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| import gradio as gr | |
| import boto3 | |
| from botocore.exceptions import ClientError | |
| import requests | |
| import json | |
| from transformers import AutoTokenizer, TFAutoModelForSeq2SeqLM | |
| def get_secret(): | |
| secret_name = "NYTimesArticleAPI" | |
| region_name = "ap-south-1" | |
| session = boto3.session.Session() | |
| client = session.client( | |
| service_name='secretsmanager', | |
| region_name=region_name | |
| ) | |
| try: | |
| get_secret_value_response = client.get_secret_value( | |
| SecretId=secret_name | |
| ) | |
| except ClientError as e: | |
| raise e | |
| secret = get_secret_value_response['SecretString'] | |
| secret_dict = json.loads(secret) | |
| return secret_dict | |
| def get_api(): | |
| api_key_dict = get_secret() | |
| api_key_value = api_key_dict['ny_times_article_api'] | |
| return api_key_value | |
| def get_abstracts(query): | |
| api_key = get_api() | |
| url = f'https://api.nytimes.com/svc/search/v2/articlesearch.json?q={query}&fq=source:("The New York Times")&api-key={api_key}' | |
| response = requests.get(url).json() | |
| abstracts = [] | |
| docs = response.get('response', {}).get('docs', []) | |
| for doc in docs: | |
| abstract = doc.get('abstract', '') | |
| if abstract: | |
| abstracts.append(abstract) | |
| return abstracts | |
| def summarizer(query): | |
| abstracts = get_abstracts(query) | |
| input_text = ' '.join(abstracts) | |
| tokenizer = AutoTokenizer.from_pretrained("stevhliu/my_awesome_billsum_model") | |
| inputs = tokenizer(input_text, return_tensors="tf").input_ids | |
| model = TFAutoModelForSeq2SeqLM.from_pretrained("stevhliu/my_awesome_billsum_model", from_pt=True) | |
| outputs = model.generate(inputs, max_length=100, do_sample=False) | |
| summary = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return abstracts, summary | |
| iface = gr.Interface( | |
| fn=summarizer, | |
| inputs=gr.inputs.Textbox(placeholder="Enter your query"), | |
| # outputs=gr.outputs.Textbox(), | |
| outputs=[ | |
| gr.outputs.Textbox(label="Abstracts"), | |
| gr.outputs.Textbox(label="Summary") | |
| ], | |
| title="New York Times Articles Summarizer", | |
| description="This summarizer actually does not yet summarize New York Times articles because of certain limitations. Type in something like 'Manipur' or 'Novak Djokovic' you will get a summary of that topic. What actually happens is that the query goes through the API. The abstract of article's content is added or concatenated, and then a text of considerable length is generated. That text is then summarized. So, this is an article summarizer but summarizes only abstracts of a particular article, ensuring that readers get the essence of a topic. This is a successful implementation of a pretrained T5 Transformer model." | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() | |