, đồng thời cản trở sự phục hồi kinh tế toàn cầu và sự phát triển của đổi mới công nghệ\". Người phát ngôn Bộ Ngoại giao Trung Quốc Uông Văn Bân cũng chỉ trích đạo luật Khoa học và Chip là một ví dụ về \"sự ép buộc kinh tế\" của Mỹ.\n\n Theo thượng nghị sĩ Todd Young, dù các bước tiến của Trung Quốc là không thể xem nhẹ, nhưng không quốc gia nào có thể vượt qua Mỹ \"nếu sử dụng tất cả nguồn lực đang có\". Một lợi thế khác là Mỹ có các mối quan hệ với nhiều đồng minh trên thế giới, điều này giúp quá trình nghiên cứu công nghệ mới có thể diễn ra nhanh hơn. \n\n \n Hình ảnh bên trong nhà máy sản xuất chip bán dẫn của TSMC. Ảnh: Time \n \n Thực tế, việc thông qua đạo luật Khoa học và Chip đánh dấu sự đồng thuận hiếm hoi của lưỡng đảng trong Quốc hội Mỹ, khi các nghị sĩ thuộc cả hai đảng đều đánh giá nó là cần thiết để giúp Mỹ cạnh tranh kinh tế với Trung Quốc cũng như tăng cường an ninh quốc gia.\n\n Nghe có vẻ kỳ lạ, nhưng chính Trung Quốc là nguyên nhân khiến cho lưỡng đảng trong Quốc hội Mỹ có thể ngưng tranh luận. Việc con chip 7 nanomet được Bắc Kinh tạo ra cho mục đích khai thác tiền điện tử đã khiến Mỹ không thể tiếp tục đứng ngoài cuộc. Ngay cả khi một số thông tin cho rằng, công nghệ này bị đánh cắp từ Đài Loan, nhưng không có nghĩa là Trung Quốc không thể tạo ra những bước đột phá từ việc sao chép. \n\n Hiện tại, Taiwan Semiconductor vẫn là nhà sản xuất chip bán dẫn lớn nhất trên thế giới, nhưng các nguy cơ bất ổn quanh eo biển Đài Loan khiến cho Mỹ buộc phải lên kế hoạch tự chủ nguồn cung. \n\n Lãnh đạo phe đa số tại Thượng viện Chuck Schumer cho rằng đạo luật Khoa học và Chip sẽ hỗ trợ làn sóng tiến bộ khoa học và công nghiệp của Mỹ, tương tự như những gì nước này đạt được sau Thế chiến thứ hai.\n\n “Nhiều kẻ đang muốn chúng ta thua cuộc, hy vọng chúng ta tự dẫm vào chân mình và không thể thích nghi trong thế kỷ 21. Chúng ta sẽ không nhường vai trò dẫn dắt của mình trong thế này”, ông Schumer nói.\n\n Việt Dũng (Theo New York Times) \n\n \n Công nghệ bán dẫn: Chiến trường mới giữa Mỹ và Trung Quốc Cuộc chiến công nghệ giữa Mỹ và Trung Quốc đã bước vào thời kỳ mới, chạy đua cho việc phát triển chip bán dẫn. \n \n \r\n Công nghệ bán dẫn: Chiến trường mới giữa Mỹ và Trung Quốc Cuộc chiến công nghệ giữa Mỹ và Trung Quốc đã bước vào thời kỳ mới, chạy đua cho việc phát triển chip bán dẫn.", + "snippet": "Việc thông qua đạo luật Khoa học và Chip, với tổng số tiền được phân bổ 280 tỷ USD, được coi là nỗ lực của Mỹ trong việc bắt kịp Trung Quốc trong lĩnh vực công nghệ.", + "source_tagids": [ + 136, + 1, + 210, + 235, + 238 + ], + "source_type": 11, + "tag_phrases": [ + "Mỹ", + "Trung Quốc", + "chip bán dẫn", + "trí tuệ nhân tạo" + ], + "title": "Đạo luật Khoa học và Chip giúp Mỹ bắt kịp Trung Quốc?", + "url": "https://vietnamnet.vn/dao-luat-khoa-hoc-va-chip-giup-my-bat-kip-trung-quoc-2050411.html", + "attachment_types": [ + "image", + "image", + "image" + ], + "attachment_urls": [ + "https://static-images.vnncdn.net/files/publish/2022/8/24/biden-sign-5.jpg", + "https://static-images.vnncdn.net/files/publish/2022/8/24/semiconductor-chips-tsmc-1-6.jpg", + "https://static-images.vnncdn.net/files/publish/2022/8/22/biden-chip-copy-1018.jpeg" + ], + "created_time": 1661302800, + "lang": "vi" + } + ] + } + top_doc: int = 200 + keyword: list = [] + sorted_field: str = '' + max_doc_per_cluster: int = 50 + command_id: int = 0 + delete_message: bool = True + is_check_spam: bool = True + +class ResponseQueue(BaseModel): + statusCode: int = 200 + message: str = "" + result: dict = {} \ No newline at end of file diff --git a/function/SessionProcess.py b/function/SessionProcess.py new file mode 100644 index 0000000000000000000000000000000000000000..c573f5ca44e4d50522599db29b9ac86573166465 --- /dev/null +++ b/function/SessionProcess.py @@ -0,0 +1,55 @@ + +import time +import json +import hashlib + + +from pydantic import BaseModel + +class InputHotTopic(BaseModel): + start_time: str = "" + end_time: str = "" + query: str = "" + keywords: list = [] + top_cluster: int = 5 + prompt: str = "" + check_relevent: str = "" +class SessionProcess(object): + + def __init__(self): + self.session = dict() + + def hash_session(self, query: InputHotTopic): + hash_dict = query.dict() + hash_dict['time'] = int(time.time()) + return hashlib.sha224(json.dumps(hash_dict).encode("utf-8")).hexdigest() + + def insert_session(self, data_input): + print('data_input: ', data_input) + # if self.mode == "command_center": + # hash_id = hash_session(data_input) + # else: + hash_id = self.hash_session(data_input) + if hash_id not in self.session: + self.session[hash_id] = {"status": 0, "created_time": time.time(), "update_time": time.time(), + "result": {}, "data": data_input} + return hash_id + + def get_info_session(self, hash_id: str): + if hash_id in self.session: + return self.session[hash_id] + return {"status": -2, "result": {}, "meta": {}} + + def update_session(self, hash_id: str, result: dict, status: int): + if hash_id in self.session: + self.session[hash_id]["status"] = status + self.session[hash_id]["result"] = result + self.session[hash_id]["update_time"] = time.time() + return True + return False + + def delete_session(self, hash_id: str): + if hash_id in self.session: + del self.session[hash_id] + return True + return False diff --git a/function/__init__.py b/function/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..d5a0d28a405ac6d48e31438edc125ac590138816 --- /dev/null +++ b/function/__init__.py @@ -0,0 +1,3 @@ +# from . import topic_clustering_v2 +# from . import sentence_embedding +from SessionProcess import SessionProcess \ No newline at end of file diff --git a/function/__pycache__/SessionProcess.cpython-37.pyc b/function/__pycache__/SessionProcess.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..75b8036432bf7a144bc0ae27e484dfa977ed1258 Binary files /dev/null and b/function/__pycache__/SessionProcess.cpython-37.pyc differ diff --git a/function/__pycache__/SessionProcess.cpython-38.pyc b/function/__pycache__/SessionProcess.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..21f0e52ff91bccbc29440a5ee19fc9f52f1e72c9 Binary files /dev/null and b/function/__pycache__/SessionProcess.cpython-38.pyc differ diff --git a/function/__pycache__/__init__.cpython-37.pyc b/function/__pycache__/__init__.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..3990ab06a79128018ac036f2c7fa06fa61563e04 Binary files /dev/null and b/function/__pycache__/__init__.cpython-37.pyc differ diff --git a/function/__pycache__/__init__.cpython-38.pyc b/function/__pycache__/__init__.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..ad02cadb803cc7f89f715d2c341c188de4c47aff Binary files /dev/null and b/function/__pycache__/__init__.cpython-38.pyc differ diff --git a/function/__pycache__/tc_v2.cpython-37.pyc b/function/__pycache__/tc_v2.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..6b80080baf90e4851d2380f1ab55a32a48f3057e Binary files /dev/null and b/function/__pycache__/tc_v2.cpython-37.pyc differ diff --git a/function/__pycache__/tc_v2.cpython-38.pyc b/function/__pycache__/tc_v2.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..eb969e0c100eb3f019be71b18bffd41e325680ef Binary files /dev/null and b/function/__pycache__/tc_v2.cpython-38.pyc differ diff --git a/function/clean_text.py b/function/clean_text.py new file mode 100644 index 0000000000000000000000000000000000000000..87d25e3d5dba0bf63081f911b66493def8f30e04 --- /dev/null +++ b/function/clean_text.py @@ -0,0 +1,84 @@ +import re + +def normalize_text(text): + # text = text.lower() + text = text.replace('🏻', '') + full_text_clean = text + full_text_clean.replace(");this.closest('table').remove();","") + full_text_clean = re.sub('(Thứ .{2,4}|Chủ nhật),( ngày)? \d{1,2}\/\d{1,2}\/\d{4}( \d{1,2}:\d{1,2})?( AM| PM)?( \(GMT.{1,3}\))?','',full_text_clean) + if not any([word in full_text_clean[:15].lower() for word in ['nga','covid']]): + full_text_clean = re.sub('^.{1,15}?-','',full_text_clean) + # full_text_clean = re.sub('-.{1,15}?$','',full_text_clean) + + full_text_clean = re.sub('- VNExplorer','',full_text_clean) + full_text_clean = re.sub('Theo .{1,20}$','',full_text_clean) + full_text_clean = re.sub('\(.*(Ảnh|Nguồn).*?\)','',full_text_clean) + full_text_clean = re.sub('\d{1,2} (giờ|phút) trước','',full_text_clean) + full_text_clean = re.sub(r"http\S+", "", full_text_clean) + # full_text_clean = re.sub('(\\r)*( )*(\\n)*( )*(\\r)*( )*(\\n)','.', full_text_clean) + full_text_clean = re.sub(r"\.( )*(\.)+", '. ', full_text_clean) + full_text_clean = re.sub('\.(?!\d)', '. ', full_text_clean) + full_text_clean = re.sub('(\.(\s)+)+', '. ', full_text_clean) + full_text_clean = re.sub('<[^<]+?>', '',full_text_clean) + full_text_clean = re.sub('\d{1,2}:\d{2}( )?\d{1,2}\/\d{1,2}\/\d{4}','',full_text_clean) + full_text_clean = re.sub("Ảnh(:)?(Getty)?","", full_text_clean) + full_text_clean = full_text_clean.replace("Read more about:","").replace("Read more","").replace("Advertising","").replace("bookmark border.","").replace('the latest tech news, global tech news daily, tech news today, startups, usa tech, asia tech, china tech, eu tech, global tech, in-depth electronics reviews, 24h tech news, 24h tech news, top mobile apps, tech news daily, gaming hardware, big tech news, useful technology tips, expert interviews, reporting on the business of technology, venture capital funding, programing language',"").replace('Live updates:','').replace('-VNExplorer','').replace('Reuters:','').replace('AFP:','').replace('�','').replace('- VNExplorer','').replace('Global Tech News Daily','').replace('AFP/TTXVN','').replace('Reuters/TTXVN','').replace('Tin quốc tế','').replace('Xem tiện ích cảnh báo giá CK','') + full_text_clean = full_text_clean.replace("COVID","Covid") + full_text_clean = re.sub('[A-Z ]{2,10}(,.{6,20})?(—|–|－|-)','',full_text_clean) #NEW YORK, Feb 27 — .... /BRUSSELS—... + full_text_clean = re.sub('\(ảnh:.*?\)','.',full_text_clean) + full_text_clean = re.sub("(\| )?(\(.{1,7}\)( )?)+$", "", full_text_clean) + full_text_clean = re.sub('\d{2} [\w]{3,4}, \d{4}. \d{2}.\d{2} (AM|PM) IST','',full_text_clean) #02 Mar, 2022, 10.01 AM IST + full_text_clean = full_text_clean.replace('Suzuka. config. supports_premium_subscription && window. localStorage. getItem ( "premiumSubscription ")) ) {var e = document. createElement ( "script "); e. setAttribute ( "class ", "titan-conditional "); e. setAttribute ( "data-ad-id ", "adspot-300x250-pos1 "); document. body. appendChild (e);}','') + + full_text_clean = re.sub('\d{2}\/\d{2}\/\d{4} \d{2}:\d{2} GMT(\+|-)\d{1,2}', "", full_text_clean) + full_text_clean = re.sub('\(.{1,20}\)', '', full_text_clean) + full_text_clean = re.sub('\{.{1,20}\}', '', full_text_clean) + full_text_clean = re.sub('\[.{1,20}\]', '', full_text_clean) + full_text_clean = re.sub('[A-Z].{5,10} , \d{2}:\d{2} (GMT(\+|-)\d{1,2})?',"",full_text_clean) + + full_text_clean = re.sub('(Theo|theo) .{1,15},', '', full_text_clean) + full_text_clean = re.sub('(Theo|theo) .{1,15},', '', full_text_clean) + full_text_clean = re.sub('theo.{3,20}$','', full_text_clean) + full_text_clean = re.sub('^Trong khi đó','', full_text_clean) + + full_text_clean = re.sub('^\d{1,10} minutes ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} hours ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} days ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} years ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} months ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} minute ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} day ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} year ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} month ago', '', full_text_clean) + full_text_clean = re.sub('^\d{1,10} hour ago', '', full_text_clean) + full_text_clean = re.sub('^(a|an) minute ago', '', full_text_clean) + full_text_clean = re.sub('^(a|an) hour ago', '', full_text_clean) + full_text_clean = re.sub('^(a|an) day ago', '', full_text_clean) + full_text_clean = re.sub('^(a|an) month ago', '', full_text_clean) + full_text_clean = re.sub('^(a|an) year ago', '', full_text_clean) + full_text_clean = re.sub('^.{0,12}(tờ|theo|nguồn|trích dẫn|trang|báo|hãng).{1,30}(đưa tin|dẫn lời|trích dẫn|nhận định|cho biết)', '', full_text_clean, flags=re.I) + + text = re.sub('\s+',' ',full_text_clean) + text = re.sub('Đọc chi tiết bài viết tại đây.*','',text,flags=re.I) + # text = re.sub('[(\d)(\:)(\|)(\/)(\s+)]+','',text) # 10:20 | 09/03/2022 + + text = re.sub('(\d{1,2}:\d{2}( )*)\|( )*\d{1,2}(/|-)\d{2}(/|-)\d{4}','',text) + text = re.sub('^(\d)+[\,\.]\s+ ','',text) # 3, phát ngôn viên Bộ T + text = re.sub('((chủ nhật)|(thứ bảy)|(thử sáu)|(thứ năm)|(thứ tư)|(thứ ba)|(thứ hai))([(\d)(\:)(,)(\|\/)(\s+)]+)((VOV)|(VTV))$','',text,flags=re.I) # và Ukraine để giải quyết xung đột Chủ Nhật, 06:32, 20/03/2022 VOV. + + text = re.sub('^((\d)|(\:)|(\.)|(\|)|(\s+)|(in bài biết)|(in bài viết)|(\/))+ ','',text,flags=re.I) # 10:20 | 09/03/2022 In bài biết. 10:20 | 09/03/2022 In bài biết Việc xuất khẩu tôm sang thị trường Nga có thể bị ảnh hưởng trước tình hình căng thẳng của Nga-Ukraine. Hiệp hội Chế biến và Xuất khẩu thuỷ sản V + text = re.sub('theo hãng tin [A-Z].{0,15},','', text, flags=re.I) + text = re.sub('((Theo.{0,30})|(Reuters)).*?(link gốc).*?$','',text,flags=re.I) + text = re.sub('video:RIA Novosti/Bộ Quốc phòng Nga','',text,flags=re.I) + text = re.sub('Báo.{5,20}$','',text) + text = re.sub('RIA Novosti/Bộ Quốc phòng Nga','',text) + text = re.sub('(chính trị|quân sự|đối ngoại|thời sự|khoa học|pháp luật) \d{1,2} giờ','',text,flags=re.I) + text = text.replace('|','') + full_text_clean = re.sub('^.*?(Link nguồn)','',text,flags=re.I) # ( + full_text_clean = re.sub(',( )*[A-z].{1,30}(đưa tin|trích dẫn)','', full_text_clean) + full_text_clean = re.sub('(Reuters|Vnexpress)(\).)?','',full_text_clean,flags=re.I) + full_text_clean = re.sub('^VOV.','',full_text_clean) + full_text_clean = full_text_clean.replace("Many Japanese worry Fortune-Takashi Nakamichi, Bloomberg • 1d","").replace('baotintuc. vn',"").replace('YÊN BÁI QUYẾT TÂM THỰC HIỆN THẮNG LỢI CHƯƠNG TRÌNH HÀNH ĐỘNG SỐ 56 – CTr/TU CỦA TỈNH ỦY QUYẾT TÂM ĐƯA Y.ÊN BÁI PHÁT TRIỂN NHANH, BỀN VỮNG THEO HƯỚNG “XANH, HÀI HÒA, BẢN SẮC VÀ HẠNH PHÚC” TRỞ THÀNH TỈNH PHÁT TRIỂN KHÁ VÀO NĂM 2025','') + full_text_clean = full_text_clean.replace("Baoquocte","").replace('ชั่วโมงที่ผ่านมา.','').replace('""challenge=" "coron= ""corona=" "covid-19= ""designs=" "endgame= ""tutorial=" "ui= ""pandemic=" "quarantine= ""list=" "similarity= " "ux. ""press=" "copyright= ""contact=" "creators= ""advertise=" "terms= ""privacy=" "policy= ""safety=" "youtube= ""works=" "test= ""features=" "creators.', '').replace('nbsp & nbsp & nbsp & nbsp & nbsp Copy Link', '').replace('Tổng thống Nga Vladimir Putin và Chủ tịch Trung Quốc Tập Cận Bình.','').replace('Thế giới Toàn cảnh Bảo Hà ','') + full_text_clean = re.sub('(a|p)\. m\.','',full_text_clean) + return full_text_clean \ No newline at end of file diff --git a/function/detect_time.py b/function/detect_time.py new file mode 100644 index 0000000000000000000000000000000000000000..92720bebceb8fb54ee18b74a2b25145f73ffe642 --- /dev/null +++ b/function/detect_time.py @@ -0,0 +1,92 @@ +import re +import requests +import datetime +import operator +from typing import * +from dateutil.relativedelta import * +from itertools import groupby +from dateparser import parse + +day = '[0-3]{0,1}[0-9]' +month = '[0,1]{0,1}[0-9]' +year = '\d{4}' +sep = '\s*[-/\.\s]\s*' + +patterns = [ + f"{day}{sep}{month}{sep}{year}", + f"{year}{sep}{month}{sep}{day}", + f"{day}\s+tháng\s+{month}", + f"{day}\s+tháng\s+{month}{sep}{year}", + f"{day}\s+tháng\s+{month}\s+năm\s+{year}", + f"{day}\s+tháng\s+{month}", + f"(?<=ngày)\s+{day}{sep}{month}", + f"(?<=ngày)\s+{day}{sep}{month}{sep}{year}", + f"(?<=sáng)\s+{day}{sep}{month}", + f"(?<=sáng)\s+{day}{sep}{month}{sep}{year}", + f"(?<=trưa)\s+{day}{sep}{month}", + f"(?<=trưa)\s+{day}{sep}{month}{sep}{year}", + f"(?<=chiều)\s+{day}{sep}{month}", + f"(?<=chiều)\s+{day}{sep}{month}{sep}{year}", + f"(?<=tối)\s+{day}{sep}{month}", + f"(?<=tối)\s+{day}{sep}{month}{sep}{year}" + f"(?<=đêm)\s+{day}{sep}{month}", + f"(?<=đêm)\s+{day}{sep}{month}{sep}{year}", + f"(?<=hôm)\s+{day}{sep}{month}", + f"(?<=hôm)\s+{day}{sep}{month}{sep}{year}", + f"{day}{sep}{month}[\s\.\,\)]" +] + + +def extract_pattern(text: str, patterns: List[str]): + detected = [] + for pattern in patterns: + for match in re.finditer(pattern, text): + detected.append((match.start(), match.end())) + detected.sort() + output = [] + curr = -1 + for start, values in groupby(detected, key=operator.itemgetter(0)): + if start < curr: + continue + values = list(values) + values.sort(key=operator.itemgetter(1), reverse=True) + output.append(values[0]) + curr = values[0][1] + return output + + +def detect_time(text: str, language: str = 'vi', base: Optional[datetime.datetime] = None): + text = text.lower() + detected_patterns = extract_pattern(text, patterns) + output = [] + settings = { + 'PREFER_DAY_OF_MONTH': 'first' + } + if base: + settings['RELATIVE_BASE'] = base + for start, end in detected_patterns: + segment = text[start:end] + segment = re.sub('\s+', ' ', segment).strip().lower() + candiate = parse(segment, languages=[language], settings=settings) + output.append((segment, candiate)) + return output + + +def get_time_post(sentences, patterns, start_time=None, end_time=None): + dict_time_evs = {} + for i, sen in enumerate(sentences): + if sen.strip() != "": + time_ex = detect_time(sen, patterns) + for te in time_ex: + if te[1] is not None: + if start_time is None or end_time is None or (end_time > te[1].timestamp() > start_time): + if te not in dict_time_evs: + dict_time_evs[te] = [] + dict_time_evs[te].append(i) + return dict_time_evs + + +if __name__ == '__main__': + print(detect_time("VietTimes – Ngoại trưởng Mỹ Antony Blinken ngày đã tuyên bố trong một cuộc họp qua" + "truyền hình với ngoại trưởng các nước ASEAN Mỹ bác bỏ các yêu sách “bất hợp pháp” của" + "Trung Quốc ở Biển Đông.", language="vi")) \ No newline at end of file diff --git a/function/embed_vncorenlp.py b/function/embed_vncorenlp.py new file mode 100644 index 0000000000000000000000000000000000000000..858a225789e976bcec95f6cefa65f004e8e082f7 --- /dev/null +++ b/function/embed_vncorenlp.py @@ -0,0 +1,161 @@ +import jnius_config +import os +import shutil + +save_dir = "/home2/vietle/icgpt/vncorenlp-1.2" +max_heap_size='-Xmx4g' +jnius_config.add_options(max_heap_size) +jnius_config.set_classpath(save_dir + "/VnCoreNLP-1.2.jar") + +def download_model(save_dir='./'): + # current_path = os.path.abspath(os.getcwd()) + if save_dir[-1] == '/': + save_dir = save_dir[:-1] + if os.path.isdir(save_dir + "/models") and os.path.exists(save_dir + '/VnCoreNLP-1.2.jar'): + print("VnCoreNLP model folder " + save_dir + " already exists! Please load VnCoreNLP from this folder!") + else: + os.mkdir(save_dir + "/models") + os.mkdir(save_dir + "/models/dep") + os.mkdir(save_dir + "/models/ner") + os.mkdir(save_dir + "/models/postagger") + os.mkdir(save_dir + "/models/wordsegmenter") + # jar + os.system("wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/VnCoreNLP-1.2.jar") + shutil.move("VnCoreNLP-1.2.jar", save_dir + "/VnCoreNLP-1.2.jar") + # wordsegmenter + os.system("wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/wordsegmenter/vi-vocab") + os.system( + "wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/wordsegmenter/wordsegmenter.rdr") + shutil.move("vi-vocab", save_dir + "/models/wordsegmenter/vi-vocab") + shutil.move("wordsegmenter.rdr", save_dir + "/models/wordsegmenter/wordsegmenter.rdr") + # postagger + os.system("wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/postagger/vi-tagger") + shutil.move("vi-tagger", save_dir + "/models/postagger/vi-tagger") + # ner + os.system("wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/ner/vi-500brownclusters.xz") + os.system("wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/ner/vi-ner.xz") + os.system( + "wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/ner/vi-pretrainedembeddings.xz") + shutil.move("vi-500brownclusters.xz", save_dir + "/models/ner/vi-500brownclusters.xz") + shutil.move("vi-ner.xz", save_dir + "/models/ner/vi-ner.xz") + shutil.move("vi-pretrainedembeddings.xz", save_dir + "/models/ner/vi-pretrainedembeddings.xz") + # parse + os.system("wget https://raw.githubusercontent.com/vncorenlp/VnCoreNLP/master/models/dep/vi-dep.xz") + shutil.move("vi-dep.xz", save_dir + "/models/dep/vi-dep.xz") + + +class VnCoreNLP: + def __init__(self, annotators=["wseg", "pos", "ner", "parse"], save_dir = './'): + if save_dir[-1] == '/': + save_dir = save_dir[:-1] + if os.path.isdir(save_dir + "/models") == False or os.path.exists(save_dir + '/VnCoreNLP-1.2.jar') == False: + raise Exception("Please download the VnCoreNLP model!") + self.current_working_dir = os.getcwd() + os.chdir(save_dir) + + from jnius import autoclass + javaclass_vncorenlp = autoclass('vn.pipeline.VnCoreNLP') + self.javaclass_String = autoclass('java.lang.String') + self.annotators = annotators + if "wseg" not in annotators: + self.annotators.append("wseg") + + self.model = javaclass_vncorenlp(annotators) + + def annotate_text(self, text): + from jnius import autoclass + javaclass_Annotation = autoclass('vn.pipeline.Annotation') + str = self.javaclass_String(text) + annotation = javaclass_Annotation(str) + self.model.annotate(annotation) + dict_sentences = {} + list_sentences = annotation.toString().split("\n\n")[:-1] + for i in range(len(list_sentences)): + list_words = list_sentences[i].split("\n") + list_dict_words = [] + for word in list_words: + dict_word = {} + word = word.replace("\t\t", "\t") + list_tags = word.split("\t") + dict_word["index"] = int(list_tags[0]) + dict_word["wordForm"] = list_tags[1] + dict_word["posTag"] = list_tags[2] + dict_word["nerLabel"] = list_tags[3] + if "parse" in self.annotators: + dict_word["head"] = int(list_tags[4]) + else: + dict_word["head"] = list_tags[4] + dict_word["depLabel"] = list_tags[5] + list_dict_words.append(dict_word) + dict_sentences[i] = list_dict_words + return dict_sentences + + def tokenize(self, text): + annotated_sens = self.annotate_text(text=text) + output = [] + for id_sen in annotated_sens: + annotated_sen = annotated_sens[id_sen] + out = [s["wordForm"] for s in annotated_sen] + output.append(out) + return output + + def pos_tag(self, text): + annotated_sens = self.annotate_text(text=text) + output = [] + for id_sen in annotated_sens: + annotated_sen = annotated_sens[id_sen] + out = [(s["wordForm"], s["posTag"]) for s in annotated_sen] + output.append(out) + return output + + def ner(self, text): + annotated_sens = self.annotate_text(text=text) + output = [] + for id_sen in annotated_sens: + annotated_sen = annotated_sens[id_sen] + out = [(s["wordForm"], s["nerLabel"]) for s in annotated_sen] + output.append(out) + return output + + def word_segment(self, text): + from jnius import autoclass + javaclass_Annotation = autoclass('vn.pipeline.Annotation') + str = self.javaclass_String(text) + annotation = javaclass_Annotation(str) + self.model.annotate(annotation) + list_segmented_sentences = [] + list_sentences = annotation.toString().split("\n\n")[:-1] + for sent in list_sentences: + list_words = sent.split("\n") + list_segmented_words = [] + for word in list_words: + word = word.replace("\t\t", "\t") + list_tags = word.split("\t") + list_segmented_words.append(list_tags[1]) + list_segmented_sentences.append(" ".join(list_segmented_words)) + return list_segmented_sentences + + def print_out(self, dict_sentences): + for sent in dict_sentences.keys(): + list_dict_words = dict_sentences[sent] + for word in list_dict_words: + print(str(word["index"]) + "\t" + word["wordForm"] + "\t" + word["posTag"] + "\t" + word["nerLabel"] + "\t" + str(word["head"]) + "\t" + word["depLabel"]) + print("") + + def annotate_file(self, input_file, output_file): + os.chdir(self.current_working_dir) + input_str = self.javaclass_String(input_file) + output_str = self.javaclass_String(output_file) + self.model.processPipeline(input_str, output_str, self.annotators) + +if __name__ == '__main__': + download_model(save_dir='/home2/vietle/icgpt/vncorenlp-1.2') + model = VnCoreNLP(annotators=["wseg","pos","ner"], save_dir='/home2/vietle/icgpt/vncorenlp-1.2') + # output = model.annotate_text("Ông Nguyễn Khắc Chúc đang làm việc tại Đại học Quốc gia Hà Nội. Bà Lan, vợ ông Chúc, cũng làm việc tại đây.") + # print(output) + + text = "Sau khi tốt nghiệp Trung học năm 1975, ông theo học dự bị Ngoại ngữ tại Đại học Ngoại ngữ (nay là Trường Đại học Hà Nội)." + out = model.tokenize(text) + print(out) + # model.print_out(output) + \ No newline at end of file diff --git a/function/sentence_embbeding.py b/function/sentence_embbeding.py new file mode 100644 index 0000000000000000000000000000000000000000..d91a5185d5061303ba8875712e71a109e5a96eb8 --- /dev/null +++ b/function/sentence_embbeding.py @@ -0,0 +1,41 @@ +import requests +import json + +URL_EMBBED_ZH = "http://10.9.3.239:1999/api/v1/extract_feature_zh" +URL_EMBBED_EN = "http://10.9.3.239:1999/api/v1/extract_feature_en" +URL_EMBBED_BGE = "http://10.9.3.240:5045/api/v1/embedding" + +def embbeded_zh(text: list): + try: + r = requests.post(URL_EMBBED_ZH, data = json.dumps({ + "text": text + })) + embs = r.json()["vectors"] + return embs + except Exception as ve: + print(ve) + return [] + + +def embbeded_en(text: list): + try: + r = requests.post(URL_EMBBED_EN, data = json.dumps({ + "text": text + })) + embs = r.json()["vectors"] + return embs + except Exception as ve: + print(ve) + return [] + + +def embedded_bge(text: list): + try: + r = requests.post(URL_EMBBED_BGE, data = json.dumps({ + "text": text + })) + embs = r.json()["embeddings"] + return embs + except Exception as ve: + print(ve) + return [] \ No newline at end of file diff --git a/function/summary_with_llm.py b/function/summary_with_llm.py new file mode 100644 index 0000000000000000000000000000000000000000..37bfe704302795d257d1c07cc1c22be42a645135 --- /dev/null +++ b/function/summary_with_llm.py @@ -0,0 +1,210 @@ +import json +import requests +import nltk +import re +import time + +nltk.download('punkt') + + +URL_LLAMA = "http://10.9.3.241:8022/api/v1/llama/QnA" +VERSION = { + "en-llama": "mistral-full", #"llama2-7b", + "vi-llama": "mistral-full" #"ic-llama-68k" +} + +SYSTEM_PROMPT = "" +POST_FIX_Q = "" + +SYSTEM_PROMPT_CHECK_RELEVANT = "Bạn là trợ lý AI giúp mọi người tìm kiếm thông tin. Người dùng sẽ cung cấp cho bạn một câu hỏi. Nhiệm vụ của bạn là trả lời trung thực nhất có thể." +PROMPT_RELEVANT = 'Câu trả lời dưới có liên quan đến câu hỏi "{0}" hay không?' + + +REMOVE_WORDS = [] +with open("data/remove.txt", 'r') as f: + for line in f: + line = line.strip() + if line: + REMOVE_WORDS.append(line.lower()) +print(REMOVE_WORDS) + + +def check_answer_contains_remove_words(text): + text = text.lower() + text = re.sub(r'\s+ ', ' ', text) + lst_sen = nltk.sent_tokenize(text) + for sen in lst_sen: + for pat in REMOVE_WORDS: + if re.search(pat, sen) is not None: + return True + return False + + +def normalize_text_after_qna_llm(text, prompt: str = ""): + + text = re.sub("^Dựa trên.{1,60}cung cấp,", "", text.strip(), flags=re.I).strip() + text = re.sub("^Dự báo.{1,60}là", "", text, flags=re.I).strip() + text = re.sub("^.{1,15}dựa trên.{1,60}cung cấp,", "", text, flags=re.I).strip() + text = re.sub("^.{1,15}theo thông tin.{1,60}cung cấp,", "", text, flags=re.I).strip() + # if len(prompt) > 10: + # print("pattern: ", "^" + prompt[:10] + ".{1,40}là") + # text = re.sub("^" + prompt[:10] + ".{1,40}là", "", text, flags=re.I).strip() + if text and text[0].islower(): + text = text[0].upper() + text[1:] + return text + + +def created_context(text, max_word=2048): + text = re.sub(r'\s+ ', ' ', text) + lst_sen = nltk.sent_tokenize(text) + count_w = 0 + contexts = [] + lst_sen_per_context = [] + for sen in lst_sen: + count_w += sen.count(" ") + lst_sen_per_context.append(sen) + if count_w > max_word: + contexts.append(" ".join(lst_sen_per_context)) + lst_sen_per_context = [] + count_w = 0 + if lst_sen_per_context: + contexts.append(" ".join(lst_sen_per_context)) + return contexts + + +def get_icgpt_result(questions, contexts, lang, version="vi-llama", system_prompt:str = "", id_cluster="", hash_str: str = ""): + json_body = { + "questions": questions, + "contexts": contexts, + "lang": lang, + "version": VERSION[version], + "system_prompt": system_prompt + } + try: + + res = requests.post(URL_LLAMA, json=json_body) + with open(f"log_llm/requests_llama/{hash_str}_{id_cluster}.txt", "w") as f: + f.write(json.dumps(json_body) + "\n") + f.write(json.dumps(res.json()) + "\n" + "$"*50) + res = res.json()["result"] + res = [x.replace("_", " ") for x in res] + return res + except Exception as ex: + print(f"[ERROR] get_icgpt_official_visit: {str(ex)}") + with open(f"log_llm/requests_llama_error/{hash_str}_{id_cluster}.txt", "w") as f: + f.write(json.dumps(json_body) + "\n") + return None + + +def check_relevant_with_llama(question, content, lang, version="en-llama", max_word_per_context=1024, id_cluster="", hash_str: str = ""): + contexts = created_context(content, max_word=max_word_per_context) + content = contexts[0] if contexts else "" + answer = "" + question_all = question.split("#####") + check_rel = True + for question in question_all: + question = question.strip() + # question = PROMPT_RELEVANT.format(question) + question_split = question.split("$$$$") + if len(question_split) < 2: + question = question + system_prompt = "" + else: + system_prompt = question_split[0].strip() + question = question_split[1].strip() + + # system_prompt = SYSTEM_PROMPT_CHECK_RELEVANT + if content: + contexts = [content] + questions = [question] + lst_res = get_icgpt_result(questions, contexts, lang, version=version, system_prompt=system_prompt, id_cluster=f"{id_cluster}_recheck_relevant", hash_str=hash_str) + if lst_res is None: + lst_res = [] + check_rel = True + # continue + # break + for an in lst_res: + if an: + is_relevant = check_answer_contains_remove_words(an) + answer = normalize_text_after_qna_llm(an, prompt=question) + if len(answer) == 0: + check_rel = True + # continue + # break + else: + check_rel = is_relevant + if not check_rel: + break + if not check_rel: + break + else: + check_rel = True + return check_rel + + +def summary_with_llama(question, content, lang, version="vi-llama", max_word_per_context=1024, id_cluster="", hash_str: str = ""): + contexts = created_context(content, max_word=max_word_per_context) + question_split = question.split("$$$$") + if len(question_split) < 2: + question = question + system_prompt = "" + else: + system_prompt = question_split[0].strip() + question = question_split[1].strip() + + if question.strip().endswith(".") or question.strip().endswith("?"): + question = (question + POST_FIX_Q).strip() + else: + question = (question + ". " + POST_FIX_Q).strip() + answer = "" + if contexts: + contexts = [contexts[0]] + questions = [question] * len(contexts) + lst_res = get_icgpt_result(questions, contexts, lang, version=version, system_prompt=system_prompt, id_cluster=id_cluster, hash_str=hash_str) + results = [] + if lst_res is None: + lst_res = [] + for an in lst_res: + + is_relevant = check_answer_contains_remove_words(an) + + if not is_relevant: + results.append(an) + # else: + # print("ans_from_llama-preview: ", an, is_relevant) + if results: + if len(results) > 1: + context_combine = [". ".join(results)] + res = get_icgpt_result([question], context_combine, lang, version=version, system_prompt=system_prompt, id_cluster=id_cluster, hash_str=hash_str) + if res: + answer = res[0] + else: + answer = results[0] + else: + if lst_res: + return "", True + if answer: + is_relevant = check_answer_contains_remove_words(answer) + # print("ans_from_llama-before: ", answer, is_relevant) + answer = normalize_text_after_qna_llm(answer, prompt=question) + + if len(answer) == 0: + is_relevant = True + # print("ans_from_llama-after: ", answer, is_relevant) + return answer, is_relevant + + +if __name__ == '__main__': + text = """ Dựa trên thông tin được cung cấp, xung đột ở Biển Đông đã gia tăng và có thể xuất hiện điểm xung đột mới giữa Philippines và Trung Quốc. Philippines đang xem xét xây dựng một ngọn hải đăng trên Bãi cạn Second Thomas (còn gọi là Bãi cạn Second Thomas), điều này đã khiến Trung Quốc tuyên bố rằng đây là một hành động vi phạm nghiêm trọng chủ quyền của họ và sẽ đáp trả kiên quyết. Giới chuyên gia cho rằng điểm bùng phát xung đột mới có thể xảy ra giữa Philippines và Trung nước ở Biển Đông. Tham vọng hung hăng của Trung Quốc đã thúc đẩy căng thẳng khu vực và các tranh chấp gần đây về vụ va chạm gần đây của các tàu gần Bãi Cỏ Mây (Second Thomas Shoal) ở Biển Đông đã làm căng th ng giữa Trung Quốc và Philippines gia tăng. """ + is_re = check_answer_contains_remove_words(text) + print(is_re) + an = normalize_text_after_qna_llm(text) + print(an) +# exit(1) +# message = "G\u1EA7n \u0111\u00E2y, Philippines \u0111\u00E3 nhi\u1EC1u l\u1EA7n g\u00E2y ra r\u1EAFc r\u1ED1i \u1EDF Bi\u1EC3n \u0110\u00F4ng, x\u00E2m nh\u1EADp \u0110\u00E1 Nh\u00E2n \u00C1i thu\u1ED9c qu\u1EA7n \u0111\u1EA3o Nam Sa c\u1EE7a Trung Qu\u1ED1c, \u0111\u1ED3ng th\u1EDDi ti\u1EBFp t\u1EE5c ph\u00F3ng \u0111\u1EA1i v\u00E0 c\u01B0\u1EDDng \u0111i\u1EC7u h\u00F3a, nh\u1EA7m l\u1EABn \u0111\u00FAng sai v\u00E0 \u0111\u01B0a ra nh\u1EEFng c\u00E1o bu\u1ED9c v\u00F4 l\u00FD ch\u1ED1ng l\u1EA1i Trung Qu\u1ED1c. \\n Ng\u01B0\u1EDDi Philippines ngh\u0129 g\u00EC v\u1EC1 h\u00E0nh \u0111\u1ED9ng c\u1EE7a ch\u00EDnh ph\u1EE7 Philippines? \\ n \u00D4ng Tan \u0111\u00E3 t\u00ECm ra Herman Laurel, m\u1ED9t nh\u00E0 b\u00ECnh lu\u1EADn ch\u00EDnh tr\u1ECB n\u1ED5i ti\u1EBFng \u1EDF Philippines, \u0111\u1ED3ng th\u1EDDi l\u00E0 gi\u00E1m \u0111\u1ED1c Vi\u1EC7n nghi\u00EAn c\u1EE9u chi\u1EBFn l\u01B0\u1EE3c \"Th\u1EBF k\u1EF7 ch\u00E2u \u00C1\" c\u1EE7a Philippines v\u00E0 l\u00E0 ng\u01B0\u1EDDi s\u00E1ng l\u1EADp Hi\u1EC7p h\u1ED9i nghi\u00EAn c\u1EE9u ch\u00EDnh s\u00E1ch BRICS c\u1EE7a Philippines. Herman Laurel, ng\u01B0\u1EDDi \u0111ang nghi\u00EAn c\u1EE9u v\u1EC1 ch\u00E2u \u00C1, \u0111\u1EB7c bi\u1EC7t l\u00E0 m\u1ED1i quan h\u1EC7 gi\u1EEFa Trung Qu\u1ED1c v\u00E0 ASEAN, chia s\u1EBB quan s\u00E1t c\u1EE7a m\u00ECnh. \\n 01 \\n Tan Zhu: K\u1EC3 t\u1EEB n\u1EEDa cu\u1ED1i n\u0103m nay, Philippines th\u01B0\u1EDDng xuy\u00EAn x\u00E2m chi\u1EBFm c\u00E1c \u0111\u1EA3o v\u00E0 b\u00E3i \u0111\u00E1 c\u1EE7a ch\u00FAng t\u00F4i \u1EDF Bi\u1EC3n \u0110\u00F4ng, l\u00E0m gia t\u0103ng c\u0103ng th\u1EB3ng \u1EDF Bi\u1EC3n \u0110\u00F4ng, \u0111\u1ED3ng th\u1EDDi vu kh\u1ED1ng Trung Qu\u1ED1c l\u00E0 k\u1EBB b\u1EAFt n\u1EA1t l\u1EDBn. , c\u00F3 nh\u1EEFng nh\u00F3m \u1EDF Philippines ph\u1EA3n \u0111\u1ED1i h\u00E0nh \u0111\u1ED9ng khi\u00EAu kh\u00EDch c\u1EE7a Philippines. B\u1EA1n c\u1EA3m th\u1EA5y th\u1EBF n\u00E0o v\u1EC1 \u0111i\u1EC1u n\u00E0y v\u1EDBi t\u01B0 c\u00E1ch l\u00E0 m\u1ED9t ng\u01B0\u1EDDi Philippines? Herman Laurel: T\u00F4i cho r\u1EB1ng C\u1EA3nh s\u00E1t bi\u1EC3n Philippines v\u00E0 m\u1ED9t s\u1ED1 t\u00E0u d\u00E2n s\u1EF1 Philippines \u0111\u00E3 c\u1ED1 t\u00ECnh g\u00E2y r\u1EAFc r\u1ED1i v\u00EC h\u1ECD \u0111ang th\u1EF1c hi\u1EC7n \u201CD\u1EF1 \u00E1n t\u1ED5ng th\u1EC3\u201D c\u1EE7a Hoa K\u1EF3. \\nM\u1EF9 khoe khoang d\u1EF1 \u00E1n n\u00E0y v\u1EDBi ch\u00FAng t\u00F4i n\u00EAn ch\u00FAng t\u00F4i bi\u1EBFt t\u00EAn d\u1EF1 \u00E1n. D\u1EF1 \u00E1n \u0111\u01B0\u1EE3c d\u1EABn d\u1EAFt b\u1EDFi \u0110\u1EA1i t\u00E1 Kh\u00F4ng qu\u00E2n Hoa K\u1EF3 \u0111\u00E3 ngh\u1EC9 h\u01B0u Raimundo Powell, l\u00E0m vi\u1EC7c v\u1EDBi c\u00E1c \u0111\u1ED1i t\u00E1c Philippines nh\u01B0 C\u1EA3nh s\u00E1t bi\u1EC3n Philippines v\u00E0 m\u1ED9t s\u1ED1 quan ch\u1EE9c c\u1EE7a B\u1ED9 Ngo\u1EA1i giao Philippines. H\u1ECD l\u00EAn k\u1EBF ho\u1EA1ch, \u00E2m m\u01B0u v\u00E0 th\u1EF1c hi\u1EC7n d\u1EF1 \u00E1n n\u00E0y nh\u1EB1m \u0111\u1ED1i \u0111\u1EA7u, khi\u00EAu kh\u00EDch v\u00E0 \u0111\u1ED1i \u0111\u1EA7u v\u1EDBi Qu\u00E2n \u0111o\u00E0n C\u1EA3nh s\u00E1t bi\u1EC3n thu\u1ED9c L\u1EF1c l\u01B0\u1EE3ng C\u1EA3nh s\u00E1t V\u0169 trang Nh\u00E2n d\u00E2n Trung Qu\u1ED1c. T\u1EA5t c\u1EA3 nh\u1EEFng \u0111i\u1EC1u n\u00E0y \u0111\u1EC1u nh\u1EB1m m\u1EE5c \u0111\u00EDch c\u1ED1 t\u00ECnh t\u1EA1o ra c\u0103ng th\u1EB3ng \u1EDF Bi\u1EC3n \u0110\u00F4ng, \u0111\u1EB7c bi\u1EC7t l\u00E0 t\u1EA1i c\u00E1c khu v\u1EF1c tranh ch\u1EA5p gi\u1EEFa Philippines v\u00E0 Trung Qu\u1ED1c nh\u01B0 B\u00E3i c\u1EA1n Scarborough hay B\u00E3i c\u1EA1n Second Thomas. \\n \\n \\n \\n \\n Vi\u1EC7c Trung Qu\u1ED1c s\u1EED d\u1EE5ng t\u00E0u l\u1EDBn v\u00E0 t\u00E0u chi\u1EBFn l\u00E0 \u0111i\u1EC1u t\u1ED1t. L\u1EE3i th\u1EBF v\u1EC1 s\u1ED1 l\u01B0\u1EE3ng v\u00E0 quy m\u00F4 c\u1EE7a L\u1EF1c l\u01B0\u1EE3ng C\u1EA3nh s\u00E1t bi\u1EC3n thu\u1ED9c L\u1EF1c l\u01B0\u1EE3ng C\u1EA3nh s\u00E1t V\u0169 trang Nh\u00E2n d\u00E2n Trung Qu\u1ED1c th\u1EF1c s\u1EF1 tr\u00E1nh \u0111\u01B0\u1EE3c m\u1ED9t cu\u1ED9c \u0111\u1ED1i \u0111\u1EA7u th\u1EF1c s\u1EF1 nghi\u00EAm tr\u1ECDng h\u01A1n, b\u1EDFi v\u00EC n\u1EBFu hai b\u00EAn c\u00F3 quy m\u00F4 ngang nhau, M\u1ED9t cu\u1ED9c xung \u0111\u1ED9t h\u1EA1m \u0111\u1ED9i c\u00F3 th\u1EC3 tr\u1EDF n\u00EAn s\u1EAFp x\u1EA3y ra. \\ n Nh\u01B0ng d\u00F9 th\u1EBF n\u00E0o \u0111i n\u1EEFa, c\u00E1c ph\u01B0\u01A1ng ti\u1EC7n truy\u1EC1n th\u00F4ng ph\u01B0\u01A1ng T\u00E2y s\u1EBD m\u00F4 t\u1EA3 Trung Qu\u1ED1c l\u00E0 k\u1EBB b\u1EAFt n\u1EA1t. \u0110\u00E2y l\u00E0 m\u1EE5c \u0111\u00EDch th\u1EF1c s\u1EF1 c\u1EE7a d\u1EF1 \u00E1n n\u00E0y v\u00E0 l\u00E0 m\u1EE5c ti\u00EAu m\u00E0 Hoa K\u1EF3 \u0111\u1EB7t ra - h\u1ECD s\u1EED d\u1EE5ng c\u00E1i g\u1ECDi l\u00E0 \"ni\u1EC1m tin v\u00E0o t\u00EDnh minh b\u1EA1ch c\u1EE7a b\u00E1o c\u00E1o\" \u0111\u1EC3 c\u1EA5u th\u00E0nh m\u1ED9t \"\u00E2m m\u01B0u \u0111en t\u1ED1i\" ch\u1ED1ng l\u1EA1i Trung Qu\u1ED1c... c\u00F4ng khai\". \u0110\u01B0\u1EE3c cho l\u00E0 minh b\u1EA1ch v\u00EC truy\u1EC1n th\u00F4ng ph\u01B0\u01A1ng T\u00E2y \u0111\u00E3 mang theo camera, nh\u00E2n vi\u00EAn truy\u1EC1n th\u00F4ng... \u0111\u1EC3 ghi l\u1EA1i qu\u00E1 tr\u00ECnh n\u00E0y v\u00E0 \u0111\u01B0a tin cho kh\u00E1n gi\u1EA3 Philippines v\u00E0 th\u1EBF gi\u1EDBi. \\nHoa K\u1EF3 \u0111\u00E3 ch\u1EC9 ra trong \u0111\u1EC1 xu\u1EA5t d\u1EF1 \u00E1n r\u1EB1ng m\u1EE5c ti\u00EAu c\u1EE7a h\u1ECD l\u00E0 khi\u1EBFn Trung Qu\u1ED1c ph\u1EA3i tr\u1EA3 gi\u00E1. T\u00F4i ngh\u0129 m\u1ECDi ng\u01B0\u1EDDi \u0111\u1EC1u c\u00F3 th\u1EC3 hi\u1EC3u \u0111i\u1EC1u n\u00E0y c\u00F3 ngh\u0129a l\u00E0 g\u00EC - Hoa K\u1EF3 mu\u1ED1n h\u1EE7y ho\u1EA1i danh ti\u1EBFng c\u1EE7a Trung Qu\u1ED1c. \\n C\u00F3 m\u1ED9t th\u1EDDi, Philippines c\u00F3 m\u1ED1i quan h\u1EC7 r\u1EA5t h\u1EEFu \u00EDch v\u00E0 th\u00E2n thi\u1EC7n v\u1EDBi Trung Qu\u1ED1c. C\u00F3 nhi\u1EC1u c\u1EA7u n\u1ED1i h\u1EE3p t\u00E1c gi\u1EEFa ch\u00FAng ta, ch\u1EB3ng h\u1EA1n nh\u01B0 c\u00E1c d\u1EF1 \u00E1n h\u1EE3p t\u00E1c trong vi\u1EC7c c\u00F9ng x\u00E2y d\u1EF1ng s\u00E1ng ki\u1EBFn \u200B\u200B\u201CV\u00E0nh \u0111ai v\u00E0 Con \u0111\u01B0\u1EDDng\u201D, gi\u00FAp t\u0103ng th\u00EAm l\u1EE3i th\u1EBF kinh t\u1EBF c\u1EE7a Philippines. \\n Tuy nhi\u00EAn, T\u1ED5ng th\u1ED1ng Philippines Marcos r\u00F5 r\u00E0ng c\u00F3 quan \u0111i\u1EC3m ri\u00EAng v\u1EC1 s\u1EF1 d\u00E0n x\u1EBFp c\u1EE7a M\u1EF9, \u00F4ng ch\u01B0a bao gi\u1EDD gi\u1EA3i th\u00EDch cho ng\u01B0\u1EDDi d\u00E2n Philippines l\u00FD do quay tr\u1EDF l\u1EA1i v\u1EDBi M\u1EF9. V\u1EC1 v\u1EA5n \u0111\u1EC1 Bi\u1EC3n \u0110\u00F4ng, ch\u00EDnh s\u00E1ch c\u1EE7a Marcos c\u00E0ng th\u00F9 \u0111\u1ECBch v\u00E0 hung h\u0103ng h\u01A1n. \\n Tuy nhi\u00EAn, ng\u01B0\u1EDDi d\u00E2n Philippines kh\u00F4ng quan t\u00E2m \u0111\u1EBFn tranh ch\u1EA5p Bi\u1EC3n \u0110\u00F4ng. \\n \"Asia Pulse\" c\u00F3 th\u1EC3 n\u00F3i l\u00E0 m\u1ED9t t\u1ED5 ch\u1EE9c b\u1ECF phi\u1EBFu, m\u1EE5c \u0111\u00EDch l\u00E0 t\u00ECm hi\u1EC3u mong mu\u1ED1n c\u1EE7a ng\u01B0\u1EDDi d\u00E2n Ch\u00E2u \u00C1. V\u00E0o th\u00E1ng 9 n\u0103m 2023, m\u1ED9t b\u00E1o c\u00E1o th\u0103m d\u00F2 \u00FD ki\u1EBFn \u200B\u200Bcho th\u1EA5y ch\u1EC9 c\u00F3 7% ng\u01B0\u1EDDi d\u00E2n Philippines quan t\u00E2m \u0111\u1EBFn tranh ch\u1EA5p Bi\u1EC3n \u0110\u00F4ng, trong khi 93% ng\u01B0\u1EDDi d\u00E2n th\u1EF1c s\u1EF1 ch\u1EC9 quan t\u00E2m \u0111\u1EBFn gi\u00E1 c\u1EA3 cao, l\u1EA1m ph\u00E1t, vi\u1EC7c l\u00E0m, v\u1EA5n \u0111\u1EC1 t\u1ED9i ph\u1EA1m gia t\u0103ng v\u00E0 v\u1EA5n \u0111\u1EC1 ma t\u00FAy, v.v. . . \\nGi\u1EDD \u0111\u00E2y, ngay c\u1EA3 gia \u0111\u00ECnh Marcos c\u0169ng b\u1ECB chia r\u1EBD. Em g\u00E1i c\u1EE7a Marcos, v\u1EDBi t\u01B0 c\u00E1ch l\u00E0 ch\u1EE7 t\u1ECBch \u1EE6y ban \u0110\u1ED1i ngo\u1EA1i Th\u01B0\u1EE3ng vi\u1EC7n Philippines, \u0111\u00E3 ph\u1EA3n \u0111\u1ED1i vi\u1EC7c Marcos quay sang Hoa K\u1EF3 v\u00E0 h\u00E0nh vi hung h\u0103ng c\u1EE7a Marcos \u1EDF ch\u00E2u \u00C1, \u0111\u1ED3ng th\u1EDDi ch\u1EC9 tr\u00EDch vi\u1EC7c tri\u1EC3n khai c\u00E1c c\u0103n c\u1EE9 c\u1EE7a M\u1EF9 \u1EDF Philippines v\u00E0 nh\u1EEFng c\u0103ng th\u1EB3ng do Hoa K\u1EF3 g\u00E2y ra \u1EDF Philippines. Bi\u1EC3n \u0110\u00F4ng. . \\n 02 \\n Tan Zhu: Sau khi th\u1ED5i ph\u1ED3ng s\u1EF1 c\u1ED1 \u0110\u00E1 Nh\u00E2n \u00C1i, kh\u00F4ng qu\u1ED1c gia n\u00E0o \u1EE7ng h\u1ED9 Philippines l\u00E0 qu\u1ED1c gia ASEAN. Ph\u1EA3i ch\u0103ng \u0111i\u1EC1u n\u00E0y c\u00F3 ngh\u0129a l\u00E0 Philippines \u0111\u00E3 b\u1ECB c\u00F4 l\u1EADp \u1EDF c\u1EA5p \u0111\u1ED9 ngo\u1EA1i giao khu v\u1EF1c do \u0111i \u0111\u1EA7u trong vi\u1EC7c g\u00E2y r\u1EAFc r\u1ED1i ? C\u00E1c n\u01B0\u1EDBc trong khu v\u1EF1c Bi\u1EC3n \u0110\u00F4ng mu\u1ED1n th\u1EA5y lo\u1EA1i Bi\u1EC3n \u0110\u00F4ng nh\u01B0 th\u1EBF n\u00E0o? \\n Herman Laurel: T\u00F4i ngh\u0129 ASEAN r\u00F5 r\u00E0ng kh\u00F4ng mu\u1ED1n c\u0103ng th\u1EB3ng leo thang. \\nTrong cu\u1ED9c ph\u1ECFng v\u1EA5n v\u1EDBi m\u1ED9t t\u1EDD b\u00E1o \u0111\u1ECBa ph\u01B0\u01A1ng \u1EDF Philippines, t\u00F4i n\u00F3i r\u1EB1ng Kh\u00F4ng qu\u00E2n Hoa K\u1EF3 v\u00E0 c\u00E1c l\u1EF1c l\u01B0\u1EE3ng qu\u00E2n s\u1EF1 kh\u00E1c \u0111\u00E3 can thi\u1EC7p v\u00E0o c\u00F4ng vi\u1EC7c c\u1EE7a Philippines \u1EDF Bi\u1EC3n \u0110\u00F4ng, v\u00E0 ASEAN kh\u00F4ng th\u00EDch s\u1EF1 can thi\u1EC7p c\u1EE7a M\u1EF9 v\u00E0o Bi\u1EC3n \u0110\u00F4ng. \\nM\u1EB7c d\u00F9 c\u00E1c n\u01B0\u1EDBc ASEAN r\u1EA5t l\u1ECBch s\u1EF1 v\u1EDBi nhau v\u00E0 kh\u00F4ng tr\u1EF1c ti\u1EBFp n\u00EAu t\u00EAn Philippines nh\u01B0ng h\u1ECD kh\u00F4ng tham gia c\u00E1c h\u00E0nh \u0111\u1ED9ng \u0111\u1ED9c l\u1EADp c\u1EE7a Philippines m\u00E0 c\u00F4 l\u1EADp Philippines. \\nT\u00F4i ngh\u0129 Th\u1EE7 t\u01B0\u1EDBng Singapore L\u00FD Hi\u1EC3n Long v\u00E0 c\u00E1c nh\u00E0 l\u00E3nh \u0111\u1EA1o kh\u00E1c \u0111\u00E3 \u0111\u01B0a ra m\u1ED9t s\u1ED1 b\u00ECnh lu\u1EADn gi\u00E1n ti\u1EBFp \u0111\u1EC1 c\u1EADp \u0111\u1EBFn Philippines v\u00E0 c\u1EA3nh b\u00E1o n\u01B0\u1EDBc n\u00E0y kh\u00F4ng n\u00EAn tr\u1EDF th\u00E0nh chi\u1EBFn tr\u01B0\u1EDDng. \u0110i\u1EC1u n\u00E0y th\u1EC3 hi\u1EC7n r\u1EA5t r\u00F5 m\u1ED1i quan ng\u1EA1i c\u1EE7a Singapore v\u00E0 truy\u1EC1n t\u1EA3i m\u1ED1i quan ng\u1EA1i t\u01B0\u01A1ng t\u1EF1 c\u1EE7a c\u00E1c n\u01B0\u1EDBc ASEAN. \\nT\u00F4i c\u0169ng \u0111ang li\u00EAn h\u1EC7 v\u1EDBi m\u1ED9t s\u1ED1 \u0111\u1EA1i s\u1EE9 qu\u00E1n ASEAN t\u1EA1i Manila. Trong cu\u1ED9c tr\u00F2 chuy\u1EC7n v\u1EDBi h\u1ECD, t\u00F4i \u0111\u00E3 nghe h\u1ECD b\u00E0y t\u1ECF m\u1ED1i quan ng\u1EA1i c\u1EE7a m\u1ED7i n\u01B0\u1EDBc v\u1EC1 c\u00E1c h\u00E0nh \u0111\u1ED9ng hi\u1EC7n t\u1EA1i c\u1EE7a Philippines \u1EDF Bi\u1EC3n \u0110\u00F4ng. \\nTr\u00EAn th\u1EF1c t\u1EBF, t\u00ECnh h\u00ECnh do Marcos v\u00E0 Hoa K\u1EF3 t\u1EA1o ra c\u0169ng \u0111\u00E3 khi\u1EBFn ng\u01B0\u1EDDi d\u00E2n c\u1EE7a ch\u00FAng t\u00F4i lo l\u1EAFng v\u1EC1 an ninh qu\u1ED1c gia. \\n Marcos v\u00E0 c\u00E1c th\u00E0nh vi\u00EAn n\u1ED9i c\u00E1c an ninh c\u1EE7a \u00F4ng \u0111\u00E3 th\u00F4ng b\u00E1o r\u1EB1ng h\u1ECD \u0111ang chuy\u1EC3n s\u1EF1 ch\u00FA \u00FD c\u1EE7a \u0111\u1EA5t n\u01B0\u1EDBc t\u1EEB an ninh n\u1ED9i b\u1ED9 sang an ninh b\u00EAn ngo\u00E0i, t\u1EE9c l\u00E0 h\u1ECD \u0111ang l\u00E0m \u0111i\u1EC1u \u0111\u00F3 m\u00E0 kh\u00F4ng th\u1EF1c s\u1EF1 t\u00ECm ra ai l\u00E0 m\u1ED1i \u0111e d\u1ECDa an ninh qu\u1ED1c gia, ho\u1EA1t \u0111\u1ED9ng \u0111\u1EC3 b\u1EA3o v\u1EC7 an ninh l\u00E3nh th\u1ED5. \\n S\u1EF1 thay \u0111\u1ED5i ch\u00EDnh s\u00E1ch n\u00E0y khi\u1EBFn m\u1ECDi ng\u01B0\u1EDDi l\u1EA7m t\u01B0\u1EDFng r\u1EB1ng ph\u1EA3i ch\u00FA \u00FD \u0111\u1EBFn an ninh b\u00EAn ngo\u00E0i, tuy nhi\u00EAn \u0111\u00E2y kh\u00F4ng ph\u1EA3i l\u00E0 m\u1ED1i \u0111e d\u1ECDa th\u1EF1c s\u1EF1 m\u00E0 ch\u1EC9 l\u00E0 m\u1ED9t \u1EA3o \u1EA3nh, khi\u1EBFn m\u1ECDi ng\u01B0\u1EDDi l\u01A1 l\u00E0 an ninh trong n\u01B0\u1EDBc v\u00E0 l\u00E0m t\u00ECnh h\u00ECnh an ninh trong n\u01B0\u1EDBc tr\u1EDF n\u00EAn t\u1ED3i t\u1EC7 h\u01A1n. \\n C\u00E1ch \u0111\u00E2y kh\u00F4ng l\u00E2u, m\u1ED9t v\u1EE5 \u0111\u00E1nh bom kh\u1EE7ng b\u1ED1 nghi\u00EAm tr\u1ECDng \u0111\u00E3 x\u1EA3y ra t\u1EA1i \u0110\u1EA1i h\u1ECDc Qu\u1ED1c gia Mindanao \u1EDF th\u00E0nh ph\u1ED1 Marawi, khi\u1EBFn nhi\u1EC1u ng\u01B0\u1EDDi Philippines thi\u1EC7t m\u1EA1ng; \u1EDF m\u1ED9t t\u1EC9nh kh\u00E1c, m\u1ED9t v\u1EE5 n\u1ED5 c\u0169ng x\u1EA3y ra tr\u00EAn m\u1ED9t chi\u1EBFc xe bu\u00FDt. \\n \\n \\n \\n \\n V\u00EC v\u1EADy, ch\u00EDnh ph\u1EE7 n\u00E0y th\u1EF1c s\u1EF1 \u0111ang g\u1EB7p r\u1EAFc r\u1ED1i li\u00EAn t\u1EE5c. Khi Marcos v\u1EA5p ph\u1EA3i s\u1EF1 ph\u1EA3n \u0111\u1ED1i \u0111\u1ED1i v\u1EDBi c\u00E1c ch\u00EDnh s\u00E1ch sai l\u1EA7m c\u1EE7a m\u00ECnh, s\u1EF1 \u1EE7ng h\u1ED9 c\u1EE7a c\u00F4ng ch\u00FAng \u0111\u1ED1i v\u1EDBi \u00F4ng \u0111\u00E3 gi\u1EA3m \u00EDt nh\u1EA5t 15%. \\n Nh\u1EEFng t\u00ECnh h\u00ECnh trong n\u01B0\u1EDBc n\u00E0y cho th\u1EA5y n\u0103m 2024 s\u1EBD l\u00E0 m\u1ED9t n\u0103m r\u1EA5t kh\u00F3 kh\u0103n \u0111\u1ED1i v\u1EDBi Marcos. \\nM\u1EF9 \u0111\u00E3 g\u00E2y \u00E1p l\u1EF1c l\u1EDBn, y\u00EAu c\u1EA7u Philippines ti\u1EBFp t\u1EE5c ki\u1EC1m ch\u1EBF Trung Qu\u1ED1c. Nh\u01B0ng t\u00F4i ngh\u0129 \u0111\u1EA1i \u0111a s\u1ED1 ng\u01B0\u1EDDi Philippines c\u0169ng \u0111ang l\u00E0m ph\u1EA7n vi\u1EC7c c\u1EE7a m\u00ECnh \u0111\u1EC3 c\u1ED1 g\u1EAFng t\u00E1i kh\u1EB3ng \u0111\u1ECBnh quan \u0111i\u1EC3m v\u00E0 quan \u0111i\u1EC3m th\u1EF1c s\u1EF1 c\u1EE7a ng\u01B0\u1EDDi Philippines v\u1EC1 Trung Qu\u1ED1c, m\u1ED9t n\u01B0\u1EDBc th\u00E2n thi\u1EC7n, \u1EA5m \u00E1p v\u00E0 hi\u1EC7u qu\u1EA3. \\n 03 \\n Zhu Tan: \u00D4ng t\u1EEBng ch\u1EC9 ra r\u1EB1ng qu\u00E1 tr\u00ECnh chuy\u1EC3n \u0111\u1ED5i kinh t\u1EBF v\u00E0 t\u0103ng tr\u01B0\u1EDFng b\u1EC1n v\u1EEFng c\u1EE7a Philippines kh\u00F4ng th\u1EC3 t\u00E1ch r\u1EDDi vi\u1EC7c duy tr\u00EC h\u1EE3p t\u00E1c ch\u1EB7t ch\u1EBD v\u1EDBi Trung Qu\u1ED1c v\u00E0 ASEAN. T\u1EA1i sao \u00F4ng l\u1EA1i \u0111\u01B0a ra nh\u1EADn \u0111\u1ECBnh nh\u01B0 v\u1EADy? \\n Herman Laurel: Sau khi Marcos nh\u1EADm ch\u1EE9c, ch\u00EDnh s\u00E1ch \u0111\u1ED1i ngo\u1EA1i \u0111\u1ED9c l\u1EADp v\u00E0 quan h\u1EC7 h\u1EEFu ngh\u1ECB c\u1EE7a ch\u00EDnh ph\u1EE7 Philippines v\u1EDBi Trung Qu\u1ED1c v\u00E0 c\u00E1c n\u01B0\u1EDBc l\u00E1ng gi\u1EC1ng ch\u00E2u \u00C1 kh\u00E1c \u0111\u00E3 quay \u0111\u1EA7u v\u00E0 quay sang Hoa K\u1EF3, \u0111i\u1EC1u n\u00E0y mang l\u1EA1i nhi\u1EC1u v\u1EA5n \u0111\u1EC1 cho Philippines, ti\u1EC1m n\u0103ng nghi\u00EAm tr\u1ECDng nh\u1EA5t t\u00E1c \u0111\u1ED9ng v\u1EABn c\u00F3 th\u1EC3 xu\u1EA5t hi\u1EC7n trong l\u0129nh v\u1EF1c kinh t\u1EBF. \\nR\u00F5 r\u00E0ng \u0111\u1ED9ng c\u01A1 ph\u1EE5c h\u1ED3i kinh t\u1EBF to\u00E0n c\u1EA7u sau cu\u1ED9c \u0110\u1EA1i suy tho\u00E1i k\u00E9o d\u00E0i hai n\u0103m r\u01B0\u1EE1i l\u00E0 Trung Qu\u1ED1c. \\ n Li\u00EAn minh Ch\u00E2u \u00C2u hi\u1EC7n \u0111ang trong v\u1EF1c th\u1EB3m suy tho\u00E1i. T\u1ED5ng s\u1EA3n ph\u1EA9m qu\u1ED1c n\u1ED9i (GDP) th\u1EF1c t\u1EBF c\u1EE7a Nh\u1EADt B\u1EA3n l\u1EA7n \u0111\u1EA7u ti\u00EAn t\u0103ng tr\u01B0\u1EDFng \u00E2m trong qu\u00FD 3 n\u0103m nay. Tuy nhi\u00EAn, Qu\u1EF9 Ti\u1EC1n t\u1EC7 Qu\u1ED1c t\u1EBF g\u1EA7n \u0111\u00E2y \u0111\u00E3 n\u00E2ng d\u1EF1 b\u00E1o t\u0103ng tr\u01B0\u1EDFng GDP c\u1EE7a Trung Qu\u1ED1c cho n\u0103m 2023 l\u00EAn 5,4% v\u00E0 n\u0103m 2024. T\u01B0\u01A1ng lai v\u1EABn t\u01B0\u01A1i s\u00E1ng. \\n B\u1EA1n ph\u1EA3i bi\u1EBFt r\u1EB1ng Trung Qu\u1ED1c kh\u00F4ng ch\u1EC9 l\u00E0 \u0111\u1ED1i t\u00E1c th\u01B0\u01A1ng m\u1EA1i l\u1EDBn nh\u1EA5t c\u1EE7a ASEAN m\u00E0 c\u00F2n l\u00E0 \u0111\u1ED1i t\u00E1c th\u01B0\u01A1ng m\u1EA1i l\u1EDBn nh\u1EA5t c\u1EE7a Philippines. \\n Tuy nhi\u00EAn, ch\u00EDnh quy\u1EC1n Marcos \u0111\u00E3 h\u1EE7y b\u1ECF nhi\u1EC1u d\u1EF1 \u00E1n x\u00E2y d\u1EF1ng c\u1EE7a Trung Qu\u1ED1c, m\u1EB7c d\u00F9 Trung Qu\u1ED1c kh\u00F4ng c\u00F3 b\u1EA5t k\u1EF3 t\u00E1c \u0111\u1ED9ng ti\u00EAu c\u1EF1c n\u00E0o v\u1EC1 kinh t\u1EBF \u0111\u1ED1i v\u1EDBi Philippines. \\n T\u00F4i \u0111\u00E3 nh\u1EAFc nh\u1EDF \u0111\u1ED3ng b\u00E0o m\u00ECnh r\u1EB1ng ch\u00FAng ta kh\u00F4ng \u0111\u01B0\u1EE3c qu\u00EAn b\u00E0i h\u1ECDc c\u1EE7a n\u0103m 2014. Khi \u0111\u00F3, d\u1EF1 \u0111o\u00E1n sai l\u1EA7m c\u1EE7a ch\u00EDnh ph\u1EE7 Aquino \u0111\u00E3 khi\u1EBFn s\u1ED1 chu\u1ED1i tr\u1ECB gi\u00E1 h\u00E0ng t\u1EF7 peso m\u00E0 n\u01B0\u1EDBc ta d\u1EF1 \u0111\u1ECBnh xu\u1EA5t sang Trung Qu\u1ED1c ban \u0111\u1EA7u kh\u00F4ng v\u00E0o \u0111\u01B0\u1EE3c Trung Qu\u1ED1c, c\u00E1c nh\u00E0 xu\u1EA5t kh\u1EA9u chu\u1ED1i Philippines ch\u1EC9 c\u00F3 th\u1EC3 \u0111\u1EE9ng nh\u00ECn chu\u1ED1i c\u1EE7a m\u00ECnh th\u1ED1i r\u1EEFa trong nh\u1EEFng l\u00F4 b\u1ECB t\u1EEB ch\u1ED1i trong h\u1ED3 s\u01A1. \\n V\u00EC v\u1EADy, c\u00F3 th\u1EC3 th\u1EA5y r\u1EB1ng m\u1ED9t d\u1EF1 \u0111o\u00E1n sai l\u1EA7m c\u1EE7a ch\u00EDnh ph\u1EE7 Philippines c\u00F3 th\u1EC3 d\u1EABn \u0111\u1EBFn t\u00ECnh th\u1EBF kh\u00F3 kh\u0103n m\u00E0 ng\u01B0\u1EDDi d\u00E2n Philippines b\u00ECnh th\u01B0\u1EDDng ng\u00E0y nay ph\u1EA3i \u0111\u1ED1i m\u1EB7t. Ch\u00FAng t\u00F4i li\u00EAn t\u1EE5c nh\u1EAFc nh\u1EDF ng\u01B0\u1EDDi d\u00E2n trong n\u01B0\u1EDBc r\u1EB1ng ch\u00FAng t\u00F4i kh\u00F4ng mu\u1ED1n nh\u1EEFng t\u00ECnh hu\u1ED1ng n\u00E0y x\u1EA3y ra l\u1EA7n n\u1EEFa. \\nC\u00F3 l\u1EBD ch\u1EC9 c\u00F3 Trung Qu\u1ED1c m\u1EDBi th\u1EF1c s\u1EF1 c\u00F3 th\u1EC3 th\u00FAc \u0111\u1EA9y s\u1EF1 ph\u00E1t tri\u1EC3n kinh t\u1EBF m\u00E0 Philippines c\u1EA7n trong nh\u1EEFng n\u0103m t\u1EDBi. L\u1EA5y n\u0103m t\u1EDBi l\u00E0m v\u00ED d\u1EE5, Hoa K\u1EF3 c\u00F3 th\u1EC3 kh\u00F4ng c\u00F3 \u0111\u1EE7 ngu\u1ED3n l\u1EF1c t\u00E0i ch\u00EDnh \u0111\u1EC3 h\u1ED7 tr\u1EE3 Philippines, Nh\u1EADt B\u1EA3n c\u00F3 th\u1EC3 kh\u00F4ng th\u1EC3 cung c\u1EA5p h\u1ED7 tr\u1EE3 do suy tho\u00E1i kinh t\u1EBF, Ng\u00E2n h\u00E0ng Ph\u00E1t tri\u1EC3n Ch\u00E2u \u00C1 v\u1EABn c\u00F2n m\u1ED9t s\u1ED1 d\u1EF1 \u00E1n c\u0169 c\u1EA7n \u0111\u01B0\u1EE3c ho\u00E0n thi\u1EC7n. ti\u1EBFp t\u1EE5c v\u00E0 c\u00F3 th\u1EC3 kh\u00F4ng c\u00F3 th\u1EDDi gian \u0111\u1EC3 quan t\u00E2m \u0111\u1EBFn Philippines. \\n Trong nh\u1EEFng th\u00E1ng t\u1EDBi, n\u1EBFu ch\u00FAng ta c\u00F3 th\u1EC3 ng\u0103n ch\u1EB7n th\u00E0nh c\u00F4ng vi\u1EC7c Hoa K\u1EF3 ph\u00E1 ho\u1EA1i m\u1ED1i quan h\u1EC7 t\u1ED1t \u0111\u1EB9p c\u1EE7a Philippines v\u1EDBi Trung Qu\u1ED1c, ch\u00FAng ta c\u00F3 th\u1EC3 ti\u1EBFp t\u1EE5c h\u01B0\u1EDBng t\u1EDBi m\u1ED9t t\u01B0\u01A1ng lai t\u1ED1t \u0111\u1EB9p h\u01A1n. \\n V\u00EC v\u1EADy, ch\u00FAng t\u00F4i hy v\u1ECDng r\u1EB1ng v\u00E0o n\u0103m 2024, Philippines c\u00F3 th\u1EC3 xoay chuy\u1EC3n t\u00ECnh th\u1EBF. \\n \\n \\n [Bi\u00EAn t\u1EADp vi\u00EAn: T\u1EC1 L\u00F4i]" +# message = "G\u1EA7n \u0111\u00E2y, Philippines \u0111\u00E3 nhi\u1EC1u l\u1EA7n g\u00E2y ra r\u1EAFc r\u1ED1i \u1EDF Bi\u1EC3n \u0110\u00F4ng, x\u00E2m nh\u1EADp \u0110\u00E1 Nh\u00E2n \u00C1i thu\u1ED9c qu\u1EA7n \u0111\u1EA3o Nam Sa c\u1EE7a Trung Qu\u1ED1c, \u0111\u1ED3ng th\u1EDDi ti\u1EBFp t\u1EE5c ph\u00F3ng \u0111\u1EA1i v\u00E0 c\u01B0\u1EDDng \u0111i\u1EC7u h\u00F3a, nh\u1EA7m l\u1EABn \u0111\u00FAng sai v\u00E0 \u0111\u01B0a ra nh\u1EEFng c\u00E1o bu\u1ED9c v\u00F4 l\u00FD ch\u1ED1ng l\u1EA1i Trung Qu\u1ED1c. \\n Ng\u01B0\u1EDDi Philippines ngh\u0129 g\u00EC v\u1EC1 h\u00E0nh \u0111\u1ED9ng c\u1EE7a ch\u00EDnh ph\u1EE7 Philippines? \\ n \u00D4ng Tan \u0111\u00E3 t\u00ECm ra Herman Laurel, m\u1ED9t nh\u00E0 b\u00ECnh lu\u1EADn ch\u00EDnh tr\u1ECB n\u1ED5i ti\u1EBFng \u1EDF Philippines, \u0111\u1ED3ng th\u1EDDi l\u00E0 gi\u00E1m \u0111\u1ED1c Vi\u1EC7n nghi\u00EAn c\u1EE9u chi\u1EBFn l\u01B0\u1EE3c \"Th\u1EBF k\u1EF7 ch\u00E2u \u00C1\" c\u1EE7a Philippines v\u00E0 l\u00E0 ng\u01B0\u1EDDi s\u00E1ng l\u1EADp Hi\u1EC7p h\u1ED9i nghi\u00EAn c\u1EE9u ch\u00EDnh s\u00E1ch BRICS c\u1EE7a Philippines. Herman Laurel, ng\u01B0\u1EDDi \u0111ang nghi\u00EAn c\u1EE9u v\u1EC1 ch\u00E2u \u00C1, \u0111\u1EB7c bi\u1EC7t l\u00E0 m\u1ED1i quan h\u1EC7 gi\u1EEFa Trung Qu\u1ED1c v\u00E0 ASEAN, chia s\u1EBB quan s\u00E1t c\u1EE7a m\u00ECnh. \\n 01 \\n Tan Zhu: K\u1EC3 t\u1EEB n\u1EEDa cu\u1ED1i n\u0103m nay, Philippines th\u01B0\u1EDDng xuy\u00EAn x\u00E2m chi\u1EBFm c\u00E1c \u0111\u1EA3o v\u00E0 b\u00E3i \u0111\u00E1 c\u1EE7a ch\u00FAng t\u00F4i \u1EDF Bi\u1EC3n \u0110\u00F4ng, l\u00E0m gia t\u0103ng c\u0103ng th\u1EB3ng \u1EDF Bi\u1EC3n \u0110\u00F4ng, \u0111\u1ED3ng th\u1EDDi vu kh\u1ED1ng Trung Qu\u1ED1c l\u00E0 k\u1EBB b\u1EAFt n\u1EA1t l\u1EDBn. , c\u00F3 nh\u1EEFng nh\u00F3m \u1EDF Philippines ph\u1EA3n \u0111\u1ED1i h\u00E0nh \u0111\u1ED9ng khi\u00EAu kh\u00EDch c\u1EE7a Philippines. B\u1EA1n c\u1EA3m th\u1EA5y th\u1EBF n\u00E0o v\u1EC1 \u0111i\u1EC1u n\u00E0y v\u1EDBi t\u01B0 c\u00E1ch l\u00E0 m\u1ED9t ng\u01B0\u1EDDi Philippines? Herman Laurel: T\u00F4i cho r\u1EB1ng C\u1EA3nh s\u00E1t bi\u1EC3n Philippines v\u00E0 m\u1ED9t s\u1ED1 t\u00E0u d\u00E2n s\u1EF1 Philippines \u0111\u00E3 c\u1ED1 t\u00ECnh g\u00E2y r\u1EAFc r\u1ED1i v\u00EC h\u1ECD \u0111ang th\u1EF1c hi\u1EC7n \u201CD\u1EF1 \u00E1n t\u1ED5ng th\u1EC3\u201D c\u1EE7a Hoa K\u1EF3. \\nM\u1EF9 khoe khoang d\u1EF1 \u00E1n n\u00E0y v\u1EDBi ch\u00FAng t\u00F4i n\u00EAn ch\u00FAng t\u00F4i bi\u1EBFt t\u00EAn d\u1EF1 \u00E1n. D\u1EF1 \u00E1n \u0111\u01B0\u1EE3c d\u1EABn d\u1EAFt b\u1EDFi \u0110\u1EA1i t\u00E1 Kh\u00F4ng qu\u00E2n Hoa K\u1EF3 \u0111\u00E3 ngh\u1EC9 h\u01B0u Raimundo Powell, l\u00E0m vi\u1EC7c v\u1EDBi c\u00E1c \u0111\u1ED1i t\u00E1c Philippines nh\u01B0 C\u1EA3nh s\u00E1t bi\u1EC3n Philippines v\u00E0 m\u1ED9t s\u1ED1 quan ch\u1EE9c c\u1EE7a B\u1ED9 Ngo\u1EA1i giao Philippines" +# qs = "Tóm tắt nội dung liên quan đến Biển Đông và Việt Nam" +# lg = "vi" +# ver = "en-llama" +# ans = summary_with_llama(qs, message, lg, version=ver, max_word_per_context=1024) +# print(ans) diff --git a/function/tc_v2.py b/function/tc_v2.py new file mode 100644 index 0000000000000000000000000000000000000000..be28451d8d7985f07853617615e49c342ce7d7fc --- /dev/null +++ b/function/tc_v2.py @@ -0,0 +1,573 @@ +from tensorRT import inference +import re +from collections import Counter +from vncorenlp import VnCoreNLP +from nltk.tokenize import sent_tokenize +import torch +import datetime +from sklearn.cluster import AgglomerativeClustering +from sklearn.metrics.pairwise import cosine_similarity +import numpy as np +import json +from . import utils +import time +from summary import text_summary, get_summary_bert +from function.clean_text import normalize_text +from .summary_with_llm import summary_with_llama +from .translate import translate_text_multi_layer +from scipy.spatial import distance +import copy +from .sentence_embbeding import embbeded_zh, embbeded_en, embedded_bge + + +# from . import detect_time as dt + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +use_cuda = torch.cuda.is_available() +print(torch.cuda.is_available()) + +# annotator = VnCoreNLP('vncorenlp/VnCoreNLP-1.1.1.jar', port=9191, annotators="wseg,pos", max_heap_size='-Xmx2g') + + +def detect_postaging(text_in): + word_segmented_text = annotator.annotate(text_in) + lst_k = [] + for se in word_segmented_text["sentences"]: + for kw in se: + if kw["posTag"] in ("Np", "Ny", "N"): + if kw["posTag"] == "N" and "_" not in kw["form"]: + continue + lst_k.append(kw["form"].replace("_", " ")) + return list(set(lst_k)) + +def clean_text(text_in): + doc = re.sub('<.*?>', '', text_in) + doc = re.sub('(function).*}', ' ', doc) + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + doc = normalize_text(doc) + return doc + + +def data_cleaning(docs): + res = [] + for d in docs: + if 'message' in d: + # css and js + doc = re.sub('<.*?>', '', d['message']) + doc = re.sub('(function).*}', ' ', doc) + + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + d['message'] = doc + res.append(d) + return res + + +def segment(docs, lang="vi"): + segmented_docs = [] + for d in docs: + # print(d) + # if len(d.get('message', "")) > 8000 or len(d.get('message', "")) < 100: + if len(d.get('message', "")) > 8000: + continue + if 'snippet' not in d: + continue + try: + if lang == "vi": + snippet = d.get('snippet', "") + segmented_snippet = "" + segmented_sentences_snippet = annotator.tokenize(snippet) + for sentence in segmented_sentences_snippet: + segmented_snippet += ' ' + ' '.join(sentence) + segmented_snippet = segmented_snippet.replace('\xa0', '') + d['segmented_snippet'] = segmented_snippet + segmented_docs.append(d) + except Exception: + pass + return segmented_docs + + +def timestamp_to_date(timestamp): + return datetime.datetime.fromtimestamp(timestamp).strftime('%d/%m/%Y') + + +def re_ranking(result_topic, vectors_prompt, sorted_field): + lst_score = [] + lst_ids = [] + lst_top = [] + try: + for k in result_topic: + lst_ids.append(k) + if not sorted_field.strip(): + lst_top.append(len(result_topic[k])) + else: + lst_top.append(result_topic[k][0]['max_score']) + vector_center = result_topic[k][0]["vector"] + max_score = 11.0 + for vec in vectors_prompt: + score = distance.cosine(np.array(vec), np.array(vector_center)) + if score < max_score: + max_score = score + lst_score.append(max_score) + result_topic[k][0]["similarity_score"] = max_score + for d in result_topic[k]: + d["similarity_score"] = max_score + del result_topic[k][0]["vector"] + idx = np.argsort(np.array(lst_score)) + except Exception as ve: + return [], lst_ids, lst_top + return idx, lst_ids, lst_top + +def post_processing(response, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster = 50, delete_message=True, prompt="", hash_str: str= "", vectors_prompt: list = []): + print(f'[INFO] sorted_field: {sorted_field}') + MAX_DOC_PER_CLUSTER = max_doc_per_cluster + + lst_ids = [] + lst_top = [] + lst_res = [] + idx = [] + if prompt: + idx, lst_ids, lst_top = re_ranking(response, vectors_prompt, sorted_field) + print("idx_prompt: ", idx) + if len(prompt) == 0 or len(idx) == 0: + for i in response: + lst_ids.append(i) + if not sorted_field.strip(): + lst_top.append(len(response[i])) + else: + lst_top.append(response[i][0]['max_score']) + idx = np.argsort(np.array(lst_top))[::-1] + print("idx_not_prompt: ", idx) + if top_cluster == -1: + top_cluster = len(idx) + for i in idx[: top_cluster]: + ik = lst_ids[i] + if top_sentence == -1: + top_sentence = len(response[ik]) + lst_check_title = [] + lst_check_not_title = [] + i_c_t = 0 + for resss in response[ik]: + r_title = resss.get("title", "") + if r_title and not r_title.endswith("..."): + lst_check_title.append(resss) + i_c_t += 1 + else: + lst_check_not_title.append(resss) + if i_c_t == top_sentence: + break + if i_c_t == top_sentence: + lst_res.append(lst_check_title) + else: + lst_check_title.extend(lst_check_not_title) + lst_res.append(lst_check_title[:top_sentence]) + #lst_res.append(response[ik][:top_sentence]) + dict_res = {} + for i in range(len(lst_res)): + dict_res[str(i + 1)] = lst_res[i][:MAX_DOC_PER_CLUSTER] + for j in range(min(len(dict_res[str(i + 1)]), 3)): + dict_res[str(i + 1)][0]["title_summarize"].append(dict_res[str(i + 1)][j].get("snippet", "")) + # t11 = time.time() + summary_text = get_summary_bert(dict_res[str(i + 1)][0].get("message", ""), dict_res[str(i + 1)][0].get("lang", "vi"), topn=topn_summary, title=dict_res[str(i + 1)][0].get("title", ""), snippet=dict_res[str(i + 1)][0].get("snippet", "")) + # print("time_summary: ", time.time() - t11) + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("snippet", "") + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("title", "") + summary_text = utils.remove_image_keyword(summary_text) + # if prompt: + # if dict_res[str(i + 1)][0].get("message", ""): + # src_lang = dict_res[str(i + 1)][0].get("lang", "") + # print("src_lang: ", src_lang) + # print("summary_text: ", summary_text) + # summary_text = translate_text_multi_layer(src_lang, "vi", summary_text) + # text_tran = translate_text_multi_layer(src_lang, "vi", dict_res[str(i + 1)][0].get("message", "")) + # ans_from_llama = summary_with_llama(prompt, text_tran, "vi", version="vi-llama", max_word_per_context=1000) + # print("ans_from_llama: ", ans_from_llama) + # summary_text = summary_text + "$$$$\n" + ans_from_llama + # print("summary_text: ", summary_text, len(summary_text)) + dict_res[str(i + 1)][0]["content_summary"] = summary_text + dict_res[str(i + 1)][0]["num_of_post"] = len(lst_res[i]) + kew_phares = [] + dict_res[str(i + 1)][0]["topic_keywords"] = kew_phares + + # print("delete_message: ", delete_message) + if delete_message: + for j in range(len(dict_res[str(i + 1)])): + if "message" in dict_res[str(i + 1)][j]: + del dict_res[str(i + 1)][j]["message"] + + with open(f"log_llm/topic_result_after_postprocessing/{hash_str}.json", "w") as f: + dict_log_pos = {} + for k in dict_res: + dict_log_pos[k] = copy.deepcopy(dict_res[k]) + for d in dict_log_pos[k]: + if "message" in d: + del d["message"] + if "vector" in d: + del d["vector"] + json.dump(dict_log_pos, f, ensure_ascii= False) + return dict_res + + +def get_lang(docs): + lang_vi = 0 + lang_en = 0 + dict_lang = {} + for d in docs: + lang = d.get("lang", "") + if lang not in dict_lang: + dict_lang[lang] = 0 + dict_lang[lang] += 1 + # if d.get("lang", "") == "vi": + # lang_vi += 1 + # else: + # lang_en += 1 + lst_lang = [] + lst_cnt = [] + for k in dict_lang: + lst_lang.append(k) + lst_cnt.append(dict_lang[k]) + idx_max = np.argsort(np.array(lst_cnt))[::-1][0] + lang = lst_lang[int(idx_max)] + + if lang.startswith("zh_"): + lang = "zh" + print("lang: ", lang, lst_cnt[int(idx_max)]) + return lang + + +def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster=50, + delete_message=True, prompt="", type_cluster:str = "single", hash_str: str= "", id_topic=""): + # global model, model_en + with open("data/topic_name.txt") as f: + dict_topic_name = json.load(f) + topic_name_relevant = dict_topic_name.get(id_topic , "") + docs = docs[:30000] + lang = get_lang(docs) + if type_cluster == "complete" and lang == "zh": + distance_threshold = 0.4 + if type_cluster == "complete" and lang == "en": + distance_threshold = 0.4 + # type_cluster = "single" + + result = {} + cluster_score = {} + cluster_real_vectors = {} + # docs = segment(docs, lang=lang) + + t1 = time.time() + if len(docs) < 1: + return result + elif len(docs) == 1: + return { + "0": docs + } + vec_prompt = [] + prompt_strips = [] + # prompt = "" + if topic_name_relevant: + prompt_split = topic_name_relevant.split("#####") + for prom in prompt_split: + sys_p = prom.strip().split("$$$$") + if len(sys_p) == 1: + prompt_strips.append(prom.strip()) + else: + prompt_strips.append(sys_p[1].strip()) + if lang == "zh": + vec_prompt = embbeded_zh(prompt_split) + elif lang == "en": + vec_prompt = embbeded_en(prompt_split) + else: + vec_prompt = inference.encode(prompt_split, lang=lang) + if lang == "zh": + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = embbeded_zh(features) + # vectors = embedded_bge(features) + if len(vectors) == 0: + print(f"[WARNING] Embedded {lang}: {len(vectors)} / {len(features)}") + vectors = inference.encode(features, lang=lang) + # vectors = model.encode(features, show_progress_bar=False) + elif lang == "en": + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = embbeded_en(features) + # vectors = embedded_bge(features) + if len(vectors) == 0: + print(f"[WARNING] Embedded {lang}: {len(vectors)} / {len(features)}") + vectors = inference.encode(features, lang=lang) + else: + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + # vectors = embedded_bge(features) + # if len(vectors) == 0: + # print(f"[WARNING] Embedded {lang}: {len(vectors)} / {len(features)}") + vectors = inference.encode(features, lang=lang) + # vectors = model_en.encode(features, show_progress_bar=False) + clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage=type_cluster, distance_threshold=distance_threshold) + clusteror.fit(vectors) + matrix_vec = np.stack(vectors, axis=0) + print(f"Time encode + clustering: {time.time() - t1} {clusteror.n_clusters_}") + for i in range(clusteror.n_clusters_): + result[str(i + 1)] = [] + cluster_score[str(i + 1)] = 0 + ids = clusteror.labels_ # == i + # cluster_real_vectors[str(i + 1)] = re_clustering(ids, matrix_vec, distance_threshold, max_doc_per_cluster) + + for i in range(len(clusteror.labels_)): + cluster_no = clusteror.labels_[i] + # if any((cluster_real_vectors[str(cluster_no+1)][:] == vectors[i]).all(1)): + if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: + response_doc = {} + response_doc = docs[i] + score = response_doc.get('score', 0) + if not docs[i].get('message','').strip(): + continue + if score > cluster_score[str(cluster_no + 1)]: + cluster_score[str(cluster_no + 1)] = score + if 'domain' in docs[i]: + response_doc['domain'] = docs[i]['domain'] + if 'url' in docs[i]: + response_doc['url'] = docs[i]['url'] + if 'title' in docs[i]: + response_doc['title'] = clean_text(docs[i]['title']) + if 'snippet' in docs[i]: + response_doc['snippet'] = clean_text(docs[i]['snippet']) + if 'created_time' in docs[i]: + response_doc['created_time'] = docs[i]['created_time'] + if "sentiment" in docs[i]: + response_doc['sentiment'] = docs[i]['sentiment'] + if 'message' in docs[i]: + title = docs[i].get('title','') + snippet = docs[i].get('snippet','') + message = docs[i].get('message','') + if title.strip(): + split_mess = message.split(title) + if len(split_mess) > 1: + message = title.join(split_mess[1:]) + if snippet.strip(): + split_mess = message.split(snippet) + if len(split_mess) > 1: + message = snippet.join(split_mess[1:]) + + response_doc['message'] = clean_text(message) + if 'id' in docs[i]: + response_doc['id'] = docs[i]['id'] + # response_doc['score'] = 0.0 + response_doc['title_summarize'] = [] + response_doc['content_summary'] = "" + response_doc['total_facebook_viral'] = 0 + response_doc["vector"] = np.array(vectors[i]).tolist() + result[str(cluster_no + 1)].append(response_doc) + empty_clus_ids = [] + for x in result: + result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) + if len( result[x]) > 0: + if len(result[x]) > 1: + result[x] = check_duplicate_title_domain(result[x]) + result[x][0]['num_docs'] = len(result[x]) + result[x][0]['max_score'] = cluster_score[x] + else: + empty_clus_ids.append(x) + + for x in empty_clus_ids: + result.pop(x,None) + # result = dict(sorted(result.items(), key=lambda i: -len(i[1])))[:top_cluster] + with open(f"log_llm/topic_result_before_postprocessing/{hash_str}.json", "w") as f: + dict_log = {} + for k in result: + dict_log[k] = copy.deepcopy(result[k]) + for d in dict_log[k]: + if "message" in d: + del d["message"] + if "vector" in d: + del d["vector"] + json.dump(dict_log, f, ensure_ascii= False) + return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=delete_message, + prompt=topic_name_relevant, hash_str=hash_str, vectors_prompt=vec_prompt) + +def check_duplicate_title_domain(docs): + lst_title_domain = [f"{d.get('domain', '')} {d.get('title','')}" for d in docs] + for i in range(1,len(lst_title_domain) -1): + for j in range(i+1,len(lst_title_domain)): + if lst_title_domain[j] == lst_title_domain[i]: + lst_title_domain[j] = 'dup' + lst_filter_docs = [docs[i] for i,x in enumerate(lst_title_domain) if x != 'dup'] + return lst_filter_docs +def convert_date(text): + text = text.replace(".", "/") + text = text.replace("-", "/") + return text + + +def check_keyword(sentence): + keyword = ['sáng', 'trưa', 'chiều', 'tối', 'đến', 'hôm', 'ngày', 'tới'] + for k in keyword: + if k in sentence: + return True + return False + + +def extract_events_and_time(docs, publish_date): + def standardize(date_str): + return date_str.replace('.', '/').replace('-', '/') + + def add_0(date_str): + + date_str = date_str.split('/') + res = [] + for o in date_str: + o = re.sub('\s+', '', o) + if len(o) < 2: + o = '0' + o + res.append(o) + date_str = '/'.join(res) + return date_str + + def get_date_list(reg, sentence): + find_object = re.finditer(reg, sentence) + date_list = [x.group() for x in find_object] + return date_list + + year = publish_date.split('/')[2] + + # dd/mm/yyyy + reg_exp_1 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # #mm/yyyy + # reg_exp_5 = '(\D|^)(?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # dd/mm + reg_exp_2 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])(\D|$)' + + # ngày dd tháng mm năm yyyy + reg_exp_3 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}\s*(năm)\s*\d{4}' + # ngày dd tháng mm + reg_exp_4 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}' + + result = [] + for d in docs: + text = d['message'] + for sentence in sent_tokenize(text): + lower_sentence = sentence.lower() + c = re.search(reg_exp_3, sentence.lower()) + d = re.search(reg_exp_4, sentence.lower()) + # e = re.search(reg_exp_5, sentence.lower()) + a = re.search(reg_exp_1, sentence) + b = re.search(reg_exp_2, sentence) + # + if (a or b or c or d) and check_keyword(lower_sentence): + date_list = get_date_list(reg_exp_1, lower_sentence) + date_entity = '' + if date_list: + date_entity = add_0(standardize(date_list[0])) + elif get_date_list(reg_exp_2, lower_sentence): + date_list = get_date_list(reg_exp_2, lower_sentence) + date_entity = add_0(standardize(date_list[0]) + '/' + year) + elif get_date_list(reg_exp_3, lower_sentence): + date_list = get_date_list(reg_exp_3, lower_sentence) + + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = add_0(date_entity) + else: + date_list = get_date_list(reg_exp_4, lower_sentence) + if date_list != []: + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = date_entity + '/' + year + date_entity = add_0(date_entity) + result.append((sentence, date_entity)) + return result + +def find_index_nearest_vector(cluster, vectors): + # Compute the centroid of the cluster + centroid = np.mean(cluster, axis=0, keepdims=True) + + # Calculate the Euclidean distance between each vector and the centroid + distances = cosine_similarity(centroid, vectors) + + # Find the index of the vector with the minimum distance + nearest_index = np.argmin(distances, axis=1) + + + return nearest_index + +def re_clustering(ids, vectors, distance_threshold, max_doc_per_cluster): + sub_vectors = vectors[ids] + + try: + if sub_vectors.shape[0] < 2: + return sub_vectors + sub_clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage='complete', distance_threshold=0.12) + sub_clusteror.fit(sub_vectors) + dict_cluster = {id_clus: sub_vectors[sub_clusteror.labels_ == id_clus] for id_clus in range(sub_clusteror.n_clusters_)} + dict_num_vec = {id_clus: v.shape[0] for id_clus, v in dict_cluster.items()} + + max_num_cluster = max(dict_num_vec, key=dict_num_vec.get) + other_vectors = sub_vectors[sub_clusteror.labels_ != max_num_cluster] + + # if other_vectors.shape[0]: + # while dict_num_vec[max_num_cluster] < max_doc_per_cluster: + # tmp_index_vec = find_index_nearest_vector(dict_cluster[max_num_cluster], other_vectors) + # dict_cluster[max_num_cluster] = np.vstack((dict_cluster[max_num_cluster], other_vectors[tmp_index_vec])) + # dict_num_vec[max_num_cluster] += 1 + # if other_vectors.shape[0] != 1: + # other_vectors = np.delete(other_vectors, tmp_index_vec, axis=0) + # else: + # break + cosine_scores = cosine_similarity(dict_cluster[max_num_cluster], dict_cluster[max_num_cluster]) + with open("/home/vietle/topic-clustering/log_score.txt", "a") as f: + f.write(str(cosine_scores) + "\n") + return dict_cluster[max_num_cluster] + except Exception as e: + with open("/home/vietle/topic-clustering/log_clustering_diemtin/log_cluster_second.txt", "a") as f: + f.write(str(e)+"$$"+json.dumps({"ids": ids.tolist(), "vectors": vectors.tolist()})) + return sub_vectors \ No newline at end of file diff --git a/function/topic_clustering.py b/function/topic_clustering.py new file mode 100644 index 0000000000000000000000000000000000000000..566cdfa1bb7c21754f4d396f19501da07d4c9434 --- /dev/null +++ b/function/topic_clustering.py @@ -0,0 +1,458 @@ +from email import message +import re +from vncorenlp import VnCoreNLP +from nltk.tokenize import sent_tokenize +import torch +from sentence_transformers import SentenceTransformer +import datetime +from sklearn.cluster import AgglomerativeClustering +from sklearn.metrics.pairwise import cosine_similarity +import numpy as np +import requests +import json +from . import utils +import time +from summary import text_summary, get_summary_bert +from function.clean_text import normalize_text +# from . import detect_time as dt + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +model = SentenceTransformer('model/distiluse-base-multilingual-cased-v2').to(device) +# model = SentenceTransformer('VoVanPhuc/sup-SimCSE-VietNamese-phobert-base').to(device) +# model.save('model/distiluse-base-multilingual-cased-v2') + +use_cuda = torch.cuda.is_available() +print(torch.cuda.is_available()) +if torch.cuda.is_available(): + model_en = SentenceTransformer('model/paraphrase-mpnet-base-v2').to(device) +else: + model_en = model +# model_en.save('model/paraphrase-mpnet-base-v2') +annotator = VnCoreNLP('vncorenlp/VnCoreNLP-1.1.1.jar', port=9191, annotators="wseg,pos", max_heap_size='-Xmx8g') + + +def detect_postaging(text_in): + word_segmented_text = annotator.annotate(text_in) + lst_k = [] + for se in word_segmented_text["sentences"]: + for kw in se: + if kw["posTag"] in ("Np", "Ny", "N"): + if kw["posTag"] == "N" and "_" not in kw["form"]: + continue + lst_k.append(kw["form"].replace("_", " ")) + return list(set(lst_k)) + +def clean_text(text_in): + doc = re.sub('<.*?>', '', text_in) + doc = re.sub('(function).*}', ' ', doc) + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + doc = normalize_text(doc) + return doc + + +def data_cleaning(docs): + res = [] + for d in docs: + if 'message' in d: + # css and js + doc = re.sub('<.*?>', '', d['message']) + doc = re.sub('(function).*}', ' ', doc) + + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + d['message'] = doc + res.append(d) + return res + + +def segment(docs, lang="vi"): + segmented_docs = [] + for d in docs: + # if len(d.get('message', "")) > 8000 or len(d.get('message', "")) < 100: + if len(d.get('message', "")) > 8000: + continue + if 'snippet' not in d: + continue + try: + if lang == "vi": + snippet = d.get('snippet', "") + segmented_snippet = "" + segmented_sentences_snippet = annotator.tokenize(snippet) + for sentence in segmented_sentences_snippet: + segmented_snippet += ' ' + ' '.join(sentence) + segmented_snippet = segmented_snippet.replace('\xa0', '') + d['segmented_snippet'] = segmented_snippet + segmented_docs.append(d) + except Exception: + pass + return segmented_docs + + +def timestamp_to_date(timestamp): + return datetime.datetime.fromtimestamp(timestamp).strftime('%d/%m/%Y') + + +def post_processing(response, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster = 50): + print(f'[INFO] sorted_field: {sorted_field}') + MAX_DOC_PER_CLUSTER = max_doc_per_cluster + + lst_ids = [] + lst_top = [] + lst_res = [] + for i in response: + lst_ids.append(i) + + if not sorted_field.strip(): + lst_top.append(len(response[i])) + else: + lst_top.append(response[i][0]['max_score']) + + idx = np.argsort(np.array(lst_top))[::-1] + if top_cluster == -1: + top_cluster = len(idx) + for i in idx[: top_cluster]: + ik = lst_ids[i] + if top_sentence == -1: + top_sentence = len(response[ik]) + lst_check_title = [] + lst_check_not_title = [] + i_c_t = 0 + for resss in response[ik]: + r_title = resss.get("title", "") + if r_title and not r_title.endswith("..."): + lst_check_title.append(resss) + i_c_t += 1 + else: + lst_check_not_title.append(resss) + if i_c_t == top_sentence: + break + if i_c_t == top_sentence: + lst_res.append(lst_check_title) + else: + lst_check_title.extend(lst_check_not_title) + lst_res.append(lst_check_title[:top_sentence]) + #lst_res.append(response[ik][:top_sentence]) + dict_res = {} + for i in range(len(lst_res)): + dict_res[str(i + 1)] = lst_res[i][:MAX_DOC_PER_CLUSTER] + for j in range(min(len(dict_res[str(i + 1)]), 3)): + dict_res[str(i + 1)][0]["title_summarize"].append(dict_res[str(i + 1)][j].get("snippet", "")) + summary_text = get_summary_bert(dict_res[str(i + 1)][0].get("message", ""), lang=dict_res[str(i + 1)][0].get("lang", "vi"), topn=topn_summary, title=dict_res[str(i + 1)][0].get("title", ""), snippet=dict_res[str(i + 1)][0].get("snippet", "")) + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("snippet", "") + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("title", "") + dict_res[str(i + 1)][0]["content_summary"] = utils.remove_image_keyword(summary_text) + kew_phares = [] + dict_res[str(i + 1)][0]["topic_keywords"] = kew_phares + for j in range(len(dict_res[str(i + 1)])): + if "message" in dict_res[str(i + 1)][j]: + del dict_res[str(i + 1)][j]["message"] + return dict_res + + +def get_lang(docs): + lang_vi = 0 + lang_en = 0 + for d in docs: + if d.get("lang", "") == "vi": + lang_vi += 1 + else: + lang_en += 1 + if lang_vi >= lang_en: + return "vi" + return "en" + + +# def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field=''): +# global model, model_en +# docs = docs[:30000] +# lang = get_lang(docs) +# result = {} +# docs = segment(docs, lang=lang) +# if len(docs) < 2: +# return result +# if lang == "vi": +# features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] +# vectors = model.encode(features, show_progress_bar=False) +# else: +# features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] +# vectors = model_en.encode(features, show_progress_bar=False) +# clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', +# linkage='single', distance_threshold=distance_threshold) +# clusteror.fit(vectors) +# print(clusteror.n_clusters_) +# for i in range(clusteror.n_clusters_): +# result[str(i + 1)] = [] +# for i in range(len(clusteror.labels_)): +# cluster_no = clusteror.labels_[i] +# if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: +# response_doc = {} +# response_doc = docs[i] +# if 'domain' in docs[i]: +# response_doc['domain'] = docs[i]['domain'] +# if 'url' in docs[i]: +# response_doc['url'] = docs[i]['url'] +# if 'title' in docs[i]: +# response_doc['title'] = clean_text(docs[i]['title']) +# if 'snippet' in docs[i]: +# response_doc['snippet'] = clean_text(docs[i]['snippet']) +# if 'created_time' in docs[i]: +# response_doc['created_time'] = docs[i]['created_time'] +# if 'message' in docs[i]: +# title = docs[i].get('title','') +# snippet = docs[i].get('snippet','') +# message = docs[i].get('message','') +# if title.strip(): +# split_mess = message.split(title) +# if len(split_mess) > 1: +# message = title.join(split_mess[1:]) +# if snippet.strip(): +# split_mess = message.split(snippet) +# if len(split_mess) > 1: +# message = snippet.join(split_mess[1:]) + +# response_doc['message'] = clean_text(message) +# if 'id' in docs[i]: +# response_doc['id'] = docs[i]['id'] +# response_doc['score'] = 0.0 +# response_doc['title_summarize'] = [] +# response_doc['content_summary'] = "" +# response_doc['total_facebook_viral'] = 0 +# result[str(cluster_no + 1)].append(response_doc) + +# empty_clus_ids = [] +# for x in result: +# result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) +# if len( result[x]) > 0: +# if len(result[x]) > 1: +# result[x] = check_duplicate_title_domain(result[x]) +# result[x][0]['num_docs'] = len(result[x]) +# else: +# empty_clus_ids.append(x) + +# for x in empty_clus_ids: +# result.pop(x,None) +# # result = dict(sorted(result.items(), key=lambda i: -len(i[1])))[:top_cluster] +# return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field) + +def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster=50, delete_message=True): + global model, model_en + docs = docs[:30000] + lang = get_lang(docs) + result = {} + cluster_score = {} + # docs = segment(docs, lang=lang) + if len(docs) < 2: + return result + if lang == "vi": + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = model.encode(features, show_progress_bar=False) + else: + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = model_en.encode(features, show_progress_bar=False) + clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage='single', distance_threshold=distance_threshold) + clusteror.fit(vectors) + print(clusteror.n_clusters_) + for i in range(clusteror.n_clusters_): + result[str(i + 1)] = [] + cluster_score[str(i + 1)] = 0 + for i in range(len(clusteror.labels_)): + cluster_no = clusteror.labels_[i] + if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: + response_doc = {} + response_doc = docs[i] + score = response_doc.get('score', 0) + if not docs[i].get('message','').strip(): + continue + if score > cluster_score[str(cluster_no + 1)]: + cluster_score[str(cluster_no + 1)] = score + if 'domain' in docs[i]: + response_doc['domain'] = docs[i]['domain'] + if 'url' in docs[i]: + response_doc['url'] = docs[i]['url'] + if 'title' in docs[i]: + response_doc['title'] = clean_text(docs[i]['title']) + if 'snippet' in docs[i]: + response_doc['snippet'] = clean_text(docs[i]['snippet']) + if 'created_time' in docs[i]: + response_doc['created_time'] = docs[i]['created_time'] + if 'message' in docs[i]: + title = docs[i].get('title','') + snippet = docs[i].get('snippet','') + message = docs[i].get('message','') + if title.strip(): + split_mess = message.split(title) + if len(split_mess) > 1: + message = title.join(split_mess[1:]) + if snippet.strip(): + split_mess = message.split(snippet) + if len(split_mess) > 1: + message = snippet.join(split_mess[1:]) + + response_doc['message'] = clean_text(message) + if 'id' in docs[i]: + response_doc['id'] = docs[i]['id'] + # response_doc['score'] = 0.0 + response_doc['title_summarize'] = [] + response_doc['content_summary'] = "" + response_doc['total_facebook_viral'] = 0 + result[str(cluster_no + 1)].append(response_doc) + + empty_clus_ids = [] + for x in result: + result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) + if len( result[x]) > 0: + if len(result[x]) > 1: + result[x] = check_duplicate_title_domain(result[x]) + result[x][0]['num_docs'] = len(result[x]) + result[x][0]['max_score'] = cluster_score[x] + else: + empty_clus_ids.append(x) + + for x in empty_clus_ids: + result.pop(x,None) + # result = dict(sorted(result.items(), key=lambda i: -len(i[1])))[:top_cluster] + return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field, max_doc_per_cluster=max_doc_per_cluster) + +def check_duplicate_title_domain(docs): + lst_title_domain = [f"{d.get('domain', '')} {d.get('title','')}" for d in docs] + for i in range(1,len(lst_title_domain) -1): + for j in range(i+1,len(lst_title_domain)): + if lst_title_domain[j] == lst_title_domain[i]: + lst_title_domain[j] = 'dup' + lst_filter_docs = [docs[i] for i,x in enumerate(lst_title_domain) if x != 'dup'] + return lst_filter_docs +def convert_date(text): + text = text.replace(".", "/") + text = text.replace("-", "/") + return text + + +def check_keyword(sentence): + keyword = ['sáng', 'trưa', 'chiều', 'tối', 'đến', 'hôm', 'ngày', 'tới'] + for k in keyword: + if k in sentence: + return True + return False + + +def extract_events_and_time(docs, publish_date): + def standardize(date_str): + return date_str.replace('.', '/').replace('-', '/') + + def add_0(date_str): + + date_str = date_str.split('/') + res = [] + for o in date_str: + o = re.sub('\s+', '', o) + if len(o) < 2: + o = '0' + o + res.append(o) + date_str = '/'.join(res) + return date_str + + def get_date_list(reg, sentence): + find_object = re.finditer(reg, sentence) + date_list = [x.group() for x in find_object] + return date_list + + year = publish_date.split('/')[2] + + # dd/mm/yyyy + reg_exp_1 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # #mm/yyyy + # reg_exp_5 = '(\D|^)(?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # dd/mm + reg_exp_2 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])(\D|$)' + + # ngày dd tháng mm năm yyyy + reg_exp_3 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}\s*(năm)\s*\d{4}' + # ngày dd tháng mm + reg_exp_4 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}' + + result = [] + for d in docs: + text = d['message'] + for sentence in sent_tokenize(text): + lower_sentence = sentence.lower() + c = re.search(reg_exp_3, sentence.lower()) + d = re.search(reg_exp_4, sentence.lower()) + # e = re.search(reg_exp_5, sentence.lower()) + a = re.search(reg_exp_1, sentence) + b = re.search(reg_exp_2, sentence) + # + if (a or b or c or d) and check_keyword(lower_sentence): + date_list = get_date_list(reg_exp_1, lower_sentence) + date_entity = '' + if date_list: + date_entity = add_0(standardize(date_list[0])) + elif get_date_list(reg_exp_2, lower_sentence): + date_list = get_date_list(reg_exp_2, lower_sentence) + date_entity = add_0(standardize(date_list[0]) + '/' + year) + elif get_date_list(reg_exp_3, lower_sentence): + date_list = get_date_list(reg_exp_3, lower_sentence) + + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = add_0(date_entity) + else: + date_list = get_date_list(reg_exp_4, lower_sentence) + if date_list != []: + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = date_entity + '/' + year + date_entity = add_0(date_entity) + result.append((sentence, date_entity)) + return result diff --git a/function/topic_clustering_mnews.py b/function/topic_clustering_mnews.py new file mode 100644 index 0000000000000000000000000000000000000000..4b703f6538e0dbe61ed7b19263900da0e3adce65 --- /dev/null +++ b/function/topic_clustering_mnews.py @@ -0,0 +1,339 @@ +import re +from vncorenlp import VnCoreNLP +from nltk.tokenize import sent_tokenize +import torch +from sentence_transformers import SentenceTransformer +import datetime +from sklearn.cluster import AgglomerativeClustering + +import numpy as np +import requests +import json +from . import utils +import time +from summary import text_summary, get_summary_bert +# from . import detect_time as dt + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +model = SentenceTransformer('VoVanPhuc/sup-SimCSE-VietNamese-phobert-base').to(device) +model_en = SentenceTransformer('paraphrase-mpnet-base-v2').to(device) +annotator = VnCoreNLP('vncorenlp/VnCoreNLP-1.1.1.jar', port=9191, annotators="wseg,pos", max_heap_size='-Xmx8g') + + +def detect_postaging(text_in): + word_segmented_text = annotator.annotate(text_in) + lst_k = [] + for se in word_segmented_text["sentences"]: + for kw in se: + if kw["posTag"] in ("Np", "Ny", "N"): + if kw["posTag"] == "N" and "_" not in kw["form"]: + continue + lst_k.append(kw["form"].replace("_", " ")) + return list(set(lst_k)) + +def clean_text(text_in): + doc = re.sub('<.*?>', '', text_in) + doc = re.sub('(function).*}', ' ', doc) + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + return doc + + +def data_cleaning(docs): + res = [] + for d in docs: + if 'message' in d: + # css and js + doc = re.sub('<.*?>', '', d['message']) + doc = re.sub('(function).*}', ' ', doc) + + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + d['message'] = doc + res.append(d) + return res + + +def segment(docs, lang="vi"): + segmented_docs = [] + for d in docs: + # if len(d.get('message', "")) > 8000 or len(d.get('message', "")) < 100: + # continue + if 'snippet' not in d and 'title' not in d: + continue + try: + if lang == "vi": + snippet = d.get('snippet', "") + segmented_snippet = "" + segmented_sentences_snippet = annotator.tokenize(snippet) + for sentence in segmented_sentences_snippet: + segmented_snippet += ' ' + ' '.join(sentence) + segmented_snippet = segmented_snippet.replace('\xa0', '') + d['segmented_snippet'] = segmented_snippet + segmented_docs.append(d) + except Exception: + pass + return segmented_docs + + +def timestamp_to_date(timestamp): + return datetime.datetime.fromtimestamp(timestamp).strftime('%d/%m/%Y') + + +def sort_content(lst_res): + lst_content = [] + lst_cnt = [] + for i in range(len(lst_res)): + lst_cnt.append(len(lst_res[i].get("message", ""))) + id_sort = np.argsort(np.array(lst_cnt))[::-1] + for i in id_sort: + lst_content.append(lst_res[i]) + return lst_content + + + +def post_processing(response, top_cluster=5, top_sentence=5, topn_summary=5): + lst_ids = [] + lst_top = [] + lst_res = [] + for i in response: + lst_ids.append(i) + lst_top.append(len(response[i])) + idx = np.argsort(np.array(lst_top))[::-1] + if top_cluster == -1: + top_cluster = len(idx) + for i in idx[: top_cluster]: + ik = lst_ids[i] + if top_sentence == -1: + top_sentence = len(response[ik]) + lst_check_title = [] + lst_check_not_title = [] + i_c_t = 0 + response_sort = sort_content(response[ik].copy()) + for resss in response_sort: + if resss.get("title", ""): + lst_check_title.append(resss) + i_c_t += 1 + else: + lst_check_not_title.append(resss) + if i_c_t == top_sentence: + break + if i_c_t == top_sentence: + lst_res.append(lst_check_title) + else: + lst_check_title.extend(lst_check_not_title) + lst_res.append(lst_check_title[:top_sentence]) + dict_res = {} + for i in range(len(lst_res)): + dict_res[str(i + 1)] = lst_res[i] + for j in range(min(len(dict_res[str(i + 1)]), 3)): + dict_res[str(i + 1)][0]["title_summarize"].append(dict_res[str(i + 1)][j].get("snippet", "")) + summary_text = get_summary_bert(dict_res[str(i + 1)][0].get("message", ""), lang = dict_res[str(i + 1)][0].get("lang", "vi"), topn=topn_summary) + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("snippet", "") + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("title", "") + dict_res[str(i + 1)][0]["content_summary"] = utils.remove_image_keyword(summary_text) + kew_phares = [] + dict_res[str(i + 1)][0]["topic_keywords"] = kew_phares + for j in range(len(dict_res[str(i + 1)])): + if "message" in dict_res[str(i + 1)][j]: + del dict_res[str(i + 1)][j]["message"] + return dict_res + + +def get_lang(docs): + lang_vi = 0 + lang_en = 0 + docs_lang_vi = [] + docs_lang_en = [] + for d in docs: + if d.get("lang", "") == "en": + lang_en += 1 + docs_lang_en.append(d) + else: + lang_vi += 1 + docs_lang_vi.append(d) + if lang_vi > lang_en: + return "vi", docs_lang_vi + return "en", docs_lang_en + + +def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, benchmark_id=1): + global model, model_en + lang, docs = get_lang(docs) + result = {} + docs = segment(docs, lang=lang) + print("docs segment: ", len(docs)) + if len(docs) < 2: + return result + if lang == "vi": + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = model.encode(features, show_progress_bar=False) + else: + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = model_en.encode(features, show_progress_bar=False) + clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage='single', distance_threshold=distance_threshold) + clusteror.fit(vectors) + print(clusteror.n_clusters_) + for i in range(clusteror.n_clusters_): + result[str(i + 1)] = [] + for i in range(len(clusteror.labels_)): + cluster_no = clusteror.labels_[i] + response_doc = {} + if 'url' in docs[i]: + response_doc['url'] = docs[i]['url'] + if 'domain' in docs[i]: + response_doc['domain'] = docs[i]['domain'] + if 'title' in docs[i]: + response_doc['title'] = clean_text(docs[i]['title']) + if 'snippet' in docs[i]: + response_doc['snippet'] = clean_text(docs[i]['snippet']) + if 'created_time' in docs[i]: + response_doc['created_time'] = docs[i]['created_time'] + if 'message' in docs[i]: + response_doc['message'] = clean_text(docs[i]['message']) + if 'id' in docs[i]: + response_doc['id'] = docs[i]['id'] + response_doc['score'] = 0.0 + response_doc['title_summarize'] = [] + response_doc['content_summary'] = "" + response_doc['total_facebook_viral'] = 0 + result[str(cluster_no + 1)].append(response_doc) + # print("before filter: ", len(result)) + # result = smart_filter(result, benchmark_id=benchmark_id) + # print("after filter: ", len(result)) + return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary) + + +def convert_date(text): + text = text.replace(".", "/") + text = text.replace("-", "/") + return text + + +def check_keyword(sentence): + keyword = ['sáng', 'trưa', 'chiều', 'tối', 'đến', 'hôm', 'ngày', 'tới'] + for k in keyword: + if k in sentence: + return True + return False + + +def extract_events_and_time(docs, publish_date): + def standardize(date_str): + return date_str.replace('.', '/').replace('-', '/') + + def add_0(date_str): + + date_str = date_str.split('/') + res = [] + for o in date_str: + o = re.sub('\s+', '', o) + if len(o) < 2: + o = '0' + o + res.append(o) + date_str = '/'.join(res) + return date_str + + def get_date_list(reg, sentence): + find_object = re.finditer(reg, sentence) + date_list = [x.group() for x in find_object] + return date_list + + year = publish_date.split('/')[2] + + # dd/mm/yyyy + reg_exp_1 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # #mm/yyyy + # reg_exp_5 = '(\D|^)(?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # dd/mm + reg_exp_2 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])(\D|$)' + + # ngày dd tháng mm năm yyyy + reg_exp_3 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}\s*(năm)\s*\d{4}' + # ngày dd tháng mm + reg_exp_4 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}' + + result = [] + for d in docs: + text = d['message'] + for sentence in sent_tokenize(text): + lower_sentence = sentence.lower() + c = re.search(reg_exp_3, sentence.lower()) + d = re.search(reg_exp_4, sentence.lower()) + # e = re.search(reg_exp_5, sentence.lower()) + a = re.search(reg_exp_1, sentence) + b = re.search(reg_exp_2, sentence) + # + if (a or b or c or d) and check_keyword(lower_sentence): + date_list = get_date_list(reg_exp_1, lower_sentence) + date_entity = '' + if date_list: + date_entity = add_0(standardize(date_list[0])) + elif get_date_list(reg_exp_2, lower_sentence): + date_list = get_date_list(reg_exp_2, lower_sentence) + date_entity = add_0(standardize(date_list[0]) + '/' + year) + elif get_date_list(reg_exp_3, lower_sentence): + date_list = get_date_list(reg_exp_3, lower_sentence) + + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = add_0(date_entity) + else: + date_list = get_date_list(reg_exp_4, lower_sentence) + if date_list != []: + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = date_entity + '/' + year + date_entity = add_0(date_entity) + result.append((sentence, date_entity)) + return result diff --git a/function/topic_clustering_not_summary.py b/function/topic_clustering_not_summary.py new file mode 100644 index 0000000000000000000000000000000000000000..e7776185ccebfc732f96d9a6512787aa70c8a15f --- /dev/null +++ b/function/topic_clustering_not_summary.py @@ -0,0 +1,463 @@ +from email import message +import re +from turtle import title +from vncorenlp import VnCoreNLP +from nltk.tokenize import sent_tokenize +import torch +from sentence_transformers import SentenceTransformer +import datetime +from sklearn.cluster import AgglomerativeClustering +from sklearn.metrics.pairwise import cosine_similarity +import numpy as np +import requests +import json +from . import utils +import time +from summary import text_summary, get_summary_bert +from function.clean_text import normalize_text +# from . import detect_time as dt + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +# model = SentenceTransformer('model/distiluse-base-multilingual-cased-v2').to(device) +model = SentenceTransformer('model/paraphrase-multilingual-MiniLM-L12-v2') + +# model = SentenceTransformer('VoVanPhuc/sup-SimCSE-VietNamese-phobert-base').to(device) +# model.save('model/distiluse-base-multilingual-cased-v2') + +use_cuda = torch.cuda.is_available() +print(torch.cuda.is_available()) +if torch.cuda.is_available(): + model_en = SentenceTransformer('model/paraphrase-mpnet-base-v2').to(device) +else: + model_en = model +# model_en.save('model/paraphrase-mpnet-base-v2') +annotator = VnCoreNLP('vncorenlp/VnCoreNLP-1.1.1.jar', port=9191, annotators="wseg,pos", max_heap_size='-Xmx8g') + + +def detect_postaging(text_in): + word_segmented_text = annotator.annotate(text_in) + lst_k = [] + for se in word_segmented_text["sentences"]: + for kw in se: + if kw["posTag"] in ("Np", "Ny", "N"): + if kw["posTag"] == "N" and "_" not in kw["form"]: + continue + lst_k.append(kw["form"].replace("_", " ")) + return list(set(lst_k)) + +def clean_text(text_in): + doc = re.sub('<.*?>', '', text_in) + doc = re.sub('(function).*}', ' ', doc) + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + doc = normalize_text(doc) + return doc + + +def data_cleaning(docs): + res = [] + for d in docs: + if 'message' in d: + # css and js + doc = re.sub('<.*?>', '', d['message']) + doc = re.sub('(function).*}', ' ', doc) + + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + d['message'] = doc + res.append(d) + return res + + +def segment(docs, lang="vi"): + segmented_docs = [] + for d in docs: + # if len(d.get('message', "")) > 8000 or len(d.get('message', "")) < 100: + if len(d.get('message', "")) > 8000: + continue + if 'snippet' not in d: + continue + try: + if lang == "vi": + snippet = d.get('snippet', "") + segmented_snippet = "" + segmented_sentences_snippet = annotator.tokenize(snippet) + for sentence in segmented_sentences_snippet: + segmented_snippet += ' ' + ' '.join(sentence) + segmented_snippet = segmented_snippet.replace('\xa0', '') + d['segmented_snippet'] = segmented_snippet + segmented_docs.append(d) + except Exception: + pass + return segmented_docs + + +def timestamp_to_date(timestamp): + return datetime.datetime.fromtimestamp(timestamp).strftime('%d/%m/%Y') + + +def post_processing(response, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster = 50, delete_message=True): + print(f'[INFO] sorted_field: {sorted_field}') + MAX_DOC_PER_CLUSTER = max_doc_per_cluster + + lst_ids = [] + lst_top = [] + lst_res = [] + for i in response: + lst_ids.append(i) + + if not sorted_field.strip(): + lst_top.append(len(response[i])) + else: + lst_top.append(response[i][0]['max_score']) + + idx = np.argsort(np.array(lst_top))[::-1] + if top_cluster == -1: + top_cluster = len(idx) + for i in idx[: top_cluster]: + ik = lst_ids[i] + if top_sentence == -1: + top_sentence = len(response[ik]) + lst_check_title = [] + lst_check_not_title = [] + i_c_t = 0 + for resss in response[ik]: + r_title = resss.get("title", "") + if r_title and not r_title.endswith("..."): + lst_check_title.append(resss) + i_c_t += 1 + else: + lst_check_not_title.append(resss) + if i_c_t == top_sentence: + break + if i_c_t == top_sentence: + lst_res.append(lst_check_title) + else: + lst_check_title.extend(lst_check_not_title) + lst_res.append(lst_check_title[:top_sentence]) + #lst_res.append(response[ik][:top_sentence]) + dict_res = {} + for i in range(len(lst_res)): + dict_res[str(i + 1)] = lst_res[i][:MAX_DOC_PER_CLUSTER] + for j in range(min(len(dict_res[str(i + 1)]), 3)): + dict_res[str(i + 1)][0]["title_summarize"].append(dict_res[str(i + 1)][j].get("snippet", "")) + summary_text = get_summary_bert(dict_res[str(i + 1)][0].get("message", ""), lang=get_summary_bert(dict_res[str(i + 1)][0].get("lang", "vi"), topn=topn_summary, title=dict_res[str(i + 1)][0].get("title", ""), snippet=dict_res[str(i + 1)][0].get("snippet", "")) + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("snippet", "") + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("title", "") + dict_res[str(i + 1)][0]["content_summary"] = utils.remove_image_keyword(summary_text) + kew_phares = [] + dict_res[str(i + 1)][0]["topic_keywords"] = kew_phares + + if delete_message: + for j in range(len(dict_res[str(i + 1)])): + if "message" in dict_res[str(i + 1)][j]: + del dict_res[str(i + 1)][j]["message"] + return dict_res + + +def get_lang(docs): + lang_vi = 0 + lang_en = 0 + for d in docs: + if d.get("lang", "") == "vi": + lang_vi += 1 + else: + lang_en += 1 + if lang_vi >= lang_en: + return "vi" + return "en" + + +# def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field=''): +# global model, model_en +# docs = docs[:30000] +# lang = get_lang(docs) +# result = {} +# docs = segment(docs, lang=lang) +# if len(docs) < 2: +# return result +# if lang == "vi": +# features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] +# vectors = model.encode(features, show_progress_bar=False) +# else: +# features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] +# vectors = model_en.encode(features, show_progress_bar=False) +# clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', +# linkage='single', distance_threshold=distance_threshold) +# clusteror.fit(vectors) +# print(clusteror.n_clusters_) +# for i in range(clusteror.n_clusters_): +# result[str(i + 1)] = [] +# for i in range(len(clusteror.labels_)): +# cluster_no = clusteror.labels_[i] +# if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: +# response_doc = {} +# response_doc = docs[i] +# if 'domain' in docs[i]: +# response_doc['domain'] = docs[i]['domain'] +# if 'url' in docs[i]: +# response_doc['url'] = docs[i]['url'] +# if 'title' in docs[i]: +# response_doc['title'] = clean_text(docs[i]['title']) +# if 'snippet' in docs[i]: +# response_doc['snippet'] = clean_text(docs[i]['snippet']) +# if 'created_time' in docs[i]: +# response_doc['created_time'] = docs[i]['created_time'] +# if 'message' in docs[i]: +# title = docs[i].get('title','') +# snippet = docs[i].get('snippet','') +# message = docs[i].get('message','') +# if title.strip(): +# split_mess = message.split(title) +# if len(split_mess) > 1: +# message = title.join(split_mess[1:]) +# if snippet.strip(): +# split_mess = message.split(snippet) +# if len(split_mess) > 1: +# message = snippet.join(split_mess[1:]) + +# response_doc['message'] = clean_text(message) +# if 'id' in docs[i]: +# response_doc['id'] = docs[i]['id'] +# response_doc['score'] = 0.0 +# response_doc['title_summarize'] = [] +# response_doc['content_summary'] = "" +# response_doc['total_facebook_viral'] = 0 +# result[str(cluster_no + 1)].append(response_doc) + +# empty_clus_ids = [] +# for x in result: +# result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) +# if len( result[x]) > 0: +# if len(result[x]) > 1: +# result[x] = check_duplicate_title_domain(result[x]) +# result[x][0]['num_docs'] = len(result[x]) +# else: +# empty_clus_ids.append(x) + +# for x in empty_clus_ids: +# result.pop(x,None) +# # result = dict(sorted(result.items(), key=lambda i: -len(i[1])))[:top_cluster] +# return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field) + +def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster=50, delete_message=True): + global model, model_en + docs = docs[:30000] + lang = get_lang(docs) + result = {} + cluster_score = {} + docs = segment(docs, lang=lang) + if len(docs) < 2: + return result + if lang == "vi": + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = model.encode(features, show_progress_bar=False) + else: + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = model_en.encode(features, show_progress_bar=False) + clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage='single', distance_threshold=distance_threshold) + clusteror.fit(vectors) + print(clusteror.n_clusters_) + for i in range(clusteror.n_clusters_): + result[str(i + 1)] = [] + cluster_score[str(i + 1)] = 0 + for i in range(len(clusteror.labels_)): + cluster_no = clusteror.labels_[i] + if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: + response_doc = {} + response_doc = docs[i] + score = response_doc.get('score', 0) + if not docs[i].get('message','').strip(): + continue + if score > cluster_score[str(cluster_no + 1)]: + cluster_score[str(cluster_no + 1)] = score + if 'domain' in docs[i]: + response_doc['domain'] = docs[i]['domain'] + if 'url' in docs[i]: + response_doc['url'] = docs[i]['url'] + if 'title' in docs[i]: + response_doc['title'] = clean_text(docs[i]['title']) + if 'snippet' in docs[i]: + response_doc['snippet'] = clean_text(docs[i]['snippet']) + if 'created_time' in docs[i]: + response_doc['created_time'] = docs[i]['created_time'] + if 'message' in docs[i]: + title = docs[i].get('title','') + snippet = docs[i].get('snippet','') + message = docs[i].get('message','') + if title.strip(): + split_mess = message.split(title) + if len(split_mess) > 1: + message = title.join(split_mess[1:]) + if snippet.strip(): + split_mess = message.split(snippet) + if len(split_mess) > 1: + message = snippet.join(split_mess[1:]) + + response_doc['message'] = clean_text(message) + if 'id' in docs[i]: + response_doc['id'] = docs[i]['id'] + # response_doc['score'] = 0.0 + response_doc['title_summarize'] = [] + response_doc['content_summary'] = "" + response_doc['total_facebook_viral'] = 0 + result[str(cluster_no + 1)].append(response_doc) + + empty_clus_ids = [] + for x in result: + result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) + if len( result[x]) > 0: + if len(result[x]) > 1: + result[x] = check_duplicate_title_domain(result[x]) + result[x][0]['num_docs'] = len(result[x]) + result[x][0]['max_score'] = cluster_score[x] + else: + empty_clus_ids.append(x) + + for x in empty_clus_ids: + result.pop(x,None) + # result = dict(sorted(result.items(), key=lambda i: -len(i[1])))[:top_cluster] + return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=delete_message) + +def check_duplicate_title_domain(docs): + lst_title_domain = [f"{d.get('domain', '')} {d.get('title','')}" for d in docs] + for i in range(1,len(lst_title_domain) -1): + for j in range(i+1,len(lst_title_domain)): + if lst_title_domain[j] == lst_title_domain[i]: + lst_title_domain[j] = 'dup' + lst_filter_docs = [docs[i] for i,x in enumerate(lst_title_domain) if x != 'dup'] + return lst_filter_docs +def convert_date(text): + text = text.replace(".", "/") + text = text.replace("-", "/") + return text + + +def check_keyword(sentence): + keyword = ['sáng', 'trưa', 'chiều', 'tối', 'đến', 'hôm', 'ngày', 'tới'] + for k in keyword: + if k in sentence: + return True + return False + + +def extract_events_and_time(docs, publish_date): + def standardize(date_str): + return date_str.replace('.', '/').replace('-', '/') + + def add_0(date_str): + + date_str = date_str.split('/') + res = [] + for o in date_str: + o = re.sub('\s+', '', o) + if len(o) < 2: + o = '0' + o + res.append(o) + date_str = '/'.join(res) + return date_str + + def get_date_list(reg, sentence): + find_object = re.finditer(reg, sentence) + date_list = [x.group() for x in find_object] + return date_list + + year = publish_date.split('/')[2] + + # dd/mm/yyyy + reg_exp_1 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # #mm/yyyy + # reg_exp_5 = '(\D|^)(?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # dd/mm + reg_exp_2 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])(\D|$)' + + # ngày dd tháng mm năm yyyy + reg_exp_3 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}\s*(năm)\s*\d{4}' + # ngày dd tháng mm + reg_exp_4 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}' + + result = [] + for d in docs: + text = d['message'] + for sentence in sent_tokenize(text): + lower_sentence = sentence.lower() + c = re.search(reg_exp_3, sentence.lower()) + d = re.search(reg_exp_4, sentence.lower()) + # e = re.search(reg_exp_5, sentence.lower()) + a = re.search(reg_exp_1, sentence) + b = re.search(reg_exp_2, sentence) + # + if (a or b or c or d) and check_keyword(lower_sentence): + date_list = get_date_list(reg_exp_1, lower_sentence) + date_entity = '' + if date_list: + date_entity = add_0(standardize(date_list[0])) + elif get_date_list(reg_exp_2, lower_sentence): + date_list = get_date_list(reg_exp_2, lower_sentence) + date_entity = add_0(standardize(date_list[0]) + '/' + year) + elif get_date_list(reg_exp_3, lower_sentence): + date_list = get_date_list(reg_exp_3, lower_sentence) + + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = add_0(date_entity) + else: + date_list = get_date_list(reg_exp_4, lower_sentence) + if date_list != []: + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = date_entity + '/' + year + date_entity = add_0(date_entity) + result.append((sentence, date_entity)) + return result diff --git a/function/topic_clustering_social.py b/function/topic_clustering_social.py new file mode 100644 index 0000000000000000000000000000000000000000..f4a14f54697cebb4e6ffe13b7843795723fca82c --- /dev/null +++ b/function/topic_clustering_social.py @@ -0,0 +1,156 @@ +import json +import time +from .utils import get_sbert_embedding, clean_text +from sklearn.cluster import AgglomerativeClustering +from sklearn.metrics.pairwise import cosine_similarity +from nltk import sent_tokenize +import requests +# from clean_text import normalize_text + +MAX_LENGTH_FEATURE = 250 +MIN_LENGTH_FEATURE = 100 +URL_CHECK_SPAM = "http://10.9.3.70:30036/predict" + +def check_spam(docs): + json_body = { + "domain_id": "", + "records": [ + { + "text": doc.get("message",""), + "idxcol": 1 + } for doc in docs + ] + } + + result = requests.post(URL_CHECK_SPAM, json = json_body).json() + docs = [x for i,x in enumerate(docs) if result[i]["label"] == 0] + return docs + +def preocess_feature(doc): + message = doc.get("message","") + paras = message.split("\n") + feature = "" + paras = [clean_text(x.strip(), normalize=False) for x in paras if x.strip() and len(x.strip()) > 10] + for para in paras: + if len(feature) + len(para) < MAX_LENGTH_FEATURE: + feature += " " +para + elif len(feature) < MIN_LENGTH_FEATURE: + sens = sent_tokenize(para) + for sen in sens: + if len(feature) + len(sen) < MAX_LENGTH_FEATURE or len(feature.strip()) < MIN_LENGTH_FEATURE: + feature += " " +sen + return feature + +def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster=50, delete_message=True, is_check_spam = True): + # global model, model_en + + docs = [x for x in docs if len(x.get("message","")) > 100] + docs = docs[:30000] + if is_check_spam: + docs = check_spam(docs) + result = {} + cluster_score = {} + + t1 = time.time() + if len(docs) < 1: + return result + elif len(docs) == 1: + return { + "0": docs + } + + # features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + + f_docs = [] + for x in docs: + ft = preocess_feature(x) + if len(ft) > MIN_LENGTH_FEATURE: + x["title"] = ft + f_docs.append(x) + docs = f_docs + + features = [x["title"] for x in docs ] + # with open("feature", 'w') as f: + # json.dump(features, f, ensure_ascii = False) + # print(features) + vectors = get_sbert_embedding(features) + + clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage='complete', distance_threshold=distance_threshold) + clusteror.fit(vectors) + print(f"Time encode + clustering: {time.time() - t1} {clusteror.n_clusters_}") + for i in range(clusteror.n_clusters_): + result[str(i + 1)] = [] + cluster_score[str(i + 1)] = 0 + for i in range(len(clusteror.labels_)): + cluster_no = clusteror.labels_[i] + if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: + response_doc = {} + response_doc = docs[i] + score = response_doc.get('score', 0) + if not docs[i].get('message','').strip(): + continue + if score > cluster_score[str(cluster_no + 1)]: + cluster_score[str(cluster_no + 1)] = score + if 'domain' in docs[i]: + response_doc['domain'] = docs[i]['domain'] + if 'url' in docs[i]: + response_doc['url'] = docs[i]['url'] + if 'title' in docs[i]: + response_doc['title'] = clean_text(docs[i]['title']) + if 'snippet' in docs[i]: + response_doc['snippet'] = clean_text(docs[i]['snippet']) + if 'created_time' in docs[i]: + response_doc['created_time'] = docs[i]['created_time'] + if "sentiment" in docs[i]: + response_doc['sentiment'] = docs[i]['sentiment'] + if 'message' in docs[i]: + title = docs[i].get('title','') + snippet = docs[i].get('snippet','') + message = docs[i].get('message','') + # if title.strip(): + # split_mess = message.split(title) + # if len(split_mess) > 1: + # message = title.join(split_mess[1:]) + # if snippet.strip(): + # split_mess = message.split(snippet) + # if len(split_mess) > 1: + # message = snippet.join(split_mess[1:]) + + response_doc['message'] = clean_text(message) + if 'id' in docs[i]: + response_doc['id'] = docs[i]['id'] + # response_doc['score'] = 0.0 + + # response_doc['title_summarize'] = [] + # response_doc['content_summary'] = "" + # response_doc['total_facebook_viral'] = 0 + result[str(cluster_no + 1)].append(response_doc) + + empty_clus_ids = [] + for x in result: + result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) + if len( result[x]) > 0: + # if len(result[x]) > 1: + # result[x] = check_duplicate_title_domain(result[x]) + result[x][0]['num_docs'] = len(result[x]) + result[x][0]['max_score'] = cluster_score[x] + else: + empty_clus_ids.append(x) + + for x in empty_clus_ids: + result.pop(x,None) + + result = dict( sorted(result.items(), key=lambda i: -len(i[1]))[:top_cluster]) + return result + # return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=delete_message) + +if __name__ == '__main__': + # with open("/home2/vietle/DA-Report/social.json", 'r') as f: + # docs = json.load(f)[:2000] + with open("/home2/vietle/news-cms/topic_summarization/data/news_cms.social.json", 'r') as f: + docs = json.load(f)[:10000] + clusters = topic_clustering(docs, distance_threshold=0.2, top_cluster=5000, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster=50, delete_message=False) + with open("/home2/vietle/news-cms/topic_summarization/cluster/news_cms.social.json", 'w') as f: + + json.dump(clusters,f, ensure_ascii =False) \ No newline at end of file diff --git a/function/topic_clustering_v2.py b/function/topic_clustering_v2.py new file mode 100644 index 0000000000000000000000000000000000000000..39891634640a0b35dc0cd626a5e9165304b77ea2 --- /dev/null +++ b/function/topic_clustering_v2.py @@ -0,0 +1,390 @@ +from tensorRT import inference +import re +from vncorenlp import VnCoreNLP +from nltk.tokenize import sent_tokenize +import torch +import datetime +from sklearn.cluster import AgglomerativeClustering +from sklearn.metrics.pairwise import cosine_similarity +import numpy as np +import json +from . import utils +import time +from summary import text_summary, get_summary_bert +from function.clean_text import normalize_text + +# from . import detect_time as dt + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +use_cuda = torch.cuda.is_available() +print(torch.cuda.is_available()) + +# annotator = VnCoreNLP('vncorenlp/VnCoreNLP-1.1.1.jar', port=9191, annotators="wseg,pos", max_heap_size='-Xmx2g') + + +def detect_postaging(text_in): + word_segmented_text = annotator.annotate(text_in) + lst_k = [] + for se in word_segmented_text["sentences"]: + for kw in se: + if kw["posTag"] in ("Np", "Ny", "N"): + if kw["posTag"] == "N" and "_" not in kw["form"]: + continue + lst_k.append(kw["form"].replace("_", " ")) + return list(set(lst_k)) + +def clean_text(text_in): + doc = re.sub('<.*?>', '', text_in) + doc = re.sub('(function).*}', ' ', doc) + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + doc = normalize_text(doc) + return doc + + +def data_cleaning(docs): + res = [] + for d in docs: + if 'message' in d: + # css and js + doc = re.sub('<.*?>', '', d['message']) + doc = re.sub('(function).*}', ' ', doc) + + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + d['message'] = doc + res.append(d) + return res + + +def segment(docs, lang="vi"): + segmented_docs = [] + for d in docs: + print(d) + # if len(d.get('message', "")) > 8000 or len(d.get('message', "")) < 100: + if len(d.get('message', "")) > 8000: + continue + if 'snippet' not in d: + continue + try: + if lang == "vi": + snippet = d.get('snippet', "") + segmented_snippet = "" + segmented_sentences_snippet = annotator.tokenize(snippet) + for sentence in segmented_sentences_snippet: + segmented_snippet += ' ' + ' '.join(sentence) + segmented_snippet = segmented_snippet.replace('\xa0', '') + d['segmented_snippet'] = segmented_snippet + segmented_docs.append(d) + except Exception: + pass + return segmented_docs + + +def timestamp_to_date(timestamp): + return datetime.datetime.fromtimestamp(timestamp).strftime('%d/%m/%Y') + + +def post_processing(response, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster = 50, delete_message=True): + print(f'[INFO] sorted_field: {sorted_field}') + MAX_DOC_PER_CLUSTER = max_doc_per_cluster + + lst_ids = [] + lst_top = [] + lst_res = [] + for i in response: + lst_ids.append(i) + + if not sorted_field.strip(): + lst_top.append(len(response[i])) + else: + lst_top.append(response[i][0]['max_score']) + + idx = np.argsort(np.array(lst_top))[::-1] + if top_cluster == -1: + top_cluster = len(idx) + for i in idx[: top_cluster]: + ik = lst_ids[i] + if top_sentence == -1: + top_sentence = len(response[ik]) + lst_check_title = [] + lst_check_not_title = [] + i_c_t = 0 + for resss in response[ik]: + r_title = resss.get("title", "") + if r_title and not r_title.endswith("..."): + lst_check_title.append(resss) + i_c_t += 1 + else: + lst_check_not_title.append(resss) + if i_c_t == top_sentence: + break + if i_c_t == top_sentence: + lst_res.append(lst_check_title) + else: + lst_check_title.extend(lst_check_not_title) + lst_res.append(lst_check_title[:top_sentence]) + #lst_res.append(response[ik][:top_sentence]) + dict_res = {} + for i in range(len(lst_res)): + dict_res[str(i + 1)] = lst_res[i][:MAX_DOC_PER_CLUSTER] + for j in range(min(len(dict_res[str(i + 1)]), 3)): + dict_res[str(i + 1)][0]["title_summarize"].append(dict_res[str(i + 1)][j].get("snippet", "")) + summary_text = get_summary_bert(dict_res[str(i + 1)][0].get("message", ""), dict_res[str(i + 1)][0].get("lang", "vi"), topn=topn_summary, title=dict_res[str(i + 1)][0].get("title", ""), snippet=dict_res[str(i + 1)][0].get("snippet", "")) + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("snippet", "") + if len(summary_text) < 10: + summary_text = dict_res[str(i + 1)][0].get("title", "") + dict_res[str(i + 1)][0]["content_summary"] = utils.remove_image_keyword(summary_text) + kew_phares = [] + dict_res[str(i + 1)][0]["topic_keywords"] = kew_phares + + print("delete_message: ", delete_message) + if delete_message: + for j in range(len(dict_res[str(i + 1)])): + if "message" in dict_res[str(i + 1)][j]: + del dict_res[str(i + 1)][j]["message"] + return dict_res + + +def get_lang(docs): + lang_vi = 0 + lang_en = 0 + for d in docs: + if d.get("lang", "") == "vi": + lang_vi += 1 + else: + lang_en += 1 + if lang_en >= lang_vi: + return "en" + return "vi" + +def topic_clustering(docs, distance_threshold, top_cluster=5, top_sentence=5, topn_summary=5, sorted_field='', max_doc_per_cluster=50, delete_message=True): + # global model, model_en + docs = docs[:30000] + lang = get_lang(docs) + result = {} + cluster_score = {} + # docs = segment(docs, lang=lang) + + t1 = time.time() + if len(docs) < 1: + return result + elif len(docs) == 1: + return { + "0": docs + } + if lang == "vi": + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = inference.encode(features, lang=lang) + # vectors = model.encode(features, show_progress_bar=False) + else: + features = [doc.get('title', "") + ". " + doc.get('snippet', "") for doc in docs] + vectors = inference.encode(features, lang=lang) + # vectors = model_en.encode(features, show_progress_bar=False) + clusteror = AgglomerativeClustering(n_clusters=None, compute_full_tree=True, affinity='cosine', + linkage='single', distance_threshold=distance_threshold) + clusteror.fit(vectors) + print(f"Time encode + clustering: {time.time() - t1} {clusteror.n_clusters_}") + for i in range(clusteror.n_clusters_): + result[str(i + 1)] = [] + cluster_score[str(i + 1)] = 0 + for i in range(len(clusteror.labels_)): + cluster_no = clusteror.labels_[i] + if docs[i].get('domain','') not in ["cungcau.vn","baomoi.com","news.skydoor.net"]: + response_doc = {} + response_doc = docs[i] + score = response_doc.get('score', 0) + if not docs[i].get('message','').strip(): + continue + if score > cluster_score[str(cluster_no + 1)]: + cluster_score[str(cluster_no + 1)] = score + if 'domain' in docs[i]: + response_doc['domain'] = docs[i]['domain'] + if 'url' in docs[i]: + response_doc['url'] = docs[i]['url'] + if 'title' in docs[i]: + response_doc['title'] = clean_text(docs[i]['title']) + if 'snippet' in docs[i]: + response_doc['snippet'] = clean_text(docs[i]['snippet']) + if 'created_time' in docs[i]: + response_doc['created_time'] = docs[i]['created_time'] + if "sentiment" in docs[i]: + response_doc['sentiment'] = docs[i]['sentiment'] + if 'message' in docs[i]: + title = docs[i].get('title','') + snippet = docs[i].get('snippet','') + message = docs[i].get('message','') + if title.strip(): + split_mess = message.split(title) + if len(split_mess) > 1: + message = title.join(split_mess[1:]) + if snippet.strip(): + split_mess = message.split(snippet) + if len(split_mess) > 1: + message = snippet.join(split_mess[1:]) + + response_doc['message'] = clean_text(message) + if 'id' in docs[i]: + response_doc['id'] = docs[i]['id'] + # response_doc['score'] = 0.0 + response_doc['title_summarize'] = [] + response_doc['content_summary'] = "" + response_doc['total_facebook_viral'] = 0 + result[str(cluster_no + 1)].append(response_doc) + + empty_clus_ids = [] + for x in result: + result[x] = sorted(result[x], key=lambda i: -len(i.get('message',''))) + if len( result[x]) > 0: + if len(result[x]) > 1: + result[x] = check_duplicate_title_domain(result[x]) + result[x][0]['num_docs'] = len(result[x]) + result[x][0]['max_score'] = cluster_score[x] + else: + empty_clus_ids.append(x) + + for x in empty_clus_ids: + result.pop(x,None) + # result = dict(sorted(result.items(), key=lambda i: -len(i[1])))[:top_cluster] + return post_processing(result, top_cluster=top_cluster, top_sentence=top_sentence, topn_summary=topn_summary, sorted_field = sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=delete_message) + +def check_duplicate_title_domain(docs): + lst_title_domain = [f"{d.get('domain', '')} {d.get('title','')}" for d in docs] + for i in range(1,len(lst_title_domain) -1): + for j in range(i+1,len(lst_title_domain)): + if lst_title_domain[j] == lst_title_domain[i]: + lst_title_domain[j] = 'dup' + lst_filter_docs = [docs[i] for i,x in enumerate(lst_title_domain) if x != 'dup'] + return lst_filter_docs +def convert_date(text): + text = text.replace(".", "/") + text = text.replace("-", "/") + return text + + +def check_keyword(sentence): + keyword = ['sáng', 'trưa', 'chiều', 'tối', 'đến', 'hôm', 'ngày', 'tới'] + for k in keyword: + if k in sentence: + return True + return False + + +def extract_events_and_time(docs, publish_date): + def standardize(date_str): + return date_str.replace('.', '/').replace('-', '/') + + def add_0(date_str): + + date_str = date_str.split('/') + res = [] + for o in date_str: + o = re.sub('\s+', '', o) + if len(o) < 2: + o = '0' + o + res.append(o) + date_str = '/'.join(res) + return date_str + + def get_date_list(reg, sentence): + find_object = re.finditer(reg, sentence) + date_list = [x.group() for x in find_object] + return date_list + + year = publish_date.split('/')[2] + + # dd/mm/yyyy + reg_exp_1 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # #mm/yyyy + # reg_exp_5 = '(\D|^)(?:0?[1-9]|1[012])[- \/.]([12]([0-9]){3})(\D|$)' + # dd/mm + reg_exp_2 = '(\D|^)(?:0?[1-9]|[12][0-9]|3[01])[- \/.](?:0?[1-9]|1[012])(\D|$)' + + # ngày dd tháng mm năm yyyy + reg_exp_3 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}\s*(năm)\s*\d{4}' + # ngày dd tháng mm + reg_exp_4 = '(ngày)\s*\d{1,2}\s*(tháng)\s*\d{1,2}' + + result = [] + for d in docs: + text = d['message'] + for sentence in sent_tokenize(text): + lower_sentence = sentence.lower() + c = re.search(reg_exp_3, sentence.lower()) + d = re.search(reg_exp_4, sentence.lower()) + # e = re.search(reg_exp_5, sentence.lower()) + a = re.search(reg_exp_1, sentence) + b = re.search(reg_exp_2, sentence) + # + if (a or b or c or d) and check_keyword(lower_sentence): + date_list = get_date_list(reg_exp_1, lower_sentence) + date_entity = '' + if date_list: + date_entity = add_0(standardize(date_list[0])) + elif get_date_list(reg_exp_2, lower_sentence): + date_list = get_date_list(reg_exp_2, lower_sentence) + date_entity = add_0(standardize(date_list[0]) + '/' + year) + elif get_date_list(reg_exp_3, lower_sentence): + date_list = get_date_list(reg_exp_3, lower_sentence) + + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = add_0(date_entity) + else: + date_list = get_date_list(reg_exp_4, lower_sentence) + if date_list != []: + date_entity = date_list[0].replace('ngày', '').replace('tháng', '').replace('năm', '').strip() + date_entity = re.sub('\s+', ' ', date_entity) + date_entity = date_entity.replace(' ', '/') + date_entity = date_entity + '/' + year + date_entity = add_0(date_entity) + result.append((sentence, date_entity)) + return result diff --git a/function/translate.py b/function/translate.py new file mode 100644 index 0000000000000000000000000000000000000000..160a5fc6ec8f3d29171ee185058a33f13ce28c07 --- /dev/null +++ b/function/translate.py @@ -0,0 +1,37 @@ +from langdetect import detect +import requests +import json +import time + +URL_TRANSLATOR = "http://10.9.3.241:8093/translator" +def detect_lang(text): + try: + lang = detect(text) + except: + lang = 'en' + return lang + +def translate_text_multi_layer(source, target, text, url = URL_TRANSLATOR): + if source == "": + source = detect_lang(text) + print("PPPPPPPPPPPPP") + if not text.strip() or source == target: + return text + + json_body = { + "doc": text, + "src_lang": source, + "tgt_lang": target + } + print("CCCCCCCCCCCC") + res= requests.post(url, json=json_body) + print("translate: ", res.status_code) + path_log = f"log_tran/requests_tran_{time.time()}.txt" + with open(path_log, "w", encoding="utf-8") as f: + f.write(json.dumps(json_body) + "\n") + if res.status_code == 200: + res = res.json() + with open(path_log, "a", encoding="utf-8") as f: + f.write(json.dumps(res) + "\n") + return res + return '' diff --git a/function/utils.py b/function/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..f94d30df694ffb312b18b42ba3a79399bfedd1d1 --- /dev/null +++ b/function/utils.py @@ -0,0 +1,94 @@ +import editdistance +import requests +import numpy as np +import re +from .clean_text import normalize_text +URL_SBERT = "http://10.9.3.240:6789/sbert/encode_list" +# app_config.parse_url_api('api_sbert') + +def get_sbert_embedding(lst_sentence, url = URL_SBERT): + input_data = { + "sentences": lst_sentence + } + embs = requests.post(url, json=input_data).json() + embs = np.array(embs) + + return embs + +def is_number(word): + lst_end = ['$', '%', 'vnđ', '.', ','] + word_lo = word.lower() + for k in lst_end: + word_lo = word_lo.replace(k, '') + + if word_lo.isdigit(): + return True + else: + return False + + +def get_number(text): + dt = text.split(' ') + for w in dt: + if is_number(w): + return w + + return '' + + +def check_editdistance(ww1, ww2): + if len(ww1) == 0 or len(ww1) == 0: + return 0 + else: + n_c = editdistance.eval(ww1.lower(), ww2.lower()) + score = n_c / max(len(ww1), len(ww2)) + return 1 - score + + +def remove_image_keyword(text_input): + lst_key = ["ảnh:", "ảnh :", "Ảnh:", "Ảnh :", + "Ảnh minh họa:", "Ảnh minh họa :", "ảnh minh họa:", "ảnh minh họa :", + "Nguồn:", "nguồn:", "Nguồn :", "nguồn :", + "Source:", "Source :", "source:", "source :", + "Src:", "Src :", "src:", "src :", + "Image:", "Image :", "img:", "img :", + "image:", "image :", "Img:", "Img :", + "xem tiếp", "xem thêm", "Xem tiếp", "Xem thêm"] + for k in lst_key: + text_input = text_input.replace(k, " ") + return text_input.strip() + +def clean_text(text_in, normalize=True): + doc = re.sub('<.*?>', '', text_in) + doc = re.sub('(function).*}', ' ', doc) + # link + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(Nguồn)\s*?(http:\/\/).*?(\.vgp)', ' ', doc) + + doc = re.sub('(http:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\/\/)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.htm)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.html)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vn)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.net)', ' ', doc) + doc = re.sub('(https:\/\/).*?(\.vgp)', ' ', doc) + doc = re.sub('(http:\/\/).*?(\.vgp)', ' ', doc) + # escape sequence + doc = re.sub('\n', ' ', doc) + doc = re.sub('\t', ' ', doc) + doc = re.sub('\r', ' ', doc) + + if normalize: + doc = normalize_text(doc) + return doc + +if __name__ == '__main__': + print(check_editdistance('tttt', 'tt')) diff --git a/get_config.py b/get_config.py new file mode 100644 index 0000000000000000000000000000000000000000..d92b421492150af5e4937b309444b16b8c8530f4 --- /dev/null +++ b/get_config.py @@ -0,0 +1,5 @@ +from yaml import load, Loader + +config_params = {} +with open('config/config.yml', encoding='utf-8') as f: + config_params.update(load(f, Loader=Loader)) diff --git a/iclibs/ic_rabbit.py b/iclibs/ic_rabbit.py new file mode 100644 index 0000000000000000000000000000000000000000..8a76698d48260b37cd892ce2ca4d5b505b55b192 --- /dev/null +++ b/iclibs/ic_rabbit.py @@ -0,0 +1,126 @@ +# -*- coding: utf-8 -*- +import pika +import json + + +class ICRabbitMQ(object): + def __init__(self, host, virtual_host, usr, passw, **kwargs): + """ + Khởi tạo + :param host: địa chỉ rabbitmq server + :param virtual_host: virtual_host + :param queue_name: tên queue + :param usr: user rabbitmq server + :param passw: password + """ + self.host = host + self.virtual_host = virtual_host + self.user = usr + self.passw = passw + self.credentials = pika.PlainCredentials(usr, passw) + self.connection = None + self.kwargs = kwargs + + def init_connection(self): + self.connection = \ + pika.BlockingConnection( + pika.ConnectionParameters(host=self.host, virtual_host=self.virtual_host, credentials=self.credentials)) + + def connection_close(self): + self.connection.close() + + def connection_status(self): + return self.connection.is_open + + def init_queue(self, queue_name, exchange="", exchange_type='fanout', durable=True, max_priority=-1): + """ + khởi tạo queue + :param exchange: + :param queue_name: tên queue + :param durable: true (Queue vẫn tồn tại nếu nhưng RabitMQ khởi động lại) + :param max_priority: Mức độ priority tối đa; None thì không xét priority; + khác None thì xét priority (tối đa priority = 10) + :return: channel + """ + if self.connection is None: + self.init_connection() + channel = self.connection.channel() + if exchange == "" and queue_name != "": + if max_priority == -1: + channel.queue_declare(queue=queue_name, durable=durable) + else: + channel.queue_declare(queue=queue_name, durable=durable, arguments={'x-max-priority': max_priority}) + else: + channel.exchange_declare(exchange=exchange, exchange_type='fanout', durable=durable) + return channel + + @staticmethod + def publish_message(channel, routing_key, body, priority=-1, delivery_mode=2, exchange=''): + """ + run pushlish message + :param channel: channel đã được tạo + :param routing_key: key hoặc tên queue (nếu exchange = '') + :param body: data push + :param priority: mức ưu tiên + :param delivery_mode: ?? + :param exchange: routing + """ + if priority == -1: + channel.basic_publish(exchange=exchange, routing_key=routing_key, body=json.dumps(body), + properties=pika.BasicProperties(delivery_mode=delivery_mode)) + else: + channel.basic_publish(exchange=exchange, routing_key=routing_key, body=json.dumps(body), + properties=pika.BasicProperties(delivery_mode=delivery_mode, priority=priority)) + print("push done: ") + + @staticmethod + def run_consummer(channel, queue_name, callback_func, is_ack=False): + """ + run consumer + :param channel: channel đã được tạo + :param queue_name: tên queue + :param callback_func: hàm callback được định nghĩa bởi người dùng + :return: + """ + print(" *wait message") + + def callback(ch, method, properties, body): + body = json.loads(body.decode("utf-8")) + if is_ack: + ch.basic_ack(delivery_tag=method.delivery_tag) + callback_func(body, properties) + else: + callback_func(body, properties) + ch.basic_ack(delivery_tag=method.delivery_tag) + + + print("receive done: ") + + channel.basic_qos(prefetch_count=10) + channel.basic_consume(queue=queue_name, on_message_callback=callback) + channel.start_consuming() + + +if __name__ == '__main__': + pass + # host, virtual_host, usr, passw = '10.9.2.220', 'camera-detect', 'tuan.dao', 'lEKUWKXwFt' + # rab = ICRabbitMQ(host, virtual_host, usr, passw) + # queue_name = 'test_rb' + # + # ## test run producer + # channel = rab.init_queue(queue_name) + # body_data = {"2": "3423432423"} + # ICRabbitMQ.publish_message(channel, queue_name, body_data) + # + # + # ## test run consumer + # def callback_func(body): + # """ + # function callback người dùng định nghĩa + # :param body: message từ queue + # :return: + # """ + # print(body) + # + # + # ICRabbitMQ.run_consummer(channel, queue_name, callback_func) diff --git a/load_model.py b/load_model.py new file mode 100644 index 0000000000000000000000000000000000000000..5f8bd9520fe1d1638e6e29695ca25b977e810748 --- /dev/null +++ b/load_model.py @@ -0,0 +1,11 @@ +from sentence_transformers import SentenceTransformer +from summarizer import Summarizer +model_sum = Summarizer() + +model = SentenceTransformer('distiluse-base-multilingual-cased-v2') +model.save('model/distiluse-base-multilingual-cased-v2') + +model = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2') +model.save('model/paraphrase-multilingual-MiniLM-L12-v2') + + diff --git a/main.py b/main.py new file mode 100644 index 0000000000000000000000000000000000000000..a30b25e0f31a90c18c702b4193ac3e5855fb7877 --- /dev/null +++ b/main.py @@ -0,0 +1,5 @@ +import uvicorn + + +if __name__ == '__main__': + uvicorn.run("service:app", host="0.0.0.0", port=8632) \ No newline at end of file diff --git a/main_cache.py b/main_cache.py new file mode 100644 index 0000000000000000000000000000000000000000..e2e18db31021a6661c55a6de3e285b2386802115 --- /dev/null +++ b/main_cache.py @@ -0,0 +1,7 @@ +# import os +# os.environ["CUDA_VISIBLE_DEVICES"] = "-1" +import uvicorn + +if __name__ == '__main__': + uvicorn.run("service_cache:app", host="0.0.0.0", port=8633, workers=2) + # uvicorn.run("service_cache:app", host="0.0.0.0", port=8635, workers=1) \ No newline at end of file diff --git a/main_cache_Thien.py b/main_cache_Thien.py new file mode 100644 index 0000000000000000000000000000000000000000..494dcbd45186f18ef5312f38ba08283fae0ab14f --- /dev/null +++ b/main_cache_Thien.py @@ -0,0 +1,6 @@ +# import os +# os.environ["CUDA_VISIBLE_DEVICES"] = "-1" +import uvicorn + +if __name__ == '__main__': + uvicorn.run("service_cache_Thien:app", host="0.0.0.0", port=8633, workers=1) \ No newline at end of file diff --git a/main_cache_v2.py b/main_cache_v2.py new file mode 100644 index 0000000000000000000000000000000000000000..c6b800a9d93c8cd75718c9e6ce577d858572c817 --- /dev/null +++ b/main_cache_v2.py @@ -0,0 +1,7 @@ +# import os +# os.environ["CUDA_VISIBLE_DEVICES"] = "-1" +import uvicorn + +if __name__ == '__main__': + uvicorn.run("service_cache_v2:app", host="0.0.0.0", port=8633, workers=1) + # uvicorn.run("service_cache:app", host="0.0.0.0", port=8635, workers=1) \ No newline at end of file diff --git a/main_cpu.py b/main_cpu.py new file mode 100644 index 0000000000000000000000000000000000000000..6313a3aa133f1191e6c2c75d231a51b1ffdd429a --- /dev/null +++ b/main_cpu.py @@ -0,0 +1,5 @@ +import uvicorn +import os + +if __name__ == '__main__': + uvicorn.run("service_cpu:app", host="0.0.0.0", port=8634, workers=1) \ No newline at end of file diff --git a/main_ondemand.py b/main_ondemand.py new file mode 100644 index 0000000000000000000000000000000000000000..b360d3dc2a083f5f307ed2f04c2237f05ea4cb1c --- /dev/null +++ b/main_ondemand.py @@ -0,0 +1,4 @@ +import uvicorn + +if __name__ == '__main__': + uvicorn.run("consumer_hot_topic_ondemand:app", host="0.0.0.0", port=1308) diff --git a/main_review_diemtin.py b/main_review_diemtin.py new file mode 100644 index 0000000000000000000000000000000000000000..88f434cb6eac5957cb04200a68e623367821a116 --- /dev/null +++ b/main_review_diemtin.py @@ -0,0 +1,4 @@ +import uvicorn + +if __name__ == '__main__': + uvicorn.run("service_review_diemtin:app", host="0.0.0.0", port=8613, workers=2) diff --git a/merge_topic.py b/merge_topic.py new file mode 100644 index 0000000000000000000000000000000000000000..08023f0a653fe9b21f32a4d60b7db0332bdb29f4 --- /dev/null +++ b/merge_topic.py @@ -0,0 +1,126 @@ +import json +import os + +# os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +from function.topic_clustering import model, AgglomerativeClustering + +def check_duplicate_title_domain(docs): + lst_title_domain = [f"{d.get('domain', '')} {d.get('title','')}" for d in docs] + for i in range(1,len(lst_title_domain) -1): + for j in range(i+1,len(lst_title_domain)): + if lst_title_domain[j] == lst_title_domain[i]: + lst_title_domain[j] = 'dup' + lst_filter_docs = [docs[i] for i,x in enumerate(lst_title_domain) if x != 'dup'] + return lst_filter_docs + +def main(req): + # threshold = req.get('threshold', 0.3) + type = req['type'] + if type == 'monthly': + MAX_CLUSTER = 50 + else: + MAX_CLUSTER = 20 + + MAX_NUM_DOC_PER_CLUSTER = 50 + + threshold = 0.4 + + preprocess = req.get('preprocess', []) + lst_labels = [] + lst_topics = [] + for date_clusters in preprocess: + # date = date_clusters['date'] + topic = date_clusters.get('topic', []) + if topic: + for topic_id in topic: + # print(topic_id) + topic_docs = topic[topic_id] + lst_topics.append(topic[topic_id]) + label = '. '.join([topic_docs[0].get('title',''),topic_docs[0].get('snippet','')]) + lst_labels.append(label) + + final_clusters = [] + label_clusters = sbert_clustering(lst_labels, distance_threshold=threshold,return_ids=True) + + # print(lst_labels) + print(label_clusters) + + if label_clusters: + for id_label_clusters in label_clusters: + merge_clusters = [] + num_docs = 0 + for topic_id in label_clusters[id_label_clusters]: + topic = lst_topics[topic_id] + count_doc = topic[0].get('num_docs',1) + num_docs += count_doc + merge_clusters.extend(lst_topics[topic_id]) + + merge_clusters = sorted(merge_clusters, key=lambda x: -x.get('created_time',0)) + merge_clusters = check_duplicate_title_domain(merge_clusters) + + merge_clusters = merge_clusters[:MAX_NUM_DOC_PER_CLUSTER] + for doc in merge_clusters: + doc['num_docs'] = num_docs + final_clusters.append(merge_clusters) + + final_clusters = sorted(final_clusters, key=lambda x: -x[0]['num_docs']) + final_clusters = final_clusters[:MAX_CLUSTER] + + final_result = {} + for i,cluster in enumerate(final_clusters): + final_result[i] = cluster + with open('zzz.json','w') as f: + json.dump(final_result, f, ensure_ascii=False) + return final_result + +def get_sbert_embedding(lst_sentence): + embs = model.encode(lst_sentence) + # embs = np.array(embs) + return embs + +def sbert_clustering(lst_sentence, distance_threshold=0.25, return_ids = False): + lst_sentence = [sen.replace('_',' ') for sen in lst_sentence] + if len(lst_sentence) == 0: + return + if len(lst_sentence) == 1: + if return_ids: + return { + 0: [0] + } + return { + 0: lst_sentence + } + + # embs = model.encode(lst_sentence, show_progress_bar=True) + embs = get_sbert_embedding(lst_sentence) + + hyer_clusteror = AgglomerativeClustering(n_clusters = None,compute_full_tree = True, affinity = 'cosine', + linkage = 'complete', distance_threshold=distance_threshold) + # print(f'[INFO] Len lst_sentence: {len(lst_sentence)}') + # print(f'[INFO] Len embs: {len(embs)}') + hyer_clusteror.fit(embs) + # print(hyer_clusteror.n_clusters_) + + dict_result = {} + dict_ids = {} + for i in range(hyer_clusteror.n_clusters_): + if i not in dict_result: + dict_result[i] = [] + dict_ids[i] = [] + for j in range(len(lst_sentence)): + if hyer_clusteror.labels_[j] == i: + dict_result[i].append(lst_sentence[j]) + dict_ids[i].append(j) + + if return_ids: + output = dict_ids + else: + output = dict_result + result = dict(sorted(output.items(), key=lambda i: -len(i[1]))) + return result + +if __name__ == '__main__': + with open("input_merge.json",'r') as f: + req = json.load(f) + main(req) \ No newline at end of file diff --git a/msg_to_tele.py b/msg_to_tele.py new file mode 100644 index 0000000000000000000000000000000000000000..4c5112fea87eadc94d27ff8150c37d3b151f6075 --- /dev/null +++ b/msg_to_tele.py @@ -0,0 +1,17 @@ +import requests + +def push_msg_tele(bot_token, chat_id, message): + url = f'https://api.telegram.org/bot{bot_token}/sendMessage' + + payload = { + 'chat_id': chat_id, + 'text': message + } + + response = requests.post(url, data=payload) + + if response.status_code == 200: + print('Message sent successfully!') + else: + print(f'Failed to send message. Error: {response.status_code}') + print(f'Response: {response.text}') \ No newline at end of file diff --git a/req.txt b/req.txt new file mode 100644 index 0000000000000000000000000000000000000000..0ef6b1f5c4ae896125fc7c0676dcdf5b5ce43885 --- /dev/null +++ b/req.txt @@ -0,0 +1,68 @@ +anyio==3.5.0 +asgiref==3.4.1 +bert-extractive-summarizer==0.10.1 +blis==0.7.5 +catalogue==2.0.6 +certifi==2021.5.30 +charset-normalizer==2.0.3 +click==8.0.1 +colorama==0.4.4 +cymem==2.0.6 +dataclasses==0.6 +date-extractor==5.1.5 +dateparser==1.0.0 +editdistance==0.5.3 +fastapi==0.66.0 +filelock==3.0.12 +flashtext==2.7 +gensim==3.8.3 +h11==0.12.0 +huggingface-hub==0.0.12 +idna==3.2 +importlib-metadata==4.6.1 +Jinja2==3.0.3 +joblib==1.0.1 +langcodes==3.3.0 +MarkupSafe==2.0.1 +murmurhash==1.0.6 +nltk==3.6.2 +numpy==1.19.5 +packaging==21.0 +pathy==0.6.1 +Pillow==8.3.1 +preshed==3.0.6 +pydantic==1.8.2 +pyparsing==2.4.7 +python-dateutil==2.8.2 +pytz==2021.1 +PyYAML==5.4.1 +regex==2021.7.6 +requests==2.26.0 +sacremoses==0.0.45 +scikit-learn==0.24.2 +scipy==1.5.4 +sentence-transformers==2.0.0 +sentencepiece==0.1.96 +six==1.16.0 +sklearn==0.0 +smart-open==5.2.1 +sniffio==1.2.0 +spacy==3.2.1 +spacy-legacy==3.0.8 +spacy-loggers==1.0.1 +srsly==2.4.2 +starlette==0.14.2 +thinc==8.0.13 +threadpoolctl==2.2.0 +tokenizers==0.10.3 +pika==1.2.0 +tqdm==4.61.2 +transformers==4.8.2 +typer==0.4.0 +typing-extensions==3.10.0.0 +tzlocal==2.1 +urllib3==1.26.6 +uvicorn==0.14.0 +vncorenlp==1.0.3 +wasabi==0.9.0 +zipp==3.5.0 diff --git a/reqs.txt b/reqs.txt new file mode 100644 index 0000000000000000000000000000000000000000..95562634b9d859095cb5617b736e1dfe10ba5017 --- /dev/null +++ b/reqs.txt @@ -0,0 +1,56 @@ +beautifulsoup4==4.9.1 +bert-extractive-summarizer==0.5.0 +blis==0.2.4 +boto==2.49.0 +boto3==1.14.24 +botocore==1.17.24 +bs4==0.0.1 +bz2file==0.98 +certifi==2020.6.20 +chardet==3.0.4 +click==7.1.2 +cymem==2.0.3 +dataclasses==0.7 +docutils==0.15.2 +en-core-web-md @ https://github.com/explosion/spacy-models/releases/download/en_core_web_md-2.1.0/en_core_web_md-2.1.0.tar.gz +fastapi==0.60.0 +future==0.18.2 +gensim==3.8.3 +h11==0.9.0 +httptools==0.1.1 +idna==2.10 +jmespath==0.10.0 +joblib==0.16.0 +jsonschema==2.6.0 +murmurhash==1.0.2 +neuralcoref==4.0 +numpy==1.19.0 +Pillow==7.2.0 +plac==0.9.6 +preshed==2.0.1 +pydantic==1.6.1 +python-dateutil==2.8.1 +regex==2020.7.14 +requests==2.24.0 +s3transfer==0.3.3 +sacremoses==0.0.43 +scikit-learn==0.23.2 +scipy==1.5.1 +sentencepiece==0.1.91 +six==1.15.0 +smart-open==2.1.0 +soupsieve==2.0.1 +spacy==2.1.3 +srsly==1.0.2 +starlette==0.13.4 +thinc==7.0.8 +threadpoolctl==2.1.0 +torch==1.6.0 +torchvision==0.7.0 +tqdm==4.48.2 +transformers==2.2.2 +urllib3==1.25.9 +uvicorn==0.11.6 +uvloop==0.14.0 +wasabi==0.7.1 +websockets==8.1 diff --git a/reqs_cpu.txt b/reqs_cpu.txt new file mode 100644 index 0000000000000000000000000000000000000000..b8086823ecc3321e2eeba9a148d3352410799125 --- /dev/null +++ b/reqs_cpu.txt @@ -0,0 +1,70 @@ +anyio==3.5.0 +asgiref==3.4.1 +bert-extractive-summarizer==0.10.1 +blis==0.7.5 +catalogue==2.0.6 +certifi==2021.5.30 +charset-normalizer==2.0.3 +click==8.0.1 +colorama==0.4.4 +cymem==2.0.6 +dataclasses==0.6 +date-extractor==5.1.5 +dateparser==1.0.0 +editdistance==0.5.3 +fastapi==0.66.0 +filelock==3.0.12 +flashtext==2.7 +gensim==3.8.3 +h11==0.12.0 +huggingface-hub==0.0.12 +idna==3.2 +importlib-metadata==4.6.1 +Jinja2==3.0.3 +joblib==1.0.1 +langcodes==3.3.0 +MarkupSafe==2.0.1 +murmurhash==1.0.6 +nltk==3.6.2 +numpy==1.19.5 +packaging==21.0 +pathy==0.6.1 +Pillow==8.3.1 +preshed==3.0.6 +pydantic==1.8.2 +pyparsing==2.4.7 +python-dateutil==2.8.2 +pytz==2021.1 +PyYAML==5.4.1 +regex==2021.7.6 +requests==2.26.0 +sacremoses==0.0.45 +scikit-learn==0.24.2 +scipy==1.5.4 +sentence-transformers==2.0.0 +sentencepiece==0.1.96 +six==1.16.0 +sklearn==0.0 +smart-open==5.2.1 +sniffio==1.2.0 +spacy==3.2.1 +spacy-legacy==3.0.8 +spacy-loggers==1.0.1 +srsly==2.4.2 +starlette==0.14.2 +thinc==8.0.13 +threadpoolctl==2.2.0 +tokenizers==0.10.3 +pika==1.2.0 +tqdm==4.61.2 +torch==1.9.0 +torchvision==0.10.0 +transformers==4.8.2 +typer==0.4.0 +typing-extensions==3.10.0.0 +tzlocal==2.1 +urllib3==1.26.6 +uvicorn==0.14.0 +vncorenlp==1.0.3 +wasabi==0.9.0 +zipp==3.5.0 diff --git a/requests_llama.txt b/requests_llama.txt new file mode 100644 index 0000000000000000000000000000000000000000..041de2d685e396e035cae6561c0d6e20a666d7fb --- /dev/null +++ b/requests_llama.txt @@ -0,0 +1,36 @@ +{"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam"], "contexts": ["Kh\u00f4ng c\u00f3 th\u00f4ng tin li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam trong v\u0103n b\u1ea3n \u0111\u01b0\u1ee3c cung c\u1ea5p. 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\u56e0\u6b64\uff0c\u6211\u4eec\u5e0c\u671b\u57282024\u5e74\uff0c\u83f2\u5f8b\u5bbe\u80fd\u626d\u8f6c\u5c40\u9762 \u3002 \u3010\u8d23\u4efb\u7f16\u8f91\uff1a\u9f50\u78ca\u3011"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a on the information provided, it can be concluded that the people of Fiji are concerned about the actions of the Peoples\u2019 Republic of China (PRC) in the South China Sea. The PRC has been accused of aggressive actions in the region, including the recent incidents at the Xisha (Phoconia) and Pien Island. The Fijian government has not shown strong support for the actions of the Chinese government in the disputes in the South China. The PRC's economic transformation and long-term partnership with China and East Timor, Fiji has been concerned about the actions. The PRC in the South China sea. The PRC\u2019s actions have caused tensions in the region. The PRC government has been accused of making Fiji\u2019s economy vulnerable. The PRC is the first major trade partner of East Timor. The PRC was once a good friend of Fiji. However, the PRC\u2019s recent actions have caused tension in the region. Fiji hopes to see a better future relationship with the PRC."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam"], "contexts": ["D\u1ef1a on the information provided, it can be concluded that the people of Fiji are concerned about the actions of the Peoples\u2019 Republic of China (PRC) in the South China Sea. The PRC has been accused of aggressive actions in the region, including the recent incidents at the Xisha (Phoconia) and Pien Island. The Fijian government has not shown strong support for the actions of the Chinese government in the disputes in the South China. The PRC's economic transformation and long-term partnership with China and East Timor, Fiji has been concerned about the actions. The PRC in the South China sea. The PRC\u2019s actions have caused tensions in the region. The PRC government has been accused of making Fiji\u2019s economy vulnerable. The PRC is the first major trade partner of East Timor. The PRC was once a good friend of Fiji. However, the PRC\u2019s recent actions have caused tension in the region. Fiji hopes to see a better future relationship with the PRC."], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a tr\u00ean th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p, c\u00f3 th\u1ec3 k\u1ebft lu\u1eadn r\u1eb1ng ng\u01b0\u1eddi d\u00e2n Fiji lo ng\u1ea1i v\u1ec1 h\u00e0nh \u0111\u1ed9ng c\u1ee7a C\u1ed9ng h\u00f2a Nh\u00e2n d\u00e2n Trung Hoa (PRC) \u1edf Bi\u1ec3n \u0110\u00f4ng. PRC \u0111\u00e3 b\u1ecb bu\u1ed9c t\u1ed9i can thi\u1ec7p v\u00e0o khu v\u1ef1c, bao g\u1ed3m c\u00e1c s\u1ef1 c\u1ed1 g\u1ea7n \u0111\u00e2y \u1edf Xisha (Phoconia) v\u00e0 Pien Island. Ch\u00ednh ph\u1ee7 Fiji kh\u00f4ng b\u00e0y t\u1ecf s\u1ef1 \u1ee7ng h\u1ed9 m\u1ea1nh m\u1ebd \u0111\u1ed1i v\u1edbi h\u00e0nh \u0111\u1ed9ng c\u1ee7a ch\u00ednh ph\u1ee7 Trung Qu\u1ed1c trong c\u00e1c tranh ch\u1ea5p \u1edf Bi\u1ec3n \u0110\u00f4ng. S\u1ef1 thay \u0111\u1ed5i kinh t\u1ebf c\u1ee7a PRC v\u00e0 m\u1ed1i quan h\u1ec7 l\u00e2u d\u00e0i v\u1edbi Trung Qu\u1ed1c c\u0169ng nh\u01b0 \u0110\u00f4ng Timor \u0111\u00e3 khi\u1ebfn Fiji lo ng\u1ea1i tr\u01b0\u1edbc h\u00e0nh \u0111\u1ed9ng c\u1ee7a PRC \u1edf Bi\u1ec3n \u0110\u00f4ng. C\u00e1c h\u00e0nh \u0111\u1ed9ng c\u1ee7a PPC \u0111\u00e3 g\u00e2y c\u0103ng th\u1eb3ng trong khu v\u1ef1c. PRC \u0111\u01b0\u1ee3c coi l\u00e0 \u0111\u1ed1i t\u00e1c th\u01b0\u01a1ng m\u1ea1i l\u1edbn \u0111\u1ea7u ti\u00ean c\u1ee7a \u0110\u00f4ng Timor. PRC t\u1eebng l\u00e0 m\u1ed9t ng\u01b0\u1eddi b\u1ea1n t\u1ed1t c\u1ee7a Fiji, nh\u01b0ng nh\u1eefng h\u00e0nh \u0111\u1ed9ng g\u1ea7n \u0111\u00e2y c\u1ee7a h\u1ecd \u0111\u00e3 g\u00e2y c\u0103ng th c\u0103ng trong khu v\u1ef1c. Fiji hy v\u1ecdng s\u1ebd c\u00f3 m\u1ed9t t\u01b0\u01a1ng lai t\u1ed1t \u0111\u1eb9p h\u01a1n trong m\u1ed1i quan h\u1ec7 v\u1edbi PRC."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam"], "contexts": ["\u25a1\u672c\u62a5\u8bb0\u8005 \u738b\u5b87\u9732 \u845b\u7476 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\u56e0\u6b64\uff0c\u6211\u4eec\u5e0c\u671b\u57282024\u5e74\uff0c\u83f2\u5f8b\u5bbe\u80fd\u626d\u8f6c\u5c40\u9762 \u3002 \u3010\u8d23\u4efb\u7f16\u8f91\uff1a\u9f50\u78ca\u3011"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a on the information provided, it can be concluded that the people of Fiji are concerned about the actions of the Peoples\u2019 Republic of China (PRC) in the South China Sea. The PRC has been accused of aggressive actions in the region, including the recent incidents at the Xisha (Phoconia) and Pien Island. The Fijian government has not shown strong support for the actions of the Chinese government in the disputes in the South China. The PRC's economic transformation and long-term partnership with China and East Timor, Fiji has been concerned about the actions. The PRC in the South China sea. The PRC\u2019s actions have caused tensions in the region. The PRC government has been accused of making Fiji\u2019s economy vulnerable. The PRC is the first major trade partner of East Timor. The PRC was once a good friend of Fiji. However, the PRC\u2019s recent actions have caused tension in the region. Fiji hopes to see a better future relationship with the PRC."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam"], "contexts": ["D\u1ef1a on the information provided, it can be concluded that the people of Fiji are concerned about the actions of the Peoples\u2019 Republic of China (PRC) in the South China Sea. The PRC has been accused of aggressive actions in the region, including the recent incidents at the Xisha (Phoconia) and Pien Island. The Fijian government has not shown strong support for the actions of the Chinese government in the disputes in the South China. The PRC's economic transformation and long-term partnership with China and East Timor, Fiji has been concerned about the actions. The PRC in the South China sea. The PRC\u2019s actions have caused tensions in the region. The PRC government has been accused of making Fiji\u2019s economy vulnerable. The PRC is the first major trade partner of East Timor. The PRC was once a good friend of Fiji. However, the PRC\u2019s recent actions have caused tension in the region. Fiji hopes to see a better future relationship with the PRC."], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a tr\u00ean th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p, c\u00f3 th\u1ec3 k\u1ebft lu\u1eadn r\u1eb1ng ng\u01b0\u1eddi d\u00e2n Fiji lo ng\u1ea1i v\u1ec1 h\u00e0nh \u0111\u1ed9ng c\u1ee7a C\u1ed9ng h\u00f2a Nh\u00e2n d\u00e2n Trung Hoa (PRC) \u1edf Bi\u1ec3n \u0110\u00f4ng. PRC \u0111\u00e3 b\u1ecb bu\u1ed9c t\u1ed9i can thi\u1ec7p v\u00e0o khu v\u1ef1c, bao g\u1ed3m c\u00e1c s\u1ef1 c\u1ed1 g\u1ea7n \u0111\u00e2y \u1edf Xisha (Phoconia) v\u00e0 Pien Island. Ch\u00ednh ph\u1ee7 Fiji kh\u00f4ng b\u00e0y t\u1ecf s\u1ef1 \u1ee7ng h\u1ed9 m\u1ea1nh m\u1ebd \u0111\u1ed1i v\u1edbi h\u00e0nh \u0111\u1ed9ng c\u1ee7a ch\u00ednh ph\u1ee7 Trung Qu\u1ed1c trong c\u00e1c tranh ch\u1ea5p \u1edf Bi\u1ec3n \u0110\u00f4ng. S\u1ef1 thay \u0111\u1ed5i kinh t\u1ebf c\u1ee7a PRC v\u00e0 m\u1ed1i quan h\u1ec7 l\u00e2u d\u00e0i v\u1edbi Trung Qu\u1ed1c c\u0169ng nh\u01b0 \u0110\u00f4ng Timor \u0111\u00e3 khi\u1ebfn Fiji lo ng\u1ea1i tr\u01b0\u1edbc h\u00e0nh \u0111\u1ed9ng c\u1ee7a PRC \u1edf Bi\u1ec3n \u0110\u00f4ng. C\u00e1c h\u00e0nh \u0111\u1ed9ng c\u1ee7a PPC \u0111\u00e3 g\u00e2y c\u0103ng th\u1eb3ng trong khu v\u1ef1c. PRC \u0111\u01b0\u1ee3c coi l\u00e0 \u0111\u1ed1i t\u00e1c th\u01b0\u01a1ng m\u1ea1i l\u1edbn \u0111\u1ea7u ti\u00ean c\u1ee7a \u0110\u00f4ng Timor. PRC t\u1eebng l\u00e0 m\u1ed9t ng\u01b0\u1eddi b\u1ea1n t\u1ed1t c\u1ee7a Fiji, nh\u01b0ng nh\u1eefng h\u00e0nh \u0111\u1ed9ng g\u1ea7n \u0111\u00e2y c\u1ee7a h\u1ecd \u0111\u00e3 g\u00e2y c\u0103ng th c\u0103ng trong khu v\u1ef1c. Fiji hy v\u1ecdng s\u1ebd c\u00f3 m\u1ed9t t\u01b0\u01a1ng lai t\u1ed1t \u0111\u1eb9p h\u01a1n trong m\u1ed1i quan h\u1ec7 v\u1edbi PRC."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam"], "contexts": ["\u25a1\u672c\u62a5\u8bb0\u8005 \u738b\u5b87\u9732 \u845b\u7476 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\u56e0\u6b64\uff0c\u6211\u4eec\u5e0c\u671b\u57282024\u5e74\uff0c\u83f2\u5f8b\u5bbe\u80fd\u626d\u8f6c\u5c40\u9762 \u3002 \u3010\u8d23\u4efb\u7f16\u8f91\uff1a\u9f50\u78ca\u3011"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a on the information provided, the relationship between the Philippines and China in the South China Sea has been tense. The Philippines has been accused of inciting conflicts and causing tensions in the region. The Philippines has also been accused of being a pawn in the U.S. \"black propaganda\" campaign against China. The Philippines has faced criticism from its own people for its actions in the South China sea dispute. The Philippines has experienced economic growth and job opportunities, but has been affected by the country's relationship with China and the East Asian countries. The Philippines has canceased on the Philippines's economic growth, the Philippines has been accused by the Philippines of inciting China from the Philippines. \u83f2\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\u0648\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\u0e49\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\u0e14\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\uff0c\ufffd\ufffd\ufffd\ufffd\u062f\ufffd\ufffd\ufffd\ufffd\u0632\ufffd\ufffd\ufffd\ufffd\u03b9\ufffd\ufffd\ufffd\ufffd\u0323\ufffd\ufffd\ufffd\ufffd\u200c\ufffd\ufffd\ufffd\ufffd`\ufffd\ufffd\ufffd\ufffd"], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": ["D\u1ef1a on the information provided, the relationship between the Philippines and China in the South China Sea has been tense. The Philippines has been accused of inciting conflicts and causing tensions in the region. The Philippines has also been accused of being a pawn in the U.S. \"black propaganda\" campaign against China. The Philippines has faced criticism from its own people for its actions in the South China sea dispute. The Philippines has experienced economic growth and job opportunities, but has been affected by the country's relationship with China and the East Asian countries. The Philippines has canceased on the Philippines's economic growth, the Philippines has been accused by the Philippines of inciting China from the Philippines. \u83f2\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\u0648\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\u0e49\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\u0e14\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\uff0c\ufffd\ufffd\ufffd\ufffd\u062f\ufffd\ufffd\ufffd\ufffd\u0632\ufffd\ufffd\ufffd\ufffd\u03b9\ufffd\ufffd\ufffd\ufffd\u0323\ufffd\ufffd\ufffd\ufffd\u200c\ufffd\ufffd\ufffd\ufffd`\ufffd\ufffd\ufffd\ufffd"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a tr\u00ean th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p, c\u00f3 m\u1ed9t s\u1ed1 kh\u00eda c\u1ea1nh li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam.\n\n 1. M\u1ed1i quan h\u1ec7 c\u0103ng th\u1eb3ng gi\u1eefa Philippines v\u00e0 Trung Qu\u1ed1c \u1edf Bi\u1ec3n \u0110\u00f4ng: M\u1ed1i quan h\u1ec7 gi\u1eefa Philippines v\u00e0 Trung qu\u1ed1c \u1edf Bi\u1ec3n \u0110\u00f4ng \u0111\u00e3 c\u0103ng th\ufffd\ufffdng, v\u1edbi Philippines b\u1ecb c\u00e1o bu\u1ed9c k\u00edch \u0111\u1ed9ng xung \u0111\u1ed9t v\u00e0 g\u00e2y c\u0103ng th\ufffd\ufffd \u0111\u1ed9 trong khu v\u1ef1c.\n\n 2. M\u1ed1i quan h\u1ec7 c\u1ee7a Philippines v\u1edbi Hoa K\u1ef3: Philippines b\u1ecb c\u00e1o bu\u1ed9c l\u00e0 con t\u1ed1t c\u1ee7a Hoa K\u1ef3 trong cu\u1ed9c chi\u1ebfn th\u00f4ng tin ch\u1ed1ng l\u1ea1i Trung Qu\u1ed1c.\n\n 3. Ph\u1ea3n \u1ee9ng c\u1ee7a ng\u01b0\u1eddi d\u00e2n Philippines: Ng\u01b0\u1eddi d\u00e2n Philippines \u0111\u00e3 ch\u1ec9 tr\u00edch h\u00e0nh \u0111\u1ed9ng c\u1ee7a ch\u00ednh ph\u1ee7 trong v\u1ea5n \u0111\u1ec1 Bi\u1ec3n \u0110\u00f4ng.\n\n 4. Kinh t\u1ebf v\u00e0 vi\u1ec7c l\u00e0m: M\u1eb7c d\u00f9 Philippines \u0111\u00e3 tr\u1ea3i qua s\u1ef1 t\u0103ng tr\u01b0\u1edfng kinh t\u1ebf v\u00e0 c\u01a1 h\u1ed9i vi\u1ec7c l\u00e0m nh\u01b0ng m\u1ed1i quan h\u1ec7 c\u0103ng th\u1eaft v\u1edbi Trung Qu\u1ed1c v\u00e0 c\u00e1c n\u01b0\u1edbc \u0110\u00f4ng \u00c1 \u0111\u00e3 \u1ea3nh h\u01b0\u1edfng \u0111\u1ebfn s\u1ef1 ti\u1ebfn b\u1ed9 c\u1ee7a \u0111\u1ea5t n\u01b0\u1edbc.\n\n 5. C\u00e2n nh\u1eafc v\u1ec1 vi\u1ec7c ch\u1ea5m d\u1ee9t: Philippines \u0111\u00e3 c\u00e2n nh\u1eafc ch\u1ea5m d\u1ee9t m\u1ed1i quan h\u1ec7 v\u1edbi Trung Qu\u1ed1c do c\u0103ng th\u1eb5ng \u1edf Bi\u1ec3n \u0110\u00f4ng."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": ["\u25a1\u672c\u62a5\u8bb0\u8005 \u738b\u5b87\u9732 \u845b\u7476 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v\u00e0 Vi\u1ec7t Nam."], "contexts": ["\u7f8e\u570b\u5929\u540eKaty Perry\u5468\u56db\uff0821\u65e5\uff09\u65bc\u8868\u63da\u79d1\u5b78\u9032\u5c55\u7684\u300aVinFuture\u9812\u734e\u79ae\u300b\u737b\u5531\uff0c\u4eca\u6b21\u662f\u5979\u9996\u5ea6\u65bc\u8d8a\u5357\u8868\u6f14\uff0c\u7279\u5225\u5b89\u6392\u7a7f\u4e0a\u7576\u5730\u6c11\u65cf\u670d\u7684\u4f34\u821e\u54e1\u4e0a\u5834\u3002 \u5979\u65bc\u793e\u4ea4\u7db2\u7ad9\u5206\u4eab\u821e\u53f0\u8207\u5f8c\u53f0\u7167\u7247\uff0c\u7559\u8a00\u8868\u793a\uff1a\u300c\u6211\u6700\u937e\u610f\u5605\u9812\u734e\u79ae\uff0c\u5c31\u4fc2\u53bb\u8868\u63da\u5091\u51fa\u79d1\u5b78\u5bb6\u6539\u8b8a\u4e16\u754c\u5605\u6210\u5c31\u3002\u591a\u8b1dVinFuture\u5e36\u6211\u8fd4\u8d8a\u5357\uff0c\u6211\u7d42\u65bc\u55ba\u7576\u5730\u9996\u6b21\u5531\u6b4c\uff01\u300d"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["Th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p kh\u00f4ng li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam. N\u00f3 n\u00f3i v\u1ec1 ca s\u0129 Katy Perry \u0111\u01b0\u1ee3c vinh danh t\u1ea1i s\u1ef1 ki\u1ec7n \"VinFuture Awards\" \u1edf Vi\u1ec7t Nam v\u00e0 bi\u1ec3u di\u1ec5n trong trang ph\u1ee5c truy\u1ec1n th\u1ed1ng c\u1ee7a \u0111\u1ecba ph\u01b0\u01a1ng. C\u00f4 b\u00e0y t\u1ecf s\u1ef1 h\u00e0o h\u1ee9ng khi \u0111\u01b0\u1ee3c vinh danh v\u00e0 c\u1ea3m \u01a1n VinFuture \u0111\u00e3 \u0111\u01b0a c\u00f4 \u0111\u1ebfn Vi\u1ec7t Nam \u0111\u1ec3 bi\u1ec3u di\u1ec5n l\u1ea7n \u0111\u1ea7u ti\u00ean."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": ["Th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p kh\u00f4ng li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam. N\u00f3 n\u00f3i v\u1ec1 ca s\u0129 Katy Perry \u0111\u01b0\u1ee3c vinh danh t\u1ea1i s\u1ef1 ki\u1ec7n \"VinFuture Awards\" \u1edf Vi\u1ec7t Nam v\u00e0 bi\u1ec3u di\u1ec5n trong trang ph\u1ee5c truy\u1ec1n th\u1ed1ng c\u1ee7a \u0111\u1ecba ph\u01b0\u01a1ng. C\u00f4 b\u00e0y t\u1ecf s\u1ef1 h\u00e0o h\u1ee9ng khi \u0111\u01b0\u1ee3c vinh danh v\u00e0 c\u1ea3m \u01a1n VinFuture \u0111\u00e3 \u0111\u01b0a c\u00f4 \u0111\u1ebfn Vi\u1ec7t Nam \u0111\u1ec3 bi\u1ec3u di\u1ec5n l\u1ea7n \u0111\u1ea7u ti\u00ean."], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["Ca s\u0129 Katy Perry \u0111\u00e3 \u0111\u01b0\u1ee3c vinh danh t\u1ea1i s\u1ef1 ki\u1ec7n \"VinFuture Awards\" \u1edf Vi\u1ec7t Nam v\u00e0 bi\u1ec3u di\u1ec5n trong trang ph\u1ee5c truy\u1ec1n th\u1ed1ng c\u1ee7a \u0111\u1ecba ph\u01b0\u01a1ng. C\u00f4 b\u00e0y t\u1ecf s\u1ef1 h\u00e0o h\u1ee9ng khi \u0111\u01b0\u1ee3c vinh danh v\u00e0 c\u1ea3m \u01a1n VinFuture \u0111\u00e3 \u0111\u01b0a c\u00f4 \u0111\u1ebfn Vi\u1ec7t Nam \u0111\u1ec3 bi\u1ec3u di\u1ec5n l\u1ea7n \u0111\u1ea7u ti\u00ean."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": [" B\u1ed1n ng\u00e0y c\u1ee7a Katy Perry \u1edf Hoa K\u1ef3 (21 ng\u00e0y) Tri\u1ec3n l\u00e3m ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n\u300aVinFuture\u9812\u734e\u79ae\u300b\u737b\u5531\uff0c\u4eca\u6b21\u662f\u5979\u9996\u5ea6\u65bc\u8d8a\u5357\u8868\u6f14\uff0c\u7279\u0110\u00f3 l\u00e0 n\u01a1i m\u1ecdi ng\u01b0\u1eddi c\u00f3 th\u1ec3 nh\u1ea3y ri\u00eang. Sau khi \u0111i\u1ec7u nh\u1ea3y ho\u00e0n th\u00e0nh , ng\u00f4n ng\u1eef c\u1ee7a th\u1ebf gi\u1edbi \u0111\u00e3 ph\u00e1t tri\u1ec3n: \u300c\u00dd \u0111\u1ecbnh c\u1ee7a b\u1ea1n t\u00f4i l\u00e0 d\u00f9ng n\u00f3 nh\u01b0 m\u1ed9t nghi l\u1ec5, v\u00e0 c\u1ea7n ph\u1ea3i thay \u0111\u1ed5i th\u1ebf gi\u1edbi c\u1ee7a th\u1ebf gi\u1edbi. Nhi\u1ec1u \u0111\u00e1nh gi\u00e1 v\u1ec1 VinFuture, T\u00f4i \u0111ang du l\u1ecbch mi\u1ec1n nam, t\u00f4i \u0111ang du l\u1ecbch trong khu v\u1ef1c! \u201d"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["Th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p kh\u00f4ng li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam. N\u00f3 n\u00f3i v\u1ec1 chuy\u1ebfn l\u01b0u di\u1ec5n c\u1ee7a Katy Perry \u1edf Vi\u1ec7t Nam v\u00e0 s\u1ef1 ki\u1ec7n trao gi\u1ea3i c\u1ee7a ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n. Kh\u00f4ng c\u00f3 \u0111\u1ec1 c\u1eadp \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c b\u1ea5t k\u1ef3 v\u1ea5n \u0111\u1ec1 li\u00ean quan n\u00e0o \u0111\u1ebfn Vi\u1ec7t Nam."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": ["Th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p kh\u00f4ng li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam. N\u00f3 n\u00f3i v\u1ec1 chuy\u1ebfn l\u01b0u di\u1ec5n c\u1ee7a Katy Perry \u1edf Vi\u1ec7t Nam v\u00e0 s\u1ef1 ki\u1ec7n trao gi\u1ea3i c\u1ee7a ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n. Kh\u00f4ng c\u00f3 \u0111\u1ec1 c\u1eadp \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c b\u1ea5t k\u1ef3 v\u1ea5n \u0111\u1ec1 li\u00ean quan n\u00e0o \u0111\u1ebfn Vi\u1ec7t Nam."], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a tr\u00ean th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p, kh\u00f4ng c\u00f3 th\u00f4ng tin n\u00e0o li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c Vi\u1ec7t Nam. Th\u00f4ng tin n\u00f3i v\u1ec1 chuy\u1ebfn l\u01b0u di\u1ec5n c\u1ee7a Katy Perry \u1edf Vi\u1ec7t Nam v\u00e0 s\u1ef1 ki\u1ec7n trao gi\u1ea3i c\u1ee7a ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n. Kh\u00f4ng c\u00f3 \u0111\u1ec1 c\u1eadp \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c b\u1ea5t k\u1ef3 v\u1ea5n \u0111\u1ec1 li\u00ean quan n\u00e0o \u0111\u1ebfn Vi\u1ec7t Nam."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": [" B\u1ed1n ng\u00e0y c\u1ee7a Katy Perry \u1edf Hoa K\u1ef3 (21 ng\u00e0y) Tri\u1ec3n l\u00e3m ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n\u300aVinFuture\u9812\u734e\u79ae\u300b\u737b\u5531\uff0c\u4eca\u6b21\u662f\u5979\u9996\u5ea6\u65bc\u8d8a\u5357\u8868\u6f14\uff0c\u7279\u0110\u00f3 l\u00e0 n\u01a1i m\u1ecdi ng\u01b0\u1eddi c\u00f3 th\u1ec3 nh\u1ea3y ri\u00eang. Sau khi \u0111i\u1ec7u nh\u1ea3y ho\u00e0n th\u00e0nh , ng\u00f4n ng\u1eef c\u1ee7a th\u1ebf gi\u1edbi \u0111\u00e3 ph\u00e1t tri\u1ec3n: \u300c\u00dd \u0111\u1ecbnh c\u1ee7a b\u1ea1n t\u00f4i l\u00e0 d\u00f9ng n\u00f3 nh\u01b0 m\u1ed9t nghi l\u1ec5, v\u00e0 c\u1ea7n ph\u1ea3i thay \u0111\u1ed5i th\u1ebf gi\u1edbi c\u1ee7a th\u1ebf gi\u1edbi. Nhi\u1ec1u \u0111\u00e1nh gi\u00e1 v\u1ec1 VinFuture, T\u00f4i \u0111ang du l\u1ecbch mi\u1ec1n nam, t\u00f4i \u0111ang du l\u1ecbch trong khu v\u1ef1c! \u201d"], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["Th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p kh\u00f4ng li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam. N\u00f3 n\u00f3i v\u1ec1 chuy\u1ebfn l\u01b0u di\u1ec5n c\u1ee7a Katy Perry \u1edf Vi\u1ec7t Nam v\u00e0 s\u1ef1 ki\u1ec7n trao gi\u1ea3i c\u1ee7a ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n. Kh\u00f4ng c\u00f3 \u0111\u1ec1 c\u1eadp \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c b\u1ea5t k\u1ef3 v\u1ea5n \u0111\u1ec1 li\u00ean quan n\u00e0o \u0111\u1ebfn Vi\u1ec7t Nam."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$${"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam."], "contexts": ["Th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p kh\u00f4ng li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam. N\u00f3 n\u00f3i v\u1ec1 chuy\u1ebfn l\u01b0u di\u1ec5n c\u1ee7a Katy Perry \u1edf Vi\u1ec7t Nam v\u00e0 s\u1ef1 ki\u1ec7n trao gi\u1ea3i c\u1ee7a ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n. Kh\u00f4ng c\u00f3 \u0111\u1ec1 c\u1eadp \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c b\u1ea5t k\u1ef3 v\u1ea5n \u0111\u1ec1 li\u00ean quan n\u00e0o \u0111\u1ebfn Vi\u1ec7t Nam."], "lang": "vi", "version": "ic-llama-68k", "system_prompt": ""} +{"status": 1, "message": "success", "result": ["D\u1ef1a tr\u00ean th\u00f4ng tin \u0111\u01b0\u1ee3c cung c\u1ea5p, kh\u00f4ng c\u00f3 th\u00f4ng tin n\u00e0o li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c Vi\u1ec7t Nam. Th\u00f4ng tin n\u00f3i v\u1ec1 chuy\u1ebfn l\u01b0u di\u1ec5n c\u1ee7a Katy Perry \u1edf Vi\u1ec7t Nam v\u00e0 s\u1ef1 ki\u1ec7n trao gi\u1ea3i c\u1ee7a ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111i\u1ec7n \u1ea3nh Nh\u1eadt B\u1ea3n. Kh\u00f4ng c\u00f3 \u0111\u1ec1 c\u1eadp \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng ho\u1eb7c b\u1ea5t k\u1ef3 v\u1ea5n \u0111\u1ec1 li\u00ean quan n\u00e0o \u0111\u1ebfn Vi\u1ec7t Nam."], "time": null} +$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ \ No newline at end of file diff --git a/requests_llama_error.txt b/requests_llama_error.txt new file mode 100644 index 0000000000000000000000000000000000000000..dec073dc635b27830db980aef4f683eab842a842 --- /dev/null +++ b/requests_llama_error.txt @@ -0,0 +1,3 @@ +{"questions": ["T\u00f3m t\u00e1t n\u1ed9i dung li\u00ean quan \u0111\u1ebfn Bi\u1ec3n \u0110\u00f4ng v\u00e0 Vi\u1ec7t Nam"], "contexts": ["\u25a1\u672c\u62a5\u8bb0\u8005 \u738b\u5b87\u9732 \u845b\u7476 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0000000000000000000000000000000000000000..5035e5fff049a9076124b7caa52103bab528e682 --- /dev/null +++ b/requests_tran.txt @@ -0,0 +1 @@ +{"doc": "\u7f8e\u570b\u5929\u540eKaty Perry\u5468\u56db\uff0821\u65e5\uff09\u65bc\u8868\u63da\u79d1\u5b78\u9032\u5c55\u7684\u300aVinFuture\u9812\u734e\u79ae\u300b\u737b\u5531\uff0c\u4eca\u6b21\u662f\u5979\u9996\u5ea6\u65bc\u8d8a\u5357\u8868\u6f14\uff0c\u7279\u5225\u5b89\u6392\u7a7f\u4e0a\u7576\u5730\u6c11\u65cf\u670d\u7684\u4f34\u821e\u54e1\u4e0a\u5834\u3002 \u5979\u65bc\u793e\u4ea4\u7db2\u7ad9\u5206\u4eab\u821e\u53f0\u8207\u5f8c\u53f0\u7167\u7247\uff0c\u7559\u8a00\u8868\u793a\uff1a\u300c\u6211\u6700\u937e\u610f\u5605\u9812\u734e\u79ae\uff0c\u5c31\u4fc2\u53bb\u8868\u63da\u5091\u51fa\u79d1\u5b78\u5bb6\u6539\u8b8a\u4e16\u754c\u5605\u6210\u5c31\u3002\u591a\u8b1dVinFuture\u5e36\u6211\u8fd4\u8d8a\u5357\uff0c\u6211\u7d42\u65bc\u55ba\u7576\u5730\u9996\u6b21\u5531\u6b4c\uff01\u300d", "src_lang": "ko", "tgt_lang": "vi"} \ No newline at end of file diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..114fae0234365dc7f8ac88be538ba5eec5ab8596 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,48 @@ +asgiref==3.4.1 +certifi==2021.5.30 +charset-normalizer==2.0.3 +click==8.0.1 +colorama==0.4.4 +dataclasses +date-extractor==5.1.5 +dateparser==1.0.0 +editdistance==0.5.3 +fastapi==0.66.0 +filelock==3.0.12 +flashtext==2.7 +h11==0.12.0 +huggingface-hub==0.0.12 +idna==3.2 +importlib-metadata==4.6.1 +joblib==1.0.1 +nltk==3.6.2 +numpy==1.19.5 +packaging==21.0 +Pillow==8.3.1 +pydantic==1.8.2 +pyparsing==2.4.7 +python-dateutil==2.8.2 +pytz==2021.1 +PyYAML==5.4.1 +regex==2021.7.6 +requests==2.26.0 +sacremoses==0.0.45 +scikit-learn==0.24.2 +scipy==1.5.4 +sentence-transformers==2.0.0 +sentencepiece==0.1.96 +six==1.16.0 +sklearn==0.0 +starlette==0.14.2 +threadpoolctl==2.2.0 +tokenizers==0.10.3 +torch==1.9.0 +torchvision==0.10.0 +tqdm==4.61.2 +transformers==4.8.2 +typing-extensions==3.10.0.0 +tzlocal==2.1 +urllib3==1.26.6 +uvicorn==0.14.0 +vncorenlp==1.0.3 +zipp==3.5.0 diff --git a/results_covid.txt b/results_covid.txt new file mode 100644 index 0000000000000000000000000000000000000000..d49914fd3a7717a1d85f10b681354acec518b430 --- /dev/null +++ b/results_covid.txt @@ -0,0 +1 @@ +{"1": [{"url": "http://suckhoemoitruong.com.vn/phong-chong-covid-trong-tinh-hinh-moi/sang-11-8-them-4-802-ca-mac-moi-covid-19;-ky-luc-1-ngay-tiem-hon-1-4-trieu-lieu-vac-xin-id34028n.html", "domain": "suckhoemoitruong.com.vn", "title": "S\u00e1ng 11/8, th\u00eam 4.802 ca m\u1eafc m\u1edbi Covid-19; k\u1ef7 l\u1ee5c 1 ng\u00e0y ti\u00eam h\u01a1n 1,4 tri\u1ec7u li\u1ec1u v\u1eafc-xin", "snippet": "S\u00e1ng 11/8, th\u00eam 4.802 ca m\u1eafc m\u1edbi Covid-19; k\u1ef7 l\u1ee5c 1 ng\u00e0y ti\u00eam h\u01a1n 1,4 tri\u1ec7u li\u1ec1u v\u1eafc-xin", "created_time": 1628648460, "id": "suckhoemoitruong.com.vn_id34028n", "score": 0.0, "title_summarize": ["S\u00e1ng 11/8, th\u00eam 4.802 ca m\u1eafc m\u1edbi Covid-19; k\u1ef7 l\u1ee5c 1 ng\u00e0y ti\u00eam h\u01a1n 1,4 tri\u1ec7u li\u1ec1u v\u1eafc-xin", "(KDPT) \u2013 B\u1ea3n tin d\u1ecbch Covid-19 s\u00e1ng 11/8 c\u1ee7a B\u1ed9 Y t\u1ebf cho bi\u1ebft, c\u00f3 th\u00eam 4.802 ca m\u1eafc m\u1edbi, TP. H\u1ed3 Ch\u00ed Minh nhi\u1ec1u nh\u1ea5t v\u1edbi 2.128 ca. Trong ng\u00e0y c\u00f3 1.408.453 li\u1ec1u v\u1eafc-xin Covid-19 \u0111\u01b0\u1ee3c ti\u00eam, n\u00e2ng t\u1ed5ng ...", "VHO- S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i cho bi\u1ebft, t\u1eeb 12h \u2013 18h chi\u1ec1u 10.8, tr\u00ean \u0111\u1ecba b\u00e0n TP ti\u1ebfp t\u1ee5c ghi nh\u1eadn th\u00eam 6 tr\u01b0\u1eddng h\u1ee3p d\u01b0\u01a1ng t\u00ednh v\u1edbi SARS-CoV-2 (3 ca t\u1ea1i khu c\u00e1ch ly v\u00e0 3 ca t\u1ea1i c\u1ed9ng \u0111\u1ed3ng), n\u00e2ng t\u1ed5ng s\u1ed1 m\u1eafc trong ng\u00e0y l\u00ean 62 tr\u01b0\u1eddng h\u1ee3p."], "content_summary": "\"(SK&MT) - B\u1ea3n tin d\u1ecbch Covid-19 s\u00e1ng 11/8 c\u1ee7a B\u1ed9 Y t\u1ebf cho bi\u1ebft, c\u00f3 th\u00eam 4.802 ca m\u1eafc m\u1edbi, TP. Trong ng\u00e0y c\u00f3 1.408.453 li\u1ec1u v\u1eafc-xin Covid-19\u00a0\u0111\u01b0\u1ee3c ti\u00eam, n\u00e2ng t\u1ed5ng s\u1ed1 li\u1ec1u \u0111\u00e3 \u0111\u01b0\u1ee3c ti\u00eam \u1edf n\u01b0\u1edbc ta l\u00ean h\u01a1n 11,3 tri\u1ec7u. T\u00ecnh h\u00ecnh d\u1ecbch Covid-19 t\u1ea1i Vi\u1ec7t Nam - T\u00ednh \u0111\u1ebfn s\u00e1ng ng\u00e0y 11/8, Vi\u1ec7t Nam c\u00f3 232.937 ca nhi\u1ec5m trong \u0111\u00f3 c\u00f3 2.377 ca nh\u1eadp c\u1ea3nh v\u00e0 230.560 ca nhi\u1ec5m trong n\u01b0\u1edbc. - S\u1ed1 b\u1ec7nh nh\u00e2n n\u1eb7ng \u0111ang \u0111i\u1ec1u tr\u1ecb ICU: 491 ca. -\"", "total_facebook_viral": 0}, {"url": "https://kinhdoanhvaphattrien.vn/sang-11-8-them-4-802-ca-mac-moi-covid-19-ky-luc-1-ngay-tiem-hon-14-trieu-lieu-vac-xin.html", "domain": "kinhdoanhvaphattrien.vn", "title": "S\u00e1ng 11/8, th\u00eam 4.802 ca m\u1eafc m\u1edbi Covid-19; k\u1ef7 l\u1ee5c 1 ng\u00e0y ti\u00eam h\u01a1n 1,4 tri\u1ec7u li\u1ec1u v\u1eafc-xin -", "snippet": "(KDPT) \u2013 B\u1ea3n tin d\u1ecbch Covid-19 s\u00e1ng 11/8 c\u1ee7a B\u1ed9 Y t\u1ebf cho bi\u1ebft, c\u00f3 th\u00eam 4.802 ca m\u1eafc m\u1edbi, TP. H\u1ed3 Ch\u00ed Minh nhi\u1ec1u nh\u1ea5t v\u1edbi 2.128 ca. Trong ng\u00e0y c\u00f3 1.408.453 li\u1ec1u v\u1eafc-xin Covid-19 \u0111\u01b0\u1ee3c ti\u00eam, n\u00e2ng t\u1ed5ng ...", "created_time": 1628623704, "id": "60fea044725cbb09f7dd335aa632b635782b2bbd", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://www.baovanhoa.vn/\u0111oi-song/y-te/artmid/585/articleid/43930/ha-noi-them-6-ca-duong-tinh-moi-bac-bo-thong-tin-sai-su-that", "domain": "baovanhoa.vn", "title": "H\u00e0 N\u1ed9i th\u00eam 6 ca d\u01b0\u01a1ng t\u00ednh m\u1edbi, b\u00e1c b\u1ecf th\u00f4ng tin sai s\u1ef1 th\u1eadt", "snippet": "VHO- S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i cho bi\u1ebft, t\u1eeb 12h \u2013 18h chi\u1ec1u 10.8, tr\u00ean \u0111\u1ecba b\u00e0n TP ti\u1ebfp t\u1ee5c ghi nh\u1eadn th\u00eam 6 tr\u01b0\u1eddng h\u1ee3p d\u01b0\u01a1ng t\u00ednh v\u1edbi SARS-CoV-2 (3 ca t\u1ea1i khu c\u00e1ch ly v\u00e0 3 ca t\u1ea1i c\u1ed9ng \u0111\u1ed3ng), n\u00e2ng t\u1ed5ng s\u1ed1 m\u1eafc trong ng\u00e0y l\u00ean 62 tr\u01b0\u1eddng h\u1ee3p.", "created_time": 1628595480, "id": "baovanhoa.vn_43930", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://infonet.vietnamnet.vn/khoe-dep/ca-moi-sang-11-8-them-4-802-ca-mac-covid-19-ky-luc-tiem-hon-1-4-trieu-lieu-vaccine-trong-1-ngay-292854.html", "domain": "infonet.vietnamnet.vn", "title": "S\u00e1ng 11/8: Th\u00eam 4.802 ca m\u1eafc COVID-19, k\u1ef7 l\u1ee5c ti\u00eam h\u01a1n 1,4 tri\u1ec7u li\u1ec1u v\u1eafc xin trong 1 ng\u00e0y", "snippet": "B\u1ea3n tin d\u1ecbch COVID-19 s\u00e1ng 11/8 c\u1ee7a B\u1ed9 Y t\u1ebf cho bi\u1ebft c\u00f3 4.802 ca m\u1eafc COVID-19, TP H\u1ed3 Ch\u00ed Minh nhi\u1ec1u nh\u1ea5t v\u1edbi 2.128 ca. Trong ng\u00e0y c\u00f3 1.408.453 li\u1ec1u vaccine COVID-19 \u0111\u01b0\u1ee3c ti\u00eam, n\u00e2ng t\u1ed5ng s\u1ed1 li\u1ec1u \u0111\u00e3 \u0111\u01b0\u1ee3c ti\u00eam \u1edf n\u01b0\u1edbc ta l\u00ean h\u01a1n 11,3 tri\u1ec7u", "created_time": 1628640720, "id": "4bf0637d874145e771f9a13db59c1750609e63c6", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://tienphong.vn/sang-11-8-them-4-802-ca-mac-covid-19-tphcm-co-2-128-ca-post1364662.tpo", "domain": "tienphong.vn", "title": "S\u00e1ng 11/8 th\u00eam 4.802 ca m\u1eafc COVID-19, TPHCM c\u00f3 2.128 ca", "snippet": "TPO - S\u00e1ng 11/8, B\u1ed9 Y t\u1ebf cho bi\u1ebft,\u00a0tr\u00ean H\u1ec7 th\u1ed1ng Qu\u1ed1c gia qu\u1ea3n l\u00fd ca b\u1ec7nh COVID-19 ghi nh\u1eadn 4.802 ca nhi\u1ec5m m\u1edbi v\u1edbi 10 ca nh\u1eadp c\u1ea3nh v\u00e0 4.792 ca ghi nh\u1eadn trong n\u01b0\u1edbc (1.135 ca trong c\u1ed9ng \u0111\u1ed3ng).", "created_time": 1628636271, "id": "tienphong.vn_1364662", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://nbtv.vn/news/205/16683/them-4-802-ca-mac-covid-19-co-1-135-ca-trong-cong-dong", "domain": "nbtv.vn", "title": "Th\u00eam 4.802 ca m\u1eafc COVID-19, c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng", "snippet": "Th\u00eam 4.802 ca m\u1eafc COVID-19, c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng", "created_time": 1628645585, "id": "9df8c9160a6c8909102c110bc3cb393fd14dbc47", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://nbtv.vn/news/240/16683/them-4-802-ca-mac-covid-19-co-1-135-ca-trong-cong-dong", "domain": "nbtv.vn", "title": "Th\u00eam 4.802 ca m\u1eafc COVID-19, c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng", "snippet": "Th\u00eam 4.802 ca m\u1eafc COVID-19, c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng", "created_time": 1628645585, "id": "287adc62dc483d188987ba40ff449df1639455a1", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://plo.vn/suc-khoe/sang-118-them-4792-ca-mac-ca-nuoc-vuot-232000-ca-1007346.html", "domain": "plo.vn", "title": "S\u00e1ng 11-8 th\u00eam 4.792 ca m\u1eafc, c\u1ea3 n\u01b0\u1edbc v\u01b0\u1ee3t 232.000 ca", "snippet": "(PLO)- S\u1ed1 ca m\u1eafc COVID-19 t\u1ea1i TP.HCM sau nhi\u1ec1u ng\u00e0y gi\u1ea3m nh\u1eb9 s\u00e1ng nay l\u1ea1i t\u0103ng l\u00ean h\u01a1n 2.000 ca.", "created_time": 1628647409, "id": "plo.vn_1007346", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://baohungyen.com.vn/xa-hoi/202108/them-4802-ca-mac-covid-19-co-1135-ca-trong-cong-dong-db81bcb/", "domain": "baohungyen.com.vn", "title": "Th\u00eam 4.802 ca m\u1eafc COVID-19, c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng", "snippet": "B\u1ea3n tin d\u1ecbch COVID-19 s\u00e1ng ng\u00e0y 11/8 c\u1ee7a B\u1ed9 Y t\u1ebf cho bi\u1ebft c\u00f3 4.802 ca m\u1eafc COVID-19, trong \u0111\u00f3 c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng. 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Trong ng\u00e0y c\u00f3 1.408.453 li\u1ec1u vaccine COVID-19 \u0111\u01b0\u1ee3c ti\u00eam, n\u00e2ng t\u1ed5ng s\u1ed1 li\u1ec1u \u0111\u00e3 \u0111\u01b0\u1ee3c ti\u00eam \u1edf n\u01b0\u1edbc ta l\u00ean h\u01a1n 11,3 tri\u1ec7u", "created_time": 1628638380, "id": "doanhnghiepvn.vn_20210811062733030", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://daibieunhandan.vn/viet-nam-ghi-nhan-them-4802-ca-mac-covid19-trong-sang-118", "domain": "daibieunhandan.vn", "title": "Vi\u1ec7t Nam ghi nh\u1eadn th\u00eam 4.802 ca m\u1eafc COVID-19 trong s\u00e1ng 11.8", "snippet": "B\u1ea3n tin d\u1ecbch COVID-19 s\u00e1ng 11.8 c\u1ee7a B\u1ed9 Y t\u1ebf cho bi\u1ebft c\u00f3 4.802 ca m\u1eafc COVID-19, Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh nhi\u1ec1u nh\u1ea5t v\u1edbi 2.128 ca.", "created_time": 1628638800, "id": "24874fc877f44b2e282d56c0fcbbb4b3df9f882d", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baophapluat.vn/sang-11-8-them-4-802-ca-mac-covid-19-trong-do-co-1-135-ca-cong-dong-post407142.html", "domain": "baophapluat.vn", "title": "S\u00e1ng 11/8 th\u00eam 4.802 ca m\u1eafc COVID-19, trong \u0111\u00f3 c\u00f3 1.135 ca c\u1ed9ng \u0111\u1ed3ng", "snippet": "(PLVN) - B\u1ed9 Y t\u1ebf cho bi\u1ebft s\u00e1ng 11/8\u00a0c\u00f3 4.802 ca m\u1eafc COVID-19, trong \u0111\u00f3 c\u00f3\u00a01.135 ca ghi nh\u1eadn trong\u00a0c\u1ed9ng \u0111\u1ed3ng.", "created_time": 1628639484, "id": "baophapluat.vn_407142", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://donghanhviet.vn/news/4275/393/sang-11-8-them-4-802-ca-moi-bo-y-te-mo-rong-nang-luc-xet-nghiem/d,news_detail_tpl", "domain": "donghanhviet.vn", "title": "S\u00e1ng 11-8: Th\u00eam 4.802 ca m\u1edbi, B\u1ed9 Y t\u1ebf m\u1edf r\u1ed9ng n\u0103ng l\u1ef1c x\u00e9t nghi\u1ec7m", "snippet": "Theo tin t\u1eeb B\u1ed9 Y t\u1ebf, t\u00ednh t\u1eeb 18h ng\u00e0y 10-8 \u0111\u1ebfn 6h ng\u00e0y 11-8, tr\u00ean H\u1ec7 th\u1ed1ng qu\u1ed1c gia qu\u1ea3n l\u00fd ca b\u1ec7nh Covid-19 ghi nh\u1eadn 4.802 ca nhi\u1ec5m m\u1edbi;\u00a0trong \u0111\u00f3, 10 ca nh\u1eadp c\u1ea3nh v\u00e0 4.792 ca ghi nh\u1eadn trong n\u01b0\u1edbc t\u1ea1i th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh (2.128), B\u00ecnh D\u01b0\u01a1ng (936), Long An (515), \u0110\u1ed3ng Nai (428), T\u00e2y Ninh (263), Ti\u1ec1n Giang (177), B\u00e0 R\u1ecba - V\u0169ng T\u00e0u (102), V\u0129nh Long (63), Kh\u00e1nh H\u00f2a (41), Ph\u00fa Y\u00ean (33), B\u00ecnh Thu\u1eadn (27), S\u01a1n La (19), \u0110\u1ed3ng Th\u00e1p (15), Ki\u00ean Giang (12), B\u00ecnh \u0110\u1ecbnh (10), Qu\u1ea3ng Ng\u00e3i (9), H\u00e0 T\u0129nh (7), H\u00e0 N\u1ed9i (3), Ngh\u1ec7 An (2), Nam \u0110\u1ecbnh (1), L\u1ea1ng S\u01a1n (1), trong \u0111\u00f3 c\u00f3 1.135 ca trong c\u1ed9ng \u0111\u1ed3ng.", "created_time": 1628648580, "id": "6c60d5c07e6643d1d6d059a7402d937fd5cf842d", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://giadinh.net.vn/y-te/ban-tin-covid-19-sang-11-8-ha-noi-tp-hcm-va-19-tinh-them-4302-ca-nhiem-moi-20210811062838967.htm", "domain": "giadinh.net.vn", "title": "B\u1ea3n tin COVID-19 s\u00e1ng 11/8: H\u00e0 N\u1ed9i, TP HCM v\u00e0 19 t\u1ec9nh th\u00eam 4.302 ca nhi\u1ec5m m\u1edbi", "snippet": "GiadinhNet - H\u1ec7 th\u1ed1ng Qu\u1ed1c gia qu\u1ea3n l\u00fd ca b\u1ec7nh COVID-19 trong 12 gi\u1edd qua ghi nh\u1eadn 4.802 ca nhi\u1ec5m m\u1edbi t\u1ea1i 21 t\u1ec9nh, th\u00e0nh ph\u1ed1. 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S\u1ed1 l\u01b0\u1ee3ng vaccine COVID-19 s\u1ebd v\u1ec1 nhi\u1ec1u v\u00e0 d\u1ed3n d\u1eadp \u0111\u1ebfn cu\u1ed1i n\u0103m 2021.", "created_time": 1628609160, "id": "ee3a375a6de86b407bbaccbc893fd0fdce996867", "score": 0.0, "title_summarize": ["Vi\u1ec7t Nam ho\u00e0n th\u00e0nh giai \u0111o\u1ea1n nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 t\u1eeb th\u1ea3o d\u01b0\u1ee3c. S\u1ed1 l\u01b0\u1ee3ng vaccine COVID-19 s\u1ebd v\u1ec1 nhi\u1ec1u v\u00e0 d\u1ed3n d\u1eadp \u0111\u1ebfn cu\u1ed1i n\u0103m 2021.", "C\u00e1c nh\u00e0 khoa h\u1ecdc Vi\u1ec7t Nam v\u1eeba c\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 th\u1eed nghi\u1ec7m ti\u1ec1n l\u00e2m s\u00e0ng \u0111\u1ed1i v\u1edbi thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19 Vipderver: An to\u00e0n v\u00e0 c\u00f3 t\u00e1c d\u1ee5ng \u1ee9c ch\u1ebf s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a virus SARS-CoV-2", "TP - \u201cT\u1eeb h\u00f4m nay (11/8), nh\u00f3m nghi\u00ean c\u1ee9u v\u1eafc-xin Covivac s\u1ebd b\u1eaft \u0111\u1ea7u s\u00e0ng l\u1ecdc, thu tuy\u1ec3n t\u00ecnh nguy\u1ec7n vi\u00ean tham gia nghi\u00ean c\u1ee9u th\u1eed nghi\u1ec7m l\u00e2m s\u00e0ng giai \u0111o\u1ea1n 2 t\u1ea1i V\u0169 Th\u01b0, Th\u00e1i B\u00ecnh\u201d, TS D\u01b0\u01a1ng H\u1eefu Th\u00e1i, Vi\u1ec7n tr\u01b0\u1edfng Vi\u1ec7n v\u1eafc-xin v\u00e0 sinh ph\u1ea9m y t\u1ebf (IVAC) - \u0111\u01a1n v\u1ecb nghi\u00ean c\u1ee9u v\u00e0 \u0111i\u1ec1u ch\u1ebf v\u1eafc- xin Covivac cho bi\u1ebft ng\u00e0y 10/8."], "content_summary": "\"- V\u1ec1 t\u00ecnh h\u00ecnh ti\u00eam ch\u1ee7ng, B\u1ed9 Y t\u1ebf cho bi\u1ebft, \u0111\u1ebfn cu\u1ed1i n\u0103m 2021, s\u1ed1 l\u01b0\u1ee3ng vaccine s\u1ebd v\u1ec1 nhi\u1ec1u v\u00e0 d\u1ed3n d\u1eadp. 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M\u1ecdi c\u00f4ng vi\u1ec7c c\u00f3 li\u00ean quan \u0111ang \u0111\u01b0\u1ee3c nh\u00f3m nghi\u00ean c\u1ee9u g\u1ea5p r\u00fat ho\u00e0n t\u1ea5t \u0111\u1ec3 b\u1eaft \u0111\u1ea7u kh\u00e1m s\u00e0ng l\u1ecdc l\u1ef1a ch\u1ecdn t\u00ecnh nguy\u1ec7n vi\u00ean v\u00e0o ng\u00e0y 11/8.", "created_time": 1628608740, "id": "daidoanket.vn_5661372", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vietq.vn/cong-bo-ket-qua-nghien-cuu-tien-lam-sang-thuoc-dieu-tri-covid-19-d189887.html", "domain": "vietq.vn", "title": "C\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19", "snippet": "Vi\u1ec7n H\u00e0n l\u00e2m Khoa h\u1ecdc v\u00e0 C\u00f4ng ngh\u1ec7 Vi\u1ec7t Nam v\u1eeba t\u1ed5 ch\u1ee9c bu\u1ed5i H\u1ecdp b\u00e1o tr\u1ef1c tuy\u1ebfn c\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19.", "created_time": 1628579280, "id": "vietq.vn_d189887", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://petrotimes.vn/nghien-cuu-thuoc-uc-che-sars-cov-2-tu-thao-duoc-620885.html", "domain": "petrotimes.vn", "title": "Nghi\u00ean c\u1ee9u thu\u1ed1c \u1ee9c ch\u1ebf SARS-CoV-2 t\u1eeb th\u1ea3o d\u01b0\u1ee3c", "snippet": "PGS.TS. 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N\u1ebfu m\u1ecdi chuy\u1ec7n thu\u1eadn l\u1ee3i, d\u1ef1 ki\u1ebfn t\u1eeb nay \u0111\u1ebfn cu\u1ed1i n\u0103m 2021, lo\u1ea1i thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19 t\u1eeb th\u1ea3o d\u01b0\u1ee3c n\u00e0y s\u1ebd \u0111\u01b0\u1ee3c c\u1ea5p ph\u00e9p l\u01b0u h\u00e0nh.", "created_time": 1628584080, "id": "sggp.org.vn_753002", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://cadn.com.vn/news/119_247918_.aspx", "domain": "cadn.com.vn", "title": "C\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 b\u1eb1ng th\u1ea3o d\u01b0\u1ee3c Vi\u1ec7t Nam", "snippet": "C\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 b\u1eb1ng th\u1ea3o d\u01b0\u1ee3c Vi\u1ec7t Nam", "created_time": 1628666160, "id": "cadn.com.vn_247918", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://congluan.vn/thuoc-dieu-tri-covid-19-made-in-viet-nam-duoc-cap-phep-thu-nghiem-lam-sang-post149410.html", "domain": "congluan.vn", "title": "Thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19 \u201cmade in Viet Nam\u201d \u0111\u01b0\u1ee3c c\u1ea5p ph\u00e9p th\u1eed nghi\u1ec7m l\u00e2m s\u00e0ng", "snippet": "(CLO) Ng\u00e0y 10/8, Vi\u1ec7n H\u00e0n l\u00e2m Khoa h\u1ecdc v\u00e0 C\u00f4ng ngh\u1ec7 Vi\u1ec7t Nam (Vi\u1ec7n H\u00e0n l\u00e2m) \u0111\u00e3 ph\u1ed1i h\u1ee3p v\u1edbi B\u1ed9 Y t\u1ebf t\u1ed5 ch\u1ee9c bu\u1ed5i h\u1ecdp b\u00e1o tr\u1ef1c tuy\u1ebfn c\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19. Thu\u1ed1c c\u00f3 t\u00ean VIPDERVIR \u0111\u01b0\u1ee3c b\u00e0o ch\u1ebf t\u1eeb th\u1ea3o d\u01b0\u1ee3c c\u1ee7a Vi\u1ec7t Nam.", "created_time": 1628582760, "id": "congluan.vn_149410", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vtc.vn/se-cap-phep-luu-hanh-thuoc-dieu-tri-covid-19-made-in-vietnam-cuoi-nam-2021-ar629939.html", "domain": "vtc.vn", "title": "S\u1ebd c\u1ea5p ph\u00e9p l\u01b0u h\u00e0nh thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 'made in Vietnam' cu\u1ed1i n\u0103m 2021?", "snippet": "\u0110\u1ea1i di\u1ec7n C\u1ee5c Khoa h\u1ecdc c\u00f4ng ngh\u1ec7 v\u00e0 \u0111\u00e0o t\u1ea1o (B\u1ed9 Y t\u1ebf) hy v\u1ecdng cu\u1ed1i n\u0103m nay, thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 Vipdervir c\u1ee7a Vi\u1ec7t Nam s\u1ebd c\u1ea5p ph\u00e9p l\u01b0u h\u00e0nh.", "created_time": 1628583159, "id": "vtc.vn_r629939", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghiepvn.vn/tin-tuc/thuoc-dieu-tri-covid-19-tu-duoc-lieu-viet-nam-dau-tien-duoc-cap-phep-thu-nghiem-lam-sang/20210810023852910", "domain": "doanhnghiepvn.vn", "title": "Thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 t\u1eeb d\u01b0\u1ee3c li\u1ec7u Vi\u1ec7t Nam \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c c\u1ea5p ph\u00e9p th\u1eed nghi\u1ec7m l\u00e2m s\u00e0ng", "snippet": "Theo PGS.TS Chu Ho\u00e0ng H\u00e0, Ph\u00f3 Ch\u1ee7 t\u1ecbch Vi\u1ec7t H\u00e0n l\u00e2m KH&CN Vi\u1ec7t Nam, VIPDERVIR c\u1ea7n ti\u1ebfp t\u1ee5c nghi\u00ean c\u1ee9u, th\u1eed nghi\u1ec7m l\u00e2m s\u00e0ng \u0111\u1ec3 c\u00f3 th\u1ec3 \u0111\u00e1nh gi\u00e1 hi\u1ec7u qu\u1ea3 \u0111i\u1ec1u tr\u1ecb COVID-19 tr\u01b0\u1edbc khi s\u1eed d\u1ee5ng.", "created_time": 1628581380, "id": "doanhnghiepvn.vn_20210810023852910", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://nongthonviet.com.vn/thoi-su/xa-hoi/202108/viet-nam-chuan-bi-thu-nghiem-thuoc-dieu-tri-covid-19-tren-nguoi-780320/", "domain": "nongthonviet.com.vn", "title": "Vi\u1ec7t Nam chu\u1ea9n b\u1ecb th\u1eed nghi\u1ec7m thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19 tr\u00ean ng\u01b0\u1eddi", "snippet": "Vi\u1ec7n H\u00e0n l\u00e2m Khoa h\u1ecdc v\u00e0 C\u00f4ng ngh\u1ec7 Vi\u1ec7t Nam v\u1eeba t\u1ed5 ch\u1ee9c h\u1ecdp b\u00e1o tr\u1ef1c tuy\u1ebfn c\u00f4ng b\u1ed1 k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u ti\u1ec1n l\u00e2m s\u00e0ng thu\u1ed1c \u0111i\u1ec1u tr\u1ecb Covid-19. 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S\u1ea3n ph\u1ea9m n\u00e0y \u0111\u01b0\u1ee3c k\u1ef3 v\u1ecdng c\u00f3 th\u1ec3 s\u1eed d\u1ee5ng v\u00e0o cu\u1ed1i n\u0103m 2021.", "created_time": 1628582536, "id": "nld.com.vn_20210810142042421", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baoangiang.com.vn/viet-nam-thu-nghiem-thuoc-dieu-tri-covid-19-tu-thao-duoc-a310203.html", "domain": "baoangiang.com.vn", "title": "Vi\u1ec7t Nam th\u1eed nghi\u1ec7m thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 t\u1eeb th\u1ea3o d\u01b0\u1ee3c", "snippet": "Thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 t\u00ean Vipdervir s\u1ebd \u0111\u01b0\u1ee3c th\u1eed nghi\u1ec7m l\u00e2m s\u00e0ng, d\u1ef1 ki\u1ebfn tr\u00ean 260 b\u1ec7nh nh\u00e2n COVID-19.", "created_time": 1628586300, "id": "baoangiang.com.vn_a310203", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://nongthonviet.com.vn/thoi-su/khoa-hoc/202108/viet-nam-thu-nghiem-thuoc-dieu-tri-covid-19-tu-thao-duoc-780296/", "domain": "nongthonviet.com.vn", "title": "Vi\u1ec7t Nam th\u1eed nghi\u1ec7m thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 t\u1eeb th\u1ea3o d\u01b0\u1ee3c", "snippet": "Thu\u1ed1c \u0111i\u1ec1u tr\u1ecb COVID-19 t\u00ean Vipdervir s\u1ebd \u0111\u01b0\u1ee3c th\u1eed nghi\u1ec7m l\u00e2m s\u00e0ng, d\u1ef1 ki\u1ebfn tr\u00ean 260 b\u1ec7nh nh\u00e2n COVID-19. 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Trong khi c\u1ea3 h\u1ec7 th\u1ed1ng ch\u00ednh tr\u1ecb \u0111ang \u201cc\u0103ng m\u00ecnh" ch\u1ed1ng d\u1ecbch, c\u00e1c c\u1ea5p, c\u00e1c ng\u00e0nh v\u00e0o cu\u1ed9c quy\u1ebft li\u1ec7t, kh\u1ea9n tr\u01b0\u01a1ng th\u00ec \u0111\u00e2u \u0111\u00f3 v\u1eabn c\u00f2n nh\u1eefng c\u00e1 nh\u00e2n c\u00f3 t\u00e2m l\u00fd l\u01a1 l\u00e0, ch\u1ee7 quan, vi ph\u1ea1m quy \u0111\u1ecbnh c\u1ee7a c\u01a1 quan ch\u1ee9c n\u0103ng, th\u1eadm ch\u00ed ch\u1ed1ng \u0111\u1ed1i l\u1ef1c l\u01b0\u1ee3ng l\u00e0m nhi\u1ec7m v\u1ee5. H\u01a1n l\u00fac n\u00e0o h\u1ebft, tinh th\u1ea7n tr\u00e1ch nhi\u1ec7m, s\u1ef1 t\u1ef1 gi\u00e1c c\u1ee7a m\u1ed7i ng\u01b0\u1eddi d\u00e2n ph\u1ea3i \u0111\u1eb7t l\u00ean h\u00e0ng \u0111\u1ea7u, \u0111\u01b0\u1ee3c coi l\u00e0 \u201cl\u00e1 ch\u1eafn th\u00e9p\u201d trong ph\u00f2ng, ch\u1ed1ng d\u1ecbch, g\u00f3p ph\u1ea7n ph\u00f2ng ng\u1eeba v\u00e0 \u0111\u1ea9y l\u00f9i d\u1ecbch b\u1ec7nh.", "created_time": 1628658000, "id": "dantocmiennui.vn_305626", "score": 0.0, "title_summarize": ["\u0110\u1ee3t d\u1ecbch COVID-19 l\u1ea7n th\u1ee9 4 v\u1edbi s\u1ef1 l\u00e2y lan nhanh ch\u00f3ng c\u1ee7a bi\u1ebfn ch\u1ee7ng Delta v\u1eabn \u0111ang di\u1ec5n bi\u1ebfn ph\u1ee9c t\u1ea1p, kh\u00f3 l\u01b0\u1eddng, \u1ea3nh h\u01b0\u1edfng nghi\u00eam tr\u1ecdng \u0111\u1ebfn cu\u1ed9c s\u1ed1ng ng\u01b0\u1eddi d\u00e2n v\u00e0 s\u1ef1 ph\u00e1t tri\u1ec3n kinh t\u1ebf - x\u00e3 h\u1ed9i. Trong khi c\u1ea3 h\u1ec7 th\u1ed1ng ch\u00ednh tr\u1ecb \u0111ang \u201cc\u0103ng m\u00ecnh" ch\u1ed1ng d\u1ecbch, c\u00e1c c\u1ea5p, c\u00e1c ng\u00e0nh v\u00e0o cu\u1ed9c quy\u1ebft li\u1ec7t, kh\u1ea9n tr\u01b0\u01a1ng th\u00ec \u0111\u00e2u \u0111\u00f3 v\u1eabn c\u00f2n nh\u1eefng c\u00e1 nh\u00e2n c\u00f3 t\u00e2m l\u00fd l\u01a1 l\u00e0, ch\u1ee7 quan, vi ph\u1ea1m quy \u0111\u1ecbnh c\u1ee7a c\u01a1 quan ch\u1ee9c n\u0103ng, th\u1eadm ch\u00ed ch\u1ed1ng \u0111\u1ed1i l\u1ef1c l\u01b0\u1ee3ng l\u00e0m nhi\u1ec7m v\u1ee5. H\u01a1n l\u00fac n\u00e0o h\u1ebft, tinh th\u1ea7n tr\u00e1ch nhi\u1ec7m, s\u1ef1 t\u1ef1 gi\u00e1c c\u1ee7a m\u1ed7i ng\u01b0\u1eddi d\u00e2n ph\u1ea3i \u0111\u1eb7t l\u00ean h\u00e0ng \u0111\u1ea7u, \u0111\u01b0\u1ee3c coi l\u00e0 \u201cl\u00e1 ch\u1eafn th\u00e9p\u201d trong ph\u00f2ng, ch\u1ed1ng d\u1ecbch, g\u00f3p ph\u1ea7n ph\u00f2ng ng\u1eeba v\u00e0 \u0111\u1ea9y l\u00f9i d\u1ecbch b\u1ec7nh.", "Tr\u1ea3i qua 3 \u0111\u1ee3t d\u1ecbch, c\u00e2u chuy\u1ec7n \u00fd th\u1ee9c, tr\u00e1ch nhi\u1ec7m c\u00f4ng d\u00e2n \u0111\u01b0\u1ee3c nh\u1eafc \u0111\u1ebfn nhi\u1ec1u nh\u01b0ng v\u1eabn c\u00f2n kh\u00f4ng \u00edt tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m, nh\u1eefng h\u00e0nh vi thi\u1ebfu \u00fd th\u1ee9c trong \u0111\u1ee3t d\u1ecbch th\u1ee9 4 n\u00e0y.", "\u0110\u1ee3t d\u1ecbch COVID-19 l\u1ea7n th\u1ee9 4 v\u1edbi s\u1ef1 l\u00e2y lan nhanh ch\u00f3ng c\u1ee7a bi\u1ebfn ch\u1ee7ng Delta v\u1eabn \u0111ang di\u1ec5n bi\u1ebfn ph\u1ee9c t\u1ea1p, kh\u00f3 l\u01b0\u1eddng."], "content_summary": "\"\u0110\u1ee3t d\u1ecbch COVID-19 l\u1ea7n th\u1ee9 4 v\u1edbi s\u1ef1 l\u00e2y lan nhanh ch\u00f3ng c\u1ee7a bi\u1ebfn ch\u1ee7ng Delta v\u1eabn \u0111ang di\u1ec5n bi\u1ebfn ph\u1ee9c t\u1ea1p, kh\u00f3 l\u01b0\u1eddng, \u1ea3nh h\u01b0\u1edfng nghi\u00eam tr\u1ecdng \u0111\u1ebfn cu\u1ed9c s\u1ed1ng ng\u01b0\u1eddi d\u00e2n v\u00e0 s\u1ef1 ph\u00e1t tri\u1ec3n kinh t\u1ebf - x\u00e3 h\u1ed9i. Ph\u01b0\u01a1ng th\u1ee9c \u0111\u01b0\u1ee3c nhi\u1ec1u \u0111\u1ed1i t\u01b0\u1ee3ng l\u1ee3i d\u1ee5ng l\u00e0 thu\u00ea ho\u1eb7c \u0111i nh\u1edd c\u00e1c ph\u01b0\u01a1ng ti\u1ec7n \u0111\u01b0\u1ee3c \u01b0u ti\u00ean (lu\u1ed3ng xanh) \u0111\u1ec3 ra, v\u00e0o c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng. \u0110\u1ed3ng th\u1eddi, c\u0169ng \u0111\u01b0a ra nh\u1eefng v\u1ee5 vi\u1ec7c b\u1ecb x\u1eed ph\u1ea1t khi ng\u01b0\u1eddi d\u00e2n kh\u00f4ng ch\u1ea5p h\u00e0nh quy \u0111\u1ecbnh \u0111\u1ec3 t\u0103ng t\u00ednh r\u0103n \u0111e.\"", "total_facebook_viral": 0}, {"url": "https://www.vietnamplus.vn/y-thuc-cua-nguoi-dan-la-chan-thep-trong-phong-chong-dich/733019.vnp", "domain": "vietnamplus.vn", "title": "\u00dd th\u1ee9c c\u1ee7a ng\u01b0\u1eddi d\u00e2n - 'L\u00e1 ch\u1eafn th\u00e9p' trong ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "snippet": "Tr\u1ea3i qua 3 \u0111\u1ee3t d\u1ecbch, c\u00e2u chuy\u1ec7n \u00fd th\u1ee9c, tr\u00e1ch nhi\u1ec7m c\u00f4ng d\u00e2n \u0111\u01b0\u1ee3c nh\u1eafc \u0111\u1ebfn nhi\u1ec1u nh\u01b0ng v\u1eabn c\u00f2n kh\u00f4ng \u00edt tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m, nh\u1eefng h\u00e0nh vi thi\u1ebfu \u00fd th\u1ee9c trong \u0111\u1ee3t d\u1ecbch th\u1ee9 4 n\u00e0y.", "created_time": 1628614800, "id": "vietnamplus.vn_733019", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baotintuc.vn/xa-hoi/y-thuc-trach-nhiem-cong-dan-la-chan-thep-trong-phong-chong-dich-20210811113249823.htm", "domain": "baotintuc.vn", "title": "\u00dd th\u1ee9c, tr\u00e1ch nhi\u1ec7m c\u00f4ng d\u00e2n: 'L\u00e1 ch\u1eafn th\u00e9p' trong ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "snippet": "\u0110\u1ee3t d\u1ecbch COVID-19 l\u1ea7n th\u1ee9 4 v\u1edbi s\u1ef1 l\u00e2y lan nhanh ch\u00f3ng c\u1ee7a bi\u1ebfn ch\u1ee7ng Delta v\u1eabn \u0111ang di\u1ec5n bi\u1ebfn ph\u1ee9c t\u1ea1p, kh\u00f3 l\u01b0\u1eddng.", "created_time": 1628656800, "id": "baotintuc.vn_20210811113249823", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.phapluatplus.vn/chinh-tri-xa-hoi/ha-noi-quyet-liet-khoanh-vung-khong-de-dich-lan-rong-d163090.html", "domain": "phapluatplus.vn", "title": "H\u00e0 N\u1ed9i quy\u1ebft li\u1ec7t khoanh v\u00f9ng kh\u00f4ng \u0111\u1ec3 d\u1ecbch lan r\u1ed9ng", "snippet": "T\u1eadn d\u1ee5ng \u201cth\u1eddi gian v\u00e0ng\u201d gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i, c\u00e1c qu\u1eadn, huy\u1ec7n tr\u00ean \u0111\u1ecba b\u00e0n TP H\u00e0 N\u1ed9i \u0111ang n\u1ed7 l\u1ef1c ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh hi\u1ec7u qu\u1ea3 nh\u1ea5t, s\u1edbm \u0111\u01b0a TP tr\u1edf v\u1ec1 tr\u1ea1ng th\u00e1i b\u00ecnh th\u01b0\u1eddng m\u1edbi.", "created_time": 1628642940, "id": "phapluatplus.vn_d163090", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kinhtedothi.vn/chu-tich-uy-ban-mttq-tp-nguyen-lan-huong-thi-xa-son-tay-can-ky-luong-trong-trien-khai-cac-bien-phap-phong-chong-dich-covid-19-430677.html", "domain": "kinhtedothi.vn", "title": "L\u00e3nh \u0111\u1ea1o TP ki\u1ec3m tra t\u1ea1i th\u1ecb x\u00e3 S\u01a1n T\u00e2y: C\u1ea7n c\u00f3 k\u1ebf ho\u1ea1ch b\u00e0i b\u1ea3n, k\u1ef9 l\u01b0\u1ee1ng duy tr\u00ec c\u00e1c bi\u1ec7n ph\u00e1p ph\u00f2ng ch\u1ed1ng d\u1ecbch Covid-19", "snippet": "Kinhtedothi-Ch\u1ee7 t\u1ecbch \u1ee6y ban MTTQ Vi\u1ec7t Nam TP H\u00e0 N\u1ed9i Nguy\u1ec5n Lan H\u01b0\u01a1ng l\u01b0u \u00fd, v\u1edbi ph\u01b0\u01a1ng \u00e1n \u201c3 t\u1ea1i ch\u1ed7\u201d, th\u1ecb x\u00e3 S\u01a1n T\u00e2y c\u1ea7n ch\u1ec9 \u0111\u1ea1o th\u1ef1c hi\u1ec7n ch\u1eb7t ch\u1ebd, ki\u1ec3m tra, gi\u00e1m s\u00e1t th\u01b0\u1eddng xuy\u00ean tr\u00ean \u0111\u1ecba b\u00e0n. Ri\u00eang ph\u01b0\u01a1ng \u00e1n s\u1ea3n xu\u1ea5t \u201c1 cung \u0111\u01b0\u1eddng 2 \u0111i\u1ec3m \u0111\u1ebfn\u201d c\u1ea7n \u0111\u01b0\u1ee3c nghi\u00ean c\u1ee9u k\u1ef9 h\u01a1n, quy\u1ebft t\u00e2m kh\u00f4ng \u0111\u1ec3 x\u1ea3y ra nh\u1eefng sai s\u00f3t trong ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19.", "created_time": 1628596860, "id": "kinhtedothi.vn_430677", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baophapluat.vn/ha-noi-quyet-liet-khoanh-vung-khong-de-dich-lan-rong-post407129.html", "domain": "baophapluat.vn", "title": "H\u00e0 N\u1ed9i quy\u1ebft li\u1ec7t khoanh v\u00f9ng kh\u00f4ng \u0111\u1ec3 d\u1ecbch lan r\u1ed9ng", "snippet": "(PLVN) -\u00a0T\u1eadn d\u1ee5ng \u201cth\u1eddi gian v\u00e0ng\u201d gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i, c\u00e1c qu\u1eadn, huy\u1ec7n tr\u00ean \u0111\u1ecba b\u00e0n TP H\u00e0 N\u1ed9i \u0111ang n\u1ed7 l\u1ef1c ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh hi\u1ec7u qu\u1ea3 nh\u1ea5t, s\u1edbm \u0111\u01b0a TP tr\u1edf v\u1ec1 tr\u1ea1ng th\u00e1i b\u00ecnh th\u01b0\u1eddng m\u1edbi.", "created_time": 1628636945, "id": "baophapluat.vn_407129", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://tienphong.vn/kiem-soat-dich-o-tphcm-truoc-15-9-post1364651.tpo", "domain": "tienphong.vn", "title": "Ki\u1ec3m so\u00e1t d\u1ecbch \u1edf TPHCM tr\u01b0\u1edbc 15/9", "snippet": "TP - Ngh\u1ecb quy\u1ebft 86 v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ph\u00f2ng, ch\u1ed1ng d\u1ecbch b\u1ec7nh COVID-19 v\u1eeba \u0111\u01b0\u1ee3c Ch\u00ednh ph\u1ee7 ban h\u00e0nh y\u00eau c\u1ea7u kh\u00f4ng \u0111\u1ec3 x\u1ea3y ra t\u00ecnh tr\u1ea1ng gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i h\u00ecnh th\u1ee9c ho\u1eb7c \u201cch\u1eb7t ngo\u00e0i, l\u1ecfng trong\u201d. Ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh \u1edf TPHCM tr\u01b0\u1edbc ng\u00e0y 15/9; c\u00e1c t\u1ec9nh B\u00ecnh D\u01b0\u01a1ng, Long An, \u00d0\u1ed3ng Nai v\u00e0 nh\u1eefng t\u1ec9nh kh\u00e1c v\u00e0o cu\u1ed1i th\u00e1ng 8 v\u00e0 \u0111\u1ea7u th\u00e1ng 9.", "created_time": 1628636639, "id": "tienphong.vn_1364651", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://dangcongsan.vn/y-te/tang-cuong-kiem-tra-kiem-soat-nang-cao-hieu-qua-thuc-hien-gian-cach-xa-hoi-587775.html", "domain": "dangcongsan.vn", "title": "T\u0103ng c\u01b0\u1eddng ki\u1ec3m tra, ki\u1ec3m so\u00e1t, n\u00e2ng cao hi\u1ec7u qu\u1ea3 th\u1ef1c hi\u1ec7n gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i", "snippet": "(\u0110CSVN) - Ph\u00f3 B\u00ed th\u01b0 Th\u01b0\u1eddng tr\u1ef1c Th\u00e0nh \u1ee7y H\u00e0 N\u1ed9i y\u00eau c\u1ea7u huy\u1ec7n Qu\u1ed1c Oai t\u0103ng c\u01b0\u1eddng ki\u1ec3m tra, ki\u1ec3m so\u00e1t, si\u1ebft ch\u1eb7t ho\u1ea1t \u0111\u1ed9ng c\u1ee7a c\u00e1c ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh t\u1ea1i c\u00e1c x\u00e3, th\u1ecb tr\u1ea5n. Trong \u0111\u00f3, huy \u0111\u1ed9ng nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n c\u00f9ng tham gia \u1ee9ng tr\u1ef1c \u0111\u1ec3 gi\u1ea3m t\u1ea3i cho c\u00e1c l\u1ef1c l\u01b0\u1ee3ng chuy\u00ean tr\u00e1ch. Qua \u0111\u00f3, gi\u00fap m\u1ed7i x\u00e3, th\u00f4n, khu ph\u1ed1 tr\u1edf th\u00e0nh nh\u1eefng \u201cph\u00e1o \u0111\u00e0i\u201d...", "created_time": 1628604900, "id": "dangcongsan.vn_587775", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghieptiepthi.vn/thu-tuong-khong-de-nguoi-dan-tu-roi-khoi-dia-ban-co-dich-phan-dau-kiem-soat-dich-covid-19-o-tphcm-truoc-15-9-161211008141509959.htm", "domain": "doanhnghieptiepthi.vn", "title": "Th\u1ee7 t\u01b0\u1edbng: Kh\u00f4ng \u0111\u1ec3 ng\u01b0\u1eddi d\u00e2n t\u1ef1 r\u1eddi kh\u1ecfi \u0111\u1ecba b\u00e0n c\u00f3 d\u1ecbch, ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t d\u1ecbch Covid-19 \u1edf TP.HCM tr\u01b0\u1edbc 15/9", "snippet": "Ch\u00ednh ph\u1ee7 n\u00eau r\u00f5 m\u1ee5c ti\u00eau TP.HCM ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 15/9; B\u00ecnh D\u01b0\u01a1ng, Long An, \u0110\u1ed3ng Nai tr\u01b0\u1edbc 1/9; c\u00f2n c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c ki\u1ec3m so\u00e1t d\u1ecbch tr\u01b0\u1edbc 25/8.", "created_time": 1628578800, "id": "doanhnghieptiepthi.vn_161211008141509959", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kinhtedothi.vn/pho-bi-thu-thuong-truc-thanh-uy-nguyen-thi-tuyen-xay-dung-moi-xa-thon-khu-pho-tro-thanh-nhung-phao-dai-chong-dich-430679.html", "domain": "kinhtedothi.vn", "title": "Ph\u00f3 B\u00ed th\u01b0 Th\u01b0\u1eddng tr\u1ef1c Th\u00e0nh \u1ee7y Nguy\u1ec5n Th\u1ecb Tuy\u1ebfn: X\u00e2y d\u1ef1ng m\u1ed7i x\u00e3, th\u00f4n, khu ph\u1ed1 tr\u1edf th\u00e0nh nh\u1eefng \u201cph\u00e1o \u0111\u00e0i\u201d ch\u1ed1ng d\u1ecbch", "snippet": "Kinhtedothi - Ph\u00f3 B\u00ed th\u01b0 Th\u01b0\u1eddng tr\u1ef1c Th\u00e0nh \u1ee7y c\u0169ng y\u00eau c\u1ea7u, huy\u1ec7n Qu\u1ed1c Oai si\u1ebft ch\u1eb7t ho\u1ea1t \u0111\u1ed9ng c\u1ee7a c\u00e1c ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh t\u1ea1i c\u00e1c x\u00e3, th\u1ecb tr\u1ea5n. Trong \u0111\u00f3, huy \u0111\u1ed9ng Nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n c\u00f9ng tham gia \u1ee9ng tr\u1ef1c \u0111\u1ec3 gi\u1ea3m t\u1ea3i cho c\u00e1c l\u1ef1c l\u01b0\u1ee3ng chuy\u00ean tr\u00e1ch. Qua \u0111\u00f3, gi\u00fap m\u1ed7i x\u00e3, th\u00f4n, khu ph\u1ed1 tr\u1edf th\u00e0nh nh\u1eefng \u201cph\u00e1o \u0111\u00e0i\u201d \u0111\u1ec3 ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh...", "created_time": 1628597100, "id": "kinhtedothi.vn_430679", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baotintuc.vn/thoi-su/tong-hop-covid19-ngay-108-chinh-phu-ban-hanh-nghi-quyet-ve-cac-giai-phap-cap-bach-phong-chong-dich-20210810194220063.htm", "domain": "baotintuc.vn", "title": "T\u1ed5ng h\u1ee3p COVID-19 ng\u00e0y 10/8: Ch\u00ednh ph\u1ee7 ban h\u00e0nh Ngh\u1ecb quy\u1ebft v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ph\u00f2ng ch\u1ed1ng d\u1ecbch", "snippet": "Nh\u1eefng th\u00f4ng tin th\u1eddi s\u1ef1 v\u1ec1 d\u1ecbch COVID-19 ng\u00e0y 10/8 thu h\u00fat s\u1ef1 quan t\u00e2m c\u1ee7a d\u01b0 lu\u1eadn g\u1ed3m: Ch\u00ednh ph\u1ee7 ban h\u00e0nh Ngh\u1ecb quy\u1ebft v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ph\u00f2ng ch\u1ed1ng d\u1ecbch.", "created_time": 1628605620, "id": "baotintuc.vn_20210810194220063", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.vietnamplus.vn/kip-thoi-phat-hien-nhung-van-de-chua-phu-hop-trong-phong-chong-dich/733167.vnp", "domain": "vietnamplus.vn", "title": "K\u1ecbp th\u1eddi ph\u00e1t hi\u1ec7n nh\u1eefng v\u1ea5n \u0111\u1ec1 ch\u01b0a ph\u00f9 h\u1ee3p trong ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "snippet": "Theo Th\u1ee7 t\u01b0\u1edbng, trong l\u00fac n\u00e0y, ch\u00fang ta t\u1eadp trung \u01b0u ti\u00ean cho ch\u1ed1ng d\u1ecbch, v\u00ec ch\u1ed1ng d\u1ecbch th\u00e0nh c\u00f4ng, s\u1ebd th\u00fac \u0111\u1ea9y ph\u00e1t tri\u1ec3n kinh t\u1ebf-x\u00e3 h\u1ed9i, ph\u1ee5c h\u1ed3i kinh t\u1ebf-x\u00e3 h\u1ed9i thu\u1eadn l\u1ee3i h\u01a1n.", "created_time": 1628614800, "id": "vietnamplus.vn_733167", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.daibieunhandan.vn/khan-truong-boc-tac-f0-ra-khoi-cong-dong-iqt70zxnfk-61643", "domain": "daibieunhandan.vn", "title": "Kh\u1ea9n tr\u01b0\u01a1ng b\u00f3c t\u00e1c F0 ra kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng", "snippet": "Qua ki\u1ec3m tra c\u00f4ng t\u00e1c ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n huy\u1ec7n Ba V\u00ec, Ph\u00f3 Ch\u1ee7 t\u1ecbch UBND TP H\u00e0 N\u1ed9i D\u01b0\u01a1ng \u0110\u1ee9c Tu\u1ea5n \u0111\u1ec1 ngh\u1ecb huy\u1ec7n x\u00e1c \u0111\u1ecbnh r\u00f5 c\u00e1c v\u00f9ng an to\u00e0n, nguy c\u01a1 v\u00e0 nguy c\u01a1 r\u1ea5t cao \u0111\u1ec3 x\u00e2y d\u1ef1ng c\u00e1c ph\u01b0\u01a1ng \u00e1n d\u1eadp d\u1ecbch hi\u1ec7u qu\u1ea3 v\u00e0 an to\u00e0n.", "created_time": 1628662620, "id": "b0f11ca6818775e8473aae504e523cddb078f370", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://tienphong.vn/giam-doc-cong-an-ha-noi-yeu-cau-kiem-soat-chat-tu-khu-dan-cu-nham-phong-chong-dich-post1364543.tpo", "domain": "tienphong.vn", "title": "Gi\u00e1m \u0111\u1ed1c C\u00f4ng an H\u00e0 N\u1ed9i: Y\u00eau c\u1ea7u ki\u1ec3m so\u00e1t ch\u1eb7t t\u1eeb khu d\u00e2n c\u01b0 nh\u1eb1m ph\u00f2ng ch\u1ed1ng d\u1ecbch", "snippet": "TPO - Trung t\u01b0\u1edbng Nguy\u1ec5n H\u1ea3i Trung - Gi\u00e1m \u0111\u1ed1c C\u00f4ng an TP H\u00e0 N\u1ed9i, y\u00eau c\u1ea7u c\u00f4ng an c\u00e1c \u0111\u01a1n v\u1ecb ph\u1ea3i ki\u1ec3m so\u00e1t ngay t\u1eeb g\u1ed1c l\u00e0 c\u00e1c khu d\u00e2n c\u01b0;\u00a0b\u1ed1 tr\u00ed \"nhi\u1ec1u t\u1ea7ng, nhi\u1ec1u\u00a0l\u1edbp\" \u0111\u1ea3m b\u1ea3o m\u1ecdi ng\u01b0\u1eddi d\u00e2n ra, v\u00e0o ph\u1ea3i \u0111\u01b0\u1ee3c ki\u1ec3m so\u00e1t nh\u1eb1m ph\u00f2ng, ch\u1ed1ng d\u1ecbch\u00a0COVID-19.", "created_time": 1628596461, "id": "tienphong.vn_1364543", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://laodongthudo.vn/huy-dong-nhan-dan-ung-truc-giup-xa-thon-khu-pho-thanh-phao-dai-kiem-soat-dich-benh-127971.html", "domain": "laodongthudo.vn", "title": "Huy \u0111\u1ed9ng nh\u00e2n d\u00e2n \u1ee9ng tr\u1ef1c gi\u00fap x\u00e3, th\u00f4n, khu ph\u1ed1 th\u00e0nh \"ph\u00e1o \u0111\u00e0i\" ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh", "snippet": "Tr\u01b0\u1edbc di\u1ec5n bi\u1ebfn ph\u1ee9c t\u1ea1p c\u1ee7a d\u1ecbch Covid-19, Ph\u00f3 B\u00ed th\u01b0 Th\u01b0\u1eddng tr\u1ef1c Th\u00e0nh \u1ee7y H\u00e0 N\u1ed9i Nguy\u1ec5n Th\u1ecb Tuy\u1ebfn ch\u1ec9 \u0111\u1ea1o, huy\u1ec7n Qu\u1ed1c Oai si\u1ebft ch\u1eb7t ho\u1ea1t \u0111\u1ed9ng c\u1ee7a c\u00e1c ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh t\u1ea1i c\u00e1c x\u00e3, th\u1ecb tr\u1ea5n; 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V\u1edbi h\u00e0ng ng\u00e0n ca b\u1ec7nh ghi nh\u1eadn m\u1ed7i ng\u00e0y, h\u1ec7 th\u1ed1ng y t\u1ebf c\u1ee7a ch\u00fang ta \u0111ang d\u1ed1c to\u00e0n l\u1ef1c \u0111\u1ec3 ph\u1ee5c v\u1ee5 c\u00f4ng t\u00e1c: x\u00e9t nghi\u1ec7m, c\u00e1ch ly, ch\u1eefa tr\u1ecb; s\u1ed1 l\u01b0\u1ee3ng b\u1ec7nh nh\u00e2n v\u00e0 c\u00e1c tr\u01b0\u1eddng h\u1ee3p c\u00e1ch ly t\u1ea1i c\u00e1c khu v\u1ef1c phong t\u1ecfa, khu c\u00e1ch ly ng\u00e0y c\u00e0ng t\u0103ng. 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Tuy nhi\u00ean, tr\u00ean th\u1ef1c t\u1ebf, v\u1eabn c\u00f2n kh\u00f4ng \u00edt s\u1ef1 ch\u1ee7 quan, l\u01a1i l\u00e0, m\u00e0 nhi\u1ec1u khi v\u00f4 t\u00ecnh xu\u1ea5t hi\u1ec7n t\u1eeb ch\u00ednh trong c\u00e1ch l\u00e0m c\u1ee7a ng\u01b0\u1eddi tham gia v\u00e0o c\u00f4ng t\u00e1c ph\u00f2ng, ch\u1ed1ng d\u1ecbch \u1edf c\u01a1 s\u1edf.", "created_time": 1628645760, "id": "kinhtedothi.vn_430695", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://laodongthudo.vn/muc-tieu-toi-thuong-la-suc-khoe-nguoi-dan-127960.html", "domain": "laodongthudo.vn", "title": "M\u1ee5c ti\u00eau t\u1ed1i th\u01b0\u1ee3ng l\u00e0 s\u1ee9c kh\u1ecfe ng\u01b0\u1eddi d\u00e2n", "snippet": "D\u1ecbch Covid-19 \u0111ang di\u1ec5n bi\u1ebfn r\u1ea5t ph\u1ee9c t\u1ea1p, trong b\u1ed1i c\u1ea3nh th\u1ef1c hi\u1ec7n gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i, H\u00e0 N\u1ed9i lu\u00f4n qu\u00e1n tri\u1ec7t tinh th\u1ea7n ng\u0103n ch\u1eb7n d\u1ecbch b\u00f9ng ph\u00e1t r\u1ed9ng, n\u1ed7 l\u1ef1c h\u1ebft s\u1ee9c b\u1ea3o v\u1ec7 an to\u00e0n s\u1ee9c kh\u1ecfe, t\u00ednh m\u1ea1ng nh\u00e2n d\u00e2n.", "created_time": 1628595720, "id": "laodongthudo.vn_127960", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://dantri.com.vn/xa-hoi/chinh-phu-tphcm-can-kiem-soat-dich-truoc-159-ha-noi-truoc-258-20210810140536496.htm", "domain": "dantri.com.vn", "title": "Ch\u00ednh ph\u1ee7: TPHCM c\u1ea7n ki\u1ec3m so\u00e1t d\u1ecbch tr\u01b0\u1edbc 15/9, H\u00e0 N\u1ed9i tr\u01b0\u1edbc 25/8", "snippet": "(D\u00e2n tr\u00ed) - V\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ch\u1ed1ng d\u1ecbch, Ch\u00ednh ph\u1ee7 \u0111\u1eb7c bi\u1ec7t l\u01b0u \u00fd c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng \u0111ang ph\u1ea3i \u00e1p d\u1ee5ng Ch\u1ec9 th\u1ecb 15, 16. TPHCM c\u1ea7n ki\u1ec3m so\u00e1t d\u1ecbch tr\u01b0\u1edbc 15/9, c\u00e1c t\u1ec9nh th\u00e0nh kh\u00e1c, trong \u0111\u00f3 c\u00f3 H\u00e0 N\u1ed9i tr\u01b0\u1edbc 25/8.", "created_time": 1628579342, "id": "dantri.com.vn_20210810140536496", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghieptiepthi.vn/chinh-phu-giao-ha-noi-phan-dau-kiem-soat-dich-benh-truoc-ngay-25-8-161211008164820631.htm", "domain": "doanhnghieptiepthi.vn", "title": "Ch\u00ednh ph\u1ee7 giao H\u00e0 N\u1ed9i ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25/8", "snippet": "Ch\u00ednh ph\u1ee7 giao TP.HCM ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 15/9, c\u00e1c t\u1ec9nh B\u00ecnh D\u01b0\u01a1ng, Long An, \u0110\u1ed3ng Nai tr\u01b0\u1edbc ng\u00e0y 1/9. H\u00e0 N\u1ed9i v\u00e0 c\u00e1c t\u1ec9nh, th\u00e0nh ph\u1ed1 kh\u00e1c tr\u01b0\u1edbc ng\u00e0y 25/8.", "created_time": 1628587740, "id": "doanhnghieptiepthi.vn_161211008164820631", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://daidoanket.vn/chinh-phu-yeu-cau-tp-hcm-kiem-soat-dich-truoc-159-ha-noi-truoc-258-5661324.html", "domain": "daidoanket.vn", "title": "Ch\u00ednh ph\u1ee7 y\u00eau c\u1ea7u: TP HCM ki\u1ec3m so\u00e1t d\u1ecbch tr\u01b0\u1edbc 15/9, H\u00e0 N\u1ed9i tr\u01b0\u1edbc 25/8", "snippet": "Ch\u00ednh ph\u1ee7 y\u00eau c\u1ea7u: Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 15/9. C\u00e1c t\u1ec9nh: B\u00ecnh D\u01b0\u01a1ng, Long An, \u0110\u1ed3ng Nai ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 1/9. 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Song, v\u1eabn c\u00f3 nh\u1eefng \u0111\u1ed1i t\u01b0\u1ee3ng c\u1ed1 t\u00ecnh vi ph\u1ea1m quy \u0111\u1ecbnh, th\u1eadm ch\u00ed ngang nhi\u00ean t\u1ea5n c\u00f4ng l\u1ef1c l\u01b0\u1ee3ng ph\u00f2ng, ch\u1ed1ng d\u1ecbch. 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HCM ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t d\u1ecbch tr\u01b0\u1edbc 15/9, H\u00e0 N\u1ed9i tr\u01b0\u1edbc 25/8", "created_time": 1628581440, "id": "b728ab4a1097d0334ffb12526c5eba869c0f5965", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baophapluat.vn/media/gia-lam-ha-noi-tang-cuong-kiem-soat-siet-chat-nguoi-va-phuong-tien-ra-vao-thanh-pho-tai-chot-kiem-dich-so-6-de-bat-trang-post5642.html", "domain": "baophapluat.vn", "title": "Gia L\u00e2m - H\u00e0 N\u1ed9i: T\u0103ng c\u01b0\u1eddng ki\u1ec3m so\u00e1t, si\u1ebft ch\u1eb7t ng\u01b0\u1eddi v\u00e0 ph\u01b0\u01a1ng ti\u1ec7n ra v\u00e0o th\u00e0nh ph\u1ed1 t\u1ea1i ch\u1ed1t ki\u1ec3m d\u1ecbch s\u1ed1 6 \u0110\u00ea B\u00e1t Tr\u00e0ng", "snippet": "(PLM) - Tr\u01b0\u1edbc nh\u1eefng di\u1ec5n bi\u1ebfn m\u1edbi c\u1ee7a d\u1ecbch b\u1ec7nh Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n th\u1ee7 \u0111\u00f4, ngay sau khi th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i c\u00f3 v\u0103n b\u1ea3n h\u1ecfa t\u1ed1c s\u1ed1 2562\u00a0y\u00eau c\u1ea7u si\u1ebft ch\u1eb7t vi\u1ec7c c\u1ea5p v\u00e0 s\u1eed d\u1ee5ng gi\u1ea5y \u0111i \u0111\u01b0\u1eddng trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i th\u00ec c\u00e1c ch\u1ed1t ch\u1eb7n t\u1ea1i c\u1eeda ng\u00f5 th\u00e0nh ph\u1ed1\u00a0\u0111\u1ec1u t\u0103ng c\u01b0\u1eddng vi\u1ec7c ki\u1ec3m tra, ki\u1ec3m so\u00e1t ng\u01b0\u1eddi v\u00e0 ph\u01b0\u01a1ng ti\u1ec7n ra v\u00e0o th\u00e0nh ph\u1ed1, \u0111\u1ea3m b\u1ea3o nghi\u00eam ng\u1eb7t c\u00e1c quy \u0111\u1ecbnh ph\u00f2ng ch\u1ed1ng d\u1ecbch b\u1ec7nh. Ph\u00f3ng vi\u00ean B\u00e1o Ph\u00e1p Lu\u1eadt Vi\u1ec7t Nam \u0111\u00e3 c\u00f3 m\u1eb7t t\u1ea1i\u00a0ch\u1ed1t ki\u1ec3m d\u1ecbch s\u1ed1 6 \u0110\u00ea B\u00e1t Tr\u00e0ng \u0111\u1ec3 ghi nh\u1eadn t\u00ecnh h\u00ecnh.", "created_time": 1628615989, "id": "baophapluat.vn_5642", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://thoibaotaichinhvietnam.vn/pages/xa-hoi/2021-08-10/infographic-ha-noi-phai-phan-dau-kiem-soat-duoc-dich-benh-truoc-ngay-25-8-109034.aspx", "domain": "thoibaotaichinhvietnam.vn", "title": "Infographic: H\u00e0 N\u1ed9i ph\u1ea3i ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25/8", "snippet": "Ch\u00ednh ph\u1ee7 \u0111\u00e3 ban h\u00e0nh Ngh\u1ecb quy\u1ebft v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19, trong \u0111\u00f3 y\u00eau c\u1ea7u: Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 15/9/2021.", "created_time": 1628602680, "id": "thoibaotaichinhvietnam.vn_109034", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://hanoimoi.com.vn/infographic/xa-hoi/1008495/nghi-quyet-cua-chinh-phu-ha-noi-phai-phan-dau-kiem-soat-duoc-dich-benh-truoc-ngay-25-8", "domain": "hanoimoi.com.vn", "title": "Ngh\u1ecb quy\u1ebft c\u1ee7a Ch\u00ednh ph\u1ee7: H\u00e0 N\u1ed9i ph\u1ea3i ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25-8", "snippet": "(HNMO) - Ch\u00ednh ph\u1ee7 \u0111\u00e3 ban h\u00e0nh Ngh\u1ecb quy\u1ebft v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19, trong \u0111\u00f3 y\u00eau c\u1ea7u: Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 15-9-2021;\u00a0c\u00e1c t\u1ec9nh\u00a0B\u00ecnh D\u01b0\u01a1ng, Long An, \u0110\u1ed3ng Nai ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 1-9-2021;\u00a0c\u00e1c t\u1ec9nh, th\u00e0nh ph\u1ed1 kh\u00e1c (trong \u0111\u00f3 c\u00f3 H\u00e0 N\u1ed9i) ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25-8-2021.", "created_time": 1628586180, "id": "hanoimoi.com.vn_1008495", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://dangcongsan.vn/multimedia/infographic/nghi-quyet-cua-chinh-phu-ha-noi-phai-phan-dau-kiem-soat-duoc-dich-benh-truoc-ngay-25-8-587851.html", "domain": "dangcongsan.vn", "title": "Ngh\u1ecb quy\u1ebft c\u1ee7a Ch\u00ednh ph\u1ee7: H\u00e0 N\u1ed9i ph\u1ea3i ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25 8", "snippet": "Ch\u00ednh ph\u1ee7 \u0111\u00e3 ban h\u00e0nh Ngh\u1ecb quy\u1ebft v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p c\u1ea5p b\u00e1ch ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19, trong \u0111\u00f3 y\u00eau c\u1ea7u: Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 15 9 2021; c\u00e1c t\u1ec9nh B\u00ecnh D\u01b0\u01a1ng, Long An, \u0110\u1ed3ng Nai ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 1 9 2021; c\u00e1c t\u1ec9nh, th\u00e0nh ph\u1ed1 kh\u00e1c (trong \u0111\u00f3 c\u00f3 H\u00e0 N\u1ed9i) ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c...", "created_time": 1628654640, "id": "dangcongsan.vn_587851", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "4": [{"url": "https://doanhnghiepvn.vn/chuyen-doi-so/xa-hoi-so/ha-noi-bac-bo-tin-don-co-5-000-f1-lien-quan-ca-mac-covid-19-tai-quan-dong-da/20210810095021605", "domain": "doanhnghiepvn.vn", "title": "H\u00e0 N\u1ed9i b\u00e1c b\u1ecf tin \u0111\u1ed3n c\u00f3 5.000 F1 li\u00ean quan ca m\u1eafc COVID-19 t\u1ea1i qu\u1eadn \u0110\u1ed1ng \u0110a", "snippet": "DNVN - Theo \u0111\u1ea1i di\u1ec7n UBND qu\u1eadn \u0110\u1ed1ng \u0110a, th\u00f4ng tin 5.000 c\u00e1c ca F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh v\u1edbi virus SASR-CoV2 lan truy\u1ec1n tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i l\u00e0 b\u1ecba \u0111\u1eb7t.", "created_time": 1628607420, "id": "doanhnghiepvn.vn_20210810095021605", "score": 0.0, "title_summarize": ["DNVN - Theo \u0111\u1ea1i di\u1ec7n UBND qu\u1eadn \u0110\u1ed1ng \u0110a, th\u00f4ng tin 5.000 c\u00e1c ca F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh v\u1edbi virus SASR-CoV2 lan truy\u1ec1n tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i l\u00e0 b\u1ecba \u0111\u1eb7t.", "Tr\u01b0\u1edbc th\u00f4ng tin lan truy\u1ec1n tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i v\u1ec1 vi\u1ec7c xu\u1ea5t hi\u1ec7n 5.000 ca F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n, UBND qu\u1eadn \u0110\u1ed1ng \u0110a kh\u1eb3ng \u0111\u1ecbnh, \u0111\u00e2y l\u00e0 th\u00f4ng tin sai s\u1ef1 th\u1eadt.", "UBND qu\u1eadn \u0110\u1ed1ng \u0110a cho bi\u1ebft, th\u00f4ng tin lan truy\u1ec1n tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i v\u1ec1 vi\u1ec7c c\u00f3 5.000 tr\u01b0\u1eddng h\u1ee3p F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n l\u00e0 sai s\u1ef1 th\u1eadt."], "content_summary": "\"Ng\u00e0y 9/8, tr\u00ean c\u00e1c nh\u00f3m m\u1ea1ng x\u00e3 h\u1ed9i lan truy\u1ec1n th\u00f4ng tin t\u1ea1i Trung t\u00e2m Y t\u1ebf qu\u1eadn \u0110\u1ed1ng \u0110a, H\u00e0 N\u1ed9i ph\u00e1t hi\u1ec7n c\u00e1c ca m\u1eafc COVID-19. \u0110\u1eb7c bi\u1ec7t, nh\u1eefng ca n\u00e0y \u0111\u00e3 tham gia ti\u00eam ch\u1ee7ng cho ng\u01b0\u1eddi d\u00e2n n\u00ean c\u00f3 nguy c\u01a1 l\u00e2y lan d\u1ecbch r\u1ea5t l\u1edbn trong c\u1ed9ng \u0111\u1ed3ng v\u1edbi s\u1ed1 F1 l\u00ean t\u1edbi 5.000 ng\u01b0\u1eddi. Theo th\u00f4ng tin t\u1eeb S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i, t\u00ednh t\u1eeb 12h \u0111\u1ebfn 18h 10/8, t\u1ea1i H\u00e0 N\u1ed9i ghi nh\u1eadn th\u00eam 6 ca m\u1eafc m\u1edbi COVID-19, g\u1ed3m 3 t\u1ea1i khu c\u00e1ch ly v\u00e0 3 t\u1ea1i c\u1ed9ng \u0111\u1ed3ng, n\u00e2ng t\u1ed5ng s\u1ed1 m\u1eafc trong ng\u00e0y l\u00ean 62 tr\u01b0\u1eddng h\u1ee3p. 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h\u1ed9i vi\u1ec7c xu\u1ea5t hi\u1ec7n 5.000 ca F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh COVID-19 tr\u00ean \u0111\u1ecba b\u00e0n H\u00e0 N\u1ed9i l\u00e0 sai s\u1ef1 th\u1eadt.", "created_time": 1628661000, "id": "baodansinh.vn_20210811080044578", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://daidoanket.vn/ha-noi-5000-f1-lien-quan-1-ca-duong-tinh-tai-quan-dong-da-la-thong-tin-sai-su-that-5661356.html", "domain": "daidoanket.vn", "title": "H\u00e0 N\u1ed9i: 5.000 F1 li\u00ean quan 1 ca d\u01b0\u01a1ng t\u00ednh t\u1ea1i Qu\u1eadn \u0110\u1ed1ng \u0110a l\u00e0 th\u00f4ng tin sai s\u1ef1 th\u1eadt", "snippet": "Tr\u01b0\u1edbc th\u00f4ng tin lan truy\u1ec1n tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i v\u1ec1 vi\u1ec7c xu\u1ea5t hi\u1ec7n 5.000 ca F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh SARS-CoV-2 tr\u00ean \u0111\u1ecba b\u00e0n, UBND qu\u1eadn \u0110\u1ed1ng \u0110a, H\u00e0 N\u1ed9i cho bi\u1ebft, \u0111\u00e2y l\u00e0 th\u00f4ng tin sai s\u1ef1 th\u1eadt.", "created_time": 1628598540, "id": "daidoanket.vn_5661356", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://nhandan.vn/factcheck/thong-tin-5-000-f1-lien-quan-den-ca-duong-tinh-tai-quan-dong-da-la-sai-su-that-659239/", "domain": "nhandan.com.vn", "title": "Th\u00f4ng tin 5.000 F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh t\u1ea1i qu\u1eadn \u0110\u1ed1ng \u0110a l\u00e0 sai s\u1ef1 th\u1eadt", "snippet": "Tr\u01b0\u1edbc th\u00f4ng tin lan truy\u1ec1n tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i v\u1ec1 vi\u1ec7c xu\u1ea5t hi\u1ec7n 5.000 ca F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n, chi\u1ec1u 10/8, \u0111\u1ea1i di\u1ec7n UBND qu\u1eadn \u0110\u1ed1ng \u0110a (H\u00e0 N\u1ed9i) cho bi\u1ebft, \u0111\u00e2y l\u00e0 th\u00f4ng tin sai s\u1ef1 th\u1eadt.", "created_time": 1628600520, "id": 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"title": "Qu\u1eadn \u0110\u1ed1ng \u0110a: 5.000 F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh Covid-19 l\u00e0 th\u00f4ng tin sai s\u1ef1 th\u1eadt", "snippet": "Kinhtedothi - \u0110\u1ea1i di\u1ec7n UBND qu\u1eadn \u0110\u1ed1ng \u0110a kh\u1eb3ng \u0111\u1ecbnh th\u00f4ng tin tr\u00ean ho\u00e0n to\u00e0n sai s\u1ef1 th\u1eadt; \u0111\u1ec1 ngh\u1ecb ng\u01b0\u1eddi d\u00e2n n\u00ean c\u1ea3nh gi\u00e1c, n\u1eafm b\u1eaft th\u00f4ng tin ch\u00ednh x\u00e1c t\u1eeb c\u00e1c c\u01a1 quan ch\u1ee9c n\u0103ng; ph\u1ed1i h\u1ee3p ph\u1ea3n \u00e1nh cho c\u01a1 quan ch\u1ee9c n\u0103ng c\u00e1c th\u00f4ng tin sai s\u1ef1 th\u1eadt.", "created_time": 1628597460, "id": "kinhtedothi.vn_430680", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://dangcongsan.vn/y-te/ha-noi-thong-tin-5000-f1-lien-quan-den-ca-duong-tinh-tai-dong-da-la-sai-su-that-587776.html", "domain": "dangcongsan.vn", "title": "H\u00e0 N\u1ed9i: Th\u00f4ng tin 5.000 F1 li\u00ean quan \u0111\u1ebfn ca d\u01b0\u01a1ng t\u00ednh t\u1ea1i \u0110\u1ed1ng \u0110a l\u00e0 sai s\u1ef1 th\u1eadt", "snippet": "(\u0110CSVN) - \u0110\u1ea1i di\u1ec7n UBND qu\u1eadn \u0110\u1ed1ng \u0110a kh\u1eb3ng \u0111\u1ecbnh th\u00f4ng tin tr\u00ean ho\u00e0n to\u00e0n sai s\u1ef1 th\u1eadt; \u0111\u1ec1 ngh\u1ecb ng\u01b0\u1eddi d\u00e2n n\u00ean c\u1ea3nh gi\u00e1c, n\u1eafm b\u1eaft th\u00f4ng tin ch\u00ednh x\u00e1c t\u1eeb c\u00e1c c\u01a1 quan ch\u1ee9c n\u0103ng; ph\u1ed1i h\u1ee3p ph\u1ea3n \u00e1nh cho c\u01a1 quan ch\u1ee9c n\u0103ng c\u00e1c th\u00f4ng tin sai s\u1ef1 th\u1eadt.", "created_time": 1628605980, "id": "dangcongsan.vn_587776", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "5": [{"url": "https://cand.com.vn/su-kien-binh-luan-thoi-su/chu-tich-nuoc-nguyen-xuan-phuc-ket-thuc-tot-dep-chuyen-tham-huu-nghi-chinh-thuc-lao-i623739/", "domain": "cand.com.vn", "title": "Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c L\u00e0o", "snippet": "Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c CHDCND L\u00e0o.", "created_time": 1628609400, "id": "cand.com.vn_623739", "score": 0.0, "title_summarize": ["Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c CHDCND L\u00e0o.", "Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c CHDCND L\u00e0o.", "Ch\u1ee7 t\u1ecbch N\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c C\u1ed9ng h\u00f2a D\u00e2n ch\u1ee7 Nh\u00e2n d\u00e2n L\u00e0o."], "content_summary": "\"T\u1ed1i 10/8, chuy\u00ean c\u01a1 ch\u1edf Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam v\u1ec1 t\u1edbi S\u00e2n bay Qu\u1ed1c t\u1ebf N\u1ed9i b\u00e0i, Th\u1ee7 \u0111\u00f4 H\u00e0 N\u1ed9i, k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c CHDCND L\u00e0o theo l\u1eddi m\u1eddi c\u1ee7a T\u1ed5ng B\u00ed th\u01b0 Ban Ch\u1ea5p h\u00e0nh Trung \u01b0\u01a1ng \u0110\u1ea3ng Nh\u00e2n d\u00e2n C\u00e1ch m\u1ea1ng L\u00e0o, Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc C\u1ed9ng h\u00f2a D\u00e2n ch\u1ee7 Nh\u00e2n d\u00e2n L\u00e0o Thongloun Sisoulith. Trong chuy\u1ebfn th\u0103m, \u0111\u00e3 c\u00f3 14 v\u0103n ki\u1ec7n h\u1ee3p t\u00e1c \u0111\u01b0\u1ee3c k\u00fd k\u1ebft, trao \u0111\u1ed5i gi\u1eefa c\u00e1c b\u1ed9, ng\u00e0nh, doanh nghi\u1ec7p v\u00e0 \u0111\u1ecba ph\u01b0\u01a1ng hai n\u01b0\u1edbc. Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac v\u00e0 T\u1ed5ng B\u00ed th\u01b0, Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc L\u00e0o Thongloun Sisoulith \u0111\u00e3 ch\u1ee7 tr\u00ec cu\u1ed9c h\u1ed9i \u0111\u00e0m gi\u1eefa hai \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao hai n\u01b0\u1edbc. Hai nh\u00e0 l\u00e3nh \u0111\u1ea1o nh\u1ea5n m\u1ea1nh c\u1ea7n ti\u1ebfp t\u1ee5c \u0111\u01b0a quan h\u1ec7 ch\u00ednh tr\u1ecb \u0111i v\u00e0o chi\u1ec1u s\u00e2u, \u0111\u1ed3ng th\u1eddi nh\u1ea5t tr\u00ed l\u1ea5y n\u0103m 2022 l\u00e0 \u201cN\u0103m \u0110o\u00e0n k\u1ebft h\u1eefu ngh\u1ecb Vi\u1ec7t Nam - L\u00e0o, L\u00e0o - Vi\u1ec7t Nam 2022\u201d \u0111\u1ec3 k\u1ef7 ni\u1ec7m 60 n\u0103m Ng\u00e0y thi\u1ebft l\u1eadp quan h\u1ec7 ngo\u1ea1i giao v\u00e0 45 n\u0103m Ng\u00e0y k\u00fd Hi\u1ec7p \u01b0\u1edbc H\u1eefu ngh\u1ecb v\u00e0 H\u1ee3p t\u00e1c gi\u1eefa Vi\u1ec7t Nam v\u00e0 L\u00e0o.\"", "total_facebook_viral": 0}, {"url": "http://baolaocai.vn/bai-viet/345862-chu-tich-nuoc-nguyen-xuan-phuc-ket-thuc-tot-dep-chuyen-tham-huu-nghi-chinh-thuc-lao", "domain": "baolaocai.vn", "title": "Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c L\u00e0o", "snippet": "Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c CHDCND L\u00e0o.", "created_time": 1628647740, "id": "cfd0d2e69df594804492d4d7af5014677e8aa330", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://daibieunhandan.vn/chu-tich-nuoc-nguyen-xuan-phuc-ket-thuc-tot-dep-chuyen-tham-huu-nghi-chinh-thuc-lao", "domain": "daibieunhandan.vn", "title": "Ch\u1ee7 t\u1ecbch N\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c L\u00e0o", "snippet": "Ch\u1ee7 t\u1ecbch N\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac c\u00f9ng Phu nh\u00e2n v\u00e0 \u0110o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p to\u00e0n b\u1ed9 ch\u01b0\u01a1ng tr\u00ecnh chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c C\u1ed9ng h\u00f2a D\u00e2n ch\u1ee7 Nh\u00e2n d\u00e2n L\u00e0o.", "created_time": 1628611380, "id": "d8488a6c0d6303d3ea0e67fc9639db0b216cf704", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baoquangbinh.vn/chinh-tri/202108/chuyen-tham-huu-nghi-lao-cua-chu-tich-nuoc-nguyen-xuan-phuc-dat-duoc-nhung-ket-qua-toan-dien-thuc-chat-2192089/", "domain": "baoquangbinh.vn", "title": "Chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb L\u00e0o c\u1ee7a Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac \u0111\u1ea1t \u0111\u01b0\u1ee3c nh\u1eefng k\u1ebft qu\u1ea3 to\u00e0n di\u1ec7n, th\u1ef1c ch\u1ea5t", "snippet": "Nh\u00e2n d\u1ecbp Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m ch\u00ednh th\u1ee9c CHDCND L\u00e0o, \u0111\u1eb7c ph\u00e1i vi\u00ean TTXVN \u0111\u00e3 c\u00f3 cu\u1ed9c ph\u1ecfng v\u1ea5n v\u1edbi Th\u1ee9 tr\u01b0\u1edfng Ngo\u1ea1i giao Nguy\u1ec5n Qu\u1ed1c D\u0169ng v\u1ec1 k\u1ebft qu\u1ea3 chuy\u1ebfn th\u0103m n\u00e0y. 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Tin t\u1ee9c ph\u00e1p lu\u1eadt 24h, th\u1eddi s\u1ef1 m\u1edbi nh\u1ea5t, n\u00f3ng nh\u1ea5t", "created_time": 1628648220, "id": "cebd765826ab373ad922a2384fdb055c4f631f4b", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.doisongphapluat.com/nhung-dau-an-trong-chuyen-tham-chdcnd-lao-cua-chu-tich-nuoc-nguyen-xuan-phuc-a509845.html", "domain": "doisongphapluat.com", "title": "Nh\u1eefng d\u1ea5u \u1ea5n trong chuy\u1ebfn th\u0103m CHDCND L\u00e0o c\u1ee7a Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac", "snippet": "Nh\u00e2n d\u1ecbp Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m ch\u00ednh th\u1ee9c CHDCND L\u00e0o, Th\u1ee9 tr\u01b0\u1edfng B\u1ed9 Ngo\u1ea1i giao Nguy\u1ec5n Qu\u1ed1c D\u0169ng \u0111\u00e3 tr\u1ea3 l\u1eddi ph\u1ecfng v\u1ea5n b\u00e1o ch\u00ed v\u1ec1 k\u1ebft qu\u1ea3 chuy\u1ebfn th\u0103m n\u00e0y.", "created_time": 1628653740, "id": "doisongphapluat.com_a509845", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://baoquankhu4.com.vn/chinh-tri/chuyen-tham-lao-cua-chu-tich-nuoc-nguyen-xuan-phuc-dat-nhieu.html", "domain": "baoquankhu4.com.vn", "title": "Chuy\u1ebfn th\u0103m L\u00e0o c\u1ee7a Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac \u0111\u1ea1t nhi\u1ec1u k\u1ebft qu\u1ea3 th\u1ef1c ch\u1ea5t v\u00e0 to\u00e0n di\u1ec7n", "snippet": "Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac v\u00e0 phu nh\u00e2n c\u00f9ng \u0111o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng v\u00e0 Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m ...", "created_time": 1628659176, "id": "dfd013a3fe6e145232c7ad60fc1e60a759341ae9", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://dangcongsan.vn/the-gioi/the-gioi-noi-ve-viet-nam/vun-dap-moi-quan-he-huu-nghi-vi-dai-tinh-doan-ket-dac-biet-va-quan-he-hop-tac-toan-dien-viet-lao-587806.html", "domain": "dangcongsan.vn", "title": "Vun \u0111\u1eafp m\u1ed1i quan h\u1ec7 h\u1eefu ngh\u1ecb v\u0129 \u0111\u1ea1i, t\u00ecnh \u0111o\u00e0n k\u1ebft \u0111\u1eb7c bi\u1ec7t v\u00e0 quan h\u1ec7 h\u1ee3p t\u00e1c to\u00e0n di\u1ec7n Vi\u1ec7t - L\u00e0o", "snippet": "(\u0110CSVN) \u2013 Chi\u1ec1u 10 8, Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac v\u00e0 Phu nh\u00e2n c\u00f9ng \u0111o\u00e0n \u0111\u1ea1i bi\u1ec3u c\u1ea5p cao \u0110\u1ea3ng v\u00e0 Nh\u00e0 n\u01b0\u1edbc Vi\u1ec7t Nam \u0111\u00e3 l\u00ean \u0111\u01b0\u1eddng v\u1ec1 n\u01b0\u1edbc, k\u1ebft th\u00fac t\u1ed1t \u0111\u1eb9p chuy\u1ebfn th\u0103m h\u1eefu ngh\u1ecb ch\u00ednh th\u1ee9c n\u01b0\u1edbc CHDCND L\u00e0o. Nh\u00e2n d\u1ecbp n\u00e0y, b\u00e1o ch\u00ed khu v\u1ef1c \u0111\u00e3 c\u00f3 nhi\u1ec1u b\u00e0i vi\u1ebft ph\u1ea3n \u00e1nh \u0111\u1eadm n\u00e9t v\u1ec1 k\u1ebft qu\u1ea3 chuy\u1ebfn th\u0103m, tin t\u01b0\u1edfng \u0111\u00e2y s\u1ebd l\u00e0 ti\u1ec1n \u0111\u1ec1 ti\u1ebfp t\u1ee5c vun \u0111\u1eafp, t\u00f4...", "created_time": 1628653980, "id": "dangcongsan.vn_587806", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "6": [{"url": "https://laodong.vn/su-kien-binh-luan/khi-giay-di-duong-duoc-phat-hanh-o-hieu-cam-do-940629.ldo", "domain": "laodong.vn", "title": "Khi gi\u1ea5y \u0111i \u0111\u01b0\u1eddng \u0111\u01b0\u1ee3c ph\u00e1t h\u00e0nh \u1edf hi\u1ec7u c\u1ea7m \u0111\u1ed3", "snippet": "B\u1ecb ki\u1ec3m tra t\u1ea1i ch\u1ed1t ki\u1ec3m so\u00e1t ph\u00f2ng ch\u1ed1ng d\u1ecbch COVID-19 \u1edf qu\u1eadn Thanh Xu\u00e2n, H\u00e0 N\u1ed9i, 3 thanh ni\u00ean \u0111\u00e3 tr\u00ecnh gi\u1ea5y \u0111i \u0111\u01b0\u1eddng mua \u1edf hi\u1ec7u c\u1ea7m \u0111\u1ed3.", "created_time": 1628666220, "id": "laodong.vn_940629", "score": 0.0, "title_summarize": ["B\u1ecb ki\u1ec3m tra t\u1ea1i ch\u1ed1t ki\u1ec3m so\u00e1t ph\u00f2ng ch\u1ed1ng d\u1ecbch COVID-19 \u1edf qu\u1eadn Thanh Xu\u00e2n, H\u00e0 N\u1ed9i, 3 thanh ni\u00ean \u0111\u00e3 tr\u00ecnh gi\u1ea5y \u0111i \u0111\u01b0\u1eddng mua \u1edf hi\u1ec7u c\u1ea7m \u0111\u1ed3.", "\u0110\u1ec3 qua \u0111\u01b0\u1ee3c c\u00e1c ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch t\u1ea1i H\u00e0 N\u1ed9i, 3 ng\u01b0\u1eddi \u0111\u00e0n \u00f4ng \u0111\u00e3 mua 9 t\u1edd gi\u1ea5y \u0111i \u0111\u01b0\u1eddng v\u1edbi gi\u00e1 12 tri\u1ec7u \u0111\u1ed3ng t\u1ea1i m\u1ed9t ti\u1ec7m c\u1ea7m \u0111\u1ed3 tr\u00ean \u0111\u1ecba b\u00e0n qu\u1eadn \u0110\u1ed1ng \u0110a.", "(D\u00e2n tr\u00ed) - Tr\u01b0\u1edbc bi\u1ec3u hi\u1ec7n nghi v\u1ea5n, l\u1ef1c l\u01b0\u1ee3ng ch\u1ee9c n\u0103ng ki\u1ec3m tra, ph\u00e1t hi\u1ec7n 3 nam thanh ni\u00ean \u0111\u00e3 mua 9 gi\u1ea5y \u0111i \u0111\u01b0\u1eddng v\u1edbi gi\u00e1 12 tri\u1ec7u \u0111\u1ed3ng \u1edf\u2026 ti\u1ec7m c\u1ea7m \u0111\u1ed3 \u0111\u1ec3 qua ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch b\u1ec7nh."], "content_summary": "\"B\u1ecb ki\u1ec3m tra t\u1ea1i ch\u1ed1t ki\u1ec3m so\u00e1t ph\u00f2ng ch\u1ed1ng d\u1ecbch COVID-19 \u1edf qu\u1eadn Thanh Xu\u00e2n, H\u00e0 N\u1ed9i, 3 thanh ni\u00ean \u0111\u00e3 tr\u00ecnh gi\u1ea5y \u0111i \u0111\u01b0\u1eddng mua \u1edf hi\u1ec7u c\u1ea7m \u0111\u1ed3. 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2026", "snippet": "STO - S\u00e1ng ng\u00e0y 11-8, t\u1ea1i th\u1ee7 \u0111\u00f4 H\u00e0 N\u1ed9i, Ch\u00ednh ph\u1ee7 h\u1ecdp phi\u00ean to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean nhi\u1ec7m k\u1ef3 2021 \u2013 2026 b\u1eb1ng h\u00ecnh th\u1ee9c tr\u1ef1c tuy\u1ebfn v\u1edbi c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng, nh\u1eb1m tri\u1ec3n khai th\u1ef1c hi\u1ec7n Ngh\u1ecb quy\u1ebft \u0110\u1ea1i h\u1ed9i XIII c\u1ee7a \u0110\u1ea3ng v\u00e0 Ngh\u1ecb quy\u1ebft c\u1ee7a Qu\u1ed1c h\u1ed9i kh\u00f3a XV v\u1ec1 ph\u00e1t tri\u1ec3n kinh t\u1ebf - x\u00e3 h\u1ed9i 5 n\u0103m 2021 - 2025. D\u1ef1 phi\u00ean h\u1ecdp t\u1ea1i \u0111i\u1ec3m c\u1ea7u Trung \u01b0\u01a1ng c\u00f3 c\u00e1c \u0111\u1ed3ng ch\u00ed: Nguy\u1ec5n Ph\u00fa Tr\u1ecdng \u2013 T\u1ed5ng B\u00ed th\u01b0 Ban Ch\u1ea5p h\u00e0nh Trung \u01b0\u01a1ng \u0110\u1ea3ng; Nguy\u1ec5n Xu\u00e2n Ph\u00fac \u2013 Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc; Ph\u1ea1m Minh Ch\u00ednh \u2013 Th\u1ee7 t\u01b0\u1edbng Ch\u00ednh ph\u1ee7; V\u01b0\u01a1ng \u0110\u00ecnh Hu\u1ec7 \u2013 Ch\u1ee7 t\u1ecbch Qu\u1ed1c h\u1ed9i; l\u00e3nh \u0111\u1ea1o c\u00e1c b\u1ed9, ng\u00e0nh.", "created_time": 1628658600, "id": "baosoctrang.org.vn_50976", "score": 0.0, "title_summarize": ["STO - S\u00e1ng ng\u00e0y 11-8, t\u1ea1i th\u1ee7 \u0111\u00f4 H\u00e0 N\u1ed9i, Ch\u00ednh ph\u1ee7 h\u1ecdp phi\u00ean to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean nhi\u1ec7m k\u1ef3 2021 \u2013 2026 b\u1eb1ng h\u00ecnh th\u1ee9c tr\u1ef1c tuy\u1ebfn v\u1edbi c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng, nh\u1eb1m tri\u1ec3n khai th\u1ef1c hi\u1ec7n Ngh\u1ecb quy\u1ebft \u0110\u1ea1i h\u1ed9i XIII c\u1ee7a \u0110\u1ea3ng v\u00e0 Ngh\u1ecb quy\u1ebft c\u1ee7a Qu\u1ed1c h\u1ed9i kh\u00f3a XV v\u1ec1 ph\u00e1t tri\u1ec3n kinh t\u1ebf - x\u00e3 h\u1ed9i 5 n\u0103m 2021 - 2025. D\u1ef1 phi\u00ean h\u1ecdp t\u1ea1i \u0111i\u1ec3m c\u1ea7u Trung \u01b0\u01a1ng c\u00f3 c\u00e1c \u0111\u1ed3ng ch\u00ed: Nguy\u1ec5n Ph\u00fa Tr\u1ecdng \u2013 T\u1ed5ng B\u00ed th\u01b0 Ban Ch\u1ea5p h\u00e0nh Trung \u01b0\u01a1ng \u0110\u1ea3ng; Nguy\u1ec5n Xu\u00e2n Ph\u00fac \u2013 Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc; Ph\u1ea1m Minh Ch\u00ednh \u2013 Th\u1ee7 t\u01b0\u1edbng Ch\u00ednh ph\u1ee7; V\u01b0\u01a1ng \u0110\u00ecnh Hu\u1ec7 \u2013 Ch\u1ee7 t\u1ecbch Qu\u1ed1c h\u1ed9i; l\u00e3nh \u0111\u1ea1o c\u00e1c b\u1ed9, ng\u00e0nh.", "T\u1ed5ng B\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng v\u00e0 nhi\u1ec1u v\u1ecb l\u00e3nh \u0111\u1ea1o \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc \u0111\u00e3 c\u00f9ng tham d\u1ef1 phi\u00ean h\u1ecdp to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 nhi\u1ec7m k\u1ef3 m\u1edbi.", "(PLVN) \u2013 Ph\u00e1t bi\u1ec3u khai m\u1ea1c phi\u00ean h\u1ecdp to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a XV nhi\u1ec7m k\u1ef3 2021-2026, c\u0169ng l\u00e0 phi\u00ean h\u1ecdp l\u1ecbch s\u1eed, Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh n\u00eau r\u00f5 quy\u1ebft t\u00e2m x\u00e2y d\u1ef1ng Ch\u00ednh ph\u1ee7 \u0111\u1ed5i m\u1edbi, li\u00eam ch\u00ednh, h\u00e0nh \u0111\u1ed9ng, hi\u1ec7u qu\u1ea3, v\u00ec nh\u00e2n d\u00e2n ph\u1ee5c v\u1ee5."], "content_summary": "\"T\u1ea1i \u0111i\u1ec3m c\u1ea7u t\u1ec9nh S\u00f3c Tr\u0103ng, c\u00f9ng d\u1ef1 c\u00f3 c\u00e1c \u0111\u1ed3ng ch\u00ed: L\u00e2m V\u0103n M\u1eabn - B\u00ed th\u01b0 T\u1ec9nh \u1ee7y; H\u1ed3 Th\u1ecb C\u1ea9m \u0110\u00e0o \u2013 Ph\u00f3 B\u00ed th\u01b0 Th\u01b0\u1eddng tr\u1ef1c T\u1ec9nh \u1ee7y, Ch\u1ee7 t\u1ecbch H\u0110ND t\u1ec9nh; Tr\u1ea7n V\u0103n L\u00e2u \u2013 Ch\u1ee7 t\u1ecbch UBND t\u1ec9nh; c\u00e1c ph\u00f3 ch\u1ee7 t\u1ecbch UBND t\u1ec9nh v\u00e0 l\u00e3nh \u0111\u1ea1o c\u00e1c s\u1edf, ban ng\u00e0nh. \u0110\u1ea1i bi\u1ec3u d\u1ef1 phi\u00ean h\u1ecdp tr\u1ef1c tuy\u1ebfn c\u1ee7a Ch\u00ednh ph\u1ee7 t\u1ea1i \u0111i\u1ec3m c\u1ea7u t\u1ec9nh S\u00f3c Tr\u0103ng. X\u1eed l\u00fd c\u0103n c\u01a1, d\u1ee9t \u0111i\u1ec3m, c\u00f3 tr\u1ecdng t\u00e2m c\u00e1c v\u1ea5n \u0111\u1ec1 kinh t\u1ebf - x\u00e3 h\u1ed9i n\u1ed5i c\u1ed9m, tr\u00e1nh h\u00ecnh th\u1ee9c, ph\u00f4 tr\u01b0\u01a1ng, n\u00e9 tr\u00e1nh, \u0111\u00f9n \u0111\u1ea9y tr\u00e1ch nhi\u1ec7m.\"", "total_facebook_viral": 0}, {"url": "https://doanhnghieptiepthi.vn/tong-bi-thu-nguyen-phu-trong-du-phien-hop-toan-the-dau-tien-cua-chinh-phu-nhiem-ky-moi-161211108102920693.htm", "domain": "doanhnghieptiepthi.vn", "title": "T\u1ed5ng B\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 phi\u00ean h\u1ecdp \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 nhi\u1ec7m k\u1ef3 m\u1edbi", "snippet": "T\u1ed5ng B\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng v\u00e0 nhi\u1ec1u v\u1ecb l\u00e3nh \u0111\u1ea1o \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc \u0111\u00e3 c\u00f9ng tham d\u1ef1 phi\u00ean h\u1ecdp to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 nhi\u1ec7m k\u1ef3 m\u1edbi.", "created_time": 1628651340, "id": "doanhnghieptiepthi.vn_161211108102920693", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baophapluat.vn/khai-mac-phien-hop-lich-su-cua-chinh-phu-khoa-xv-post407157.html", "domain": "baophapluat.vn", "title": "Khai m\u1ea1c phi\u00ean h\u1ecdp l\u1ecbch s\u1eed c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a XV", "snippet": "(PLVN) \u2013 Ph\u00e1t bi\u1ec3u khai m\u1ea1c phi\u00ean h\u1ecdp to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a XV nhi\u1ec7m k\u1ef3 2021-2026, c\u0169ng l\u00e0 phi\u00ean h\u1ecdp l\u1ecbch s\u1eed, Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh n\u00eau r\u00f5 quy\u1ebft t\u00e2m x\u00e2y d\u1ef1ng Ch\u00ednh ph\u1ee7 \u0111\u1ed5i m\u1edbi, li\u00eam ch\u00ednh, h\u00e0nh \u0111\u1ed9ng, hi\u1ec7u qu\u1ea3, v\u00ec nh\u00e2n d\u00e2n ph\u1ee5c v\u1ee5.", "created_time": 1628648526, "id": "baophapluat.vn_407157", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/tong-bi-thu-du-phien-hop-dau-tien-cua-chinh-phu-khoa-moi-post1249649.html", "domain": "zingnews.vn", "title": "T\u1ed5ng b\u00ed th\u01b0 d\u1ef1 phi\u00ean h\u1ecdp \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a m\u1edbi", "snippet": "Ng\u00e0y 11/8, Ch\u00ednh ph\u1ee7 kh\u00f3a XV h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh. T\u1ed5ng b\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 c\u00f3 b\u00e0i ph\u00e1t bi\u1ec3u ch\u1ec9 \u0111\u1ea1o \u0111\u1ecbnh h\u01b0\u1edbng.", "created_time": 1628649044, "id": "zingnews.vn_1249649", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/tong-bi-thu-du-phien-hop-dau-tien-cua-chinh-phu-khoa-moi-post1249649.html", "domain": "news.zing.vn", "title": "T\u1ed5ng b\u00ed th\u01b0 d\u1ef1 phi\u00ean h\u1ecdp \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a m\u1edbi", "snippet": "Ng\u00e0y 11/8, Ch\u00ednh ph\u1ee7 kh\u00f3a XV h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh. 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T\u1ed5ng b\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 c\u00f3 b\u00e0i ph\u00e1t bi\u1ec3u ch\u1ec9 \u0111\u1ea1o \u0111\u1ecbnh h\u01b0\u1edbng.", "created_time": 1628649044, "id": "48f57cb39e2cdca6da8308fefc60b4bf15515b5f", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://vneconomy.vn/chinh-phu-khoa-moi-hop-phien-toan-the-dau-tien.htm", "domain": "vneconomy.vn", "title": "Ch\u00ednh ph\u1ee7 kh\u00f3a m\u1edbi h\u1ecdp phi\u00ean to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean", "snippet": "Ng\u00e0y 11/8, Ch\u00ednh ph\u1ee7 kh\u00f3a XV h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh. 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T\u1ed5ng B\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 ch\u1ec9 \u0111\u1ea1o Phi\u00ean h\u1ecdp. Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac, Ch\u1ee7 t\u1ecbch Qu\u1ed1c h\u1ed9i V\u01b0\u01a1ng \u0110\u00ecnh Hu\u1ec7 d\u1ef1 Phi\u00ean h\u1ecdp. 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T\u1ed5ng B\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 ch\u1ec9 \u0111\u1ea1o Phi\u00ean h\u1ecdp. Ch\u1ee7 t\u1ecbch n\u01b0\u1edbc Nguy\u1ec5n Xu\u00e2n Ph\u00fac, Ch\u1ee7 t\u1ecbch Qu\u1ed1c h\u1ed9i V\u01b0\u01a1ng \u0110\u00ecnh Hu\u1ec7 d\u1ef1 Phi\u00ean h\u1ecdp. C\u00f9ng ch\u1ee7 tr\u00ec Phi\u00ean h\u1ecdp \u2026", "created_time": 1628646341, "id": "b7f6670e256b12a6a3cad3add47932f3e3cae412", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://cand.com.vn/su-kien-binh-luan-thoi-su/quyet-tam-xay-dung-chinh-phu-doi-moi-liem-chinh-ky-cuong-hanh-dong-hieu-qua-vi-nhan-dan-phuc-vu-i623799/", "domain": "cand.com.vn", "title": "Quy\u1ebft t\u00e2m x\u00e2y d\u1ef1ng Ch\u00ednh ph\u1ee7 \u0111\u1ed5i m\u1edbi, li\u00eam ch\u00ednh, k\u1ef7 c\u01b0\u01a1ng, h\u00e0nh \u0111\u1ed9ng, hi\u1ec7u qu\u1ea3, v\u00ec nh\u00e2n d\u00e2n ph\u1ee5c v\u1ee5", "snippet": "Ph\u00e1t bi\u1ec3u khai m\u1ea1c phi\u00ean h\u1ecdp to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a XV nhi\u1ec7m k\u1ef3 2021-2026, c\u0169ng l\u00e0 phi\u00ean h\u1ecdp l\u1ecbch s\u1eed, Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh n\u00eau r\u00f5 quy\u1ebft t\u00e2m x\u00e2y d\u1ef1ng Ch\u00ednh ph\u1ee7 \u0111\u1ed5i m\u1edbi, li\u00eam ch\u00ednh, k\u1ef7 c\u01b0\u01a1ng, h\u00e0nh \u0111\u1ed9ng, hi\u1ec7u qu\u1ea3, v\u00ec nh\u00e2n d\u00e2n ph\u1ee5c v\u1ee5.", "created_time": 1628659440, "id": "cand.com.vn_623799", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.com.vn/tong-bi-thu-du-phien-hop-dau-tien-cua-chinh-phu-khoa-moi-post1249649.html", "domain": "trithuctructuyen.com.vn", "title": "T\u1ed5ng b\u00ed th\u01b0 d\u1ef1 phi\u00ean h\u1ecdp \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a m\u1edbi", "snippet": "Ng\u00e0y 11/8, Ch\u00ednh ph\u1ee7 kh\u00f3a XV h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh. T\u1ed5ng b\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 c\u00f3 b\u00e0i ph\u00e1t bi\u1ec3u ch\u1ec9 \u0111\u1ea1o \u0111\u1ecbnh h\u01b0\u1edbng.", "created_time": 1628649044, "id": "877ef4f2bc5bce6a9c4a892de0b8ecade92a2180", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://www.baoyenbai.com.vn/11/215331/tong_bi_thu_du_phien_hop_dau_tien_cua_chinh_phu_khoa_moi.aspx", "domain": "baoyenbai.com.vn", "title": "T\u1ed5ng B\u00ed th\u01b0 d\u1ef1 phi\u00ean h\u1ecdp \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a m\u1edbi", "snippet": "Ng\u00e0y 11/8, Ch\u00ednh ph\u1ee7 kh\u00f3a XV h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh. T\u1ed5ng b\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 c\u00f3 b\u00e0i ph\u00e1t bi\u1ec3u ch\u1ec9 \u0111\u1ea1o \u0111\u1ecbnh h\u01b0\u1edbng.", "created_time": 1628649600, "id": "baoyenbai.com.vn_215331", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kienthuc.net.vn/xa-hoi/tong-bi-thu-du-phien-hop-toan-the-dau-tien-cua-chinh-phu-khoa-moi-1575699.html", "domain": "kienthuc.net.vn", "title": "T\u1ed5ng B\u00ed th\u01b0 d\u1ef1 phi\u00ean h\u1ecdp to\u00e0n th\u1ec3 \u0111\u1ea7u ti\u00ean c\u1ee7a Ch\u00ednh ph\u1ee7 kh\u00f3a m\u1edbi", "snippet": "Ng\u00e0y 11/8, Ch\u00ednh ph\u1ee7 kh\u00f3a XV h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh. T\u1ed5ng B\u00ed th\u01b0 Nguy\u1ec5n Ph\u00fa Tr\u1ecdng d\u1ef1 v\u00e0 c\u00f3 b\u00e0i ph\u00e1t bi\u1ec3u ch\u1ec9 \u0111\u1ea1o \u0111\u1ecbnh h\u01b0\u1edbng.", "created_time": 1628666111, "id": "kienthuc.net.vn_1575699", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baotayninh.vn/hom-nay-chinh-phu-hop-phien-dau-tien-cua-nhiem-ky-moi-2021-2026-a135555.html", "domain": "baotayninh.vn", "title": "H\u00f4m nay, Ch\u00ednh ph\u1ee7 h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean c\u1ee7a nhi\u1ec7m k\u1ef3 m\u1edbi 2021-2026", "snippet": "S\u00e1ng nay (11.8), Ch\u00ednh ph\u1ee7 nhi\u1ec7m k\u1ef3 2021-2026 h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh.", "created_time": 1628649780, "id": "baotayninh.vn_135555", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://plo.vn/thoi-su/hom-nay-chinh-phu-hop-phien-dau-tien-cua-nhiem-ky-moi-20212026-1007285.html", "domain": "plo.vn", "title": "H\u00f4m nay, Ch\u00ednh ph\u1ee7 h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean c\u1ee7a nhi\u1ec7m k\u1ef3 m\u1edbi 2021-2026", "snippet": "(PLO)- S\u00e1ng nay, 11-8, Ch\u00ednh ph\u1ee7 nhi\u1ec7m k\u1ef3 2021-2026 h\u1ecdp phi\u00ean \u0111\u1ea7u ti\u00ean d\u01b0\u1edbi s\u1ef1 ch\u1ee7 tr\u00ec c\u1ee7a Th\u1ee7 t\u01b0\u1edbng Ph\u1ea1m Minh Ch\u00ednh, v\u1edbi \u0111\u1ea7y \u0111\u1ee7 l\u00e3nh \u0111\u1ea1o ch\u1ee7 ch\u1ed1t c\u1ee7a \u0110\u1ea3ng, Nh\u00e0 n\u01b0\u1edbc \u0111\u01b0\u1ee3c m\u1eddi d\u1ef1.", "created_time": 1628640000, "id": "plo.vn_1007285", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "8": [{"url": "https://theleader.vn/ha-noi-xet-nghiem-sang-loc-covid-19-tren-dien-rong-voi-13-trieu-mau-1628658791291.htm", "domain": "theleader.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc Covid-19 tr\u00ean di\u1ec7n r\u1ed9ng v\u1edbi 1,3 tri\u1ec7u m\u1eabu", "snippet": "\u0110\u1ec3 ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch Covid-19 tr\u01b0\u1edbc ng\u00e0y 25/8, TP. H\u00e0 N\u1ed9i s\u1ebd tri\u1ec3n khai x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u00ean di\u1ec7n r\u1ed9ng v\u1edbi 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR v\u00e0 2 tri\u1ec7u test nhanh nh\u1eb1m b\u00f3c t\u00e1ch c\u00e1c ca F0 kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng.", "created_time": 1628661840, "id": "theleader.vn_1628658791291", "score": 0.0, "title_summarize": ["\u0110\u1ec3 ki\u1ec3m so\u00e1t \u0111\u01b0\u1ee3c d\u1ecbch Covid-19 tr\u01b0\u1edbc ng\u00e0y 25/8, TP. H\u00e0 N\u1ed9i s\u1ebd tri\u1ec3n khai x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u00ean di\u1ec7n r\u1ed9ng v\u1edbi 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR v\u00e0 2 tri\u1ec7u test nhanh nh\u1eb1m b\u00f3c t\u00e1ch c\u00e1c ca F0 kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng.", "TTO - TP H\u00e0 N\u1ed9i s\u1ebd tri\u1ec3n khai \u0111\u1ee3t cao \u0111i\u1ec3m x\u00e9t nghi\u1ec7m COVID-19 t\u1eeb ng\u00e0y 9-8 \u0111\u1ebfn ng\u00e0y 17-8, s\u1ed1 m\u1eabu x\u00e9t nghi\u1ec7m d\u1ef1 ki\u1ebfn \u0111\u01b0\u1ee3c l\u1ea5y kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu.", "Trong kho\u1ea3ng m\u1ed9t tu\u1ea7n, H\u00e0 N\u1ed9i \u0111\u1eb7t m\u1ee5c ti\u00eau l\u1ea5y 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt PT-PCR t\u1ea1i khu v\u1ef1c nguy c\u01a1 cao. C\u00e1c \u0111\u1ecba b\u00e0n c\u00f2n l\u1ea1i ch\u1ee7 \u0111\u1ed9ng tri\u1ec3n khai x\u00e9t nghi\u1ec7m test nhanh, d\u1ef1 ki\u1ebfn l\u1ea5y kho\u1ea3ng 2 tri\u1ec7u m\u1eabu."], "content_summary": "\"Tr\u01b0\u1edbc \u0111\u00e0 l\u00e2y lan c\u1ee7a d\u1ecbch b\u1ec7nh, th\u00e0nh ph\u1ed1 ti\u1ebfp t\u1ee5c ghi nh\u1eadn s\u1ed1 ca m\u1eafc m\u1edbi \u1edf m\u1ee9c cao v\u1edbi trung b\u00ecnh 60 - 80 ca m\u1eafc m\u1edbi m\u1ed7i ng\u00e0y \u0111\u1eb7c bi\u1ec7t \u0111\u00e3 c\u00f3 nhi\u1ec1u ch\u00f9m ca b\u1ec7nh ph\u1ee9c t\u1ea1p v\u1edbi s\u1ed1 l\u01b0\u1ee3ng ca m\u1eafc l\u1edbn, nhi\u1ec1u ca b\u1ec7nh ch\u01b0a x\u00e1c \u0111\u1ecbnh \u0111\u01b0\u1ee3c ngu\u1ed3n l\u00e2y. \u0110\u1ed1i v\u1edbi \\\"v\u00f9ng cam\\\" (nguy c\u01a1 cao), c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng \u0111\u01b0\u1ee3c l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m g\u1ed3m nh\u00e2n vi\u00ean y t\u1ebf, b\u1ec7nh nh\u00e2n, ng\u01b0\u1eddi lao \u0111\u1ed9ng tr\u1ef1c ti\u1ebfp t\u1ea1i c\u00e1c chu\u1ed7i cung \u1ee9ng, l\u00e1i xe, shipper, b\u1ea3o v\u1ec7 t\u00f2a nh\u00e0... tr\u00ean c\u01a1 s\u1edf ch\u1ec9 \u0111\u1ecbnh chuy\u00ean m\u00f4n d\u1ecbch t\u1ec5. Th\u00e0nh ph\u1ed1 c\u0169ng x\u00e9t nghi\u1ec7m \\\"v\u00f9ng xanh\\\" theo h\u1ed9 gia \u0111\u00ecnh t\u1ea1i c\u00e1c qu\u1eadn n\u1ed9i th\u00e0nh v\u00e0 c\u00e1c huy\u1ec7n c\u00f3 nguy c\u01a1 cao, m\u1ed7i h\u1ed9 gia \u0111\u00ecnh l\u1ea5y \u0111\u1ea1i di\u1ec7n 1 m\u1eabu c\u1ee7a 1 th\u00e0nh vi\u00ean c\u00f3 nguy c\u01a1 cao nh\u1ea5t - c\u0103n c\u1ee9 theo l\u1ecbch s\u1eed di chuy\u1ec3n nhi\u1ec1u n\u01a1i, ti\u1ebfp x\u00fac v\u1edbi nhi\u1ec1u ng\u01b0\u1eddi, th\u01b0\u1eddng xuy\u00ean t\u1edbi c\u00e1c khu v\u1ef1c nguy c\u01a1 cao nh\u01b0 b\u1ec7nh vi\u1ec7n, ch\u1ee3... C\u00f9ng v\u1edbi vi\u1ec7c th\u1ef1c hi\u1ec7n x\u00e9t nghi\u1ec7m b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR cho ng\u01b0\u1eddi d\u00e2n thu\u1ed9c \\\"nh\u00f3m \u0111\u1ecf\\\", \u0111\u1ed1i t\u01b0\u1ee3ng trong \u201cv\u00f9ng cam\u201d v\u00e0 \\\"v\u00f9ng xanh\\\" t\u1ea1i c\u00e1c \u0111\u1ecba b\u00e0n c\u00f3 nguy c\u01a1 cao, c\u00e1c \u0111\u1ecba b\u00e0n c\u00f2n l\u1ea1i ch\u1ee7 \u0111\u1ed9ng tri\u1ec3n khai x\u00e9t nghi\u1ec7m test nhanh, d\u1ef1 ki\u1ebfn th\u1ef1c hi\u1ec7n 2 tri\u1ec7u test nhanh. D\u1ef1 ki\u1ebfn ho\u00e0n thi\u1ec7n sau 1 th\u00e1ng kh\u1edfi c\u00f4ng, t\u1ee9c cu\u1ed1i th\u00e1ng 8.\"", "total_facebook_viral": 0}, {"url": "https://tuoitre.vn/ha-noi-se-xet-nghiem-dien-rong-1-3-trieu-mau-de-vet-sach-f0-khoi-cong-dong-2021081023522961.htm", "domain": "tuoitre.vn", "title": "H\u00e0 N\u1ed9i s\u1ebd x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng 1,3 tri\u1ec7u m\u1eabu \u0111\u1ec3 'v\u00e9t s\u1ea1ch' F0 kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng", "snippet": "TTO - TP H\u00e0 N\u1ed9i s\u1ebd tri\u1ec3n khai \u0111\u1ee3t cao \u0111i\u1ec3m x\u00e9t nghi\u1ec7m COVID-19 t\u1eeb ng\u00e0y 9-8 \u0111\u1ebfn ng\u00e0y 17-8, s\u1ed1 m\u1eabu x\u00e9t nghi\u1ec7m d\u1ef1 ki\u1ebfn \u0111\u01b0\u1ee3c l\u1ea5y kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu.", "created_time": 1628633456, "id": "tuoitre.vn_2021081023522961", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghiep.kinhtechungkhoan.vn/ha-noi-xet-nghiem-covid-19-dien-rong-toan-tp-trong-1-tuan-lay-hon-1-trieu-mau-4220211189292794.htm", "domain": "doanhnghiep.kinhtechungkhoan.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m COVID-19 di\u1ec7n r\u1ed9ng to\u00e0n TP, trong 1 tu\u1ea7n l\u1ea5y h\u01a1n 1 tri\u1ec7u m\u1eabu", "snippet": "Trong kho\u1ea3ng m\u1ed9t tu\u1ea7n, H\u00e0 N\u1ed9i \u0111\u1eb7t m\u1ee5c ti\u00eau l\u1ea5y 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt PT-PCR t\u1ea1i khu v\u1ef1c nguy c\u01a1 cao. C\u00e1c \u0111\u1ecba b\u00e0n c\u00f2n l\u1ea1i ch\u1ee7 \u0111\u1ed9ng tri\u1ec3n khai x\u00e9t nghi\u1ec7m test nhanh, d\u1ef1 ki\u1ebfn l\u1ea5y kho\u1ea3ng 2 tri\u1ec7u m\u1eabu.", "created_time": 1628614800, "id": "1bfa9e81c7088b0afc3145f9d02d419a6765cc54", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vietnambiz.vn/ha-noi-xet-nghiem-covid-19-dien-rong-toan-tp-trong-1-tuan-lay-hon-1-trieu-mau-202108110904571.htm", "domain": "vietnambiz.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m COVID-19 di\u1ec7n r\u1ed9ng to\u00e0n TP, trong 1 tu\u1ea7n l\u1ea5y h\u01a1n 1 tri\u1ec7u m\u1eabu", "snippet": "Trong kho\u1ea3ng m\u1ed9t tu\u1ea7n, H\u00e0 N\u1ed9i \u0111\u1eb7t m\u1ee5c ti\u00eau l\u1ea5y 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt PT-PCR t\u1ea1i khu v\u1ef1c nguy c\u01a1 cao. C\u00e1c \u0111\u1ecba b\u00e0n c\u00f2n l\u1ea1i ch\u1ee7 \u0111\u1ed9ng tri\u1ec3n khai x\u00e9t nghi\u1ec7m test nhanh, d\u1ef1 ki\u1ebfn l\u1ea5y kho\u1ea3ng 2 tri\u1ec7u m\u1eabu.", "created_time": 1628648880, "id": "vietnambiz.vn_202108110904571", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.giadinhmoi.vn/ha-noi-se-lay-mau-xet-nghiem-covid-19-cho-hon-3-trieu-nguoi-d61203.html", "domain": "giadinhmoi.vn", "title": "H\u00e0 N\u1ed9i s\u1ebd l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m COVID-19 cho h\u01a1n 3 tri\u1ec7u ng\u01b0\u1eddi \u0111\u1ec3 'v\u00e9t s\u1ea1ch' F0", "snippet": "H\u00e0 N\u1ed9i s\u1ebd ti\u1ebfn h\u00e0nh l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m COVID-19 v\u1edbi t\u1ed5ng s\u1ed1 kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR v\u00e0 d\u1ef1 ki\u1ebfn 2 tri\u1ec7u test nhanh \u0111\u1ec3 \u201cv\u00e9t s\u1ea1ch\u201d F0", "created_time": 1628662380, "id": "f6d60497744d0a74f2643822ff0886e4909636c7", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://datviet.trithuccuocsong.vn/chinh-tri-xa-hoi/tin-tuc-thoi-su/ha-noi-xet-nghiem-sang-loc-hon-3-trieu-nguoi-3437084/", "domain": "baodatviet.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc h\u01a1n 3 tri\u1ec7u ng\u01b0\u1eddi", "snippet": "T\u1eeb ng\u00e0y 9/8-17/8, H\u00e0 N\u1ed9i t\u1eadp trung x\u00e9t nghi\u1ec7m v\u1edbi t\u1ed5ng s\u1ed1 t\u1ed1i \u0111a kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR cho to\u00e0n b\u1ed9 ng\u01b0\u1eddi d\u00e2n trong \u201cv\u00f9ng \u0111\u1ecf\u201d.", "created_time": 1628651400, "id": "baodatviet.vn_3437084", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baotintuc.vn/ha-noi/ha-noi-se-xet-nghiem-covid19-dien-rong-lay-khoang-13-trieu-mau-bang-ky-thuat-rtpcr-20210811060746259.htm", "domain": "baotintuc.vn", "title": "H\u00e0 N\u1ed9i s\u1ebd x\u00e9t nghi\u1ec7m COVID-19 di\u1ec7n r\u1ed9ng, l\u1ea5y kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR", "snippet": "T\u1eeb ng\u00e0y 9/8 \u0111\u1ebfn ng\u00e0y 17/8, H\u00e0 N\u1ed9i s\u1ebd th\u1ef1c hi\u1ec7n l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m COVID-19 tr\u00ean di\u1ec7n r\u1ed9ng v\u1edbi t\u1ed5ng s\u1ed1 kho\u1ea3ng 1.300.000 m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR.", "created_time": 1628637900, "id": "baotintuc.vn_20210811060746259", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnhan.vn/ha-noi-lay-mau-xet-nghiem-hon-3-trieu-nguoi-uu-tien-vung-do-lay-mau-xac-suat-vung-xanh-42373.html", "domain": "doanhnhan.vn", "title": "H\u00e0 N\u1ed9i l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m h\u01a1n 3 tri\u1ec7u ng\u01b0\u1eddi: \u01b0u ti\u00ean \u201cv\u00f9ng \u0111\u1ecf\u201d, l\u1ea5y m\u1eabu x\u00e1c su\u1ea5t \u201cv\u00f9ng xanh\"", "snippet": "T\u1eeb 9 - 17/8, H\u00e0 N\u1ed9i s\u1ebd x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR v\u00e0 2 tri\u1ec7u test nhanh.", "created_time": 1628661780, "id": "doanhnhan.vn_42373", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://nhandan.vn/tin-tuc-xa-hoi/ha-noi-trien-khai-xet-nghiem-covid-19-dien-rong-659317/", "domain": "nhandan.com.vn", "title": "H\u00e0 N\u1ed9i tri\u1ec3n khai x\u00e9t nghi\u1ec7m Covid-19 di\u1ec7n r\u1ed9ng", "snippet": "\u0110\u1ee3t cao \u0111i\u1ec3m x\u00e9t nghi\u1ec7m Covid-19 di\u1ec7n r\u1ed9ng t\u1ea1i H\u00e0 N\u1ed9i di\u1ec5n ra trong th\u00e1ng 8, trong \u0111\u00f3, t\u1eeb ng\u00e0y 9 \u0111\u1ebfn 17/8, t\u1eadp trung th\u1ef1c hi\u1ec7n x\u00e9t nghi\u1ec7m v\u1edbi t\u1ed5ng s\u1ed1 kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt Realtime RT-PCR\u00a0v\u00e0 d\u1ef1 ki\u1ebfn 2 tri\u1ec7u test nhanh.", "created_time": 1628666640, "id": "nhandan.com.vn_659317", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "9": [{"url": "https://nhandan.vn/tin-tuc-y-te/ha-noi-xet-nghiem-sang-loc-dien-rong-toan-thanh-pho-659277/", "domain": "nhandan.com.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc di\u1ec7n r\u1ed9ng to\u00e0n th\u00e0nh ph\u1ed1", "snippet": "Nh\u1eb1m ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t t\u1ed1t h\u01a1n d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25/8/2021, th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i l\u1eadp k\u1ebf ho\u1ea1ch tri\u1ec3n khai x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng \u0111\u1ec3 ch\u1ee7 \u0111\u1ed9ng ph\u00f2ng ch\u1ed1ng d\u1ecbch b\u1ec7nh Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n th\u00e0nh ph\u1ed1, ph\u00e2n chia t\u1eebng nh\u00f3m \u0111\u1ed1i t\u01b0\u1ee3ng x\u00e9t nghi\u1ec7m c\u1ee5 th\u1ec3 theo nguy", "created_time": 1628638140, "id": "nhandan.com.vn_659277", "score": 0.0, "title_summarize": ["Nh\u1eb1m ph\u1ea5n \u0111\u1ea5u ki\u1ec3m so\u00e1t t\u1ed1t h\u01a1n d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25/8/2021, th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i l\u1eadp k\u1ebf ho\u1ea1ch tri\u1ec3n khai x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng \u0111\u1ec3 ch\u1ee7 \u0111\u1ed9ng ph\u00f2ng ch\u1ed1ng d\u1ecbch b\u1ec7nh Covid-19 tr\u00ean \u0111\u1ecba b\u00e0n th\u00e0nh ph\u1ed1, ph\u00e2n chia t\u1eebng nh\u00f3m \u0111\u1ed1i t\u01b0\u1ee3ng x\u00e9t nghi\u1ec7m c\u1ee5 th\u1ec3 theo nguy", "H\u00e0 N\u1ed9i b\u1eb1ng m\u1ecdi bi\u1ec7n ph\u00e1p t\u1eadn d\u1ee5ng t\u1ed1i \u0111a \"th\u1eddi gian v\u00e0ng\" c\u00e1c ng\u00e0y gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i th\u1ef1c hi\u1ec7n x\u00e9t nghi\u1ec7m tr\u00ean di\u1ec7n r\u1ed9ng \u0111\u1ea3m b\u1ea3o an to\u00e0n \u1edf m\u1ee9c t\u1ed1i \u0111a, k\u1ebft h\u1ee3p v\u1edbi c\u00e1c ho\u1ea1t \u0111\u1ed9ng x\u00e9t nghi\u1ec7m theo truy v\u1ebft, \u0111\u00e1nh gi\u00e1 nguy c\u01a1 l\u00e2y nhi\u1ec5m \u0111\u1ec3 trong th\u1eddi gian ng\u1eafn nh\u1ea5t \"b\u00f3c t\u00e1ch tri\u1ec7t \u0111\u1ec3 F0\".", "H\u00e0 N\u1ed9i t\u1eadp trung m\u1ecdi ngu\u1ed3n l\u1ef1c, x\u00e9t nghi\u1ec7m theo truy v\u1ebft, khoanh v\u00f9ng, b\u00f3c t\u00e1ch tri\u1ec7t \u0111\u1ec3 F0, ki\u1ec3m so\u00e1t kh\u00f4ng \u0111\u1ec3 d\u1ecbch b\u1ec7nh l\u00e2y lan, b\u00f9ng ph\u00e1t."], "content_summary": "\"Trong nh\u1eefng ng\u00e0y g\u1ea7n \u0111\u00e2y, th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i ti\u1ebfp t\u1ee5c ghi nh\u1eadn s\u1ed1 ca m\u1eafc m\u1edbi \u1edf m\u1ee9c cao (trung b\u00ecnh t\u1eeb 60 \u0111\u1ebfn 80 ca m\u1eafc m\u1edbi/ng\u00e0y) \u0111\u1eb7c bi\u1ec7t \u0111\u00e3 c\u00f3 nhi\u1ec1u ch\u00f9m ca b\u1ec7nh ph\u1ee9c t\u1ea1p v\u1edbi s\u1ed1 l\u01b0\u1ee3ng ca m\u1eafc l\u1edbn, nhi\u1ec1u ca b\u1ec7nh ch\u01b0a x\u00e1c \u0111\u1ecbnh \u0111\u01b0\u1ee3c ngu\u1ed3n l\u00e2y. Trong kho\u1ea3ng th\u1eddi gian t\u1eeb nay \u0111\u1ebfn ng\u00e0y 17/8, th\u00e0nh ph\u1ed1 t\u1eadp trung th\u1ef1c hi\u1ec7n x\u00e9t nghi\u1ec7m t\u1ed1i \u0111a kho\u1ea3ng 1,3 tri\u1ec7u m\u1eabu b\u1eb1ng k\u1ef9 thu\u1eadt RT-PCR cho to\u00e0n b\u1ed9 ng\u01b0\u1eddi d\u00e2n trong \u201cv\u00f9ng \u0111\u1ecf\u201d l\u00e0 khu v\u1ef1c trong c\u00e1c x\u00e3, ph\u01b0\u1eddng nguy c\u01a1 r\u1ea5t cao theo Quy\u1ebft \u0111\u1ecbnh s\u1ed1 2686/Q\u0110-BC\u0110QG, c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng nguy c\u01a1 cao c\u0103n c\u1ee9 theo y\u1ebfu t\u1ed1 d\u1ecbch t\u1ec5, c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng di chuy\u1ec3n nhi\u1ec1u, ti\u1ebfp x\u00fac nhi\u1ec1u nh\u01b0: chu\u1ed7i cung \u1ee9ng, ch\u1ee3, c\u00f4ng nh\u00e2n, b\u1ea3o v\u1ec7 c\u00e1c t\u00f2a nh\u00e0... v\u00e0 c\u00e1c khu v\u1ef1c nguy c\u01a1 cao kh\u00e1c (\u0111\u1ed1i t\u01b0\u1ee3ng nguy c\u01a1 cao kh\u00e1c theo ch\u1ec9 \u0111\u1ecbnh chuy\u00ean m\u00f4n v\u1ec1 d\u1ecbch t\u1ec5). Nh\u1ea5n m\u1ea1nh v\u1ec1 k\u1ebf ho\u1ea1ch l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m n\u00e0y, b\u00e0 Tr\u1ea7n Th\u1ecb Nh\u1ecb H\u00e0, Gi\u00e1m \u0111\u1ed1c S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i kh\u1eb3ng \u0111\u1ecbnh, c\u00f9ng v\u1edbi chi\u1ebfn d\u1ecbch ti\u00eam ch\u1ee7ng vaccine l\u1edbn nh\u1ea5t, \u0111\u00e2y c\u0169ng l\u00e0 \u0111\u1ee3t l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m l\u1edbn nh\u1ea5t t\u1eeb tr\u01b0\u1edbc \u0111\u1ebfn nay trong c\u00f4ng t\u00e1c ph\u00f2ng, ch\u1ed1ng d\u1ecbch b\u1ec7nh Covid-19.\"", "total_facebook_viral": 0}, {"url": "https://www.sggp.org.vn/ha-noi-xet-nghiem-dien-rong-hon-3-trieu-nguoi-de-boc-tach-triet-de-f0-753177.html", "domain": "sggp.org.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng h\u01a1n 3 tri\u1ec7u ng\u01b0\u1eddi \u0111\u1ec3 b\u00f3c t\u00e1ch tri\u1ec7t \u0111\u1ec3 F0", "snippet": "H\u00e0 N\u1ed9i b\u1eb1ng m\u1ecdi bi\u1ec7n ph\u00e1p t\u1eadn d\u1ee5ng t\u1ed1i \u0111a \"th\u1eddi gian v\u00e0ng\" c\u00e1c ng\u00e0y gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i th\u1ef1c hi\u1ec7n x\u00e9t nghi\u1ec7m tr\u00ean di\u1ec7n r\u1ed9ng \u0111\u1ea3m b\u1ea3o an to\u00e0n \u1edf m\u1ee9c t\u1ed1i \u0111a, k\u1ebft h\u1ee3p v\u1edbi c\u00e1c ho\u1ea1t \u0111\u1ed9ng x\u00e9t nghi\u1ec7m theo truy v\u1ebft, \u0111\u00e1nh gi\u00e1 nguy c\u01a1 l\u00e2y nhi\u1ec5m \u0111\u1ec3 trong th\u1eddi gian ng\u1eafn nh\u1ea5t \"b\u00f3c t\u00e1ch tri\u1ec7t \u0111\u1ec3 F0\".", "created_time": 1628656945, "id": "sggp.org.vn_753177", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.nguoiduatin.vn/ha-noi-tan-dung-thoi-gian-vang-xet-nghiem-dien-rong-toan-thanh-pho-a523881.html", "domain": "nguoiduatin.vn", "title": "H\u00e0 N\u1ed9i t\u1eadn d\u1ee5ng \u201cth\u1eddi gian v\u00e0ng\u201d x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng to\u00e0n th\u00e0nh ph\u1ed1", "snippet": "H\u00e0 N\u1ed9i t\u1eadp trung m\u1ecdi ngu\u1ed3n l\u1ef1c, x\u00e9t nghi\u1ec7m theo truy v\u1ebft, khoanh v\u00f9ng, b\u00f3c t\u00e1ch tri\u1ec7t \u0111\u1ec3 F0, ki\u1ec3m so\u00e1t kh\u00f4ng \u0111\u1ec3 d\u1ecbch b\u1ec7nh l\u00e2y lan, b\u00f9ng ph\u00e1t.", "created_time": 1628652395, "id": "nguoiduatin.vn_a523881", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://nhadautu.vn/ha-noi-xet-nghiem-sang-loc-dien-rong-toan-thanh-pho-d56313.html", "domain": "nhadautu.vn", "title": "H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc di\u1ec7n r\u1ed9ng to\u00e0n th\u00e0nh ph\u1ed1", "snippet": "Nh\u1eb1m ki\u1ec3m so\u00e1t t\u1ed1t h\u01a1n d\u1ecbch b\u1ec7nh tr\u01b0\u1edbc ng\u00e0y 25/8, TP. H\u00e0 N\u1ed9i \u0111\u00e3 l\u1eadp k\u1ebf ho\u1ea1ch tri\u1ec3n khai x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng \u0111\u1ec3 ch\u1ee7 \u0111\u1ed9ng ph\u00f2ng ch\u1ed1ng d\u1ecbch b\u1ec7nh COVID-19, ph\u00e2n chia t\u1eebng nh\u00f3m \u0111\u1ed1i t\u01b0\u1ee3ng x\u00e9t nghi\u1ec7m c\u1ee5 th\u1ec3 theo nguy c\u01a1 nh\u00f3m \u0111\u1ecf, nh\u00f3m da cam, nh\u00f3m xanh.", "created_time": 1628646120, "id": "nhadautu.vn_d56313", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://danviet.vn/ha-noi-tong-luc-xet-nghiem-300000-mau-test-covid-19-vet-sach-f0-ngoai-cong-dong-2021081018494092.htm", "domain": "danviet.vn", "title": "H\u00e0 N\u1ed9i t\u1ed5ng l\u1ef1c x\u00e9t nghi\u1ec7m 300.000 m\u1eabu test Covid-19 \"v\u00e9t s\u1ea1ch\" F0 ngo\u00e0i c\u1ed9ng \u0111\u1ed3ng", "snippet": "Ng\u00e0y 10/8, H\u00e0 N\u1ed9i b\u1eaft \u0111\u1ea7u t\u1ed5ng l\u1ef1c tri\u1ec3n khai l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m Covid-19 t\u1ea1i c\u00e1c qu\u1eadn, huy\u1ec7n, th\u1ecb x\u00e3, cho khu v\u1ef1c v\u00e0 nh\u00f3m ng\u01b0\u1eddi nguy c\u01a1 cao trong 7 ng\u00e0y \u0111\u1ec3 \"v\u00e9t s\u1ea1ch\" F0 ngo\u00e0i c\u1ed9ng \u0111\u1ed3ng.", "created_time": 1628596800, "id": "danviet.vn_2021081018494092", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kinhtedothi.vn/quan-hai-ba-trung-lay-25000-mau-xet-nghiem-covid-19-cho-nguoi-dan-tai-nhung-khu-vuc-nguy-co-cao-430662.html", "domain": "kinhtedothi.vn", "title": "Qu\u1eadn Hai B\u00e0 Tr\u01b0ng: L\u1ea5y 25.000 m\u1eabu x\u00e9t nghi\u1ec7m Covid-19 cho ng\u01b0\u1eddi d\u00e2n t\u1ea1i nh\u1eefng khu v\u1ef1c nguy c\u01a1 cao", "snippet": "Kinhtedothi-Trong \u0111\u1ee3t l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m n\u00e0y, Trung t\u00e2m Y t\u1ebf qu\u1eadn Hai B\u00e0 Tr\u01b0ng s\u1ebd ch\u1ee7 tr\u00ec t\u1ed5 ch\u1ee9c l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m nh\u1eb1m ph\u00e1t hi\u1ec7n s\u1edbm c\u00e1c tr\u01b0\u1eddng h\u1ee3p nhi\u1ec5m SARS-CoV-2 t\u1ea1i 8 ph\u01b0\u1eddng c\u00f3 nhi\u1ec1u ca b\u1ec7nh, nguy c\u01a1 cao. V\u1edbi 10 ph\u01b0\u1eddng c\u00f2n l\u1ea1i, s\u1ebd l\u1ea5y m\u1eabu v\u1edbi c\u00e1c nh\u00f3m \u0111\u1ed1i t\u01b0\u1ee3ng c\u00f3 nguy c\u01a1 nh\u01b0 ng\u01b0\u1eddi l\u00e0m d\u1ecbch v\u1ee5 v\u1eadn chuy\u1ec3n h\u00e0ng h\u00f3a, nh\u00e2n vi\u00ean, ti\u1ec3u th\u01b0\u01a1ng b\u00e1n h\u00e0ng \u1edf ch\u1ee3, si\u00eau th\u1ecb, c\u1eeda h\u00e0ng ti\u1ec7n \u00edch, nh\u00e2n vi\u00ean v\u1eadn chuy\u1ec3n ph\u00e2n ph\u1ed1i m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu...", "created_time": 1628594520, "id": "kinhtedothi.vn_430662", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://ngaynay.vn/ha-noi-thuc-hien-7-ngay-cao-diem-xet-nghiem-dien-rong-300-000-nguoi-post111043.html", "domain": "ngaynay.vn", "title": "H\u00e0 N\u1ed9i th\u1ef1c hi\u1ec7n 7 ng\u00e0y cao \u0111i\u1ec3m x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng 300.000 ng\u01b0\u1eddi", "snippet": "H\u00e0 N\u1ed9i d\u1ef1 ki\u1ebfn l\u1ea5y kho\u1ea3ng 300.000 m\u1eabu test COVID-19 nguy c\u01a1 cao t\u1ea1i 30 qu\u1eadn, huy\u1ec7n, th\u1ecb x\u00e3 trong 7 ng\u00e0y t\u1eeb 10 - 17/8 \u0111\u1ec3 \"b\u00f3c s\u1ea1ch\" F0 kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng.", "created_time": 1628588638, "id": "ngaynay.vn_111043", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghieptiepthi.vn/anh-ha-noi-bat-dau-xet-nghiem-dien-rong-cho-khoang-300000-nguoi-de-vet-sach-f0-ra-khoi-cong-dong-161211008185831519.htm", "domain": "doanhnghieptiepthi.vn", "title": "\u1ea2nh: H\u00e0 N\u1ed9i b\u1eaft \u0111\u1ea7u x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng cho kho\u1ea3ng 300.000 ng\u01b0\u1eddi \u0111\u1ec3 \"v\u00e9t s\u1ea1ch\" F0 ra kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng", "snippet": "Ng\u00e0y 10/8, TP H\u00e0 N\u1ed9i b\u1eaft \u0111\u1ea7u l\u1ea5y m\u1eabu x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng nh\u1eb1m ph\u00e1t hi\u1ec7n s\u1edbm ng\u01b0\u1eddi m\u1eafc b\u1ec7nh trong c\u00e1c khu v\u1ef1c nguy c\u01a1 cao, c\u00e1c nh\u00f3m nguy c\u01a1 cao, d\u1ec5 m\u1eafc b\u1ec7nh v\u00e0 l\u00e2y lan.", "created_time": 1628595660, "id": "doanhnghieptiepthi.vn_161211008185831519", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghiepvn.vn/tin-tuc/anh-ha-noi-xet-nghiem-dien-rong-voi-khoang-300-000-nguoi-de-truy-lung-f0/20210810063513970", "domain": "doanhnghiepvn.vn", "title": "\u1ea2nh: H\u00e0 N\u1ed9i x\u00e9t nghi\u1ec7m di\u1ec7n r\u1ed9ng v\u1edbi kho\u1ea3ng 300.000 ng\u01b0\u1eddi \u0111\u1ec3 'truy l\u00f9ng' F0", "snippet": "T\u1eeb ng\u00e0y 10 - 17/8, \u0111\u1ec3 \"v\u00e9t s\u1ea1ch\" F0 kh\u1ecfi c\u1ed9ng \u0111\u1ed3ng, H\u00e0 N\u1ed9i d\u1ef1 ki\u1ebfn l\u1ea5y kho\u1ea3ng 300.000 m\u1eabu test COVID-19 thu\u1ed9c nh\u00f3m nguy c\u01a1 cao t\u1ea1i 30 qu\u1eadn, huy\u1ec7n, th\u1ecb x\u00e3.", "created_time": 1628595600, "id": "doanhnghiepvn.vn_20210810063513970", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "10": [{"url": "https://vnmedia.vn/su-kien-va-van-de/202108/tu-tap-danh-bac-khi-dang-gian-cach-5-doi-tuong-bi-phat-hon-40-trieu-dong-7891bcf/", "domain": "vnmedia.vn", "title": "T\u1ee5 t\u1eadp \u0111\u00e1nh b\u1ea1c khi \u0111ang gi\u00e3n c\u00e1ch, 5 \u0111\u1ed1i t\u01b0\u1ee3ng b\u1ecb ph\u1ea1t h\u01a1n 40 tri\u1ec7u \u0111\u1ed3ng", "snippet": "(VnMedia) - C\u00f4ng an huy\u1ec7n \u0110\u00f4ng Anh (TP H\u00e0 N\u1ed9i) \u0111\u00e3 ra quy\u1ebft \u0111\u1ecbnh x\u1eed ph\u1ea1t vi ph\u1ea1m h\u00e0nh ch\u00ednh \u0111\u1ed1i v\u1edbi 5 \u0111\u1ed1i t\u01b0\u1ee3ng\u00a0kh\u00f4ng tu\u00e2n th\u1ee7 quy \u0111\u1ecbnh gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i, t\u1ee5 t\u1eadp \u0111\u00e1nh b\u1ea1c, v\u1edbi s\u1ed1 ti\u1ec1n 43,5 tri\u1ec7u \u0111\u1ed3ng...", "created_time": 1628665620, "id": "2b0603558e27db321f5afa1ccf85d709ce55aa83", "score": 0.0, "title_summarize": ["(VnMedia) - 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C\u00f4ng an huy\u1ec7n \u0110\u00f4ng Anh (TP H\u00e0 N\u1ed9i) \u0111\u00e3 ra quy\u1ebft \u0111\u1ecbnh x\u1eed ph\u1ea1t vi ph\u1ea1m h\u00e0nh ch\u00ednh \u0111\u1ed1i v\u1edbi 5 \u0111\u1ed1i t\u01b0\u1ee3ng\u00a0kh\u00f4ng tu\u00e2n th\u1ee7 quy \u0111\u1ecbnh gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i, t\u1ee5 t\u1eadp \u0111\u00e1nh b\u1ea1c, v\u1edbi s\u1ed1 ti\u1ec1n 43,5 tri\u1ec7u \u0111\u1ed3ng... Tr\u01b0\u1edbc \u0111\u00f3, kho\u1ea3ng 11h30 ng\u00e0y 9/8, C\u00f4ng an x\u00e3 Uy N\u1ed7, huy\u1ec7n \u0110\u00f4ng Anh l\u00e0m nhi\u1ec7m v\u1ee5 t\u1ea1i th\u00f4n Ph\u00fac L\u1ed9c, x\u00e3 Uy N\u1ed7, ph\u00e1t hi\u1ec7n t\u1ea1i ph\u00f2ng kh\u00e1ch c\u1ee7a gia \u0111\u00ecnh \u00f4ng N.V.A SN 1963; \u1edf th\u00f4n Ph\u00fac L\u1ed9c, x\u00e3 Uy N\u1ed7, huy\u1ec7n \u0110\u00f4ng Anh, H\u00e0 N\u1ed9i) c\u00f3 5 ng\u01b0\u1eddi \u0111ang t\u1ee5 t\u1eadp, vi ph\u1ea1m quy \u0111\u1ecbnh v\u1ec1 ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19. 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tri\u1ec7u \u0111\u1ed3ng \u0111\u1ed1i v\u1edbi 5 \u0111\u1ed1i t\u01b0\u1ee3ng kh\u00f4ng tu\u00e2n th\u1ee7 quy \u0111\u1ecbnh gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i, t\u1ee5 t\u1eadp \u0111\u00e1nh b\u1ea1c.", "created_time": 1628645520, "id": "hanoimoi.com.vn_1008572", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://congluan.vn/ha-noi-danh-bac-giua-mua-dich-5-doi-tuong-bi-xu-phat-43-trieu-dong-post149581.html", "domain": "congluan.vn", "title": "H\u00e0 N\u1ed9i: \u0110\u00e1nh b\u1ea1c gi\u1eefa m\u00f9a d\u1ecbch, 5 \u0111\u1ed1i t\u01b0\u1ee3ng b\u1ecb x\u1eed ph\u1ea1t 43 tri\u1ec7u \u0111\u1ed3ng", "snippet": "(CLO) Ng\u00e0y 11/8, th\u00f4ng tin t\u1eeb C\u00f4ng an huy\u1ec7n \u0110\u00f4ng Anh (H\u00e0 N\u1ed9i) cho bi\u1ebft \u0111\u01a1n v\u1ecb \u0111\u00e3 ra quy\u1ebft \u0111\u1ecbnh x\u1eed ph\u1ea1t vi ph\u1ea1m h\u00e0nh ch\u00ednh t\u1ed5ng c\u1ed9ng 43,5 tri\u1ec7u \u0111\u1ed3ng \u0111\u1ed1i v\u1edbi 5 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\u0111\u00e1nh ch\u1eafn \u0103n ti\u1ec1n.", "created_time": 1628664402, "id": "ded427c9660862625f12b9ce8c8be96d188f6df2", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/nhom-nguoi-tu-tap-dot-dich-bi-phat-hon-43-trieu-post1249729.html", "domain": "zingnews.vn", "title": "Nh\u00f3m ng\u01b0\u1eddi t\u1ee5 t\u1eadp \u0111\u1ee3t d\u1ecbch b\u1ecb ph\u1ea1t h\u01a1n 43 tri\u1ec7u", "snippet": "Trong c\u0103n nh\u00e0 \u1edf huy\u1ec7n \u0110\u00f4ng Anh, H\u00e0 N\u1ed9i, c\u00f4ng an ph\u00e1t hi\u1ec7n 4 ng\u01b0\u1eddi \u0111ang \u0111\u00e1nh ch\u1eafn \u0103n ti\u1ec1n.", "created_time": 1628664402, "id": "zingnews.vn_1249729", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "11": [{"url": "http://vneconomy.vn/tham-cong-truong-xay-dung-benh-vien-da-chien-500-giuong-cua-ha-noi.htm", "domain": "vneconomy.vn", "title": "Th\u0103m c\u00f4ng tr\u01b0\u1eddng x\u00e2y d\u1ef1ng B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn 500 gi\u01b0\u1eddng c\u1ee7a H\u00e0 N\u1ed9i", "snippet": "T\u1ea1i ng\u00f5 587 Tam Trinh (qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i) nh\u1eefng ng\u00e0y n\u00e0y, h\u00e0ng tr\u0103m c\u00f4ng nh\u00e2n \u0111ang ti\u1ebfn h\u00e0nh x\u00e2y d\u1ef1ng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn h\u1ed3i s\u1ee9c \u0111i\u1ec1u tr\u1ecb cho b\u1ec7nh nh\u00e2n Covid-19 n\u1eb7ng v\u00e0 nguy k\u1ecbch tr\u00ean \u0111\u1ecba b\u00e0n Th\u1ee7 \u0111\u00f4\u2026", "created_time": 1628607840, "id": "2e4036ed0c62d1cecb3f1a5f8e49e42e5673a4c4", "score": 0.0, "title_summarize": ["T\u1ea1i ng\u00f5 587 Tam Trinh (qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i) nh\u1eefng ng\u00e0y n\u00e0y, h\u00e0ng tr\u0103m c\u00f4ng nh\u00e2n \u0111ang ti\u1ebfn h\u00e0nh x\u00e2y d\u1ef1ng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn h\u1ed3i s\u1ee9c \u0111i\u1ec1u tr\u1ecb cho b\u1ec7nh nh\u00e2n Covid-19 n\u1eb7ng v\u00e0 nguy k\u1ecbch tr\u00ean \u0111\u1ecba b\u00e0n Th\u1ee7 \u0111\u00f4\u2026", "Sau 16 ng\u00e0y x\u00e2y d\u1ef1ng, v\u1edbi kho\u1ea3ng 500 c\u00f4ng nh\u00e2n vi\u00ean l\u00e0m vi\u1ec7c li\u00ean t\u1ee5c, B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn h\u1ed3i s\u1ee9c t\u00edch c\u1ef1c COVID-19, n\u01a1i \u0111i\u1ec1u tr\u1ecb b\u1ec7nh nh\u00e2n COVID-19 n\u1eb7ng v\u00e0 nguy k\u1ecbch t\u1ea1i Ho\u00e0ng Mai c\u1ee7a TP H\u00e0 N\u1ed9i \u0111\u00e3 c\u01a1 b\u1ea3n ho\u00e0n th\u00e0nh.", "TPO - V\u1edbi kho\u1ea3ng 500\u00a0c\u00f4ng nh\u00e2n c\u00f9ng h\u00e0ng ch\u1ee5c m\u00e1y m\u00f3c thay nhau l\u00e0m vi\u1ec7c 24/24h tr\u00ean c\u00f4ng tr\u01b0\u1eddng\u00a0b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn t\u1ea1i qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i, sau h\u01a1n 10 ng\u00e0y th\u1ea7n t\u1ed1c x\u00e2y d\u1ef1ng, nhi\u1ec1u h\u1ea1ng m\u1ee5c \u0111\u00e3 c\u01a1 b\u1ea3n\u00a0ho\u00e0n thi\u1ec7n."], "content_summary": "\"Chi\u1ec1u 10/8, \u1ee6y vi\u00ean B\u1ed9 Ch\u00ednh tr\u1ecb, B\u00ed th\u01b0 Th\u00e0nh \u1ee7y H\u00e0 N\u1ed9i \u0110inh Ti\u1ebfn D\u0169ng \u0111\u00e3 c\u00f3 bu\u1ed5i l\u00e0m vi\u1ec7c v\u1edbi Qu\u1eadn \u1ee7y Ho\u00e0ng Mai v\u1ec1 c\u00f4ng t\u00e1c ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19; \u0111\u1ed3ng th\u1eddi ki\u1ec3m tra c\u00f4ng t\u00e1c x\u00e2y d\u1ef1ng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn h\u1ed3i s\u1ee9c \u0111i\u1ec1u tr\u1ecb b\u1ec7nh nh\u00e2n Covid-19 n\u1eb7ng v\u00e0 nguy k\u1ecbch t\u1ea1i ph\u01b0\u1eddng Y\u00ean S\u1edf, qu\u1eadn Ho\u00e0ng Mai. X\u00e1c \u0111\u1ecbnh \u0111\u00e2y l\u00e0 c\u00f4ng tr\u00ecnh c\u1ea5p b\u00e1ch ph\u1ee5c v\u1ee5 c\u00f4ng t\u00e1c ph\u00f2ng, ch\u1ed1ng d\u1ecbch\u00a0Covid-19, b\u1ec7nh vi\u1ec7n \u0111\u00e3 \u0111\u01b0\u1ee3c th\u00e0nh ph\u1ed1\u00a0H\u00e0 N\u1ed9i\u00a0quan t\u00e2m, h\u1ed7 tr\u1ee3 v\u00e0 t\u1ea1o \u0111i\u1ec1u ki\u1ec7n \u0111\u1eb7c bi\u1ec7t \u0111\u1ec3 c\u00f3 th\u1ec3 thu\u1eadn l\u1ee3i thi c\u00f4ng trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i. B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn quy m\u00f4 l\u1edbn n\u00e0y b\u1eaft \u0111\u1ea7u x\u00e2y d\u1ef1ng t\u1eeb ng\u00e0y 24/7\u00a0v\u1edbi quy m\u00f4 t\u1eeb 500 \u2013 700 gi\u01b0\u1eddng b\u1ec7nh. Tuy nhi\u00ean, \u0111\u01b0\u1eddng v\u00e0o b\u1ec7nh vi\u1ec7n v\u1eabn \u0111ang v\u01b0\u1edbng m\u1eafc trong c\u00f4ng t\u00e1c gi\u1ea3i ph\u00f3ng m\u1eb7t b\u1eb1ng.\"", "total_facebook_viral": 0}, {"url": "https://kienthuc.net.vn/xa-hoi/benh-vien-da-chien-tai-ha-noi-sau-16-ngay-than-toc-xay-dung-1575519.html", "domain": "kienthuc.net.vn", "title": "B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn t\u1ea1i H\u00e0 N\u1ed9i sau 16 ng\u00e0y th\u1ea7n t\u1ed1c x\u00e2y d\u1ef1ng", "snippet": "Sau 16 ng\u00e0y x\u00e2y d\u1ef1ng, v\u1edbi kho\u1ea3ng 500 c\u00f4ng nh\u00e2n vi\u00ean l\u00e0m vi\u1ec7c li\u00ean t\u1ee5c, B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn h\u1ed3i s\u1ee9c t\u00edch c\u1ef1c COVID-19, n\u01a1i \u0111i\u1ec1u tr\u1ecb b\u1ec7nh nh\u00e2n COVID-19 n\u1eb7ng v\u00e0 nguy k\u1ecbch t\u1ea1i Ho\u00e0ng Mai c\u1ee7a TP H\u00e0 N\u1ed9i \u0111\u00e3 c\u01a1 b\u1ea3n ho\u00e0n th\u00e0nh.", "created_time": 1628644201, "id": "kienthuc.net.vn_1575519", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://tienphong.vn/benh-vien-da-chien-lon-nhat-ha-noi-hien-ra-sao-sau-hon-10-ngay-than-toc-xay-dung-post1364556.tpo", "domain": "tienphong.vn", "title": "B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn l\u1edbn nh\u1ea5t H\u00e0 N\u1ed9i hi\u1ec7n ra sao sau h\u01a1n 10 ng\u00e0y th\u1ea7n t\u1ed1c x\u00e2y d\u1ef1ng?", "snippet": "TPO - V\u1edbi kho\u1ea3ng 500\u00a0c\u00f4ng nh\u00e2n c\u00f9ng h\u00e0ng ch\u1ee5c m\u00e1y m\u00f3c thay nhau l\u00e0m vi\u1ec7c 24/24h tr\u00ean c\u00f4ng tr\u01b0\u1eddng\u00a0b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn t\u1ea1i qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i, sau h\u01a1n 10 ng\u00e0y th\u1ea7n t\u1ed1c x\u00e2y d\u1ef1ng, nhi\u1ec1u h\u1ea1ng m\u1ee5c \u0111\u00e3 c\u01a1 b\u1ea3n\u00a0ho\u00e0n thi\u1ec7n.", "created_time": 1628598905, "id": "tienphong.vn_1364556", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kienthuc.net.vn/xa-hoi/benh-vien-da-chien-lon-nhat-ha-noi-sau-hon-10-ngay-xay-dung-1575452.html", "domain": "kienthuc.net.vn", "title": "B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn l\u1edbn nh\u1ea5t H\u00e0 N\u1ed9i sau h\u01a1n 10 ng\u00e0y x\u00e2y d\u1ef1ng", "snippet": "V\u1edbi kho\u1ea3ng 500 c\u00f4ng nh\u00e2n c\u00f9ng h\u00e0ng ch\u1ee5c m\u00e1y m\u00f3c thay nhau l\u00e0m vi\u1ec7c 24/24h tr\u00ean c\u00f4ng tr\u01b0\u1eddng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn t\u1ea1i qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i, sau h\u01a1n 10 ng\u00e0y th\u1ea7n t\u1ed1c x\u00e2y d\u1ef1ng, nhi\u1ec1u h\u1ea1ng m\u1ee5c \u0111\u00e3 c\u01a1 b\u1ea3n ho\u00e0n thi\u1ec7n.", "created_time": 1628604540, "id": "kienthuc.net.vn_1575452", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://danviet.vn/nhung-hinh-anh-moi-nhat-tren-dai-cong-truong-xay-dung-benh-vien-da-chien-o-ha-noi-2021081108000101.htm", "domain": "danviet.vn", "title": "Nh\u1eefng h\u00ecnh \u1ea3nh m\u1edbi nh\u1ea5t tr\u00ean \u0111\u1ea1i c\u00f4ng tr\u01b0\u1eddng x\u00e2y d\u1ef1ng B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn \u1edf H\u00e0 N\u1ed9i", "snippet": "Kho\u1ea3ng 500 c\u00f4ng nh\u00e2n c\u00f9ng h\u00e0ng ch\u1ee5c m\u00e1y m\u00f3c g\u1ea5p r\u00fat l\u00e0m vi\u1ec7c 24/24h tr\u00ean c\u00f4ng tr\u01b0\u1eddng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn t\u1ea1i qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i. D\u01b0\u1edbi \u0111\u00e2y l\u00e0 nh\u1eefng h\u00ecnh \u1ea3nh m\u1edbi nh\u1ea5t v\u1ec1 nh\u1ecbp \u0111\u1ed9 l\u00e0m vi\u1ec7c h\u1ed1i h\u1ea3 tr\u00ean c\u00f4ng tr\u00ecnh n\u00e0y.", "created_time": 1628645820, "id": "danviet.vn_2021081108000101", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://khoe365.nguoiduatin.vn/nhung-hinh-anh-moi-nhat-tren-dai-cong-truong-xay-dung-benh-vien-da-chien-o-ha-noi-77440.html", "domain": "khoe365.nguoiduatin.vn", "title": "Nh\u1eefng h\u00ecnh \u1ea3nh m\u1edbi nh\u1ea5t tr\u00ean \u0111\u1ea1i c\u00f4ng tr\u01b0\u1eddng x\u00e2y d\u1ef1ng B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn \u1edf H\u00e0 N\u1ed9i", "snippet": "Kho\u1ea3ng 500 c\u00f4ng nh\u00e2n c\u00f9ng h\u00e0ng ch\u1ee5c m\u00e1y m\u00f3c g\u1ea5p r\u00fat l\u00e0m vi\u1ec7c 24/24h tr\u00ean c\u00f4ng tr\u01b0\u1eddng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn t\u1ea1i qu\u1eadn Ho\u00e0ng Mai, H\u00e0 N\u1ed9i. D\u01b0\u1edbi \u0111\u00e2y l\u00e0 nh\u1eefng h\u00ecnh \u1ea3nh m\u1edbi nh\u1ea5t v\u1ec1 nh\u1ecbp \u0111\u1ed9 l\u00e0m vi\u1ec7c h\u1ed1i h\u1ea3 tr\u00ean c\u00f4ng tr\u00ecnh n\u00e0y.", "created_time": 1628655900, "id": "13ce33ea4f47fd89a3a3d7566417c1fc5f000021", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://petrotimes.vn/can-canh-cong-truong-xay-dung-benh-vien-da-chien-dieu-tri-covid-19-tai-ha-noi-620978.html", "domain": "petrotimes.vn", "title": "C\u1eadn c\u1ea3nh c\u00f4ng tr\u01b0\u1eddng x\u00e2y d\u1ef1ng b\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn \u0111i\u1ec1u tr\u1ecb Covid-19 t\u1ea1i H\u00e0 N\u1ed9i", "snippet": "B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn h\u1ed3i s\u1ee9c \u0111i\u1ec1u tr\u1ecb Covid-19 c\u00f3 quy m\u00f4 l\u1edbn t\u1ea1i qu\u1eadn Ho\u00e0ng Mai \u0111ang \u0111\u01b0\u1ee3c th\u1ea7n t\u1ed1c x\u00e2y d\u1ef1ng.", "created_time": 1628651905, "id": "petrotimes.vn_620978", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://dantri.com.vn/xa-hoi/ha-noi-muc-so-thi-canh-than-toc-xay-benh-vien-da-chien-hoang-mai-20210810200928490.htm", "domain": "dantri.com.vn", "title": "H\u00e0 N\u1ed9i: \"M\u1ee5c s\u1edf th\u1ecb\" c\u1ea3nh th\u1ea7n t\u1ed1c x\u00e2y B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn Ho\u00e0ng Mai", "snippet": "(D\u00e2n tr\u00ed) - B\u1ec7nh vi\u1ec7n d\u00e3 chi\u1ebfn qu\u1eadn Ho\u00e0ng Mai b\u01b0\u1edbc v\u00e0o giai \u0111o\u1ea1n thi c\u00f4ng \"n\u01b0\u1edbc r\u00fat\". Tr\u00ean c\u00f4ng tr\u01b0\u1eddng, 1.500 c\u00f4ng nh\u00e2n ch\u1ea1y \u0111ua m\u1ed7i ng\u00e0y, chia 3 ca, l\u00e0m vi\u1ec7c 24/24 gi\u1edd \u0111\u1ec3 g\u1ea5p r\u00fat ho\u00e0n th\u00e0nh d\u1ef1 \u00e1n.", "created_time": 1628605834, "id": "dantri.com.vn_20210810200928490", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "12": [{"url": "https://zingnews.vn/ha-noi-ghi-nhan-62-nguoi-nhiem-ncov-trong-ngay-108-post1249060.html", "domain": "news.zing.vn", "title": "H\u00e0 N\u1ed9i ghi nh\u1eadn 62 ng\u01b0\u1eddi nhi\u1ec5m nCoV trong ng\u00e0y 10/8", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: C\u00e1c tr\u01b0\u1eddng h\u1ee3p n\u00e0y \u0111a s\u1ed1 l\u00e0 F1, li\u00ean quan F0 \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n qua x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u01b0\u1edbc \u0111\u00f3.", "created_time": 1628597040, "id": "news.zing.vn_post1249060", "score": 0.0, "title_summarize": ["D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: C\u00e1c tr\u01b0\u1eddng h\u1ee3p n\u00e0y \u0111a s\u1ed1 l\u00e0 F1, li\u00ean quan F0 \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n qua x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u01b0\u1edbc \u0111\u00f3.", "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: C\u00e1c tr\u01b0\u1eddng h\u1ee3p n\u00e0y \u0111a s\u1ed1 l\u00e0 F1, li\u00ean quan F0 \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n qua x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u01b0\u1edbc \u0111\u00f3.", "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: C\u00e1c tr\u01b0\u1eddng h\u1ee3p n\u00e0y \u0111a s\u1ed1 l\u00e0 F1, li\u00ean quan F0 \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n qua x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u01b0\u1edbc \u0111\u00f3."], "content_summary": "\"Theo th\u00f4ng tin t\u1eeb S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i t\u1ed1i 10/8, m\u1ed9t tr\u01b0\u1eddng h\u1ee3p li\u00ean quan ch\u00f9m l\u00e2y nhi\u1ec5m t\u1ea1i C\u00f4ng ty SEI, khu c\u00f4ng nghi\u1ec7p Th\u0103ng Long, v\u1eeba c\u00f3 k\u1ebft qu\u1ea3 x\u00e9t nghi\u1ec7m d\u01b0\u01a1ng t\u00ednh v\u1edbi nCoV l\u00e0 V.T.S., nam, 34 tu\u1ed5i, tr\u00fa t\u1ea1i th\u00f4n B\u1ea7u, Kim Chung, \u0110\u00f4ng Anh. Nh\u01b0 v\u1eady, t\u1eeb 6h \u0111\u1ebfn 18h ng\u00e0y 10/8, H\u00e0 N\u1ed9i x\u00e1c \u0111\u1ecbnh \u0111\u01b0\u1ee3c 62 tr\u01b0\u1eddng h\u1ee3p nhi\u1ec5m SARS-CoV0-2. Theo th\u1ed1ng k\u00ea c\u1ee7a S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i, c\u00e1c ch\u00f9m l\u00e2y nhi\u1ec5m m\u1edbi ph\u00e1t hi\u1ec7n t\u1eeb ng\u00e0y 5/7 \u0111\u1ebfn nay \u0111\u00e3 c\u00f3 1.646 tr\u01b0\u1eddng h\u1ee3p cho k\u1ebft qu\u1ea3 x\u00e9t nghi\u1ec7m d\u01b0\u01a1ng t\u00ednh v\u1edbi virus. M\u1ed9t s\u1ed1 ca b\u1ec7nh trong c\u1ed9ng \u0111\u1ed3ng bu\u1ed9c ph\u1ea3i \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n th\u00f4ng qua x\u00e9t nghi\u1ec7m v\u00e0 kh\u00f4ng c\u00f3 y\u1ebfu t\u1ed1 d\u1ecbch t\u1ec5.\"", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/ha-noi-ghi-nhan-62-nguoi-nhiem-ncov-trong-ngay-108-post1249060.html", "domain": "zingnews.vn", "title": "H\u00e0 N\u1ed9i ghi nh\u1eadn 62 ng\u01b0\u1eddi nhi\u1ec5m nCoV trong ng\u00e0y 10/8", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: C\u00e1c tr\u01b0\u1eddng h\u1ee3p n\u00e0y \u0111a s\u1ed1 l\u00e0 F1, li\u00ean quan F0 \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n qua x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u01b0\u1edbc \u0111\u00f3.", "created_time": 1628597080, "id": "zingnews.vn_1249060", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.vn/ha-noi-ghi-nhan-62-nguoi-nhiem-ncov-trong-ngay-108-post1249060.html", "domain": "trithuctructuyen.vn", "title": "H\u00e0 N\u1ed9i ghi nh\u1eadn 62 ng\u01b0\u1eddi nhi\u1ec5m nCoV trong ng\u00e0y 10/8", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: C\u00e1c tr\u01b0\u1eddng h\u1ee3p n\u00e0y \u0111a s\u1ed1 l\u00e0 F1, li\u00ean quan F0 \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n qua x\u00e9t nghi\u1ec7m s\u00e0ng l\u1ecdc tr\u01b0\u1edbc \u0111\u00f3.", "created_time": 1628597080, "id": "b656278038c8452373d3ef279156fec218e1058e", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.vn/ha-noi-phat-hien-28-nguoi-nhiem-ncov-post1249636.html", "domain": "trithuctructuyen.vn", "title": "H\u00e0 N\u1ed9i ph\u00e1t hi\u1ec7n 28 ng\u01b0\u1eddi nhi\u1ec5m nCoV", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: Ngo\u00e0i c\u00e1c tr\u01b0\u1eddng h\u1ee3p li\u00ean quan F0 \u0111\u01b0\u1ee3c s\u00e0ng l\u1ecdc, m\u1ed9t s\u1ed1 \u1ed5 d\u1ecbch c\u0169 t\u1ea1i H\u00e0 N\u1ed9i v\u1eabn c\u00f3 th\u00eam ng\u01b0\u1eddi nhi\u1ec5m nCoV tuy kh\u00f4ng nhi\u1ec1u.", "created_time": 1628661701, "id": "5d4b4984dc9a4eb6ee5853806fd3ed0873e3cc33", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/ha-noi-phat-hien-28-nguoi-nhiem-ncov-post1249636.html", "domain": "news.zing.vn", "title": "H\u00e0 N\u1ed9i ph\u00e1t hi\u1ec7n 28 ng\u01b0\u1eddi nhi\u1ec5m nCoV", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: Ngo\u00e0i c\u00e1c tr\u01b0\u1eddng h\u1ee3p li\u00ean quan F0 \u0111\u01b0\u1ee3c s\u00e0ng l\u1ecdc, m\u1ed9t s\u1ed1 \u1ed5 d\u1ecbch c\u0169 t\u1ea1i H\u00e0 N\u1ed9i v\u1eabn c\u00f3 th\u00eam ng\u01b0\u1eddi nhi\u1ec5m nCoV tuy kh\u00f4ng nhi\u1ec1u.", "created_time": 1628661660, "id": "news.zing.vn_post1249636", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/ha-noi-phat-hien-28-nguoi-nhiem-ncov-post1249636.html", "domain": "zingnews.vn", "title": "H\u00e0 N\u1ed9i ph\u00e1t hi\u1ec7n 28 ng\u01b0\u1eddi nhi\u1ec5m nCoV", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: Ngo\u00e0i c\u00e1c tr\u01b0\u1eddng h\u1ee3p li\u00ean quan F0 \u0111\u01b0\u1ee3c s\u00e0ng l\u1ecdc, m\u1ed9t s\u1ed1 \u1ed5 d\u1ecbch c\u0169 t\u1ea1i H\u00e0 N\u1ed9i v\u1eabn c\u00f3 th\u00eam ng\u01b0\u1eddi nhi\u1ec5m nCoV tuy kh\u00f4ng nhi\u1ec1u.", "created_time": 1628661701, "id": "zingnews.vn_1249636", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vnexpress.net/covid-19-hanoi-11-8-4338797.html", "domain": "vnexpress.net", "title": "H\u00e0 N\u1ed9i th\u00eam 3 ca nghi Covid-19", "snippet": "S\u1edf Y t\u1ebf H\u00e0 N\u1ed9i ghi nh\u1eadn 3 tr\u01b0\u1eddng h\u1ee3p d\u01b0\u01a1ng t\u00ednh nCoV t\u1eeb 18h ng\u00e0y 10/8 \u0111\u1ebfn 6h ng\u00e0y 11/8, li\u00ean quan nh\u1eefng ng\u01b0\u1eddi b\u1ecb ho, s\u1ed1t, ph\u00e1t hi\u1ec7n qua s\u00e0ng l\u1ecdc c\u1ed9ng \u0111\u1ed3ng.", "created_time": 1628646308, "id": "vnexpress.net_4338797", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "13": [{"url": "https://laodong.vn/thi-truong/ha-noi-bo-tri-khu-dat-trong-cho-tieu-thuong-khi-cho-bi-dung-hoat-dong-940653.ldo", "domain": "laodong.vn", "title": "H\u00e0 N\u1ed9i b\u1ed1 tr\u00ed khu \u0111\u1ea5t tr\u1ed1ng cho ti\u1ec3u th\u01b0\u01a1ng khi ch\u1ee3 b\u1ecb d\u1eebng ho\u1ea1t \u0111\u1ed9ng", "snippet": "UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh v\u1ec1 vi\u1ec7c \u0111\u1ea3m b\u1ea3o ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i.", "created_time": 1628656860, "id": "laodong.vn_940653", "score": 0.0, "title_summarize": ["UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh v\u1ec1 vi\u1ec7c \u0111\u1ea3m b\u1ea3o ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i.", "(HNMO) - UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh K\u1ebf ho\u1ea1ch s\u1ed1 181/KH-UBND\u00a0v\u1ec1 b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n...", "Kinhtedothi - UBND TP H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh K\u1ebf ho\u1ea1ch s\u1ed1 181/KH-UBND v\u1ec1 b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a Nh\u00e2n d\u00e2n ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19 trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i."], "content_summary": "\"UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh v\u1ec1 vi\u1ec7c \u0111\u1ea3m b\u1ea3o ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i. \u0110\u0103ng k\u00fd c\u00e1c \u0111i\u1ec3m cung \u1ee9ng h\u00e0ng h\u00f3a thi\u1ebft y\u1ebfu c\u1ee7a doanh nghi\u1ec7p m\u1edf c\u1eeda 24/24 gi\u1edd s\u1eb5n s\u00e0ng ph\u1ee5c v\u1ee5 nh\u00e2n d\u00e2n khi c\u00f3 s\u1ef1 cho ph\u00e9p c\u1ee7a Th\u00e0nh ph\u1ed1. V\u1ec1 ngu\u1ed3n h\u00e0ng, th\u00e0nh ph\u1ed1 s\u1ebd huy \u0111\u1ed9ng t\u1ed5ng l\u1ef1c h\u00e0ng h\u00f3a c\u1ee7a c\u00e1c \u0111\u01a1n v\u1ecb doanh nghi\u1ec7p \u0111\u00f3ng tr\u00ean \u0111\u1ecba b\u00e0n v\u00e0 doanh nghi\u1ec7p c\u00e1c t\u1ec9nh, th\u00e0nh ph\u1ed1 \u0111\u00e3 cam k\u1ebft cung c\u1ea5p h\u00e0ng h\u00f3a cho H\u00e0 N\u1ed9i; c\u00e1c doanh nghi\u1ec7p tham gia ch\u01b0\u01a1ng tr\u00ecnh b\u00ecnh \u1ed5n th\u1ecb tr\u01b0\u1eddng c\u1ee7a Th\u00e0nh ph\u1ed1. Trong tr\u01b0\u1eddng h\u1ee3p c\u00e1c t\u1ec9nh, th\u00e0nh ph\u1ed1 th\u01b0\u1eddng xuy\u00ean cung \u1ee9ng h\u00e0ng h\u00f3a cho H\u00e0 N\u1ed9i b\u1ecb h\u1ea1n ch\u1ebf ngu\u1ed3n cung ho\u1eb7c b\u1ecb d\u1ecbch ph\u1ea3i phong t\u1ecfa, c\u00e1ch ly\u2026 th\u00ec S\u1edf C\u00f4ng Th\u01b0\u01a1ng, S\u1edf N\u00f4ng nghi\u1ec7p v\u00e0 Ph\u00e1t tri\u1ec3n n\u00f4ng th\u00f4n ti\u1ebfp t\u1ee5c li\u00ean k\u1ebft v\u1edbi c\u00e1c t\u1ec9nh th\u00e0nh ph\u1ed1 kh\u00e1c, ch\u1ec9 \u0111\u1ea1o c\u00e1c \u0111\u01a1n v\u1ecb ph\u00e2n ph\u1ed1i tr\u00ean \u0111\u1ecba b\u00e0n th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i thu mua \u0111\u01b0a v\u1ec1 c\u00e1c kho d\u1ef1 tr\u1eef, c\u00e1c \u0111i\u1ec3m b\u00e1n h\u00e0ng ph\u1ee5c v\u1ee5 nh\u00e2n d\u00e2n.\"", "total_facebook_viral": 0}, {"url": "http://hanoimoi.com.vn/tin-tuc/kinh-te/1008493/trien-khai-2500-diem-ban-hang-luu-dong-neu-nhieu-cho-sieu-thi-ngung-kinh-doanh", "domain": "hanoimoi.com.vn", "title": "Tri\u1ec3n khai 2.500 \u0111i\u1ec3m b\u00e1n h\u00e0ng l\u01b0u \u0111\u1ed9ng n\u1ebfu nhi\u1ec1u ch\u1ee3, si\u00eau th\u1ecb ng\u1eebng kinh doanh", "snippet": "(HNMO) - UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh K\u1ebf ho\u1ea1ch s\u1ed1 181/KH-UBND\u00a0v\u1ec1 b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n...", "created_time": 1628585520, "id": "hanoimoi.com.vn_1008493", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kinhtedothi.vn/ha-noi-dam-bao-khong-thieu-hang-tieu-dung-thiet-yeu-phong-chong-dich-covid-19-430656.html", "domain": "kinhtedothi.vn", "title": "H\u00e0 N\u1ed9i \u0111\u1ea3m b\u1ea3o kh\u00f4ng thi\u1ebfu h\u00e0ng ti\u00eau d\u00f9ng thi\u1ebft y\u1ebfu ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19", "snippet": "Kinhtedothi - UBND TP H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh K\u1ebf ho\u1ea1ch s\u1ed1 181/KH-UBND v\u1ec1 b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a Nh\u00e2n d\u00e2n ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19 trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i.", "created_time": 1628592840, "id": "kinhtedothi.vn_430656", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baotintuc.vn/kinh-te/ha-noi-khong-de-thieu-hang-hoa-thiet-yeu-20210810182710438.htm", "domain": "baotintuc.vn", "title": "H\u00e0 N\u1ed9i kh\u00f4ng \u0111\u1ec3 thi\u1ebfu h\u00e0ng h\u00f3a thi\u1ebft y\u1ebfu", "snippet": "H\u00e0 N\u1ed9i b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n trong th\u1eddi gian gi\u00e3n c\u00e1ch.", "created_time": 1628594820, "id": "baotintuc.vn_20210810182710438", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghiepvadautu.info.vn/ha-noi-dam-bao-hang-hoa-thiet-yeu-phuc-vu-nhan-dan/", "domain": "doanhnghiepvadautu.info.vn", "title": "H\u00e0 N\u1ed9i \u0111\u1ea3m b\u1ea3o h\u00e0ng h\u00f3a thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nh\u00e2n d\u00e2n\u00a0 - T\u1ea1p ch\u00ed Doanh nghi\u1ec7p & \u0110\u1ea7u t\u01b0", "snippet": "\u1ee6y ban Nh\u00e2n d\u00e2n (UBND) th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh K\u1ebf ho\u1ea1ch s\u1ed1 181/KH-UBND v\u1ec1 b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n.", "created_time": 1628617219, "id": "a2ddb75fe6f6742af1d19d869d5170a3f25e3ba2", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://baokiemtoannhanuoc.vn/thi-truong/xac-dinh-nhom-hang-hoa-thiet-yeu-duoc-luu-thong-trong-gian-cach-xa-hoi-150352", "domain": "baokiemtoannhanuoc.vn", "title": "B\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung th\u1ef1c ph\u1ea9m v\u00e0 c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i - Bao Kiem Toan", "snippet": "(BKTO) - UBND TP. H\u00e0 N\u1ed9i v\u1eeba ban h\u00e0nh K\u1ebf ho\u1ea1ch b\u1ea3o \u0111\u1ea3m ngu\u1ed3n cung l\u01b0\u01a1ng th\u1ef1c, th\u1ef1c ph\u1ea9m v\u00e0 cung \u1ee9ng c\u00e1c m\u1eb7t h\u00e0ng thi\u1ebft y\u1ebfu ph\u1ee5c v\u1ee5 nhu c\u1ea7u ti\u00eau d\u00f9ng c\u1ee7a nh\u00e2n d\u00e2n trong th\u1eddi gian gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i.", "created_time": 1628667300, "id": "baokiemtoannhanuoc.vn_150352", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "14": [{"url": "http://suckhoemoitruong.com.vn/tin-tuc-24h/nguoi-dan-tren-dia-ban-ha-noi-chi-can-giay-di-duong-va-cccd-cmtnd-ho-chieu-khi-luu-thong-qua-chot-kiem-soat-id34024n.html", "domain": "suckhoemoitruong.com.vn", "title": "Ng\u01b0\u1eddi d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n H\u00e0 N\u1ed9i ch\u1ec9 c\u1ea7n gi\u1ea5y \u0111i \u0111\u01b0\u1eddng v\u00e0 CCCD/ CMTND/ H\u1ed9 chi\u1ebfu khi l\u01b0u th\u00f4ng qua ch\u1ed1t ki\u1ec3m so\u00e1t", "snippet": "Ng\u01b0\u1eddi d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n H\u00e0 N\u1ed9i ch\u1ec9 c\u1ea7n gi\u1ea5y \u0111i \u0111\u01b0\u1eddng, CCCD khi l\u01b0u th\u00f4ng qua ch\u1ed1t ki\u1ec3m so\u00e1t", "created_time": 1628587260, "id": "suckhoemoitruong.com.vn_id34024n", "score": 0.0, "title_summarize": ["Ng\u01b0\u1eddi d\u00e2n tr\u00ean \u0111\u1ecba b\u00e0n H\u00e0 N\u1ed9i ch\u1ec9 c\u1ea7n gi\u1ea5y \u0111i \u0111\u01b0\u1eddng, CCCD khi l\u01b0u th\u00f4ng qua ch\u1ed1t ki\u1ec3m so\u00e1t", "(ThanhtraVietNam) \u2013 Theo \u0111\u00f3 th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i (TP) th\u00f4ng b\u00e1o ng\u01b0\u1eddi \u0111i \u0111\u01b0\u1eddng ch\u1ec9 c\u1ea7n xu\u1ea5t tr\u00ecnh gi\u1ea5y t\u1edd t\u00f9y th\u00e2n (ch\u1ee9ng minh nh\u00e2n d\u00e2n, c\u0103n c\u01b0\u1edbc c\u00f4ng d\u00e2n, h\u1ed9 chi\u1ebfu) k\u00e8m theo gi\u1ea5y \u0111i \u0111\u01b0\u1eddng. \u0110\u1ed3ng th\u1eddi c\u0169ng y\u00eau c\u1ea7u UBND c\u1ea5p qu\u1eadn, huy\u1ec7n, c\u1ea5p ph\u01b0\u1eddng, x\u00e3 kh\u00f4ng \u0111\u01b0\u1ee3c quy \u0111\u1ecbnh ph\u00e1t sinh th\u00eam c\u00e1c th\u1ee7 t\u1ee5c, gi\u1ea5y t\u1edd g\u00e2y kh\u00f3 kh\u0103n cho t\u1ed5 ch\u1ee9c, c\u00e1 nh\u00e2n.", "Sau m\u1ed9t ng\u00e0y ban h\u00e0nh quy \u0111\u1ecbnh \u201csi\u1ebft\u201d vi\u1ec7c c\u1ea5p v\u00e0 s\u1eed d\u1ee5ng gi\u1ea5y \u0111i \u0111\u01b0\u1eddng, TP H\u00e0 N\u1ed9i \u0111\u00e3 r\u1ea5t nhanh ch\u00f3ng \u0111i\u1ec1u ch\u1ec9nh theo h\u01b0\u1edbng gi\u1ea3m b\u1edbt gi\u1ea5y t\u1edd."], "content_summary": "\"(SK&MT) - H\u00e0 N\u1ed9i v\u1eeba ra th\u00f4ng b\u00e1o h\u1ecfa t\u1ed1c \u0111i\u1ec1u ch\u1ec9nh vi\u1ec7c ki\u1ec3m so\u00e1t gi\u1ea5y \u0111i \u0111\u01b0\u1eddng. C\u00f4ng v\u0103n n\u00eau r\u00f5, ng\u00e0y 7/8/2021, UBND th\u00e0nh ph\u1ed1 ban h\u00e0nh C\u00f4ng v\u0103n s\u1ed1 2562/UBND-KT nh\u1eb1m gi\u1ea3m l\u01b0\u1ee3ng ng\u01b0\u1eddi ra \u0111\u01b0\u1eddng, t\u1eadn d\u1ee5ng kho\u1ea3ng th\u1eddi gian \\\"v\u00e0ng\\\" \u0111\u1ec3 th\u1ef1c hi\u1ec7n truy v\u1ebft, khoanh v\u00f9ng c\u00e1c \u1ed5 d\u1ecbch v\u00e0 c\u00e1c ngu\u1ed3n c\u00f3 nguy c\u01a1 l\u00e2y nhi\u1ec5m c\u1ed9ng \u0111\u1ed3ng. \\\" \u0110\u1ed1i v\u1edbi c\u00e1c tr\u01b0\u1eddng h\u1ee3p doanh nghi\u1ec7p, c\u01a1 s\u1edf s\u1ea3n xu\u1ea5t, kinh doanh d\u1ecbch v\u1ee5 \u0111\u01b0\u1ee3c ph\u00e9p ho\u1ea1t \u0111\u1ed9ng c\u1ea7n b\u1ed1 tr\u00ed nhi\u1ec1u lao \u0111\u1ed9ng \u0111\u1ebfn l\u00e0m vi\u1ec7c, UBND c\u1ea5p ph\u01b0\u1eddng, x\u00e3 ch\u1ee7 \u0111\u1ed9ng ph\u1ed1i h\u1ee3p, c\u1eed c\u00e1n b\u1ed9 xu\u1ed1ng l\u00e0m vi\u1ec7c tr\u1ef1c ti\u1ebfp v\u1edbi \u0111\u01a1n v\u1ecb t\u1ea1i \u0111\u1ecba \u0111i\u1ec3m \u0111\u1ec3 th\u1ed1ng nh\u1ea5t ph\u01b0\u01a1ng \u00e1n s\u1ea3n xu\u1ea5t kinh doanh \u0111\u1ea3m b\u1ea3o an to\u00e0n ph\u00f2ng ch\u1ed1ng d\u1ecbch v\u00e0 x\u00e1c nh\u1eadn danh s\u00e1ch ng\u01b0\u1eddi lao \u0111\u1ed9ng c\u1ea7n l\u01b0u th\u00f4ng tr\u00ean \u0111\u01b0\u1eddng, l\u00e0m c\u01a1 s\u1edf \u0111\u1ec3 Th\u1ee7 tr\u01b0\u1edfng, ng\u01b0\u1eddi \u0111\u1ee9ng \u0111\u1ea7u \u0111\u01a1n v\u1ecb c\u1ea5p Gi\u1ea5y \u0111i \u0111\u01b0\u1eddng cho ng\u01b0\u1eddi lao \u0111\u1ed9ng.\"", "total_facebook_viral": 0}, {"url": "http://thanhtravietnam.vn/phong-chong-covid-19/ha-noi-chinh-thuc-bo-yeu-cau-nguoi-di-duong-phai-co-lich-truc-lich-lam-viec-196941", "domain": "thanhtravietnam.vn", "title": "H\u00e0 N\u1ed9i ch\u00ednh th\u1ee9c b\u1ecf y\u00eau c\u1ea7u ng\u01b0\u1eddi \u0111i \u0111\u01b0\u1eddng ph\u1ea3i c\u00f3 \"l\u1ecbch tr\u1ef1c, l\u1ecbch l\u00e0m vi\u1ec7c\"", "snippet": "(ThanhtraVietNam) \u2013 Theo \u0111\u00f3 th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i (TP) th\u00f4ng b\u00e1o ng\u01b0\u1eddi \u0111i \u0111\u01b0\u1eddng ch\u1ec9 c\u1ea7n xu\u1ea5t tr\u00ecnh gi\u1ea5y t\u1edd t\u00f9y th\u00e2n (ch\u1ee9ng minh nh\u00e2n d\u00e2n, c\u0103n c\u01b0\u1edbc c\u00f4ng d\u00e2n, h\u1ed9 chi\u1ebfu) k\u00e8m theo gi\u1ea5y \u0111i \u0111\u01b0\u1eddng. \u0110\u1ed3ng th\u1eddi c\u0169ng y\u00eau c\u1ea7u UBND c\u1ea5p qu\u1eadn, huy\u1ec7n, c\u1ea5p ph\u01b0\u1eddng, x\u00e3 kh\u00f4ng \u0111\u01b0\u1ee3c quy \u0111\u1ecbnh ph\u00e1t sinh th\u00eam c\u00e1c th\u1ee7 t\u1ee5c, gi\u1ea5y t\u1edd g\u00e2y kh\u00f3 kh\u0103n cho t\u1ed5 ch\u1ee9c, c\u00e1 nh\u00e2n.", "created_time": 1628589600, "id": "thanhtravietnam.vn_196941", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.baogiaothong.vn/giay-di-duong-va-y-thuc-cong-dan-d520115.html", "domain": "baogiaothong.vn", "title": "Gi\u1ea5y \u0111i \u0111\u01b0\u1eddng v\u00e0 \u00fd th\u1ee9c c\u00f4ng d\u00e2n", "snippet": "Sau m\u1ed9t ng\u00e0y ban h\u00e0nh quy \u0111\u1ecbnh \u201csi\u1ebft\u201d vi\u1ec7c c\u1ea5p v\u00e0 s\u1eed d\u1ee5ng gi\u1ea5y \u0111i \u0111\u01b0\u1eddng, TP H\u00e0 N\u1ed9i \u0111\u00e3 r\u1ea5t nhanh ch\u00f3ng \u0111i\u1ec1u ch\u1ec9nh theo h\u01b0\u1edbng gi\u1ea3m b\u1edbt gi\u1ea5y t\u1edd.", "created_time": 1628637360, "id": "baogiaothong.vn_d520115", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://thitruongtaichinhtiente.vn/ha-noi-dieu-chinh-thong-nhat-viec-kiem-tra-giay-to-nguoi-di-duong-36633.html", "domain": "thitruongtaichinhtiente.vn", "title": "H\u00e0 N\u1ed9i \u0111i\u1ec1u ch\u1ec9nh, th\u1ed1ng nh\u1ea5t vi\u1ec7c ki\u1ec3m tra gi\u1ea5y t\u1edd ng\u01b0\u1eddi \u0111i \u0111\u01b0\u1eddng", "snippet": "(thitruongtaichinhtiente.vn) - Ng\u01b0\u1eddi \u0111i \u0111\u01b0\u1eddng xu\u1ea5t tr\u00ecnh gi\u1ea5y t\u1edd t\u00f9y th\u00e2n (Ch\u1ee9ng minh nh\u00e2n d\u00e2n/C\u0103n c\u01b0\u1edbc c\u00f4ng d\u00e2n/H\u1ed9 chi\u1ebfu) k\u00e8m theo Gi\u1ea5y \u0111i \u0111\u01b0\u1eddng (m\u1eabu Gi\u1ea5y \u0111i \u0111\u01b0\u1eddng \u0111\u00e3 \u0111\u01b0\u1ee3c ban h\u00e0nh k\u00e8m theo C\u00f4ng v\u0103n s\u1ed1 2434/UBND-KT ng\u00e0y 29/7). UBND c\u1ea5p qu\u1eadn, huy\u1ec7n, c\u1ea5p ph\u01b0\u1eddng, x\u00e3 kh\u00f4ng \u0111\u01b0\u1ee3c quy \u0111\u1ecbnh ph\u00e1t sinh th\u00eam c\u00e1c th\u1ee7 t\u1ee5c, gi\u1ea5y t\u1edd g\u00e2y kh\u00f3 kh\u0103n cho t\u1ed5 ch\u1ee9c, c\u00e1 nh\u00e2n.", "created_time": 1628587380, "id": "thitruongtaichinhtiente.vn_36633", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://www.dvt.vn/ha-noi-loai-bo-giay-phan-cong-lich-truc-vi-chua-phu-hop-a91832.html", "domain": "dvt.vn", "title": "H\u00e0 N\u1ed9i lo\u1ea1i b\u1ecf gi\u1ea5y ph\u00e2n c\u00f4ng l\u1ecbch tr\u1ef1c v\u00ec \"ch\u01b0a ph\u00f9 h\u1ee3p\"", "snippet": "Sau 1 ng\u00e0y y\u00eau c\u1ea7u ng\u01b0\u1eddi d\u00e2n c\u1ea7n nhi\u1ec1u lo\u1ea1i gi\u1ea5y t\u1edd, s\u00e1ng 10/9, TP.H\u00e0 N\u1ed9i th\u00f4ng b\u00e1o ng\u01b0\u1eddi d\u00e2n ch\u1ec9 c\u1ea7n xu\u1ea5t tr\u00ecnh gi\u1ea5y t\u1edd t\u00f9y th\u00e2n v\u00e0 gi\u1ea5y \u0111i \u0111\u01b0\u1eddng m\u1eabu m\u1edbi.", "created_time": 1628586360, "id": "7a5a961aca10ccf61586cfcc55f5e4eac5bb8bf6", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://tuoitre.vn/hieu-ung-nguoc-cua-chinh-sach-20210811084627916.htm", "domain": "tuoitre.vn", "title": "Hi\u1ec7u \u1ee9ng ng\u01b0\u1ee3c c\u1ee7a ch\u00ednh s\u00e1ch", "snippet": "TTO - H\u00e0 N\u1ed9i \u0111\u00e3 nhanh ch\u00f3ng s\u1eeda \u0111\u1ed5i c\u00f4ng v\u0103n ban h\u00e0nh t\u1ed1i 8-8 v\u1ec1 vi\u1ec7c ng\u01b0\u1eddi \u0111i \u0111\u01b0\u1eddng ph\u1ea3i xu\u1ea5t tr\u00ecnh c\u0103n c\u01b0\u1edbc c\u00f4ng d\u00e2n/ch\u1ee9ng minh nh\u00e2n d\u00e2n, l\u1ecbch tr\u1ef1c, l\u1ecbch l\u00e0m vi\u1ec7c, v\u0103n b\u1ea3n ph\u00e2n c\u00f4ng nhi\u1ec7m v\u1ee5 c\u1ee7a c\u01a1 quan, gi\u1ea5y \u0111i \u0111\u01b0\u1eddng...", "created_time": 1628647088, "id": "tuoitre.vn_20210811084627916", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "15": [{"url": "http://baokiemtoannhanuoc.vn/trong-nuoc/ha-noi-ho-tro-54-ty-dong-cho-18-tinh-thanh-pho-phia-nam-gap-kho-khan-do-dich-benh-150345", "domain": "baokiemtoannhanuoc.vn", "title": "H\u00e0 N\u1ed9i h\u1ed7 tr\u1ee3 54 t\u1ef7 \u0111\u1ed3ng cho 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 ph\u00eda Nam g\u1eb7p kh\u00f3 kh\u0103n do d\u1ecbch b\u1ec7nh - Bao Kiem Toan", "snippet": "(BKTO) - TP. H\u00e0 N\u1ed9i s\u1ebd d\u00e0nh 54 t\u1ef7 \u0111\u1ed3ng h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 ph\u00eda Nam \u0111ang g\u1eb7p kh\u00f3 kh\u0103n do d\u1ecbch Covid-19 (m\u1ed7i \u0111\u1ecba ph\u01b0\u01a1ng 3 t\u1ef7 \u0111\u1ed3ng).", "created_time": 1628664900, "id": "baokiemtoannhanuoc.vn_150345", "score": 0.0, "title_summarize": ["(BKTO) - TP. H\u00e0 N\u1ed9i s\u1ebd d\u00e0nh 54 t\u1ef7 \u0111\u1ed3ng h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 ph\u00eda Nam \u0111ang g\u1eb7p kh\u00f3 kh\u0103n do d\u1ecbch Covid-19 (m\u1ed7i \u0111\u1ecba ph\u01b0\u01a1ng 3 t\u1ef7 \u0111\u1ed3ng).", "(Chinhphu.vn) - Theo S\u1edf Lao \u0111\u1ed9ng-Th\u01b0\u01a1ng binh v\u00e0 X\u00e3 h\u1ed9i H\u00e0 N\u1ed9i, t\u00ednh \u0111\u1ebfn ng\u00e0y 10/8, c\u00e1c s\u1edf, ng\u00e0nh li\u00ean quan v\u00e0 c\u00e1c qu\u1eadn, huy\u1ec7n, th\u1ecb x\u00e3 tr\u00ean \u0111\u1ecba b\u00e0n th\u00e0nh ph\u1ed1 \u0111\u00e3 ra quy\u1ebft \u0111\u1ecbnh h\u1ed7 tr\u1ee3 cho ng\u01b0\u1eddi lao \u0111\u1ed9ng, ng\u01b0\u1eddi s\u1eed d\u1ee5ng lao \u0111\u1ed9ng g\u1eb7p kh\u00f3 kh\u0103n do \u0111\u1ea1i d\u1ecbch COVID-19 v\u1edbi kinh ph\u00ed g\u1ea7n 150 t\u1ef7 \u0111\u1ed3ng, trong \u0111\u00f3, \u0111\u00e3 th\u1ef1c hi\u1ec7n \u0111\u01b0\u1ee3c 140,4 t\u1ef7 \u0111\u1ed3ng. - Th\u00f4ng tin ch\u00ednh th\u1ed1ng ho\u1ea1t \u0111\u1ed9ng, quy\u1ebft \u0111\u1ecbnh, ch\u1ec9 \u0111\u1ea1o c\u1ee7a Ch\u00ednh ph\u1ee7, Th\u1ee7 t\u01b0\u1edbng, Ph\u00f3 Th\u1ee7 t\u01b0\u1edbng v\u1ec1 kinh t\u1ebf, x\u00e3 h\u1ed9i, qu\u1ed1c ph\u00f2ng, an ninh, ngo\u1ea1i giao; v\u00e0 th\u1ebf gi\u1edbi...", "(Chinhphu.vn) - Ng\u00e0y 9/8, Ch\u1ee7 t\u1ecbch UBND TP. H\u00e0 N\u1ed9i Chu Ng\u1ecdc Anh \u0111\u00e3 k\u00fd ban h\u00e0nh c\u00e1c quy\u1ebft \u0111\u1ecbnh v\u1ec1 vi\u1ec7c h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 khu v\u1ef1c ph\u00eda nam kinh ph\u00ed b\u1ed5 sung ngu\u1ed3n l\u1ef1c th\u1ef1c hi\u1ec7n ph\u00f2ng, ch\u1ed1ng d\u1ecbch COVID-19. - Th\u00f4ng tin ch\u00ednh th\u1ed1ng ho\u1ea1t \u0111\u1ed9ng, quy\u1ebft \u0111\u1ecbnh, ch\u1ec9 \u0111\u1ea1o c\u1ee7a Ch\u00ednh ph\u1ee7, Th\u1ee7 t\u01b0\u1edbng, Ph\u00f3 Th\u1ee7 t\u01b0\u1edbng v\u1ec1 kinh t\u1ebf, x\u00e3 h\u1ed9i, qu\u1ed1c ph\u00f2ng, an ninh, ngo\u1ea1i giao; v\u00e0 th\u1ebf gi\u1edbi..."], "content_summary": "\"H\u00e0 N\u1ed9i s\u1ebd d\u00e0nh 54 t\u1ef7 \u0111\u1ed3ng h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 ph\u00eda Nam \u0111ang g\u1eb7p kh\u00f3 kh\u0103n do d\u1ecbch Covid-19 (m\u1ed7i \u0111\u1ecba ph\u01b0\u01a1ng 3 t\u1ef7 \u0111\u1ed3ng). T\u1ea1o thu\u1eadn l\u1ee3i cho ng\u01b0\u1eddi lao \u0111\u1ed9ng, doanh nghi\u1ec7p ti\u1ebfp c\u1eadn g\u00f3i h\u1ed7 tr\u1ee3 26.000 t\u1ef7 \u0111\u1ed3ng H\u00e0 N\u1ed9i \u0111\u00e3 huy \u0111\u1ed9ng nhi\u1ec1u c\u00e1n b\u1ed9 y t\u1ebf h\u1ed7 tr\u1ee3 c\u00e1c t\u1ec9nh mi\u1ec1n Nam\u00a0ch\u1ed1ng d\u1ecbch TTXVN V\u1eeba qua, UBND TP. Kinh ph\u00ed n\u00e0y \u0111\u01b0\u1ee3c tr\u00edch t\u1eeb ngu\u1ed3n d\u1ef1 ph\u00f2ng ng\u00e2n s\u00e1ch c\u1ea5p th\u00e0nh ph\u1ed1 n\u0103m 2021.\"", "total_facebook_viral": 0}, {"url": "http://baochinhphu.vn/doi-song/ha-noi-da-ho-tro-hon-140-ty-dong-cho-nld-theo-nghi-quyet-68/442070.vgp", "domain": "baochinhphu.vn", "title": "H\u00e0 N\u1ed9i: \u0110\u00e3 h\u1ed7 tr\u1ee3 h\u01a1n 140 t\u1ef7 \u0111\u1ed3ng cho NL\u0110 theo Ngh\u1ecb quy\u1ebft 68", "snippet": "(Chinhphu.vn) - Theo S\u1edf Lao \u0111\u1ed9ng-Th\u01b0\u01a1ng binh v\u00e0 X\u00e3 h\u1ed9i H\u00e0 N\u1ed9i, t\u00ednh \u0111\u1ebfn ng\u00e0y 10/8, c\u00e1c s\u1edf, ng\u00e0nh li\u00ean quan v\u00e0 c\u00e1c qu\u1eadn, huy\u1ec7n, th\u1ecb x\u00e3 tr\u00ean \u0111\u1ecba b\u00e0n th\u00e0nh ph\u1ed1 \u0111\u00e3 ra quy\u1ebft \u0111\u1ecbnh h\u1ed7 tr\u1ee3 cho ng\u01b0\u1eddi lao \u0111\u1ed9ng, ng\u01b0\u1eddi s\u1eed d\u1ee5ng lao \u0111\u1ed9ng g\u1eb7p kh\u00f3 kh\u0103n do \u0111\u1ea1i d\u1ecbch COVID-19 v\u1edbi kinh ph\u00ed g\u1ea7n 150 t\u1ef7 \u0111\u1ed3ng, trong \u0111\u00f3, \u0111\u00e3 th\u1ef1c hi\u1ec7n \u0111\u01b0\u1ee3c 140,4 t\u1ef7 \u0111\u1ed3ng. - Th\u00f4ng tin ch\u00ednh th\u1ed1ng ho\u1ea1t \u0111\u1ed9ng, quy\u1ebft \u0111\u1ecbnh, ch\u1ec9 \u0111\u1ea1o c\u1ee7a Ch\u00ednh ph\u1ee7, Th\u1ee7 t\u01b0\u1edbng, Ph\u00f3 Th\u1ee7 t\u01b0\u1edbng v\u1ec1 kinh t\u1ebf, x\u00e3 h\u1ed9i, qu\u1ed1c ph\u00f2ng, an ninh, ngo\u1ea1i giao; v\u00e0 th\u1ebf gi\u1edbi...", "created_time": 1628652600, "id": "baochinhphu.vn_442070", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://baochinhphu.vn/doi-song/ha-noi-danh-54-ty-dong-ho-tro-18-tinh-thanh-pho-phia-nam-phong-chong-dich/442037.vgp", "domain": "baochinhphu.vn", "title": "H\u00e0 N\u1ed9i d\u00e0nh 54 t\u1ef7 \u0111\u1ed3ng h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 ph\u00eda nam ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "snippet": "(Chinhphu.vn) - Ng\u00e0y 9/8, Ch\u1ee7 t\u1ecbch UBND TP. H\u00e0 N\u1ed9i Chu Ng\u1ecdc Anh \u0111\u00e3 k\u00fd ban h\u00e0nh c\u00e1c quy\u1ebft \u0111\u1ecbnh v\u1ec1 vi\u1ec7c h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 khu v\u1ef1c ph\u00eda nam kinh ph\u00ed b\u1ed5 sung ngu\u1ed3n l\u1ef1c th\u1ef1c hi\u1ec7n ph\u00f2ng, ch\u1ed1ng d\u1ecbch COVID-19. - Th\u00f4ng tin ch\u00ednh th\u1ed1ng ho\u1ea1t \u0111\u1ed9ng, quy\u1ebft \u0111\u1ecbnh, ch\u1ec9 \u0111\u1ea1o c\u1ee7a Ch\u00ednh ph\u1ee7, Th\u1ee7 t\u01b0\u1edbng, Ph\u00f3 Th\u1ee7 t\u01b0\u1edbng v\u1ec1 kinh t\u1ebf, x\u00e3 h\u1ed9i, qu\u1ed1c ph\u00f2ng, an ninh, ngo\u1ea1i giao; v\u00e0 th\u1ebf gi\u1edbi...", "created_time": 1628593020, "id": "baochinhphu.vn_442037", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://nhandan.vn/tin-tuc-kinh-te/ha-noi-ho-tro-18-dia-phuong-phia-nam-54-ty-dong-659238/", "domain": "nhandan.com.vn", "title": "H\u00e0 N\u1ed9i h\u1ed7 tr\u1ee3 18 \u0111\u1ecba ph\u01b0\u01a1ng ph\u00eda nam 54 t\u1ef7 \u0111\u1ed3ng", "snippet": "Ng\u00e0y 9/8, Ch\u1ee7 t\u1ecbch UBND TP H\u00e0 N\u1ed9i Chu Ng\u1ecdc Anh \u0111\u00e3 k\u00fd ban h\u00e0nh c\u00e1c quy\u1ebft \u0111\u1ecbnh v\u1ec1 vi\u1ec7c h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 khu v\u1ef1c ph\u00eda nam kinh ph\u00ed b\u1ed5 sung ngu\u1ed3n l\u1ef1c th\u1ef1c hi\u1ec7n ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19.", "created_time": 1628600400, "id": "nhandan.com.vn_659238", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://kinhtedothi.vn/ha-noi-danh-54-ty-dong-ho-tro-18-tinh-thanh-pho-phia-nam-phong-chong-dich-covid-19-430660.html", "domain": "kinhtedothi.vn", "title": "H\u00e0 N\u1ed9i d\u00e0nh 54 t\u1ef7 \u0111\u1ed3ng h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 ph\u00eda Nam ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19", "snippet": "Kinhtedothi - Ng\u00e0y 9/8, Ch\u1ee7 t\u1ecbch UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i Chu Ng\u1ecdc Anh \u0111\u00e3 k\u00fd ban h\u00e0nh c\u00e1c quy\u1ebft \u0111\u1ecbnh v\u1ec1 vi\u1ec7c h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 khu v\u1ef1c ph\u00eda Nam kinh ph\u00ed b\u1ed5 sung ngu\u1ed3n l\u1ef1c th\u1ef1c hi\u1ec7n ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19.", "created_time": 1628593500, "id": "kinhtedothi.vn_430660", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://hanoimoi.com.vn/tin-tuc/xa-hoi/1008502/ha-noi-danh-54-ty-dong-ho-tro-18-tinh-thanh-pho\u00a0phia-nam-phong-chong-dich-covid-19", "domain": "hanoimoi.com.vn", "title": "H\u00e0 N\u1ed9i d\u00e0nh 54 t\u1ef7 \u0111\u1ed3ng h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1\u00a0ph\u00eda Nam ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19", "snippet": "(HNMO) - Ch\u1ee7 t\u1ecbch UBND th\u00e0nh ph\u1ed1 H\u00e0 N\u1ed9i Chu Ng\u1ecdc Anh \u0111\u00e3 k\u00fd\u00a0c\u00e1c quy\u1ebft \u0111\u1ecbnh h\u1ed7 tr\u1ee3 18 t\u1ec9nh, th\u00e0nh ph\u1ed1 khu v\u1ef1c ph\u00eda Nam kinh ph\u00ed b\u1ed5 sung ngu\u1ed3n l\u1ef1c th\u1ef1c hi\u1ec7n ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19.", "created_time": 1628589360, "id": "hanoimoi.com.vn_1008502", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "16": [{"url": "https://vietnammoi.vn/du-bao-gia-heo-hoi-ngay-11-8-gia-thu-mua-se-tiep-tuc-tang-giam-tren-ca-nuoc-20210810153651501.htm", "domain": "vietnammoi.vn", "title": "D\u1ef1 b\u00e1o gi\u00e1 heo h\u01a1i ng\u00e0y 11/8: Gi\u00e1 thu mua s\u1ebd ti\u1ebfp t\u1ee5c t\u0103ng gi\u1ea3m tr\u00ean c\u1ea3 n\u01b0\u1edbc?", "snippet": "Gi\u00e1 heo h\u01a1i h\u00f4m nay (10/8) bi\u1ebfn \u0111\u1ed9ng tr\u00e1i chi\u1ec1u, m\u1ee9c \u0111i\u1ec1u ch\u1ec9nh 1.000 - 2.000 \u0111\u1ed3ng/kg. Ng\u00e0nh ch\u0103n nu\u00f4i H\u00e0 N\u1ed9i \u0111\u1ed1i m\u1eb7t nhi\u1ec1u th\u00e1ch th\u1ee9c trong ti\u00eau th\u1ee5 s\u1ea3n ph\u1ea9m.", "created_time": 1628595000, "id": "77ca953fe5609a644fe13b761c97416b627a782a", "score": 0.0, "title_summarize": ["Gi\u00e1 heo h\u01a1i h\u00f4m nay (10/8) bi\u1ebfn \u0111\u1ed9ng tr\u00e1i chi\u1ec1u, m\u1ee9c \u0111i\u1ec1u ch\u1ec9nh 1.000 - 2.000 \u0111\u1ed3ng/kg. Ng\u00e0nh ch\u0103n nu\u00f4i H\u00e0 N\u1ed9i \u0111\u1ed1i m\u1eb7t nhi\u1ec1u th\u00e1ch th\u1ee9c trong ti\u00eau th\u1ee5 s\u1ea3n ph\u1ea9m.", "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) t\u0103ng - gi\u1ea3m r\u1ea3i r\u00e1c \u1edf khu v\u1ef1c ph\u00eda B\u1eafc v\u00e0 ph\u00eda Nam. Thay v\u00ec t\u0103ng t\u00e1i \u0111\u00e0n, ng\u01b0\u1eddi ch\u0103n nu\u00f4i huy\u1ec7n Qu\u1ed1c Oai s\u1ebd \u0111i\u1ec1u ch\u1ec9nh k\u1ebf ho\u1ea1ch s\u1ea3n xu\u1ea5t v\u00e0 t\u1eadp trung n\u00e2ng cao ch\u1ea5t l\u01b0\u1ee3ng s\u1ea3n ph\u1ea9m.", "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) t\u0103ng - gi\u1ea3m r\u1ea3i r\u00e1c \u1edf khu v\u1ef1c ph\u00eda B\u1eafc v\u00e0 ph\u00eda Nam. Thay v\u00ec t\u0103ng t\u00e1i \u0111\u00e0n, ng\u01b0\u1eddi ch\u0103n nu\u00f4i huy\u1ec7n Qu\u1ed1c Oai s\u1ebd \u0111i\u1ec1u ch\u1ec9nh k\u1ebf ho\u1ea1ch s\u1ea3n xu\u1ea5t v\u00e0 t\u1eadp trung n\u00e2ng cao ch\u1ea5t l\u01b0\u1ee3ng s\u1ea3n ph\u1ea9m."], "content_summary": "\"Gi\u00e1 heo h\u01a1i h\u00f4m nay gi\u1ea3m r\u1ea3i r\u00e1c hai mi\u1ec1n B\u1eafc - Nam : D\u1ef1 b\u00e1o gi\u00e1 heo h\u01a1i xu\u1ea5t chu\u1ed3ng trong th\u1eddi gian t\u1edbi T\u1ea1i th\u1ecb tr\u01b0\u1eddng mi\u1ec1n B\u1eafc h\u00f4m nay, gi\u00e1 thu mua dao \u0111\u1ed9ng trong kho\u1ea3ng 52.000 - 56.000 \u0111\u1ed3ng/kg. Trong \u0111\u00f3, th\u01b0\u01a1ng l\u00e1i t\u1ec9nh Th\u00e1i B\u00ecnh \u0111ang thu mua heo h\u01a1i v\u1edbi gi\u00e1 55.000 \u0111\u1ed3ng/kg sau khi t\u0103ng nh\u1eb9 1.000 \u0111\u1ed3ng/kg, ngang b\u1eb1ng v\u1edbi t\u1ec9nh Th\u00e1i Nguy\u00ean. Sau khi t\u0103ng 2.000 \u0111\u1ed3ng/kg, t\u1ec9nh H\u01b0ng Y\u00ean \u0111ang giao d\u1ecbch v\u1edbi gi\u00e1 cao nh\u1ea5t khu v\u1ef1c l\u00e0 56.000 \u0111\u1ed3ng/kg. The Wall Street Journal Ng\u00e0nh ch\u0103n nu\u00f4i H\u00e0 N\u1ed9i \u0111\u1ed1i m\u1eb7t nhi\u1ec1u th\u00e1ch th\u1ee9c trong ti\u00eau th\u1ee5 s\u1ea3n ph\u1ea9m V\u1ec1 t\u00ecnh h\u00ecnh s\u1ea3n xu\u1ea5t tr\u00ean \u0111\u1ecba b\u00e0n th\u00e0nh ph\u1ed1, Chi c\u1ee5c tr\u01b0\u1edfng Chi c\u1ee5c Ch\u0103n nu\u00f4i v\u00e0 Th\u00fa y H\u00e0 N\u1ed9i Nguy\u1ec5n Ng\u1ecdc S\u01a1n nh\u1eadn \u0111\u1ecbnh, ch\u0103n nu\u00f4i c\u1ee7a H\u00e0 N\u1ed9i th\u1eddi \u0111i\u1ec3m n\u00e0y t\u01b0\u01a1ng \u0111\u1ed1i \u1ed5n \u0111\u1ecbnh.\"", "total_facebook_viral": 0}, {"url": "https://doanhnghiep.kinhtechungkhoan.vn/gia-heo-hoi-hom-nay-11-8-nhieu-dia-phuong-tiep-tuc-dieu-chinh-trai-chieu-42202111860393.htm", "domain": "doanhnghiep.kinhtechungkhoan.vn", "title": "Gi\u00e1 heo h\u01a1i h\u00f4m nay 11/8: Nhi\u1ec1u \u0111\u1ecba ph\u01b0\u01a1ng ti\u1ebfp t\u1ee5c \u0111i\u1ec1u ch\u1ec9nh tr\u00e1i chi\u1ec1u", "snippet": "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) t\u0103ng - gi\u1ea3m r\u1ea3i r\u00e1c \u1edf khu v\u1ef1c ph\u00eda B\u1eafc v\u00e0 ph\u00eda Nam. Thay v\u00ec t\u0103ng t\u00e1i \u0111\u00e0n, ng\u01b0\u1eddi ch\u0103n nu\u00f4i huy\u1ec7n Qu\u1ed1c Oai s\u1ebd \u0111i\u1ec1u ch\u1ec9nh k\u1ebf ho\u1ea1ch s\u1ea3n xu\u1ea5t v\u00e0 t\u1eadp trung n\u00e2ng cao ch\u1ea5t l\u01b0\u1ee3ng s\u1ea3n ph\u1ea9m.", "created_time": 1628614800, "id": "1beff433237cf9b96742ef2afa52cf814536f8b4", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vietnambiz.vn/gia-heo-hoi-hom-nay-11-8-nhieu-dia-phuong-tiep-tuc-dieu-chinh-trai-chieu-20210810233506063.htm", "domain": "vietnambiz.vn", "title": "Gi\u00e1 heo h\u01a1i h\u00f4m nay 11/8: Nhi\u1ec1u \u0111\u1ecba ph\u01b0\u01a1ng ti\u1ebfp t\u1ee5c \u0111i\u1ec1u ch\u1ec9nh tr\u00e1i chi\u1ec1u", "snippet": "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) t\u0103ng - gi\u1ea3m r\u1ea3i r\u00e1c \u1edf khu v\u1ef1c ph\u00eda B\u1eafc v\u00e0 ph\u00eda Nam. Thay v\u00ec t\u0103ng t\u00e1i \u0111\u00e0n, ng\u01b0\u1eddi ch\u0103n nu\u00f4i huy\u1ec7n Qu\u1ed1c Oai s\u1ebd \u0111i\u1ec1u ch\u1ec9nh k\u1ebf ho\u1ea1ch s\u1ea3n xu\u1ea5t v\u00e0 t\u1eadp trung n\u00e2ng cao ch\u1ea5t l\u01b0\u1ee3ng s\u1ea3n ph\u1ea9m.", "created_time": 1628636400, "id": "vietnambiz.vn_20210810233506063", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghiep.kinhtechungkhoan.vn/du-bao-gia-heo-hoi-ngay-12-8-da-tang-giam-trai-chieu-lieu-co-dung-lai-432021118183014997.htm", "domain": "doanhnghiep.kinhtechungkhoan.vn", "title": "D\u1ef1 b\u00e1o gi\u00e1 heo h\u01a1i ng\u00e0y 12/8: \u0110\u00e0 t\u0103ng - gi\u1ea3m tr\u00e1i chi\u1ec1u li\u1ec7u c\u00f3 d\u1eebng l\u1ea1i?", "snippet": "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) \u0111i ngang t\u1ea1i c\u00e1c t\u1ec9nh mi\u1ec1n Trung, T\u00e2y Nguy\u00ean, trong khi \u0111i\u1ec1u ch\u1ec9nh tr\u00e1i chi\u1ec1u \u1edf hai khu v\u1ef1c mi\u1ec1n B\u1eafc v\u00e0 mi\u1ec1n Nam. T\u00ecnh h\u00ecnh d\u1ecbch b\u1ec7nh gia s\u00fac tr\u00ean \u0111\u1ecba b\u00e0n huy\u1ec7n \u1ee8ng H\u00f2a, TP H\u00e0 N\u1ed9i ti\u1ec1m \u1ea9n nhi\u1ec1u ph\u1ee9c t\u1ea1p.", "created_time": 1628614800, "id": "a06213fc31c6e2098b4b1fb3619281e4d7e8b8cc", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://doanhnghiep.kinhtechungkhoan.vn/gia-heo-hoi-hom-nay-11-8-hai-mien-bac-nam-tang-dieu-chinh-1000-2000-dong-kg-4320211185020370.htm", "domain": "doanhnghiep.kinhtechungkhoan.vn", "title": "Gi\u00e1 heo h\u01a1i h\u00f4m nay 11/8: Hai mi\u1ec1n B\u1eafc - Nam t\u0103ng \u0111i\u1ec1u ch\u1ec9nh 1.000 - 2.000 \u0111\u1ed3ng/kg", "snippet": "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) \u0111i\u1ec1u ch\u1ec9nh kh\u00f4ng qu\u00e1 2.000 \u0111\u1ed3ng/kg \u1edf m\u1ed9t s\u1ed1 \u0111\u1ecba ph\u01b0\u01a1ng thu\u1ed9c hai mi\u1ec1n B\u1eafc - Nam. Tr\u00ean \u0111\u1ecba b\u00e0n t\u1ec9nh C\u00e0 Mau \u0111\u00e3 c\u00f3 3 x\u00e3 Nguy\u1ec5n Hu\u00e2n, T\u00e2n D\u00e2n v\u00e0 Tr\u1ea7n Ph\u00e1n c\u00f4ng b\u1ed1 d\u1ecbch t\u1ea3 heo ch\u00e2u Phi.", "created_time": 1628614800, "id": "818ba6bcdf947ee10f009cf0947586c28de0cae5", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vietnammoi.vn/gia-heo-hoi-hom-nay-11-8-hai-mien-bac-nam-tang-dieu-chinh-1000-2000-dong-kg-2021081023300251.htm", "domain": "vietnammoi.vn", "title": "Gi\u00e1 heo h\u01a1i h\u00f4m nay 11/8: Hai mi\u1ec1n B\u1eafc - Nam t\u0103ng \u0111i\u1ec1u ch\u1ec9nh 1.000 - 2.000 \u0111\u1ed3ng/kg", "snippet": "Gi\u00e1 heo h\u01a1i h\u00f4m nay (11/8) \u0111i\u1ec1u ch\u1ec9nh kh\u00f4ng qu\u00e1 2.000 \u0111\u1ed3ng/kg \u1edf m\u1ed9t s\u1ed1 \u0111\u1ecba ph\u01b0\u01a1ng thu\u1ed9c hai mi\u1ec1n B\u1eafc - Nam. Tr\u00ean \u0111\u1ecba b\u00e0n t\u1ec9nh C\u00e0 Mau \u0111\u00e3 c\u00f3 3 x\u00e3 Nguy\u1ec5n Hu\u00e2n, T\u00e2n D\u00e2n v\u00e0 Tr\u1ea7n Ph\u00e1n c\u00f4ng b\u1ed1 d\u1ecbch t\u1ea3 heo ch\u00e2u Phi.", "created_time": 1628632800, "id": "08e5eed9639fbe3dc4e1695b633e9d866db63a6d", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "17": [{"url": "https://anninhthudo.vn/o-to-tai-cho-4-nguoi-dinh-thong-chot-phong-chong-dich-vao-ha-noi-post476325.antd", "domain": "anninhthudo.vn", "title": "\u00d4 t\u00f4 t\u1ea3i ch\u1edf 4 ng\u01b0\u1eddi \u0111\u1ecbnh \"th\u00f4ng\" ch\u1ed1t ph\u00f2ng ch\u1ed1ng d\u1ecbch v\u00e0o H\u00e0 N\u1ed9i", "snippet": "Xe \u00f4 t\u00f4 t\u1ea3i d\u00e1n gi\u1ea5y \u01b0u ti\u00ean \"lu\u1ed3ng xanh\"\u00a0ch\u1edf th\u00eam\u00a04 ng\u01b0\u1eddi \u0111\u1ecbnh \u201cth\u00f4ng\u201d ch\u1ed1t ki\u1ec3m d\u1ecbch s\u1ed1 17, t\u1ea1i x\u00e3 Th\u00e1i H\u00f2a, huy\u1ec7n Ba V\u00ec \u0111\u1ec3 v\u00e0o H\u00e0 N\u1ed9i.", "created_time": 1628581624, "id": "anninhthudo.vn_476325", "score": 0.0, "title_summarize": ["Xe \u00f4 t\u00f4 t\u1ea3i d\u00e1n gi\u1ea5y \u01b0u ti\u00ean \"lu\u1ed3ng xanh\"\u00a0ch\u1edf th\u00eam\u00a04 ng\u01b0\u1eddi \u0111\u1ecbnh \u201cth\u00f4ng\u201d ch\u1ed1t ki\u1ec3m d\u1ecbch s\u1ed1 17, t\u1ea1i x\u00e3 Th\u00e1i H\u00f2a, huy\u1ec7n Ba V\u00ec \u0111\u1ec3 v\u00e0o H\u00e0 N\u1ed9i.", "Kinhtedothi \u2013 L\u1ef1c l\u01b0\u1ee3ng t\u1ea1i ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch s\u1ed1 17 ti\u1ebfn h\u00e0nh d\u1eebng, ki\u1ec3m tra xe \u00f4 t\u00f4 b\u00e1n t\u1ea3i di chuy\u1ec3n theo h\u01b0\u1edbng t\u1eeb t\u1ec9nh Ph\u00fa Th\u1ecd qua c\u1ea7u Trung H\u00e0 (huy\u1ec7n Ba V\u00ec) \u0111\u1ec3 v\u00e0o \u0111\u1ecba ph\u1eadn H\u00e0 N\u1ed9i \u0111\u00e3 ph\u00e1t hi\u1ec7n xe ch\u1edf 4 ng\u01b0\u1eddi kh\u00f4ng c\u00f3 gi\u1ea5y x\u00e9t nghi\u1ec7m Covid-19 \u0111\u1ecbnh v\u00e0o Th\u1ee7 \u0111\u00f4 theo \u0111\u01b0\u1eddng \"lu\u1ed3ng xanh\".", "Ch\u1ed1t ki\u1ec3m so\u00e1t s\u1ed1 17 huy\u1ec7n Ba V\u00ec, H\u00e0 N\u1ed9i ph\u00e1t hi\u1ec7n xe b\u00e1n t\u1ea3i c\u00f3 d\u00e1n gi\u1ea5y \u01b0u ti\u00ean \"lu\u1ed3ng xanh\" ch\u1edf theo 4 ng\u01b0\u1eddi \u0111\u1ecbnh v\u00e0o Th\u1ee7 \u0111\u00f4."], "content_summary": "\"Tr\u01b0\u1edbc \u0111\u00f3, kho\u1ea3ng 18h15 ng\u00e0y 9-8, trong qu\u00e1 tr\u00ecnh l\u00e0m nhi\u1ec7m v\u1ee5 t\u1ea1i ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch s\u1ed1 17, x\u00e3 Th\u00e1i H\u00f2a, huy\u1ec7n Ba V\u00ec, t\u1ed5 c\u00f4ng t\u00e1c ki\u1ec3m so\u00e1t d\u1ecbch Covid-19 s\u1ed1 17 \u0111\u00e3 ti\u1ebfn h\u00e0nh d\u1eebng, ki\u1ec3m tra xe \u00f4 t\u00f4 b\u00e1n t\u1ea3i bi\u1ec3n ki\u1ec3m so\u00e1t 29H-435.39 \u0111ang di chuy\u1ec3n theo h\u01b0\u1edbng t\u1eeb t\u1ec9nh Ph\u00fa Th\u1ecd qua c\u1ea7u Trung H\u00e0 (huy\u1ec7n Ba V\u00ec) \u0111\u1ec3 v\u00e0o \u0111\u1ecba ph\u1eadn H\u00e0 N\u1ed9i. C\u1ea3 4 ng\u01b0\u1eddi n\u00e0y kh\u00f4ng c\u00f3 h\u1ed9 kh\u1ea9u t\u1ea1i H\u00e0 N\u1ed9i v\u00e0 khi ki\u1ec3m tra \u0111\u1ec1u kh\u00f4ng c\u00f3 gi\u1ea5y x\u00e9t nghi\u1ec7m Covid-19. T\u1ea1i ch\u1ed1t ki\u1ec3m tra, t\u00e0i x\u1ebf P cho bi\u1ebft, anh nh\u1eadn ch\u1edf s\u1ed1 ng\u01b0\u1eddi tr\u00ean v\u00ec \u0111\u01b0\u1ee3c m\u1ed9t ng\u01b0\u1eddi quen nh\u1edd. \u0110\u1ea1i di\u1ec7n t\u1ed5 c\u00f4ng t\u00e1c cho bi\u1ebft, \u0111\u1ed1i v\u1edbi h\u00e0nh vi vi ph\u1ea1m n\u00e0y, theo Ngh\u1ecb \u0111\u1ecbnh s\u1ed1 117/N\u0110-CP c\u1ee7a Ch\u00ednh ph\u1ee7, l\u00e1i xe c\u00f3 th\u1ec3 s\u1ebd b\u1ecb x\u1eed ph\u1ea1t h\u00e0nh ch\u00ednh t\u1ed1i \u0111a l\u00ean t\u1edbi 40 tri\u1ec7u \u0111\u1ed3ng.\"", "total_facebook_viral": 0}, {"url": "https://kinhtedothi.vn/chot-kiem-soat-dich-phat-hien-xe-luong-xanh-cho-chui-4-nguoi-vao-ha-noi-430635.html", "domain": "kinhtedothi.vn", "title": "Ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch ph\u00e1t hi\u1ec7n xe \u201clu\u1ed3ng xanh\u201d ch\u1edf 'chui' 4 ng\u01b0\u1eddi v\u00e0o H\u00e0 N\u1ed9i", "snippet": "Kinhtedothi \u2013 L\u1ef1c l\u01b0\u1ee3ng t\u1ea1i ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch s\u1ed1 17 ti\u1ebfn h\u00e0nh d\u1eebng, ki\u1ec3m tra xe \u00f4 t\u00f4 b\u00e1n t\u1ea3i di chuy\u1ec3n theo h\u01b0\u1edbng t\u1eeb t\u1ec9nh Ph\u00fa Th\u1ecd qua c\u1ea7u Trung H\u00e0 (huy\u1ec7n Ba V\u00ec) \u0111\u1ec3 v\u00e0o \u0111\u1ecba ph\u1eadn H\u00e0 N\u1ed9i \u0111\u00e3 ph\u00e1t hi\u1ec7n xe ch\u1edf 4 ng\u01b0\u1eddi kh\u00f4ng c\u00f3 gi\u1ea5y x\u00e9t nghi\u1ec7m Covid-19 \u0111\u1ecbnh v\u00e0o Th\u1ee7 \u0111\u00f4 theo \u0111\u01b0\u1eddng \"lu\u1ed3ng xanh\".", "created_time": 1628585700, "id": "kinhtedothi.vn_430635", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://petrotimes.vn/phat-hien-xe-luong-xanh-cho-4-nguoi-vao-ha-noi-620889.html", "domain": "petrotimes.vn", "title": "Ph\u00e1t hi\u1ec7n xe \u201clu\u1ed3ng xanh\u201d ch\u1edf 4 ng\u01b0\u1eddi v\u00e0o H\u00e0 N\u1ed9i", "snippet": "Ch\u1ed1t ki\u1ec3m so\u00e1t s\u1ed1 17 huy\u1ec7n Ba V\u00ec, H\u00e0 N\u1ed9i ph\u00e1t hi\u1ec7n xe b\u00e1n t\u1ea3i c\u00f3 d\u00e1n gi\u1ea5y \u01b0u ti\u00ean \"lu\u1ed3ng xanh\" ch\u1edf theo 4 ng\u01b0\u1eddi \u0111\u1ecbnh v\u00e0o Th\u1ee7 \u0111\u00f4.", "created_time": 1628588390, "id": "petrotimes.vn_620889", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://laodong.vn/phap-luat/oto-ban-tai-luong-xanh-giau-4-nguoi-o-ghe-sau-dinh-thong-chot-vao-ha-noi-940401.ldo", "domain": "laodong.vn", "title": "\u00d4t\u00f4 b\u00e1n t\u1ea3i \u201clu\u1ed3ng xanh\u201d gi\u1ea5u 4 ng\u01b0\u1eddi \u1edf gh\u1ebf sau \u0111\u1ecbnh th\u00f4ng ch\u1ed1t v\u00e0o H\u00e0 N\u1ed9i", "snippet": "T\u00e0i x\u1ebf \u00f4t\u00f4 b\u00e1n t\u1ea3i d\u00e1n gi\u1ea5y \u01b0u ti\u00ean \"lu\u1ed3ng xanh\" ch\u1edf 4 ng\u01b0\u1eddi \u0111\u1ecbnh th\u00f4ng ch\u1ed1t ki\u1ec3m so\u00e1t \u1edf huy\u1ec7n Ba V\u00ec \u0111\u1ec3 v\u00e0o H\u00e0 N\u1ed9i song b\u1ecb t\u1ed5 c\u00f4ng t\u00e1c ph\u00e1t hi\u1ec7n.", "created_time": 1628589000, "id": "laodong.vn_940401", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://baophapluat.vn/xe-luong-xanh-giau-4-nguoi-chua-xet-nghiem-covid-19-dua-vao-ha-noi-post407047.html", "domain": "baophapluat.vn", "title": "Xe lu\u1ed3ng xanh 'gi\u1ea5u' 4 ng\u01b0\u1eddi ch\u01b0a x\u00e9t nghi\u1ec7m COVID-19 \u0111\u01b0a v\u00e0o H\u00e0 N\u1ed9i", "snippet": "Ng\u00e0y 10/8, C\u00f4ng an huy\u1ec7n Ba V\u00ec cho bi\u1ebft \u0111ang th\u1ee5 l\u00fd, gi\u1ea3i quy\u1ebft v\u1ee5 l\u00e1i xe b\u00e1n t\u1ea3i 'gi\u1ea5u' 4 ng\u01b0\u1eddi \u1edf h\u00e0ng gh\u1ebf sau \u0111\u1ec3 \u0111\u01b0a v\u00e0o H\u00e0 N\u1ed9i.", "created_time": 1628579243, "id": "baophapluat.vn_407047", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "18": [{"url": "http://trithuctructuyen.vn/bo-y-te-mot-trieu-lieu-vero-cell-nhap-ve-tphcm-du-dieu-kien-su-dung-post1249366.html", "domain": "trithuctructuyen.vn", "title": "B\u1ed9 Y t\u1ebf: M\u1ed9t tri\u1ec7u li\u1ec1u Vero Cell nh\u1eadp v\u1ec1 TP.HCM \u0111\u1ee7 \u0111i\u1ec1u ki\u1ec7n s\u1eed d\u1ee5ng", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "created_time": 1628656457, "id": "834cc1a8f0646f6aaf3ea9c9edd22e1155375c31", "score": 0.0, "title_summarize": ["D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "Di\u1ec5n bi\u1ebfn Covid-19: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "Di\u1ec5n bi\u1ebfn Covid-19: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng."], "content_summary": "\"Ng\u00e0y 11/8, Th\u1ee9 tr\u01b0\u1edfng Y t\u1ebf Tr\u01b0\u01a1ng Qu\u1ed1c C\u01b0\u1eddng v\u1eeba k\u00fd v\u0103n b\u1ea3n g\u1eedi UBND TP.HCM v\u1ec1 vi\u1ec7c s\u1eed d\u1ee5ng vaccine Covid-19 Vero Cell Inactivated (Sinopharm). Sinopharm c\u0169ng \u0111\u01b0\u1ee3c nhi\u1ec1u n\u01b0\u1edbc tr\u00ean th\u1ebf gi\u1edbi \u0111\u01b0a v\u00e0o s\u1eed d\u1ee5ng trong ti\u00eam ch\u1ee7ng. 28 ph\u00fat tr\u01b0\u1edbc D\u1ecbch Covid-19 \u0110i\u1ec1u quan tr\u1ecdng nh\u1ea5t khi \u0111i\u1ec1u tr\u1ecb b\u1ec7nh nh\u00e2n Covid-19 t\u1ea1i Vi\u1ec7t Nam 41 ph\u00fat tr\u01b0\u1edbc 11:02 11/8/2021 S\u1ee9c kh\u1ecfe S\u1ee9c kh\u1ecfe 0 Theo PGS.TS Nguy\u1ec5n L\u00e2n Hi\u1ebfu, ph\u00e2n lo\u1ea1i F0 thu\u1ed9c t\u1ea7ng \u0111i\u1ec1u tr\u1ecb n\u00e0o l\u00e0 \u0111i\u1ec1u r\u1ea5t quan tr\u1ecdng.\"", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.vn/bo-y-te-cho-phep-tphcm-su-dung-mot-trieu-lieu-vaccine-vero-cell-post1249366.html", "domain": "trithuctructuyen.vn", "title": "B\u1ed9 Y t\u1ebf cho ph\u00e9p TP.HCM s\u1eed d\u1ee5ng m\u1ed9t tri\u1ec7u li\u1ec1u vaccine Vero Cell", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "created_time": 1628656457, "id": "ef16576a34bedb618791fd4abdd65174ba61f920", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/bo-y-te-cho-phep-tphcm-su-dung-mot-trieu-lieu-vaccine-vero-cell-post1249366.html", "domain": "news.zing.vn", "title": "B\u1ed9 Y t\u1ebf cho ph\u00e9p TP.HCM s\u1eed d\u1ee5ng m\u1ed9t tri\u1ec7u li\u1ec1u vaccine Vero Cell", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "created_time": 1628656440, "id": "news.zing.vn_post1249366", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.com.vn/bo-y-te-mot-trieu-lieu-vero-cell-nhap-ve-tphcm-du-dieu-kien-su-dung-post1249366.html", "domain": "trithuctructuyen.com.vn", "title": "B\u1ed9 Y t\u1ebf: M\u1ed9t tri\u1ec7u li\u1ec1u Vero Cell nh\u1eadp v\u1ec1 TP.HCM \u0111\u1ee7 \u0111i\u1ec1u ki\u1ec7n s\u1eed d\u1ee5ng", "snippet": "D\u1ecbch Covid-19 b\u00f9ng ph\u00e1t: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "created_time": 1628656457, "id": "de7e1e71473bbbca1b29e5a0f80a8925dcc8b3d7", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.com.vn/bo-y-te-cho-phep-tphcm-su-dung-mot-trieu-lieu-vaccine-vero-cell-post1249366.html", "domain": "trithuctructuyen.com.vn", "title": "B\u1ed9 Y t\u1ebf cho ph\u00e9p TP.HCM s\u1eed d\u1ee5ng m\u1ed9t tri\u1ec7u li\u1ec1u vaccine Vero Cell", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: L\u00f4 vaccine n\u00e0y \u0111\u00e3 \u0111\u01b0\u1ee3c Vi\u1ec7n Ki\u1ec3m \u0111\u1ecbnh Qu\u1ed1c gia Vaccine v\u00e0 Sinh ph\u1ea9m y t\u1ebf ki\u1ec3m \u0111\u1ecbnh ch\u1ea5t l\u01b0\u1ee3ng.", "created_time": 1628656457, "id": "cfb63ad2ef8304f42617958cfef94217ecf481b8", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "19": [{"url": "http://trithuctructuyen.com.vn/ly-do-remdesivir-duoc-dung-de-chua-covid-19-du-khong-giam-tu-vong-post1249516.html", "domain": "trithuctructuyen.com.vn", "title": "L\u00fd do Remdesivir \u0111\u01b0\u1ee3c d\u00f9ng \u0111\u1ec3 ch\u1eefa Covid-19 d\u00f9 kh\u00f4ng gi\u1ea3m t\u1eed vong", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "created_time": 1628648427, "id": "eb640da11d9609566627cfc9b93ee6a723555c9b", "score": 0.0, "title_summarize": ["Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n."], "content_summary": "\"\u0110\u00e2y l\u00e0 th\u00f4ng tin \u0111\u01b0\u1ee3c PGS.TS Nguy\u1ec5n L\u00e2n Hi\u1ebfu (Gi\u00e1m \u0111\u1ed1c B\u1ec7nh vi\u1ec7n \u0110\u1ea1i h\u1ecdc Y H\u00e0 N\u1ed9i) \u0111\u01b0a ra b\u00e0n lu\u1eadn trong khu\u00f4n kh\u1ed5 ch\u01b0\u01a1ng tr\u00ecnh Telehealth do B\u1ec7nh vi\u1ec7n \u0110\u1ea1i h\u1ecdc Y H\u00e0 N\u1ed9i t\u1ed5 ch\u1ee9c v\u00e0o chi\u1ec1u 10/8. Sau \u0111\u00f3, t\u1eeb ng\u00e0y th\u1ee9 2 \u0111\u1ebfn ng\u00e0y th\u1ee9 5, b\u1ec7nh nh\u00e2n \u0111\u01b0\u1ee3c d\u00f9ng li\u1ec1u l\u01b0\u1ee3ng 100 mg/ng\u00e0y, truy\u1ec1n qua t\u0129nh m\u1ea1ch. Khi d\u1ecbch Covid-19 b\u00f9ng ph\u00e1t, c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u ph\u00e1t hi\u1ec7n r\u1eb1ng lo\u1ea1i thu\u1ed1c n\u00e0y c\u00f3 th\u1ec3 ng\u0103n SARS-CoV-2 ph\u00e2n b\u00e0o. \u0110\u00e2y c\u0169ng l\u00e0 k\u1ebft lu\u1eadn trong nghi\u00ean c\u1ee9u \u0111\u0103ng t\u1ea3i tr\u00ean t\u1ea1p ch\u00ed c\u1ee7a Hi\u1ec7p h\u1ed9i Y khoa M\u1ef9 ng\u00e0y 6/7, sau \u0111\u00f3 \u0111\u01b0\u1ee3c WHO khuy\u1ebfn c\u00e1o s\u1eed d\u1ee5ng trong ph\u00e1c \u0111\u1ed3 \u0111i\u1ec1u tr\u1ecb b\u1ec7nh nh\u00e2n Covid-19 c\u1eadp nh\u1eadt ng\u00e0y 7/7.\"", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/ly-do-remdesivir-duoc-dung-de-chua-covid-19-du-khong-giam-tu-vong-post1249516.html", "domain": "zingnews.vn", "title": "L\u00fd do Remdesivir \u0111\u01b0\u1ee3c d\u00f9ng \u0111\u1ec3 ch\u1eefa Covid-19 d\u00f9 kh\u00f4ng gi\u1ea3m t\u1eed vong", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "created_time": 1628648427, "id": "zingnews.vn_1249516", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/ly-do-remdesivir-duoc-dung-de-chua-covid-19-du-khong-giam-tu-vong-post1249516.html", "domain": "news.zing.vn", "title": "L\u00fd do Remdesivir \u0111\u01b0\u1ee3c d\u00f9ng \u0111\u1ec3 ch\u1eefa Covid-19 d\u00f9 kh\u00f4ng gi\u1ea3m t\u1eed vong", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "created_time": 1628648400, "id": "news.zing.vn_post1249516", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.vn/ly-do-remdesivir-duoc-dung-de-chua-covid-19-du-khong-giam-tu-vong-post1249516.html", "domain": "trithuctructuyen.vn", "title": "L\u00fd do Remdesivir \u0111\u01b0\u1ee3c d\u00f9ng \u0111\u1ec3 ch\u1eefa Covid-19 d\u00f9 kh\u00f4ng gi\u1ea3m t\u1eed vong", "snippet": "Di\u1ec5n bi\u1ebfn Covid-19: Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "created_time": 1628648427, "id": "4b3099d85d248ec681cbdc6886b72accfbb293b7", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://vnreview.vn/tin-tuc-covid-19/-/view_content/content/3505477/ly-do-remdesivir-duoc-dung-de-chua-covid-19-du-khong-giam-tu-vong", "domain": "vnreview.vn", "title": "L\u00fd do Remdesivir \u0111\u01b0\u1ee3c d\u00f9ng \u0111\u1ec3 ch\u1eefa Covid-19 d\u00f9 kh\u00f4ng gi\u1ea3m t\u1eed vong", "snippet": "Theo Ph\u00f3 gi\u00e1o s\u01b0 Nguy\u1ec5n L\u00e2n Hi\u1ebfu, Remdesivir ch\u01b0a ch\u1ee9ng minh \u0111\u01b0\u1ee3c kh\u1ea3 n\u0103ng gi\u1ea3m t\u1ef7 l\u1ec7 t\u1eed vong nh\u01b0ng n\u00f3 gi\u00fap b\u1ec7nh nh\u00e2n Covid-19 h\u1ed3i ph\u1ee5c nhanh, s\u1edbm ra vi\u1ec7n.", "created_time": 1628656022, "id": "vnreview.vn_3505477", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "20": [{"url": "https://kienthuc.net.vn/xa-hoi/hai-nhiem-vu-trong-tam-cua-ha-noi-trong-15-ngay-gian-cach-1575514.html", "domain": "kienthuc.net.vn", "title": "Hai nhi\u1ec7m v\u1ee5 tr\u1ecdng t\u00e2m c\u1ee7a H\u00e0 N\u1ed9i trong 15 ng\u00e0y gi\u00e3n c\u00e1ch", "snippet": "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "created_time": 1628645400, "id": "kienthuc.net.vn_1575514", "score": 0.0, "title_summarize": ["C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra."], "content_summary": "\"15 ng\u00e0y gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i l\u00e0 th\u1eddi gian \u0111\u1ec3 H\u00e0 N\u1ed9i \u0111\u00e1nh gi\u00e1 t\u00ecnh h\u00ecnh d\u1ecbch b\u1ec7nh v\u00e0 chu\u1ea9n b\u1ecb cho t\u00ecnh hu\u1ed1ng x\u1ea5u c\u00f3 th\u1ec3 x\u1ea3y ra. Tuy nhi\u00ean, v\u1ea5n \u0111\u1ec1 ph\u1ea3i ph\u1ea3i l\u00e0m sao n\u00e2ng cao n\u0103ng l\u1ef1c x\u00e9t nghi\u1ec7m b\u1eb1ng vi\u1ec7c nhanh ch\u00f3ng b\u1ed5 sung m\u00e1y m\u00f3c, sinh ph\u1ea9m, \u0111\u00e0o t\u1ea1o nh\u00e2n l\u1ef1c l\u1ea5y m\u1eabu \u0111\u1ec3 c\u00f3 k\u1ebft qu\u1ea3 trong th\u1eddi gian ng\u1eafn. C\u00e1c lo\u1ea1i vaccine nh\u01b0 Pfizer, Moderna tr\u01b0\u1edbc khi \u0111\u01b0\u1ee3c c\u1ea5p ph\u00e9p s\u1eed d\u1ee5ng \u0111\u00e3 \u0111\u01b0\u1ee3c th\u1eed nghi\u1ec7m tr\u00ean h\u00e0ng ch\u1ee5c ngh\u00ecn ng\u01b0\u1eddi cao tu\u1ed5i t\u00ecnh nguy\u1ec7n tr\u00ean th\u1ebf gi\u1edbi. \u0110\u00f3 l\u00e0 l\u00fd do t\u1ef7 l\u1ec7 nh\u1eadp vi\u1ec7n \u1edf nh\u1eefng ng\u01b0\u1eddi cao tu\u1ed5i l\u1edbn h\u01a1n v\u00e0 s\u1eed d\u1ee5ng ngu\u1ed3n l\u1ef1c y t\u1ebf cao g\u1ea5p nhi\u1ec1u l\u1ea7n ng\u01b0\u1eddi tr\u1ebb tu\u1ed5i.\"", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/hai-nhiem-vu-trong-tam-cua-ha-noi-trong-15-ngay-gian-cach-post1249360.html", "domain": "zingnews.vn", "title": "Hai nhi\u1ec7m v\u1ee5 tr\u1ecdng t\u00e2m c\u1ee7a H\u00e0 N\u1ed9i trong 15 ng\u00e0y gi\u00e3n c\u00e1ch", "snippet": "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "created_time": 1628636419, "id": "zingnews.vn_1249360", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.com.vn/hai-nhiem-vu-trong-tam-cua-ha-noi-trong-15-ngay-gian-cach-post1249360.html", "domain": "trithuctructuyen.com.vn", "title": "Hai nhi\u1ec7m v\u1ee5 tr\u1ecdng t\u00e2m c\u1ee7a H\u00e0 N\u1ed9i trong 15 ng\u00e0y gi\u00e3n c\u00e1ch", "snippet": "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "created_time": 1628636419, "id": "cd33bd53669afa2ae07b538aea9afee0a3f48788", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://zingnews.vn/hai-nhiem-vu-trong-tam-cua-ha-noi-trong-15-ngay-gian-cach-post1249360.html", "domain": "news.zing.vn", "title": "Hai nhi\u1ec7m v\u1ee5 tr\u1ecdng t\u00e2m c\u1ee7a H\u00e0 N\u1ed9i trong 15 ng\u00e0y gi\u00e3n c\u00e1ch", "snippet": "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "created_time": 1628636400, "id": "news.zing.vn_post1249360", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://trithuctructuyen.vn/hai-nhiem-vu-trong-tam-cua-ha-noi-trong-15-ngay-gian-cach-post1249360.html", "domain": "trithuctructuyen.vn", "title": "Hai nhi\u1ec7m v\u1ee5 tr\u1ecdng t\u00e2m c\u1ee7a H\u00e0 N\u1ed9i trong 15 ng\u00e0y gi\u00e3n c\u00e1ch", "snippet": "C\u00e1c chuy\u00ean gia nh\u1eadn \u0111\u1ecbnh di\u1ec5n bi\u1ebfn d\u1ecbch b\u1ec7nh kh\u00f3 l\u01b0\u1eddng t\u1ea1i c\u00e1c \u0111\u1ecba ph\u01b0\u01a1ng kh\u00e1c \u0111\u00f2i h\u1ecfi H\u00e0 N\u1ed9i ph\u1ea3i c\u00f3 s\u1ef1 chu\u1ea9n b\u1ecb k\u1ef9 l\u01b0\u1ee1ng \u0111\u1ec3 s\u1eb5n s\u00e0ng \u1ee9ng ph\u00f3 m\u1ecdi v\u1edbi t\u00ecnh hu\u1ed1ng x\u1ea3y ra.", "created_time": 1628636419, "id": "cbbe6f555997779070df85e68c423a21ff775f27", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "21": [{"url": "https://kinhtedothi.vn/nghia-tan-va-mo-hinh-to-dan-pho-xanh-cap-phuong-dau-tien-cua-ha-noi-430735.html", "domain": "kinhtedothi.vn", "title": "Ngh\u0129a T\u00e2n v\u00e0 m\u00f4 h\u00ecnh 'T\u1ed5 d\u00e2n ph\u1ed1 xanh' c\u1ea5p ph\u01b0\u1eddng \u0111\u1ea7u ti\u00ean c\u1ee7a H\u00e0 N\u1ed9i", "snippet": "Kinhtedothi - B\u1eaft \u0111\u1ea7u t\u1eeb ng\u00e0y 10/8, ph\u01b0\u1eddng Ngh\u0129a T\u00e2n, qu\u1eadn C\u1ea7u Gi\u1ea5y \u0111\u00e3 tri\u1ec3n khai x\u00e2y d\u1ef1ng m\u00f4 h\u00ecnh \u201cT\u1ed5 d\u00e2n ph\u1ed1 xanh\u201d ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19 tr\u00ean to\u00e0n \u0111\u1ecba b\u00e0n.", "created_time": 1628659500, "id": "kinhtedothi.vn_430735", "score": 0.0, "title_summarize": ["Kinhtedothi - B\u1eaft \u0111\u1ea7u t\u1eeb ng\u00e0y 10/8, ph\u01b0\u1eddng Ngh\u0129a T\u00e2n, qu\u1eadn C\u1ea7u Gi\u1ea5y \u0111\u00e3 tri\u1ec3n khai x\u00e2y d\u1ef1ng m\u00f4 h\u00ecnh \u201cT\u1ed5 d\u00e2n ph\u1ed1 xanh\u201d ph\u00f2ng, ch\u1ed1ng d\u1ecbch Covid-19 tr\u00ean to\u00e0n \u0111\u1ecba b\u00e0n.", "Do tr\u00ean \u0111\u1ecba b\u00e0n ch\u01b0a c\u00f3 ca f0 n\u00e0o n\u00ean ch\u00ednh quy\u1ec1n v\u00e0 nh\u00e2n d\u00e2n ph\u01b0\u1eddng Ngh\u0129a T\u00e2n, qu\u1eadn C\u1ea7u Gi\u1ea5y \u0111\u00e3 thi\u1ebft l\u1eadp nhi\u1ec1u ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch COVID-19.", "M\u00f4 h\u00ecnh \u2018T\u1ed5 d\u00e2n ph\u1ed1 xanh\u2019 c\u1ea5p Ph\u01b0\u1eddng \u0111\u1ea7u ti\u00ean c\u1ee7a TP H\u00e0 N\u1ed9i \u0111\u01b0\u1ee3c tri\u1ec3n khai ph\u01b0\u1eddng Ngh\u0129a T\u00e2n, qu\u1eadn C\u1ea7u Gi\u1ea5y."], "content_summary": "\"B\u1eaft \u0111\u1ea7u t\u1eeb ng\u00e0y 10/8, ph\u01b0\u1eddng Ngh\u0129a T\u00e2n t\u1ed5 ch\u1ee9c 6 \u0111i\u1ec3m ch\u1ed1t ch\u00ednh v\u00e0 28 \u0111i\u1ec3m ch\u1ed1t ph\u1ee5 ''T\u1ed5 d\u00e2n ph\u1ed1 xanh''. C\u00e1c ch\u1ed1t n\u00e0y c\u00f3 t\u1eeb 4 - 5 th\u00e0nh vi\u00ean v\u1edbi s\u1ef1 tham gia c\u1ee7a UBND, c\u00f4ng an ph\u01b0\u1eddng, l\u1ef1c l\u01b0\u1ee3ng d\u00e2n ph\u00f2ng v\u00e0 l\u00e3nh \u0111\u1ea1o t\u1ed5 d\u00e2n ph\u1ed1 tr\u00ean \u0111\u1ecba b\u00e0n. \u201c T\u1ea1i c\u00e1c ch\u1ed1t \\\"T\u1ed5 d\u00e2n ph\u1ed1 xanh\\\"\u00a0an to\u00e0n, ng\u01b0\u1eddi l\u1ea1 ra v\u00e0o \u0111\u1ec1u ph\u1ea3i khai b\u00e1o y t\u1ebf, th\u1ef1c hi\u1ec7n nghi\u00eam nguy\u00ean t\u1eafc \\\"5K\\\", ng\u01b0\u1eddi v\u1eadn chuy\u1ec3n h\u00e0ng h\u00f3a \u0111\u1ebfn ch\u1ec9 \u0111\u01b0\u1ee3c giao t\u1ea1i b\u00e0n ch\u1ed1t tr\u1ef1c, kh\u00f4ng \u0111\u01b0a tr\u1ef1c ti\u1ebfp v\u00e0o nh\u00e0 d\u00e2n\u201d - \u00f4ng L\u00e2m V\u0103n Th\u1ea3o cho bi\u1ebft. C\u00e1c ch\u1ed1t n\u00e0y s\u1ebd do T\u1ed5 Covid c\u1ed9ng \u0111\u1ed3ng v\u00e0 ng\u01b0\u1eddi d\u00e2n trong khu v\u1ef1c tr\u1ef1c ti\u1ebfp th\u1ef1c hi\u1ec7n.\"", "total_facebook_viral": 0}, {"url": "https://tv.congluan.vn/to-dan-pho-xanh-cap-phuong-dau-tien-o-ha-noi-post149593.html", "domain": "congluan.vn", "title": "'T\u1ed5 d\u00e2n ph\u1ed1 xanh' c\u1ea5p ph\u01b0\u1eddng \u0111\u1ea7u ti\u00ean \u1edf H\u00e0 N\u1ed9i", "snippet": "Do tr\u00ean \u0111\u1ecba b\u00e0n ch\u01b0a c\u00f3 ca f0 n\u00e0o n\u00ean ch\u00ednh quy\u1ec1n v\u00e0 nh\u00e2n d\u00e2n ph\u01b0\u1eddng Ngh\u0129a T\u00e2n, qu\u1eadn C\u1ea7u Gi\u1ea5y \u0111\u00e3 thi\u1ebft l\u1eadp nhi\u1ec1u ch\u1ed1t ki\u1ec3m so\u00e1t d\u1ecbch COVID-19.", "created_time": 1628656140, "id": "congluan.vn_149593", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://video.vietnamnet.vn/nhung-to-dan-pho-xanh-dau-tien-bao-ve-vung-xanh-ha-noi-a-93824.html", "domain": "video.vietnamnet.vn", "title": "Nh\u1eefng 't\u1ed5 d\u00e2n ph\u1ed1 xanh' \u0111\u1ea7u ti\u00ean b\u1ea3o v\u1ec7 'v\u00f9ng xanh' H\u00e0 N\u1ed9i", "snippet": "M\u00f4 h\u00ecnh \u2018T\u1ed5 d\u00e2n ph\u1ed1 xanh\u2019 c\u1ea5p Ph\u01b0\u1eddng \u0111\u1ea7u ti\u00ean c\u1ee7a TP H\u00e0 N\u1ed9i \u0111\u01b0\u1ee3c tri\u1ec3n khai ph\u01b0\u1eddng Ngh\u0129a T\u00e2n, qu\u1eadn C\u1ea7u Gi\u1ea5y.", "created_time": 1628614800, "id": "video.vietnamnet.vn_93824", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://trian.vn/-to-dan-pho-xanh-dau-tien-duoc-thanh-lap-tai-ha-noi/d20210811065617968.htm", "domain": "trian.vn", "title": "`T\u1ed5 d\u00e2n ph\u1ed1 xanh` \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c th\u00e0nh l\u1eadp t\u1ea1i H\u00e0 N\u1ed9i", "snippet": "6 ch\u1ed1t `T\u1ed5 d\u00e2n ph\u1ed1 xanh` \u0111\u00e3 \u0111\u01b0\u1ee3c ph\u01b0\u1eddng Ngh\u0129a T\u00e2n ( qu\u1eadn C\u1ea7u Gi\u1ea5y, H\u00e0 N\u1ed9i) thi\u1ebft l\u1eadp trong s\u00e1ng ng\u00e0y 10.8.", "created_time": 1628639760, "id": "trian.vn_20210811065617968", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}], "22": [{"url": "https://dangcongsan.vn/thoi-su/ha-noi-xu-phat-hon-19-5-ty-dong-vi-pham-quy-dinh-phong-chong-dich-587782.html", "domain": "dangcongsan.vn", "title": "H\u00e0 N\u1ed9i x\u1eed ph\u1ea1t h\u01a1n 19,5 t\u1ef7 \u0111\u1ed3ng vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "snippet": "(\u0110CSVN) - Trong h\u01a1n trong 02 tu\u1ea7n th\u1ef1c hi\u1ec7n gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i theo Ch\u1ec9 th\u1ecb c\u1ee7a Ch\u1ee7 t\u1ecbch UBND TP H\u00e0 N\u1ed9i, c\u00e1c c\u01a1 quan ch\u1ee9c n\u0103ng H\u00e0 N\u1ed9i \u0111\u00e3 x\u1eed ph\u1ea1t h\u00e0nh ch\u00ednh h\u01a1n 12.500 tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng ch\u1ed1ng d\u1ecbch COVID-19 v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n h\u01a1n 19,5 t\u1ef7 \u0111\u1ed3ng.", "created_time": 1628646660, "id": "dangcongsan.vn_587782", "score": 0.0, "title_summarize": ["(\u0110CSVN) - Trong h\u01a1n trong 02 tu\u1ea7n th\u1ef1c hi\u1ec7n gi\u00e3n c\u00e1ch x\u00e3 h\u1ed9i theo Ch\u1ec9 th\u1ecb c\u1ee7a Ch\u1ee7 t\u1ecbch UBND TP H\u00e0 N\u1ed9i, c\u00e1c c\u01a1 quan ch\u1ee9c n\u0103ng H\u00e0 N\u1ed9i \u0111\u00e3 x\u1eed ph\u1ea1t h\u00e0nh ch\u00ednh h\u01a1n 12.500 tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng ch\u1ed1ng d\u1ecbch COVID-19 v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n h\u01a1n 19,5 t\u1ef7 \u0111\u1ed3ng.", "VTV.vn - T\u1eeb ng\u00e0y 24/7 \u0111\u1ebfn chi\u1ec1u ng\u00e0y 9/8, C\u00f4ng an qu\u1eadn C\u1ea7u Gi\u1ea5y cho bi\u1ebft \u0111\u00e3 x\u1eed ph\u1ea1t 827 v\u1ee5 vi\u1ec7c vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng ch\u1ed1ng d\u1ecbch v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n ph\u1ea1t h\u01a1n 1,5 t\u1ef7 \u0111\u1ed3ng.", "H\u00e0 N\u1ed9i x\u1eed ph\u1ea1t h\u01a1n 19,5 t\u1ef7 \u0111\u1ed3ng vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng, ch\u1ed1ng d\u1ecbch"], "content_summary": "\"');this.closest('table').remove();\\\"> 1 tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m v\u1ec1 ph\u00f2ng ch\u1ed1ng d\u1ecbch COVID-19 b\u1ecb t\u1ed5 c\u00f4ng t\u00e1c t\u1ea1i qu\u1eadn B\u1eafc T\u1eeb Li\u00eam, H\u00e0 N\u1ed9i x\u1eed ph\u1ea1t. \u0110\u1ed3ng th\u1eddi, x\u1eed ph\u1ea1t 87 c\u01a1 s\u1edf ho\u1ea1t \u0111\u1ed9ng kinh doanh kh\u00f4ng thi\u1ebft y\u1ebfu v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n 918 tri\u1ec7u \u0111\u1ed3ng. C\u00f9ng ng\u00e0y, C\u00f4ng an qu\u1eadn Nam T\u1eeb Li\u00eam l\u00e0m nhi\u1ec7m v\u1ee5 t\u1ea1i khu v\u1ef1c b\u1ebfn xe M\u1ef9 \u0110\u00ecnh, ph\u00e1t hi\u1ec7n 01 xe c\u1ee9u th\u01b0\u01a1ng ch\u1edf 02 ng\u01b0\u1eddi t\u1eeb Vinh ra H\u00e0 N\u1ed9i tr\u00e1i quy \u0111\u1ecbnh.\"", "total_facebook_viral": 0}, {"url": "https://vtv.vn/xa-hoi/quan-cau-giay-phat-hon-15-ty-dong-vi-pham-phong-chong-dich-covid-19-20210810141344437.htm", "domain": "vtv.vn", "title": "Qu\u1eadn C\u1ea7u Gi\u1ea5y ph\u1ea1t h\u01a1n 1,5 t\u1ef7 \u0111\u1ed3ng vi ph\u1ea1m ph\u00f2ng, ch\u1ed1ng d\u1ecbch COVID-19", "snippet": "VTV.vn - T\u1eeb ng\u00e0y 24/7 \u0111\u1ebfn chi\u1ec1u ng\u00e0y 9/8, C\u00f4ng an qu\u1eadn C\u1ea7u Gi\u1ea5y cho bi\u1ebft \u0111\u00e3 x\u1eed ph\u1ea1t 827 v\u1ee5 vi\u1ec7c vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng ch\u1ed1ng d\u1ecbch v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n ph\u1ea1t h\u01a1n 1,5 t\u1ef7 \u0111\u1ed3ng.", "created_time": 1628580120, "id": "vtv.vn_20210810141344437", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "http://dientudacam.vn/van-hoa-xa-hoi/xa-hoi/ha-noi-xu-phat-hon-19-5-ty-dong-vi-pham-quy-dinh-phong-chong-dich-5899.html", "domain": "dientudacam.vn", "title": "H\u00e0 N\u1ed9i x\u1eed ph\u1ea1t h\u01a1n 19,5 t\u1ef7 \u0111\u1ed3ng vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "snippet": "H\u00e0 N\u1ed9i x\u1eed ph\u1ea1t h\u01a1n 19,5 t\u1ef7 \u0111\u1ed3ng vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng, ch\u1ed1ng d\u1ecbch", "created_time": 1628651220, "id": "7741444c6dac07ccca0cf2c58653c961193fe5db", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}, {"url": "https://thuonghieucongluan.com.vn/tu-ngay-24-7-den-10-8-ha-noi-xu-phat-hon-12-400-truong-hop-vi-pham-quy-dinh-phong-dich-voi-tong-so-tien-gan-19-ty-a142776.html", "domain": "thuonghieucongluan.com.vn", "title": "T\u1eeb ng\u00e0y 24/7 \u0111\u1ebfn 10/8: H\u00e0 N\u1ed9i x\u1eed ph\u1ea1t h\u01a1n 12.400 tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng d\u1ecbch, v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n g\u1ea7n 19 t\u1ef7", "snippet": "Th\u00f4ng tin m\u1edbi nh\u1ea5t t\u1eeb C\u00f4ng an H\u00e0 N\u1ed9i cho bi\u1ebft, t\u00ednh t\u1eeb ng\u00e0y 24/7 \u0111\u1ebfn 10/8, l\u1ef1c l\u01b0\u1ee3ng ch\u1ee9c n\u0103ng \u0111\u00e3 x\u1eed ph\u1ea1t h\u01a1n 12.400 tr\u01b0\u1eddng h\u1ee3p vi ph\u1ea1m quy \u0111\u1ecbnh ph\u00f2ng ch\u1ed1ng d\u1ecbch Covid-19 v\u1edbi t\u1ed5ng s\u1ed1 ti\u1ec1n g\u1ea7n 19 t\u1ef7 \u0111\u1ed3ng.", "created_time": 1628602740, "id": "thuonghieucongluan.com.vn_a142776", "score": 0.0, "title_summarize": [], "content_summary": "", "total_facebook_viral": 0}]} \ No newline at end of file diff --git a/run_multi_process.py b/run_multi_process.py new file mode 100644 index 0000000000000000000000000000000000000000..f69fef8528ea54bede4485c6d2e3a9a7ef0105c8 --- /dev/null +++ b/run_multi_process.py @@ -0,0 +1,28 @@ +import subprocess +from multiprocessing import Process +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +def run_consumer_clustering(): + proc = subprocess.Popen("python consumer_clustering.py", shell=True) + print(proc.pid) + proc.communicate() + +def run_consumer_merge_clustering(): + proc = subprocess.Popen("python consumer_merge_clustering.py", shell=True) + print(proc.pid) + proc.communicate() + +if __name__ == '__main__': + execs = [] + + n_pro = 5 + + for pro in [run_consumer_clustering ,run_consumer_merge_clustering]: + for i in range(n_pro): + ex = Process(target=pro, args=()) + execs.append(ex) + ex.start() + + for exe in execs: + exe.join() diff --git a/service.py b/service.py new file mode 100644 index 0000000000000000000000000000000000000000..1a53b28e1aec8de5d9e6ada2d7577f4b7e5bc1de --- /dev/null +++ b/service.py @@ -0,0 +1,39 @@ +from entity import Docs, Cluster +from fastapi import FastAPI +import time +import json +from fastapi.middleware.cors import CORSMiddleware +from function import topic_clustering as tc + + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +@app.post("/newsanalysis/topic_clustering") +def topic_clustering(item: Docs): + docs = item.response["docs"] + # threshold = item.threshold + hash_id = str(time.time()) + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + with open("log/input_{0}.txt".format(hash_id), "w+") as f: + f.write(json.dumps({"docs": docs, "key": item.keyword})) + st_time = time.time() + print("start ") + print("len doc: ", len(docs)) + threshold = 0.1 + results = tc.topic_clustering(docs, threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary) + with open("log/result_{0}.txt".format(hash_id), "w+") as f: + f.write(json.dumps(results)) + print("time analysis: ", time.time() - st_time) + return results + diff --git a/service_cache.py b/service_cache.py new file mode 100644 index 0000000000000000000000000000000000000000..f064fa29e150aba10f60986f66bf777b91d905ac --- /dev/null +++ b/service_cache.py @@ -0,0 +1,181 @@ +from entity import Docs, Cluster, Preprocess, SummaryInput +from fastapi import FastAPI +import time +import hashlib +import json +from fastapi.middleware.cors import CORSMiddleware +# from function import topic_clustering as tc +from function import topic_clustering_v2 as tc +from iclibs.ic_rabbit import ICRabbitMQ +from get_config import config_params + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +def get_hash_id(item: Docs): + str_hash = "" + for it in item.response["docs"]: + str_hash += it["url"] + str_hash += str(item.top_cluster) + str_hash += str(item.top_sentence) + str_hash += str(item.topn_summary) + str_hash += str(item.top_doc) + str_hash += str(item.threshold) + if item.sorted_field.strip(): + str_hash += str(item.sorted_field) + if item.delete_message: + str_hash += str(item.delete_message) + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + + +try: + with open("log_run/log.txt") as f: + data_dict = json.load(f) +except Exception as ve: + print(ve) + data_dict = {} + + +@app.post("/newsanalysis/topic_clustering") +async def topic_clustering(item: Docs): + docs = item.response["docs"] + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + sorted_field = item.sorted_field + max_doc_per_cluster = item.max_doc_per_cluster + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + # with open("log/input_{0}.txt".format(st_time), "w+") as f: + # f.write(json.dumps({"docs": docs, "key": item.keyword})) + + print(hash_str) + if len(docs) > 200: + + try: + if hash_str in data_dict: + path_res = data_dict[hash_str]["response_path"] + with open(path_res) as ff: + results = json.load(ff) + print("time analysis (cache): ", time.time() - st_time) + return results + except Exception as vee: + print(vee) + + results = tc.topic_clustering(docs, item.threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, sorted_field=sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=item.delete_message) + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, "w+") as ff: + ff.write(json.dumps(results)) + data_dict[hash_str] = {"time": st_time, "response_path": path_res} + + lst_rm = [] + for dt in data_dict: + if time.time() - data_dict[dt]["time"] > 30 * 24 * 3600: + lst_rm.append(dt) + for dt in lst_rm: + del data_dict[dt] + with open("log_run/log.txt", "w+") as ff: + ff.write(json.dumps(data_dict)) + print("time analysis: ", time.time() - st_time) + return results + +def init_rabbit_queue(usr, passw, host, vir_host, queue_name, durable, max_priority, exchange=""): + connection = ICRabbitMQ(host, vir_host, usr, passw) + connection.init_connection() + channel = connection.init_queue( + queue_name, exchange=exchange, durable=durable, max_priority=max_priority) + return channel, connection, queue_name + + +@app.post("/newsanalysis/topic_clustering_2") +async def topic_clustering_v2(item: Docs): + docs = item.response["docs"] + meta = item.response.get('meta', {}) + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + # with open("log/input_{0}.txt".format(st_time), "w+") as f: + # f.write(json.dumps({"docs": docs, "key": item.keyword})) + + data_push = { + "docs": docs, + "threshold": item.threshold, + "top_cluster": top_cluster, + "top_sentence": top_sentence, + "topn_summary": topn_summary, + "hash_str": hash_str, + "st_time": st_time, + "meta": meta + } + params = config_params['queue_topic_clustering'] + usr_name = params["usr_name"] + password = str(params["password"]) + host = params["host"] + virtual_host = params["virtual_host"] + queue_name = params["queue_name"] + + channel_consumer, rb_consumer, queue_consumer = init_rabbit_queue(usr_name, password, host, virtual_host, queue_name, True, 10) + + ICRabbitMQ.publish_message(channel_consumer, queue_consumer, data_push, priority= 1,delivery_mode=2, exchange='') + return {"message":"success"} + + +@app.post("/newsanalysis/topic_clustering_with_preprocess") +async def topic_clustering_with_preprocess(item: Preprocess): + with open('preprocess.json','w') as f: + json.dump(item.__dict__,f,ensure_ascii=False) + + data_push = { + "type": item.type, + "threshold": item.threshold, + "top_cluster": item.top_cluster, + "benchmark_id": item.benchmark_id, + "benchmark_children_id": item.benchmark_children_id, + "source_tagids": item.source_tagids, + "preprocess": item.preprocess, + "meta": item.meta + + } + params = config_params['queue_merge_clustering'] + usr_name = params["usr_name"] + password = str(params["password"]) + host = params["host"] + virtual_host = params["virtual_host"] + queue_name = params["queue_name"] + + channel_consumer, rb_consumer, queue_consumer = init_rabbit_queue(usr_name, password, host, virtual_host, queue_name, True, 10) + + ICRabbitMQ.publish_message(channel_consumer, queue_consumer, data_push, priority= 1,delivery_mode=2, exchange='') + return {"message":"success"} + + +@app.post("/newsanalysis/summary") +async def summary(item: SummaryInput): + try: + summary_txt = tc.get_summary_bert(item.text, lang=None, topn=item.topn, ratio = 0.2) + except Exception as ex: + # raise ex + summary_txt = '' + return summary_txt diff --git a/service_cache_Thien.py b/service_cache_Thien.py new file mode 100644 index 0000000000000000000000000000000000000000..52c15069e6997cfbc1dfcfe9da62494c6c43e6f2 --- /dev/null +++ b/service_cache_Thien.py @@ -0,0 +1,57 @@ + +import requests + +def get_data_sorl(query, keywords, start_time, end_time, max_posts = 100): + start_time = start_time.strip() + end_time = end_time.strip() + json_data = { + 'category_ids': [], + 'text_query': query, + 'max_posts': max_posts, + 'top': 50, + 'lang': 'vi', + 'source_tagids': [], + 'cee': True, + 'keywords': keywords, + 'start_time': start_time.replace(' ', 'T'), + 'end_time': end_time.replace(' ', 'T'), + } + + res = [] + request_search_qna = 'http://10.9.3.241:2436/service_get_data_sorl' + try: + response = requests.post('http://10.9.3.241:2436/service_get_data_sorl', json=json_data) + if response.status_code == 200: + res = response.json()['results'] + else: + print("Error search QnA: ", response.text) + except Exception as ex: + print("Error search QnA: ", ex) + + + json_data = { + 'category_ids': [], + 'text_query': query, + 'max_posts': 100, + 'top': 50, + 'lang': 'vi', + 'source_tagids': [], + 'cee': False, + 'keywords': keywords, + 'start_time': start_time, + 'end_time': end_time, + } + res_2 = [] + try: + response = requests.post('http://10.9.3.241:2436/service_get_data_sorl', json=json_data) + if response.status_code == 200: + res_2 = response.json()['results'] + else: + print("Error search QnA: ", response.text) + except Exception as ex: + print("Error search QnA: ", ex) + + res.extend(res_2) + return res + + diff --git a/service_cache_v2.py b/service_cache_v2.py new file mode 100644 index 0000000000000000000000000000000000000000..eac45b3b7722dfe19fcf50d647b2f5856d2592f9 --- /dev/null +++ b/service_cache_v2.py @@ -0,0 +1,104 @@ +from entity import Docs, Cluster, Preprocess, SummaryInput, DocsWithSamples +from fastapi import FastAPI +import time +import hashlib +import json +from fastapi.middleware.cors import CORSMiddleware +# from function import topic_clustering as tc +from function import topic_clustering_v2 as tc +from iclibs.ic_rabbit import ICRabbitMQ +from get_config import config_params +from summary import postprocess_title_clusters + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +def get_hash_id(item: DocsWithSamples): + str_hash = "" + for it in item.response["docs"]: + str_hash += it["url"] + str_hash += str(item.top_cluster) + str_hash += str(item.top_sentence) + str_hash += str(item.topn_summary) + str_hash += str(item.top_doc) + str_hash += str(item.threshold) + if item.sorted_field.strip(): + str_hash += str(item.sorted_field) + if item.delete_message: + str_hash += str(item.delete_message) + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + + +try: + with open("log_run/log.txt") as f: + data_dict = json.load(f) +except Exception as ve: + print(ve) + data_dict = {} + + +@app.post("/newsanalysis/topic_clustering") +async def topic_clustering(item: DocsWithSamples): + docs = item.response["docs"] + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + sorted_field = item.sorted_field + max_doc_per_cluster = item.max_doc_per_cluster + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + print(hash_str) + if len(docs) > 200: + + try: + if hash_str in data_dict: + path_res = data_dict[hash_str]["response_path"] + with open(path_res) as ff: + results = json.load(ff) + print("time analysis (cache): ", time.time() - st_time) + return results + except Exception as vee: + print(vee) + + results = tc.topic_clustering(docs, item.threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, sorted_field=sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=False) + results = postprocess_title_clusters(results, delete_message=item.delete_message) + + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, "w+") as ff: + ff.write(json.dumps(results)) + data_dict[hash_str] = {"time": st_time, "response_path": path_res} + + lst_rm = [] + for dt in data_dict: + if time.time() - data_dict[dt]["time"] > 30 * 24 * 3600: + lst_rm.append(dt) + for dt in lst_rm: + del data_dict[dt] + with open("log_run/log.txt", "w+") as ff: + ff.write(json.dumps(data_dict)) + print("time analysis: ", time.time() - st_time) + return results + +def init_rabbit_queue(usr, passw, host, vir_host, queue_name, durable, max_priority, exchange=""): + connection = ICRabbitMQ(host, vir_host, usr, passw) + connection.init_connection() + channel = connection.init_queue( + queue_name, exchange=exchange, durable=durable, max_priority=max_priority) + return channel, connection, queue_name + + + diff --git a/service_cpu.py b/service_cpu.py new file mode 100644 index 0000000000000000000000000000000000000000..331b02ff80a64825edc921ce4fc17d9f24e471f9 --- /dev/null +++ b/service_cpu.py @@ -0,0 +1,176 @@ +from entity import Docs, Cluster, Preprocess, SummaryInput +from fastapi import FastAPI +import time +import hashlib +import json +from fastapi.middleware.cors import CORSMiddleware +from function import topic_clustering as tc +# from function import topic_clustering_v2 as tc +from iclibs.ic_rabbit import ICRabbitMQ +from get_config import config_params + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +def get_hash_id(item: Docs): + str_hash = "" + for it in item.response["docs"]: + str_hash += it["url"] + str_hash += str(item.top_cluster) + str_hash += str(item.top_sentence) + str_hash += str(item.topn_summary) + str_hash += str(item.top_doc) + str_hash += str(item.threshold) + if item.sorted_field.strip(): + str_hash += str(item.sorted_field) + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + + +try: + with open("log_run/log.txt") as f: + data_dict = json.load(f) +except Exception as ve: + print(ve) + data_dict = {} + + +@app.post("/newsanalysis/topic_clustering") +async def topic_clustering(item: Docs): + docs = item.response["docs"] + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + sorted_field = item.sorted_field + max_doc_per_cluster = item.max_doc_per_cluster + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + # with open("log/input_{0}.txt".format(st_time), "w+") as f: + # f.write(json.dumps({"docs": docs, "key": item.keyword})) + + try: + if hash_str in data_dict: + path_res = data_dict[hash_str]["response_path"] + with open(path_res) as ff: + results = json.load(ff) + print("time analysis (cache): ", time.time() - st_time) + return results + except Exception as vee: + print(vee) + + results = tc.topic_clustering(docs, item.threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, sorted_field=sorted_field, max_doc_per_cluster=max_doc_per_cluster) + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, "w+") as ff: + ff.write(json.dumps(results)) + data_dict[hash_str] = {"time": st_time, "response_path": path_res} + + lst_rm = [] + for dt in data_dict: + if time.time() - data_dict[dt]["time"] > 30 * 24 * 3600: + lst_rm.append(dt) + for dt in lst_rm: + del data_dict[dt] + with open("log_run/log.txt", "w+") as ff: + ff.write(json.dumps(data_dict)) + print("time analysis: ", time.time() - st_time) + return results + +def init_rabbit_queue(usr, passw, host, vir_host, queue_name, durable, max_priority, exchange=""): + connection = ICRabbitMQ(host, vir_host, usr, passw) + connection.init_connection() + channel = connection.init_queue( + queue_name, exchange=exchange, durable=durable, max_priority=max_priority) + return channel, connection, queue_name + + +@app.post("/newsanalysis/topic_clustering_2") +async def topic_clustering_v2(item: Docs): + docs = item.response["docs"] + meta = item.response.get('meta', {}) + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + # with open("log/input_{0}.txt".format(st_time), "w+") as f: + # f.write(json.dumps({"docs": docs, "key": item.keyword})) + + data_push = { + "docs": docs, + "threshold": item.threshold, + "top_cluster": top_cluster, + "top_sentence": top_sentence, + "topn_summary": topn_summary, + "hash_str": hash_str, + "st_time": st_time, + "meta": meta + } + params = config_params['queue_topic_clustering'] + usr_name = params["usr_name"] + password = str(params["password"]) + host = params["host"] + virtual_host = params["virtual_host"] + queue_name = params["queue_name"] + + channel_consumer, rb_consumer, queue_consumer = init_rabbit_queue(usr_name, password, host, virtual_host, queue_name, True, 10) + + ICRabbitMQ.publish_message(channel_consumer, queue_consumer, data_push, priority= 1,delivery_mode=2, exchange='') + return {"message":"success"} + + +@app.post("/newsanalysis/topic_clustering_with_preprocess") +async def topic_clustering_with_preprocess(item: Preprocess): + with open('preprocess.json','w') as f: + json.dump(item.__dict__,f,ensure_ascii=False) + + data_push = { + "type": item.type, + "threshold": item.threshold, + "top_cluster": item.top_cluster, + "benchmark_id": item.benchmark_id, + "benchmark_children_id": item.benchmark_children_id, + "source_tagids": item.source_tagids, + "preprocess": item.preprocess, + "meta": item.meta + + } + params = config_params['queue_merge_clustering'] + usr_name = params["usr_name"] + password = str(params["password"]) + host = params["host"] + virtual_host = params["virtual_host"] + queue_name = params["queue_name"] + + channel_consumer, rb_consumer, queue_consumer = init_rabbit_queue(usr_name, password, host, virtual_host, queue_name, True, 10) + + ICRabbitMQ.publish_message(channel_consumer, queue_consumer, data_push, priority= 1,delivery_mode=2, exchange='') + return {"message":"success"} + + +@app.post("/newsanalysis/summary") +async def summary(item: SummaryInput): + try: + summary_txt = tc.get_summary_bert(item.text, lang=None, topn=item.topn, ratio = 0.2) + except Exception as ex: + print(ex) + summary_txt = '' + return summary_txt \ No newline at end of file diff --git a/service_mnews.py b/service_mnews.py new file mode 100644 index 0000000000000000000000000000000000000000..53d1cd1c27d00294e1b0941b8c391b383b15257e --- /dev/null +++ b/service_mnews.py @@ -0,0 +1,90 @@ +from entity import Docs, Cluster, Preprocess, SummaryInput +from fastapi import FastAPI +import time +import hashlib +import json +from fastapi.middleware.cors import CORSMiddleware +from iclibs.ic_rabbit import ICRabbitMQ +from get_config import config_params + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +def get_hash_id(item: Docs): + str_hash = "" + for it in item.response["docs"]: + str_hash += it["url"] + str_hash += str(item.top_cluster) + str_hash += str(item.top_sentence) + str_hash += str(item.topn_summary) + str_hash += str(item.top_doc) + str_hash += str(item.threshold) + if item.sorted_field.strip(): + str_hash += str(item.sorted_field) + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + + +try: + with open("log_mnews/log.txt") as f: + data_dict = json.load(f) +except Exception as ve: + print(ve) + data_dict = {} + +def init_rabbit_queue(usr, passw, host, vir_host, queue_name, durable, max_priority, exchange=""): + connection = ICRabbitMQ(host, vir_host, usr, passw) + connection.init_connection() + channel = connection.init_queue( + queue_name, exchange=exchange, durable=durable, max_priority=max_priority) + return channel, connection, queue_name + + +@app.post("/mnews/topic_clustering") +async def topic_clustering_v2(item: Docs): + print("command id: ", item.command_id) + docs = item.response["docs"] + meta = item.response.get('meta', {}) + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + # with open("log/input_{0}.txt".format(st_time), "w+") as f: + # f.write(json.dumps({"docs": docs, "key": item.keyword})) + + data_push = { + + "threshold": item.threshold, + "top_cluster": top_cluster, + "top_sentence": top_sentence, + "topn_summary": topn_summary, + "hash_str": hash_str, + "st_time": st_time, + "command_id": item.command_id, + "docs": docs, + "meta": meta + } + params = config_params['queue_topic_clustering_mnews'] + usr_name = params["usr_name"] + password = str(params["password"]) + host = params["host"] + virtual_host = params["virtual_host"] + queue_name = params["queue_name"] + + channel_consumer, rb_consumer, queue_consumer = init_rabbit_queue(usr_name, password, host, virtual_host, queue_name, True, 10) + + ICRabbitMQ.publish_message(channel_consumer, queue_consumer, data_push, priority= 1,delivery_mode=2, exchange='') + return {"message":"success"} diff --git a/service_periodic.py b/service_periodic.py new file mode 100644 index 0000000000000000000000000000000000000000..5f30bedd335be4a7577d1fb628311d8c2211f5ff --- /dev/null +++ b/service_periodic.py @@ -0,0 +1,50 @@ +import gradio as gr +import json +import ast + +def push_queue(CONFIG): + return + +def wirte_config(CONFIG): + CONFIG = ast.literal_eval(CONFIG) + str = f""" + ******CONFIG UPDATE****** + start_time: {CONFIG['start_time']} + end_time: {CONFIG['end_time']} + query: {CONFIG['query']} + keywords: {CONFIG['keywords']} + top_cluster: {CONFIG['top_cluster']} + prompt: {CONFIG['prompt']} + check_relevent: {CONFIG['check_relevent']} + max_posts: {CONFIG['max_posts']} + """ + with open('/home2/cuongnguyen2/topic-clustering-global-dashboard/config_periodic.json', 'w') as f: + json.dump(CONFIG, f, ensure_ascii= False) + return str + +demo = gr.Blocks() + +def gradio_function(): + with demo: + gr.Markdown( + """ + # Flip Text! + Start typing below to see the output. + """ + ) + with open('/home2/cuongnguyen2/topic-clustering-global-dashboard/config_periodic.json') as f: + CONFIG = json.load(f) + + input1 = gr.Textbox(placeholder="Enter input", value=str(CONFIG)) + # input2 = gr.Textbox(placeholder="Enter second text") + + # Tạo ô output + output = gr.Textbox() + + # Kết nối các input với hàm process_text + gr.Button("Submit").click(fn=wirte_config, inputs=[input1], outputs=output) + + demo.launch(share=True) + +if __name__ == '__main__': + gradio_function() \ No newline at end of file diff --git a/service_review_diemtin.py b/service_review_diemtin.py new file mode 100644 index 0000000000000000000000000000000000000000..699ac0ed39341a422f0e1c0924f2959a922ba22a --- /dev/null +++ b/service_review_diemtin.py @@ -0,0 +1,63 @@ +from entity import InputCheckReview +from fastapi import FastAPI +import time +import hashlib +import json +from fastapi.middleware.cors import CORSMiddleware +import os + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +def get_hash_id(item: InputCheckReview): + str_hash = "" + if item.id_topic: + str_hash += item.id_topic + str_hash += item.start_time + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + else: + return "" + + +@app.post("/newsanalysis/review/topic_clustering") +async def topic_clustering(item: InputCheckReview): + hash_str = get_hash_id(item) + print("item.id_topic: ", item.id_topic) + print("item.start_time: ", item.start_time) + print("item.end_time: ", item.end_time) + print(hash_str) + # if len(docs) > 200: + results = {"status": 1, "res": {}} + if hash_str and os.path.exists("log/result_{0}.txt".format(hash_str)): + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, encoding="utf-8") as ff: + res_clus = json.load(ff) + return {"status": 1, "res": res_clus} + return results + + +@app.post("/newsanalysis/update/topic_clustering") +async def topic_clustering(item: InputCheckReview): + hash_str = get_hash_id(item) + print("item.id_topic: ", item.id_topic) + print("item.start_time: ", item.start_time) + print("item.end_time: ", item.end_time) + print(hash_str) + # if len(docs) > 200: + results = {"status": 0} + if hash_str and os.path.exists("log/result_{0}.txt".format(hash_str)): + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, "w+", encoding="utf-8") as ff: + ff.write(json.dumps(item.data)) + return {"status": 1} + return results + + + diff --git a/service_social.py b/service_social.py new file mode 100644 index 0000000000000000000000000000000000000000..98de3ff497a2fae2eaa78e27f791fc6b9c598b69 --- /dev/null +++ b/service_social.py @@ -0,0 +1,95 @@ +from entity import Docs, Cluster, Preprocess, SummaryInput +from fastapi import FastAPI +import time +import hashlib +import json +from fastapi.middleware.cors import CORSMiddleware +from function import topic_clustering_social as tc +# from function import topic_clustering_v2 as tc +from iclibs.ic_rabbit import ICRabbitMQ +from get_config import config_params + +app = FastAPI() +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +def get_hash_id(item: Docs): + str_hash = "" + for it in item.response["docs"]: + str_hash += it["url"] + str_hash += str(item.top_cluster) + str_hash += str(item.top_sentence) + str_hash += str(item.topn_summary) + str_hash += str(item.top_doc) + str_hash += str(item.threshold) + if item.sorted_field.strip(): + str_hash += str(item.sorted_field) + if item.delete_message: + str_hash += str(item.delete_message) + return hashlib.sha224(str_hash.encode("utf-8")).hexdigest() + + +try: + with open("log_run/log.txt") as f: + data_dict = json.load(f) +except Exception as ve: + print(ve) + data_dict = {} + + +@app.post("/newsanalysis/topic_clustering") +async def topic_clustering(item: Docs): + docs = item.response["docs"] + # threshold = item.threshold + print("start ") + print("len doc: ", len(docs)) + st_time = time.time() + top_cluster = item.top_cluster + top_sentence = item.top_sentence + topn_summary = item.topn_summary + sorted_field = item.sorted_field + max_doc_per_cluster = item.max_doc_per_cluster + hash_str = get_hash_id(item) + # threshold = 0.1 + # item.threshold = threshold + + # with open("log/input_{0}.txt".format(st_time), "w+") as f: + # f.write(json.dumps({"docs": docs, "key": item.keyword})) + + print(hash_str) + if len(docs) > 200: + + try: + if hash_str in data_dict: + path_res = data_dict[hash_str]["response_path"] + with open(path_res) as ff: + results = json.load(ff) + print("time analysis (cache): ", time.time() - st_time) + return results + except Exception as vee: + print(vee) + + results = tc.topic_clustering(docs, item.threshold, top_cluster=top_cluster, top_sentence=top_sentence, + topn_summary=topn_summary, sorted_field=sorted_field, max_doc_per_cluster=max_doc_per_cluster, delete_message=item.delete_message, is_check_spam=item.is_check_spam) + + path_res = "log/result_{0}.txt".format(hash_str) + with open(path_res, "w+") as ff: + ff.write(json.dumps(results)) + data_dict[hash_str] = {"time": st_time, "response_path": path_res} + + lst_rm = [] + for dt in data_dict: + if time.time() - data_dict[dt]["time"] > 30 * 24 * 3600: + lst_rm.append(dt) + for dt in lst_rm: + del data_dict[dt] + with open("log_run/log.txt", "w+") as ff: + ff.write(json.dumps(data_dict)) + print("time analysis: ", time.time() - st_time) + return results \ No newline at end of file diff --git a/summary.py b/summary.py new file mode 100644 index 0000000000000000000000000000000000000000..8d2e497fc2318af9097751b3ef1895721536167d --- /dev/null +++ b/summary.py @@ -0,0 +1,396 @@ +# from fastapi import FastAPI +# from pydantic import BaseModel +from summarizer import Summarizer +from gensim.summarization import summarize +import re +import os +import json +import requests +import time +from langdetect import detect +from copy import deepcopy +from translate import translate_text_multi_layer +from function.summary_with_llm import summary_with_llama, check_relevant_with_llama, normalize_text_after_qna_llm, check_answer_contains_remove_words +# os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" +os.environ["CUDA_VISIBLE_DEVICES"] = "0" +model = Summarizer() +print("model") + +URL_SUMMARY = { + "extractive": "http://10.9.3.240:1251/api/v1/summarization/extractive", + "icgpt": "http://10.9.3.240:1251/api/v1/summarization/icgpt", + "chatgpt": "http://10.9.3.240:1251/api/v1/summarization/chatgpt" +} +URL_SUMMARY_TITLE_CLUSTER = "http://10.9.3.241:3004/rnd/nlp/v1/summary_cluster" + +# class Item(BaseModel): +# title: str = "" +# snippet: str = "" +# content: str = "" +# topn: int = 3 +# sentence_separator: str = None +# method = 'tf-idf' +# num_word: int = 200 +# ratio: int = 0.2 +# lang: str = "vi" + +def detect_lang(text, default_lang="en"): + try: + lang = detect(text) + except: + lang = default_lang + if lang not in ["en","vi"]: + lang = default_lang + return lang + +def text_summary_old(item, ratio = None): + title_re = re.sub(r"\s\s+", " ", item["title"]) + snippet_re = re.sub(r"\s\s+", " ", item["snippet"]) + content_re = re.sub(r"\s\s+", " ", item["content"]) + text_re = snippet_re + " " + content_re + text_re = text_re.strip() + print(len(text_re)) + if 10 < len(text_re) < 10000: + + + # if ratio: + # result = model(text_re, ratio=0.2) + # else: + result = model(text_re, num_sentences=item["topn"]) + else: + result = title_re + " " + snippet_re + " " + content_re + try: + if len(result.strip()) < 3: + result = summarize(text_re) + except Exception as ve: + print(ve) + result = text_re[0: 500] + "..." + if len(result.strip()) < 3: + result = text_re[0: 500] + "..." + return result.strip() + + +def text_summary(doc, lang, mode="icgpt", num_sent = 4, ratio=0.2): + title = doc.get("title", "") + snippet = doc.get("snippet","") + message = doc.get("content", "") + + title = re.sub(r"\s\s+", " ", title) + snippet = re.sub(r"\s\s+", " ", snippet) + message = re.sub(r"\s\s+", " ", message) + + text_sum = " \n ".join([x for x in [snippet, message] if x.strip()]) + + json_body = { + "texts": [text_sum], + "lang": lang, + "num_sent": num_sent, + # "ratio": ratio + } + + result = "" + try: + url = URL_SUMMARY[mode] if model in URL_SUMMARY else URL_SUMMARY["icgpt"] + res = requests.post(url, json=json_body) + # print(url, json_body, res.text) + result = res.json()["result"][0] + + except Exception as ex: + print(f"[ERROR] text summary got ex: {str(ex)}") + + return result + +def text_summary(doc, lang, mode="icgpt", num_sent = 4, ratio=0.2): + title = doc.get("title", "") + snippet = doc.get("snippet","") + message = doc.get("content", "") + if not message.strip(): + message = doc.get("message", "") + + title = re.sub(r"\s\s+", " ", title) + snippet = re.sub(r"\s\s+", " ", snippet) + message = re.sub(r"\s\s+", " ", message) + + text_sum = " \n ".join([x for x in [snippet, message] if x.strip()]) + + json_body = { + "texts": [text_sum], + "lang": lang, + "num_sent": num_sent, + # "ratio": ratio + } + + result = "" + try: + url = URL_SUMMARY[mode] if model in URL_SUMMARY else URL_SUMMARY["icgpt"] + res = requests.post(url, json=json_body) + # print(url, json_body, res.text) + result = res.json()["result"][0] + + except Exception as ex: + print(f"[ERROR] text summary got ex: {str(ex)}") + + return result + +def text_summary_batch(docs, lang, mode="icgpt", num_sent = 4, ratio=0.2): + text_sums = [] + for doc in docs: + title = doc.get("title", "") + snippet = doc.get("snippet","") + message = doc.get("content", "") + if not message.strip(): + message = doc.get("message", "") + + title = re.sub(r"\s\s+", " ", title) + snippet = re.sub(r"\s\s+", " ", snippet) + message = re.sub(r"\s\s+", " ", message) + + text_sum = " \n ".join([x for x in [title, snippet, message] if x.strip()]) + if lang != "vi": + text_sum = translate_text_multi_layer(source=lang, target="vi", text = text_sum) + text_sums.append(text_sum) + + json_body = { + "texts": text_sums, + "lang": lang, + "num_sent": num_sent + # "ratio": ratio + } + with open(f"log_llama/text_summary_batch_in_{time.time()}.txt", "w+") as f: + f.write(json.dumps(json_body)) + + result = [""] * len(docs) + try: + url = URL_SUMMARY[mode] if model in URL_SUMMARY else URL_SUMMARY["icgpt"] + res = requests.post(url, json=json_body) + print("text_summary_batch: ", res.status_code) + with open(f"log_llama/text_summary_batch_out_{time.time()}.txt", "w+") as f: + f.write(json.dumps(res.json())) + # print(url, json_body, res.text) + result = res.json()["result"] + + except Exception as ex: + print(f"[ERROR] text summary batch got ex: {str(ex)}") + + return result + +def get_summary_bert(corpus, lang, topn=5, title='', snippet='', ratio = None, mode=None): + # if not use_cuda: + # return "" + # return "" + if not lang or not mode: + + item = { + "title": title, + "snippet": snippet, + "content": corpus, + "topn": topn + } + result = snippet #text_summary_old(item, ratio = ratio) + # print("get_summary extractive: ", result) + return result + else: + lang = detect_lang(corpus) + + st_time = time.time() + + data_post = { + "title": title, + "snippet": snippet, + "content": corpus, + "topn": topn + } + print("start query extractive") + try: + r = text_summary(data_post, lang = lang, num_sent=topn, ratio = ratio) + print("time summaries", time.time() - st_time, len(corpus)) + return r.replace("Read more about:","").replace("Read more","").replace("Advertising","") + except Exception as ex: + print(ex) + return "" + + + +def get_title_summary_cluster(clusters, url = URL_SUMMARY_TITLE_CLUSTER): + json_body = { + "clusters": clusters + } + with open(f"log_llm/log_title_summary_cluster/{time.time()}.json", "w") as f: + json.dump(json_body, f, ensure_ascii= False) + + result = [""] * len(clusters.keys()) + try: + res = requests.post(url, json=json_body) + res = res.json() + result = res["result"] + except Exception as ex: + print("[ERROR] get_title_summary_cluster: ", str(ex)) + + return result + +def translate_clusters(clusters, lang_process:str = "vi"): + TGT_LANG = lang_process + for id_cluster in clusters: + cluster_info = clusters[id_cluster] + for i,doc in enumerate(cluster_info): + if "lang" not in doc: + doc["lang"] = "en" + if doc.get("lang", "").startswith("zh_"): + doc["lang"] = "zh" + if doc.get("lang", "") != TGT_LANG: + if i <= 5: + if doc.get("title","").strip() : + doc["title"] = translate_text_multi_layer(source=doc["lang"], target=TGT_LANG, text = doc["title"] ) + if doc.get("snippet","").strip() : + doc["snippet"] = translate_text_multi_layer(source=doc["lang"], target=TGT_LANG, text = doc["snippet"] ) + if i == 0: + if doc.get("message","").strip() : + # path_log = f"log_tran/requests_tran_message_{time.time()}.txt" + # with open(path_log, "w", encoding="utf-8") as f: + # f.write(json.dumps({ + # "doc": doc["message"], + # "src_lang": doc["lang"], + # "tgt_lang": TGT_LANG + # }) + "\n") + doc["message"] = translate_text_multi_layer(source=doc["lang"], target=TGT_LANG, text = doc["message"] ) + doc["lang"] = TGT_LANG + clusters[id_cluster] = cluster_info[:5] + return clusters +def postprocess_title_clusters(clusters, delete_message=True, prompt: str = "", top_cluster: int = 5, hash_str: str = "", lang_process: str = "", topic_name: str = ""): + with open("data/prompt_rewrite.txt") as f: + DICT_PROMPT_REWRITE = json.load(f) + + print("start_translate") + t11 = time.time() + clusters = translate_clusters(clusters, lang_process=lang_process) + print("end_translate: ", time.time() - t11) + titles = get_title_summary_cluster(clusters) + if lang_process != "vi": + for i in range(len(titles)): + titles[i] = translate_text_multi_layer(source=lang_process, target="vi", text = titles[i]) + lst_reps_docs = [] + idx = 0 + count_lang = {} + for id_cluster in clusters: + cluster_info = clusters[id_cluster] + doc = cluster_info[0] + lst_reps_docs.append(doc) + lang = doc.get("lang", "") + if lang not in count_lang: + count_lang[lang] = 0 + count_lang[lang] += 1 + if "title_summarize" not in doc: + doc["title_summarize"] = [deepcopy(doc["title"])] + else: + doc["title_summarize"].insert(0, doc["title"]) + + if titles[idx].strip() and len(titles[idx].split()) > 4: + #doc["title"] = titles[idx] + doc["title_summarize"].insert(0, titles[idx]) + idx += 1 + + try: + count_lang = sorted(list(count_lang.items()), key=lambda x: -x[1]) + main_lang = count_lang[0][0] + except: + main_lang = "" + if main_lang == '': + lang = 'vi' + print("main_lang: ", main_lang) + content_sums = text_summary_batch(lst_reps_docs, lang=main_lang, mode="icgpt") + idx = 0 + list_not_relevant_id = [] + list_id_cluster = [] + ii_c = 0 + for id_cluster in clusters: + cluster_info = clusters[id_cluster] + if prompt: + message_tran = ". ".join([cluster_info[0].get("title", ""), cluster_info[0].get("snippet", ""), cluster_info[0].get("message", "")]) + ans_from_llama = "" + if message_tran: + list_id_cluster.append(int(id_cluster)) + prompt_lst = prompt.split("#####") + is_pass_llama = False + for iii, prompt_i in enumerate(prompt_lst): + prompt_i = prompt_i.strip() + print("prompt_i: ", prompt_i) + # if len(topic_name) == 0: + # topic_name = DICT_PROMPT_RELEVANT.get(prompt_i, topic_name) + + ans_from_llama, is_check_relevant = summary_with_llama(prompt_i, message_tran, lang_process, version=f"{lang_process}-llama", max_word_per_context=1200, id_cluster=id_cluster, hash_str=hash_str + "_" + str(iii)) + if not is_check_relevant: + print("topic_name: ", topic_name) + if topic_name == "": + is_check_relevant_v2 = False + else: + try: + if content_sums[idx].strip(): + message_check_rele = content_sums[idx] + else: + message_check_rele = ans_from_llama + except Exception as ve: + message_check_rele = ans_from_llama + is_check_relevant_v2 = check_relevant_with_llama(topic_name, message_check_rele, lang_process, version="en-llama", max_word_per_context=1200, id_cluster=id_cluster, hash_str=hash_str + "_" + str(iii)) + # is_check_relevant_v22 = check_relevant_with_llama(topic_name, message_check_rele, lang_process, version="vi-llama", max_word_per_context=1200, id_cluster=id_cluster, hash_str=hash_str + "_" + str(iii)) + if not is_check_relevant_v2: + if lang_process != 'vi': + ans_from_llama = translate_text_multi_layer(source=lang_process, target="vi", text = ans_from_llama) + ans_from_llama = normalize_text_after_qna_llm(ans_from_llama) + is_check_relevant_v3 = check_answer_contains_remove_words(ans_from_llama) + if not is_check_relevant_v3: + content_sums[idx] = translate_text_multi_layer(source=lang_process, target="vi", text = content_sums[idx]) + print("ans_from_llama: ", ans_from_llama, is_check_relevant, is_check_relevant_v2, is_check_relevant_v3) + print("content_sums[idx].strip(): ", id_cluster, content_sums[idx].strip()) + is_pass_llama = True + break + else: + + if ans_from_llama and prompt_i in DICT_PROMPT_REWRITE: + print("ans_from_llama previe: ", ans_from_llama) + print("DICT_PROMPT_REWRITE: ", DICT_PROMPT_REWRITE[prompt_i]) + ans_from_llama_rewrite, is_check_relevant_rew = summary_with_llama(DICT_PROMPT_REWRITE[prompt_i], message_tran, lang_process, version=f"en-llama", + max_word_per_context=1200, id_cluster=id_cluster, hash_str=hash_str + "_rewrite_" + str(iii)) + if ans_from_llama_rewrite: + ans_from_llama = ans_from_llama_rewrite + print("ans_from_llama: ", ans_from_llama, is_check_relevant, is_check_relevant_v2) + print("content_sums[idx].strip(): ", id_cluster) + is_pass_llama = True + break + + if not is_pass_llama: + list_not_relevant_id.append(int(id_cluster)) + else: + if ii_c >= top_cluster: + break + ii_c += 1 + try: + + if content_sums and content_sums[idx].strip() : + cluster_info[0]["content_summary"] = content_sums[idx] + "
\nNội dung phân tích: \n
" + ans_from_llama + except Exception as ex: + print("content_sums ex: ", str(ex)) + cluster_info[0]["content_summary"] = "
\nNội dung phân tích: \n
" + ans_from_llama + else: + list_id_cluster.append(int(id_cluster)) + try: + if content_sums[idx].strip() : cluster_info[0]["content_summary"] = content_sums[idx] + except Exception as ex: + print("content_sums ex: ", str(ex)) + for doc in cluster_info: + doc.pop("message", None) + + idx += 1 + dict_final_cluster = {} + list_id_cluster.sort() + ii_c = 0 + print("list_not_relevant_id: ", list_not_relevant_id) + print("list_relevant_id: ", list_id_cluster) + for k_i in list_id_cluster: + if k_i not in list_not_relevant_id: + ii_c += 1 + for doc in clusters[str(k_i)]: + doc.pop("message", None) + dict_final_cluster[str(k_i)] = clusters[str(k_i)] + if ii_c >= top_cluster: + break + return dict_final_cluster diff --git a/tensorRT/__pycache__/inference.cpython-37.pyc b/tensorRT/__pycache__/inference.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..b3ad669a5aa77a7b608bb7bf4e0c2f5b34b587c2 Binary files /dev/null and b/tensorRT/__pycache__/inference.cpython-37.pyc differ diff --git a/tensorRT/__pycache__/inference.cpython-38.pyc b/tensorRT/__pycache__/inference.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..ea212ca347e4362fdeab275d72ce61442e794188 Binary files /dev/null and b/tensorRT/__pycache__/inference.cpython-38.pyc differ diff --git a/tensorRT/convert.py b/tensorRT/convert.py new file mode 100644 index 0000000000000000000000000000000000000000..76991e0bb88130f4662cf8b2b29652a72530c94a --- /dev/null +++ b/tensorRT/convert.py @@ -0,0 +1,202 @@ +import torch +import transformers +from sentence_transformers import SentenceTransformer, models + + +class OnnxEncoder: + """OnxEncoder dedicated to run SentenceTransformer under OnnxRuntime.""" + + def __init__(self, session, tokenizer, pooling, normalization): + self.session = session + self.tokenizer = tokenizer + self.max_length = tokenizer.__dict__["model_max_length"] + self.pooling = pooling + self.normalization = normalization + + def encode(self, sentences: list): + + sentences = [sentences] if isinstance(sentences, str) else sentences + + inputs = { + k: v.numpy() + for k, v in self.tokenizer( + sentences, + padding='max_length', + truncation=True, + max_length=self.max_length, + return_tensors="pt", + ).items() + } + + hidden_state = self.session.run(None, inputs) + # import json + # with open('tensorRT/z.json', 'w') as f: + # json.dump(hidden_state[0].tolist(), f, ensure_ascii=False) + # with open('tensorRT/z_7.json', 'w') as f: + # json.dump(hidden_state[7].tolist(), f, ensure_ascii=False) + print("cls_token_embeddings:",hidden_state[0][0].shape) + sentence_embedding = self.pooling.forward( + features={ + "token_embeddings": torch.Tensor(hidden_state[0]), + "attention_mask": torch.Tensor(inputs.get("attention_mask")), + "cls_token_embeddings": hidden_state[0][0] + }, + ) + + # print("sentence_embedding 1:",sentence_embedding) + if self.normalization is not None: + sentence_embedding = self.normalization.forward(features=sentence_embedding) + print("="*100) + # print("sentence_embedding 2:",sentence_embedding) + sentence_embedding = sentence_embedding["sentence_embedding"] + + if sentence_embedding.shape[0] == 1: + sentence_embedding = sentence_embedding[0] + + return sentence_embedding#.numpy() + + +def sentence_transformers_onnx( + model, + path, + do_lower_case=True, + input_names=["input_ids", "attention_mask", "segment_ids"], + providers=["CPUExecutionProvider"], +): + """OnxRuntime for sentence transformers. + + Parameters + ---------- + model + SentenceTransformer model. + path + Model file dedicated to session inference. + do_lower_case + Either or not the model is cased. + input_names + Fields needed by the Transformer. + providers + Either run the model on CPU or GPU: ["CPUExecutionProvider", "CUDAExecutionProvider"]. + + """ + try: + import onnxruntime + except: + raise ValueError("You need to install onnxruntime.") + + model.save(path) + + configuration = transformers.AutoConfig.from_pretrained( + path, from_tf=False, local_files_only=True + ) + + tokenizer = transformers.AutoTokenizer.from_pretrained( + path, do_lower_case=do_lower_case, from_tf=False, local_files_only=True + ) + + encoder = transformers.AutoModel.from_pretrained( + path, from_tf=False, config=configuration, local_files_only=True + ) + + st = ["xin chào"] + print("max_length: ",tokenizer.__dict__["model_max_length"]) + inputs = tokenizer( + st, + padding='max_length', + truncation=True, + max_length=tokenizer.__dict__["model_max_length"], + return_tensors="pt", + ) + print(inputs) + model.eval() + + with torch.no_grad(): + + symbolic_names = {0: "batch_size", 1: "max_seq_len"} + + torch.onnx.export( + encoder, + # args=tuple(inputs.values()), + args=(torch.tensor(inputs['input_ids'], dtype=torch.long),torch.tensor(inputs['attention_mask'], dtype=torch.long), torch.tensor(inputs['token_type_ids'], dtype=torch.long)), + f=f"{path}.onx", + opset_version=13, # ONX version needs to be >= 13 for sentence transformers. + do_constant_folding=True, + input_names=input_names, + # output_names=["start", "end"], + output_names=["output"], + dynamic_axes={ + "input_ids": symbolic_names, + "attention_mask": symbolic_names, + "token_type_ids": symbolic_names, + "output": symbolic_names + # "start": symbolic_names, + # "end": symbolic_names, + }, + ) + + normalization = None + for modules in model.modules(): + print(model.modules()) + for idx, module in enumerate(modules): + if idx == 1: + pooling = module + if idx == 2: + normalization = module + break + + return OnnxEncoder( + session=onnxruntime.InferenceSession(f"{path}.onx", providers=providers), + tokenizer=tokenizer, + pooling=pooling, + normalization=normalization, + ) + +def infer_onnx(lst_input): + import onnxruntime + import numpy as np + from transformers import AutoTokenizer + tokenizer = AutoTokenizer.from_pretrained('tensorRT/models/paraphrase-mpnet-base-v2') + + + + + test_data = tokenizer(lst_input, padding="max_length", truncation=True) + ort_session = onnxruntime.InferenceSession("tensorRT/models/paraphrase-mpnet-base-v2.onnx") + print(len(ort_session.get_inputs())) + ort_inputs = { + ort_session.get_inputs()[0].name: np.array(test_data['input_ids'], dtype = np.int64), + ort_session.get_inputs()[1].name: np.array(test_data['attention_mask'], dtype = np.int64), + } + print(ort_inputs) + net_out = ort_session.run(None, ort_inputs) + + print(net_out[1]) + print(net_out[1].shape) + +if __name__ == "__main__": + lst_input = ["Pham Minh Chinh is Vietnam's Prime Minister"] + + outpath = 'tensorRT/models/distiluse-base-multilingual-cased-v2' + model_name = "model/distiluse-base-multilingual-cased-v2" + + outpath = 'tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2' + model_name = "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2" + + outpath = 'tensorRT/models/msmacro-base-4' + model_name = "model/msmacro-base-4" + + outpath = 'tensorRT/models/model-sup-simcse-vn' + model_name = "model/model-sup-simcse-vn" + + # model_name = "model/paraphrase-mpnet-base-v2" + model = SentenceTransformer(model_name) + embs = model.encode(lst_input) + print(embs) + print('-----------------') + + onnx_encoder = sentence_transformers_onnx(model, outpath,input_names=["input_ids", "attention_mask", "token_type_ids"], do_lower_case=False) + # onnx_encoder = sentence_transformers_onnx(model, outpath) + embs2 = onnx_encoder.encode(lst_input) + print(embs2) + # infer_onnx(lst_input) + print(embs.shape) \ No newline at end of file diff --git a/tensorRT/convert_onnx.py b/tensorRT/convert_onnx.py new file mode 100644 index 0000000000000000000000000000000000000000..8206dad723bb443b57c5d3fd871fc4ed8fb80f10 --- /dev/null +++ b/tensorRT/convert_onnx.py @@ -0,0 +1,49 @@ +from sentence_transformers import SentenceTransformer +import torch +from transformers import AutoTokenizer +def convert_onnx(): + # model = AutoModelForQuestionAnswering.from_pretrained("deepset/roberta-base-squad2") + model = SentenceTransformer('model/distiluse-base-multilingual-cased-v2') + torch.save(model, "model/distiluse-base-multilingual-cased-v2.pt") + + model = torch.load("model/distiluse-base-multilingual-cased-v2.pt") + tokenizer = AutoTokenizer.from_pretrained('model/distiluse-base-multilingual-cased-v2') + # tokenizer = AutoTokenizer.from_pretrained('deepset/roberta-base-squad2') + # lst_input = [" Experts predict China will soon attack Taiwan"] + lst_input = ["Pham Minh Chinh is Vietnam's Prime Minister"] + + x = tokenizer(lst_input, padding="max_length", truncation=True) + + print(x) + save_path = 'tensorRT/models/distiluse-base-multilingual-cased-v2.onnx' + + torch.onnx.export(model, (torch.tensor(x['input_ids'], dtype=torch.long),torch.tensor(x['attention_mask'], dtype=torch.long)), save_path, export_params=True, opset_version=13, do_constant_folding=True, + input_names = ['input_ids', 'attention_mask'], + output_names = ['output'], + dynamic_axes={'input_ids' : {0 : 'batch_size'}, 'attention_mask': {0 : 'batch_size'}, + 'output' : {0 : 'batch_size'}} + ) + + +def convert_onnx_(model_name= "model/model-sup-simcse-vn", pt_model = 'model-sup-simcse-vn', max_length = 256, save_path = "tensorRT/models/tensorRT/models/model-sup-simcse-vn.onnx"): + model = SentenceTransformer(model_name) + torch.save(model, f"model/{pt_model}.pt") + + model = torch.load(f"model/{pt_model}.pt") + tokenizer = AutoTokenizer.from_pretrained(model_name) + # tokenizer = AutoTokenizer.from_pretrained('deepset/roberta-base-squad2') + # lst_input = [" Experts predict China will soon attack Taiwan"] + lst_input = ["Pham Minh Chinh is Vietnam's Prime Minister"] + + x = tokenizer(lst_input, padding="max_length", truncation=True, max_length=256) + + print(x) + + torch.onnx.export(model, (torch.tensor(x['input_ids'], dtype=torch.long),torch.tensor(x['attention_mask'], dtype=torch.long), torch.tensor(x['token_type_ids'], dtype=torch.long)), save_path, export_params=True, opset_version=13, do_constant_folding=True, + input_names = ['input_ids', 'attention_mask','token_type_ids'], + output_names = ['output'], + dynamic_axes={'input_ids' : {0 : 'batch_size'}, 'attention_mask': {0 : 'batch_size'}, + 'output' : {0 : 'batch_size'}} + ) +if __name__ == '__main__': + convert_onnx_() \ No newline at end of file diff --git a/tensorRT/exec_backends/__init__.py b/tensorRT/exec_backends/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/tensorRT/exec_backends/__pycache__/__init__.cpython-37.pyc b/tensorRT/exec_backends/__pycache__/__init__.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..5a9618769152251767cc7589a3c186208c0f88ac Binary files /dev/null and b/tensorRT/exec_backends/__pycache__/__init__.cpython-37.pyc differ diff --git a/tensorRT/exec_backends/__pycache__/__init__.cpython-38.pyc b/tensorRT/exec_backends/__pycache__/__init__.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..6240af7c561ee1476350ef3cb3c600a80b2ab4b3 Binary files /dev/null and b/tensorRT/exec_backends/__pycache__/__init__.cpython-38.pyc differ diff --git a/tensorRT/exec_backends/__pycache__/trt_loader.cpython-37.pyc b/tensorRT/exec_backends/__pycache__/trt_loader.cpython-37.pyc new file mode 100644 index 0000000000000000000000000000000000000000..2558d7b2d75627b0f638dc3811fe11bb1f4100f6 Binary files /dev/null and b/tensorRT/exec_backends/__pycache__/trt_loader.cpython-37.pyc differ diff --git a/tensorRT/exec_backends/__pycache__/trt_loader.cpython-38.pyc b/tensorRT/exec_backends/__pycache__/trt_loader.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..836f6d5ade7807485e22fbf6b6bc35aa18b5aedd Binary files /dev/null and b/tensorRT/exec_backends/__pycache__/trt_loader.cpython-38.pyc differ diff --git a/tensorRT/exec_backends/trt_loader.py b/tensorRT/exec_backends/trt_loader.py new file mode 100644 index 0000000000000000000000000000000000000000..5084a5ba302f845e8ed8e39137de32eb745bde45 --- /dev/null +++ b/tensorRT/exec_backends/trt_loader.py @@ -0,0 +1,194 @@ +import pycuda.driver as cuda +import pycuda.autoinit +import numpy as np +import tensorrt as trt +import torch +TRT_LOGGER = trt.Logger() + +# Simple helper data class that's a little nicer to use than a 2-tuple. +class HostDeviceMem(object): + def __init__(self, host_mem, device_mem): + self.host = host_mem + self.device = device_mem + + def __str__(self): + return "Host:\n" + str(self.host) + "\nDevice:\n" + str(self.device) + + def __repr__(self): + return self.__str__() + +# Allocates all buffers required for an engine, i.e. host/device inputs/outputs. +def allocate_buffers(engine): + inputs = [] + outputs = [] + bindings = [] + stream = cuda.Stream() + out_shapes = [] + input_shapes = [] + out_names = [] + max_batch_size = engine.get_profile_shape(0, 0)[2][0] + # max_batch_size = 1 + for binding in engine: + + binding_shape = engine.get_binding_shape(binding) + #Fix -1 dimension for proper memory allocation for batch_size > 1 + if binding_shape[0] == -1: + binding_shape = (1,) + binding_shape[1:] + size = trt.volume(binding_shape) * max_batch_size + dtype = trt.nptype(engine.get_binding_dtype(binding)) + # Allocate host and device buffers + host_mem = cuda.pagelocked_empty(size, dtype) + device_mem = cuda.mem_alloc(host_mem.nbytes) + # Append the device buffer to device bindings. + bindings.append(int(device_mem)) + # Append to the appropriate list. + if engine.binding_is_input(binding): + inputs.append(HostDeviceMem(host_mem, device_mem)) + input_shapes.append(engine.get_binding_shape(binding)) + else: + outputs.append(HostDeviceMem(host_mem, device_mem)) + #Collect original output shapes and names from engine + out_shapes.append(engine.get_binding_shape(binding)) + out_names.append(binding) + return inputs, outputs, bindings, stream, input_shapes, out_shapes, out_names, max_batch_size + +# This function is generalized for multiple inputs/outputs. +# inputs and outputs are expected to be lists of HostDeviceMem objects. +def do_inference(context, bindings, inputs, outputs, stream): + # Transfer input data to the GPU. + [cuda.memcpy_htod_async(inp.device, inp.host, stream) for inp in inputs] + # Run inference. + context.execute_async_v2(bindings=bindings, stream_handle=stream.handle) + # Transfer predictions back from the GPU. + [cuda.memcpy_dtoh_async(out.host, out.device, stream) for out in outputs] + # Synchronize the stream + stream.synchronize() + # Return only the host outputs. + return [out.host for out in outputs] + +class TrtModel(object): + def __init__(self, model): + self.engine_file = model + self.engine = None + self.inputs = None + self.outputs = None + self.bindings = None + self.stream = None + self.context = None + self.input_shapes = None + self.out_shapes = None + self.max_batch_size = 1 + + def build(self): + with open(self.engine_file, 'rb') as f, trt.Runtime(TRT_LOGGER) as runtime: + self.engine = runtime.deserialize_cuda_engine(f.read()) + self.inputs, self.outputs, self.bindings, self.stream, self.input_shapes, self.out_shapes, self.out_names, self.max_batch_size = allocate_buffers( + self.engine) + # print(self.inputs, self.outputs, self.bindings, self.stream, self.input_shapes, self.out_shapes, self.out_names, self.max_batch_size) + self.context = self.engine.create_execution_context() + self.context.active_optimization_profile = 0 + + def run(self, input, deflatten: bool = False, as_dict = False, use_token_type_ids=None): + # assert len(input) == 2, "You must input 2 ndarrays [attention_mask, input_ids]" + # assert len(input[0]) == len(input[1]), "Invalid input shape: {} vs {}".format(input[0].shape, input[1].shape) + + # lazy load implementation + if self.engine is None: + self.build() + batch_size = input[0].shape[0] + # Allocate mem for first input + input_ids = np.array(input[0], dtype = np.int32) + allocate_place = np.prod(input_ids.shape) + self.inputs[0].host[:allocate_place] = input_ids.flatten(order='C') + + # Allocate mem for second input + attent_mask = np.array(input[1], dtype = np.int32) + allocate_place = np.prod(attent_mask.shape) + self.inputs[1].host[:allocate_place] = attent_mask.flatten(order='C') + + # Set binding + self.context.set_binding_shape(0, input_ids.shape) + self.context.set_binding_shape(1, attent_mask.shape) + + if use_token_type_ids: + token_type_ids = np.array(input[2], dtype = np.int32) + allocate_place = np.prod(token_type_ids.shape) + self.inputs[2].host[:allocate_place] = token_type_ids.flatten(order='C') + self.context.set_binding_shape(2, token_type_ids.shape) + + trt_outputs = do_inference( + self.context, bindings=self.bindings, + inputs=self.inputs, outputs=self.outputs, stream=self.stream) + + # print(self.inputs, self.outputs, self.bindings, self.stream, self.input_shapes, self.out_shapes, self.out_names, self.max_batch_size) + # Reshape TRT outputs to original shape instead of flattened array + # print(trt_outputs[0].shape) + + if deflatten: + out_shapes = [(batch_size, ) + out_shape[1:] for out_shape in self.out_shapes] + trt_outputs = [output[:np.prod(shape)].reshape(shape) for output, shape in zip(trt_outputs, out_shapes)] + # if as_dict: + # return {name: trt_outputs[i] for i, name in enumerate(self.out_names)} + + # trt_outputs = [trt_output.reshape(-1,512) for trt_output in trt_outputs] + trt_outputs = [trt_output[:batch_size] for trt_output in trt_outputs] + return trt_outputs + + +def mean_pooling(token_embeddings, attention_mask): + # print(token_embeddings.shape) + # token_embeddings = model_output[0] #First element of model_output contains all token embeddings + input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() + return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) + +def encode(sentences: list, tokenizer, trt_model:TrtModel, use_token_type_ids = False, max_lengh =512): + + sentences = [sentences] if isinstance(sentences, str) else sentences + + # inputs = { + # k: v.numpy() + # for k, v in tokenizer( + # sentences, + # padding='max_length', + # truncation=True, + # return_tensors="pt", + # ).items() + # } + + x = tokenizer(sentences, padding='max_length', truncation=True, max_length = max_lengh) + input_ids = x["input_ids"] + attention_mask = x["attention_mask"] + input_ids = np.array(input_ids, dtype = np.int32) + attention_mask = np.array(attention_mask, dtype = np.int32) + + if use_token_type_ids: + token_type_ids = x["token_type_ids"] + token_type_ids = np.array(token_type_ids, dtype = np.int32) + hidden_states = trt_model.run([input_ids, attention_mask, token_type_ids ], deflatten=True, use_token_type_ids=True) + else: + hidden_states = trt_model.run([input_ids, attention_mask], deflatten=True) + sentence_embeddings = mean_pooling(torch.from_numpy(hidden_states[0]), torch.from_numpy(attention_mask)) + # import json + # with open("tensorRT/embs.json", 'w') as f: + # json.dump(sentence_embeddings.tolist(), f, ensure_ascii=False) + + return sentence_embeddings.numpy() +if __name__ == "__main__": + import torch + import json + + + + + from transformers import AutoTokenizer + + # tokenizer = AutoTokenizer.from_pretrained("tensorRT/models/paraphrase-mpnet-base-v2") + # model = TrtModel("tensorRT/models/paraphrase-mpnet-base-v2.engine") + # tokenizer = AutoTokenizer.from_pretrained("tensorRT/models/distiluse-base-multilingual-cased-v2") + # model = TrtModel("tensorRT/models/distiluse-base-multilingual-cased-v2.endgine") + + tokenizer = AutoTokenizer.from_pretrained("tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2") + model = TrtModel("tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2.engine") + + lst_input = ["Pham Minh Chinh is Vietnam's Prime Minister"] *2 + encode(lst_input, tokenizer, model, use_token_type_ids=False) \ No newline at end of file diff --git a/tensorRT/inference.py b/tensorRT/inference.py new file mode 100644 index 0000000000000000000000000000000000000000..beecd2245bb3946d3500f0d9ce24b3e63dfa96e9 --- /dev/null +++ b/tensorRT/inference.py @@ -0,0 +1,27 @@ +from .exec_backends.trt_loader import TrtModel, encode as encode_trt +from transformers import AutoTokenizer +import math + +tokenizer_en = AutoTokenizer.from_pretrained("tensorRT/models/paraphrase-mpnet-base-v2") +model_en = TrtModel("tensorRT/models/paraphrase-mpnet-base-v2.engine") + +tokenizer_multilingual = AutoTokenizer.from_pretrained("tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2") +model_multilingual= TrtModel("tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2.engine") + +def encode(sentences, lang, batch_size = 8): + if batch_size >=8: + batch_size = 8 + all_embs = [] + + NUM_BATCH = math.ceil(len(sentences) / batch_size) + for j in range(NUM_BATCH): + lst_sen = sentences[j*batch_size: j*batch_size + batch_size] + + if lang == 'en': + # print(lst_sen) + embs = encode_trt(lst_sen, tokenizer=tokenizer_en, trt_model= model_en, use_token_type_ids=False) + else: + # print(lst_sen) + embs = encode_trt(lst_sen, tokenizer=tokenizer_multilingual, trt_model= model_multilingual, use_token_type_ids=False) + all_embs.extend(embs) + return all_embs diff --git a/tensorRT/trt.sh b/tensorRT/trt.sh new file mode 100644 index 0000000000000000000000000000000000000000..92dcd1e62cff60edce50646cf742b1e2067c13a8 --- /dev/null +++ b/tensorRT/trt.sh @@ -0,0 +1,11 @@ +docker run --gpus all -it --rm -v /home/vietle/topic-clustering:/home/vietle/topic-clustering --name topic_clustering -p 8635:8633 nvcr.io/nvidia/tensorrt:22.07-py3 +docker run --gpus all -it --rm -v /home/vietle/topic-clustering:/home/vietle/topic-clustering --name topic_clustering_trt -p 8633:8633 topic-clustering-trt + +/usr/src/tensorrt/bin/trtexec --onnx=tensorRT/models/paraphrase-mpnet-base-v2.onx --minShapes=input_ids:1x512,attention_mask:1x512 --optShapes=input_ids:32x512,attention_mask:32x512 --maxShapes=input_ids:32x512,attention_mask:32x512 --verbose --explicitBatch --saveEngine=tensorRT/models/paraphrase-mpnet-base-v2.engine --device=4 + +/usr/src/tensorrt/bin/trtexec --onnx=tensorRT/models/distiluse-base-multilingual-cased-v2.onx --minShapes=input_ids:1x512,attention_mask:1x512 --optShapes=input_ids:32x512,attention_mask:32x512 --maxShapes=input_ids:32x512,attention_mask:32x512 --verbose --explicitBatch --saveEngine=tensorRT/models/distiluse-base-multilingual-cased-v2.engine --device=4 + +/usr/src/tensorrt/bin/trtexec --onnx=tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2.onx --minShapes=input_ids:1x512,attention_mask:1x512,token_type_ids:1x512 --optShapes=input_ids:32x512,attention_mask:32x512,token_type_ids:32x512 --maxShapes=input_ids:32x512,attention_mask:32x512,token_type_ids:32x512 --verbose --explicitBatch --saveEngine=tensorRT/models/paraphrase-multilingual-MiniLM-L12-v2.engine --device=4 + + +/usr/src/tensorrt/bin/trtexec --onnx=tensorRT/models/model-sup-simcse-vn.onx --minShapes=input_ids:1x256,attention_mask:1x256,token_type_ids:1x256 --optShapes=input_ids:32x256,attention_mask:32x256,token_type_ids:32x256 --maxShapes=input_ids:32x256,attention_mask:32x256,token_type_ids:32x256 --verbose --explicitBatch --saveEngine=tensorRT/models/model-sup-simcse-vn2.engine --device=0 \ No newline at end of file diff --git a/translate.py b/translate.py new file mode 100644 index 0000000000000000000000000000000000000000..19a1af42259a942ed6c54115a4fd8961e9036d60 --- /dev/null +++ b/translate.py @@ -0,0 +1,42 @@ +from langdetect import detect +import requests +import time +import json + +URL_TRANSLATOR = "http://10.9.3.241:8094/translator" +URL_ZH_TRANSLATOR = "http://10.9.3.241:1253/translate_multiple_language" + +def detect_lang(text): + try: + lang = detect(text) + except: + lang = 'en' + return lang + +def translate_text_multi_layer(source, target, text, url = URL_TRANSLATOR): + if not text.strip() or source == target: + return text + json_body = { + "doc": text, + "src_lang": source, + "tgt_lang": target, + "type_pipeline": "not_ic" + } + + # if "zh" in str(source).lower(): + # res = requests.post(URL_ZH_TRANSLATOR, json=json_body) + # print(source) + # print(res.json()) + # else: + # st_time = time.time() + res= requests.post(url, json=json_body) + # print("time translate per doc: ", time.time() - st_time) + # path_log = f"log_tran/requests_tran_{time.time()}.txt" + # with open(path_log, "w", encoding="utf-8") as f: + # f.write(json.dumps(json_body) + "\n") + if res.status_code == 200: + res = res.json() + # with open(path_log, "a", encoding="utf-8") as f: + # f.write(json.dumps(res) + "\n") + return res + return '' \ No newline at end of file