Upload 38 files

ChuanhuChatbot.py

@@ -67,13 +67,18 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                 retryBtn = gr.Button(i18n("🔄 重新生成"))
                 delFirstBtn = gr.Button(i18n("🗑️ 删除最旧对话"))
                 delLastBtn = gr.Button(i18n("🗑️ 删除最新对话"))
+                with gr.Row(visible=False) as like_dislike_area:
+                    with gr.Column(min_width=20, scale=1):
+                        likeBtn = gr.Button(i18n("👍"))
+                    with gr.Column(min_width=20, scale=1):
+                        dislikeBtn = gr.Button(i18n("👎"))
 
         with gr.Column():
             with gr.Column(min_width=50, scale=1):
                 with gr.Tab(label=i18n("模型")):
                     keyTxt = gr.Textbox(
                         show_label=True,
-                        placeholder=f"OpenAI API-key...",
+                        placeholder=f"Your API-key...",
                         value=hide_middle_chars(user_api_key.value),
                         type="password",
                         visible=not HIDE_MY_KEY,
@@ -101,7 +106,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                         multiselect=False,
                         value=REPLY_LANGUAGES[0],
                     )
-                    index_files = gr.Files(label=i18n("上传索引文件"), type="file")
+                    index_files = gr.Files(label=i18n("上传"), type="file")
                     two_column = gr.Checkbox(label=i18n("双栏pdf"), value=advance_docs["pdf"].get("two_column", False))
                     # TODO: 公式ocr
                     # formula_ocr = gr.Checkbox(label=i18n("识别公式"), value=advance_docs["pdf"].get("formula_ocr", False))
@@ -269,6 +274,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
 
     gr.Markdown(CHUANHU_DESCRIPTION, elem_id="description")
     gr.HTML(FOOTER.format(versions=versions_html()), elem_id="footer")
+    demo.load(refresh_ui_elements_on_load, [current_model, model_select_dropdown], [usageTxt, like_dislike_area], show_progress=False)
     chatgpt_predict_args = dict(
         fn=predict,
         inputs=[
@@ -331,7 +337,6 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         outputs=[chatbot, status_display],
         show_progress=True,
     )
-    emptyBtn.click(**reset_textbox_args)
 
     retryBtn.click(**start_outputing_args).then(
         retry,
@@ -361,6 +366,20 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
         show_progress=False
     )
 
+    likeBtn.click(
+        like,
+        [current_model],
+        [status_display],
+        show_progress=False
+    )
+
+    dislikeBtn.click(
+        dislike,
+        [current_model],
+        [status_display],
+        show_progress=False
+    )
+
     two_column.change(update_doc_config, [two_column], None)
 
     # LLM Models
@@ -368,6 +387,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
     keyTxt.submit(**get_usage_args)
     single_turn_checkbox.change(set_single_turn, [current_model, single_turn_checkbox], None)
     model_select_dropdown.change(get_model, [model_select_dropdown, lora_select_dropdown, user_api_key, temperature_slider, top_p_slider, systemPromptTxt], [current_model, status_display, lora_select_dropdown], show_progress=True)
+    model_select_dropdown.change(toggle_like_btn_visibility, [model_select_dropdown], [like_dislike_area], show_progress=False)
     lora_select_dropdown.change(get_model, [model_select_dropdown, lora_select_dropdown, user_api_key, temperature_slider, top_p_slider, systemPromptTxt], [current_model, status_display], show_progress=True)
 
     # Template
@@ -443,9 +463,7 @@ demo.title = i18n("川虎Chat 🚀")
 if __name__ == "__main__":
     reload_javascript()
     demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
-        auth=auth_list if authflag else None,
         favicon_path="./assets/favicon.ico",
-        inbrowser=not dockerflag, # 禁止在docker下开启inbrowser
     )
     # demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口
     # demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码

config_example.json

@@ -2,6 +2,8 @@
     // 你的OpenAI API Key，一般必填，
     // 若缺省填为 "openai_api_key": "" 则必须再在图形界面中填入API Key
     "openai_api_key": "",
+    // 你的xmchat API Key，与OpenAI API Key不同
+    "xmchat_api_key": "",
     "language": "auto",
     // 如果使用代理，请取消注释下面的两行，并替换代理URL
     // "https_proxy": "http://127.0.0.1:1079",

locale/en_US.json

@@ -14,7 +14,7 @@
     "单轮对话": "Single-turn dialogue",
     "使用在线搜索": "Use online search",
     "选择回复语言（针对搜索&索引功能）": "Select reply language (for search & index)",
-    "上传索引文件": "Upload index file",
+    "上传索引文件": "Upload",
     "双栏pdf": "Two-column pdf",
     "识别公式": "formula OCR",
     "在这里输入System Prompt...": "Type in System Prompt here...",

locale/ja_JP.json

@@ -14,7 +14,7 @@
     "单轮对话": "単発会話",
     "使用在线搜索": "オンライン検索を使用",
     "选择回复语言（针对搜索&索引功能）": "回答言語を選択（検索とインデックス機能に対して）",
-    "上传索引文件": "インデックスファイルをアップロード",
+    "上传索引文件": "アップロード",
     "双栏pdf": "2カラムpdf",
     "识别公式": "formula OCR",
     "在这里输入System Prompt...": "System Promptを入力してください...",

modules/base_model.py

@@ -29,7 +29,7 @@ class ModelType(Enum):
     OpenAI = 0
     ChatGLM = 1
     LLaMA = 2
-    XMBot = 3
+    XMChat = 3
 
     @classmethod
     def get_type(cls, model_name: str):
@@ -41,8 +41,8 @@ class ModelType(Enum):
             model_type = ModelType.ChatGLM
         elif "llama" in model_name_lower or "alpaca" in model_name_lower:
             model_type = ModelType.LLaMA
-        elif "xmbot" in model_name_lower:
-            model_type = ModelType.XMBot
+        elif "xmchat" in model_name_lower:
+            model_type = ModelType.XMChat
         else:
             model_type = ModelType.Unknown
         return model_type
@@ -201,7 +201,7 @@ class BaseLLMModel:
             msg = "索引获取成功，生成回答中……"
             logging.info(msg)
             if local_embedding or self.model_type != ModelType.OpenAI:
-                embed_model = LangchainEmbedding(HuggingFaceEmbeddings())
+                embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name = "sentence-transformers/distiluse-base-multilingual-cased-v2"))
             else:
                 embed_model = OpenAIEmbedding()
             # yield chatbot + [(inputs, "")], msg
@@ -245,10 +245,11 @@ class BaseLLMModel:
                 domain_name = urllib3.util.parse_url(result["href"]).host
                 reference_results.append([result["body"], result["href"]])
                 display_append.append(
-                    f"{idx+1}. [{domain_name}]({result['href']})\n"
+                    # f"{idx+1}. [{domain_name}]({result['href']})\n"
+                    f"<li><a href=\"{result['href']}\" target=\"_blank\">{domain_name}</a></li>\n"
                 )
             reference_results = add_source_numbers(reference_results)
-            display_append = "\n\n" + "".join(display_append)
+            display_append = "<ol>\n\n" + "".join(display_append) + "</ol>"
             real_inputs = (
                 replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
                 .replace("{query}", real_inputs)
@@ -463,9 +464,9 @@ class BaseLLMModel:
 
     def set_key(self, new_access_key):
         self.api_key = new_access_key.strip()
-        msg = f"API密钥更改为了{hide_middle_chars(self.api_key)}"
+        msg = i18n("API密钥更改为了") + hide_middle_chars(self.api_key)
         logging.info(msg)
-        return new_access_key, msg
+        return self.api_key, msg
 
     def set_single_turn(self, new_single_turn):
         self.single_turn = new_single_turn
@@ -548,3 +549,13 @@ class BaseLLMModel:
         except FileNotFoundError:
             logging.warning(f"{user_name} 没有找到对话历史文件，不执行任何操作")
             return filename, self.system_prompt, chatbot
+
+    def like(self):
+        """like the last response, implement if needed
+        """
+        return gr.update()
+
+    def dislike(self):
+        """dislike the last response, implement if needed
+        """
+        return gr.update()

modules/config.py

@@ -32,9 +32,8 @@ if os.path.exists("config.json"):
 else:
     config = {}
 
-language = config.get("language", "auto") # 在这里输入你的 API 密钥
-language = os.environ.get("LANGUAGE", language)
-
+lang_config = config.get("language", "auto")
+language = os.environ.get("default_ui_lang", lang_config)
 
 if os.path.exists("api_key.txt"):
     logging.info("检测到api_key.txt文件，正在进行迁移...")
@@ -66,8 +65,11 @@ if os.environ.get("dockerrun") == "yes":
     dockerflag = True
 
 ## 处理 api-key 以及 允许的用户列表
-my_api_key = config.get("openai_api_key", "") # 在这里输入你的 API 密钥
-my_api_key = os.environ.get("OPENAI_API_KEY", my_api_key)
+my_api_key = config.get("openai_api_key", "")
+my_api_key = os.environ.get("my_api_key", my_api_key)
+
+xmchat_api_key = config.get("xmchat_api_key", "")
+os.environ["XMCHAT_API_KEY"] = xmchat_api_key
 
 ## 多账户机制
 multi_api_key = config.get("multi_api_key", False) # 是否开启多账户机制

modules/llama_func.py

@@ -134,7 +134,7 @@ def construct_index(
         try:
             documents = get_documents(file_src)
             if local_embedding:
-                embed_model = LangchainEmbedding(HuggingFaceEmbeddings())
+                embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name = "sentence-transformers/distiluse-base-multilingual-cased-v2"))
             else:
                 embed_model = OpenAIEmbedding()
             logging.info("构建索引中……")

modules/models.py

@@ -9,6 +9,9 @@ import sys
 import requests
 import urllib3
 import platform
+import base64
+from io import BytesIO
+from PIL import Image
 
 from tqdm import tqdm
 import colorama
@@ -96,6 +99,8 @@ class OpenAIClient(BaseLLMModel):
             status_text = STANDARD_ERROR_MSG + READ_TIMEOUT_MSG + ERROR_RETRIEVE_MSG
             return status_text
         except Exception as e:
+            import traceback
+            traceback.print_exc()
             logging.error(i18n("获取API使用情况失败:") + str(e))
             return STANDARD_ERROR_MSG + ERROR_RETRIEVE_MSG
 
@@ -328,15 +333,6 @@ class LLaMA_Client(BaseLLMModel):
                 data_args=data_args,
                 pipeline_args=pipeline_args,
             )
-        # Chats
-        # model_name = model_args.model_name_or_path
-        # if model_args.lora_model_path is not None:
-        #     model_name += f" + {model_args.lora_model_path}"
-
-        # context = (
-        #     "You are a helpful assistant who follows the given instructions"
-        #     " unconditionally."
-        # )
 
     def _get_llama_style_input(self):
         history = []
@@ -391,9 +387,9 @@ class LLaMA_Client(BaseLLMModel):
             yield partial_text
 
 
-class XMBot_Client(BaseLLMModel):
+class XMChat(BaseLLMModel):
     def __init__(self, api_key):
-        super().__init__(model_name="xmbot")
+        super().__init__(model_name="xmchat")
         self.api_key = api_key
         self.session_id = None
         self.reset()
@@ -401,36 +397,77 @@ class XMBot_Client(BaseLLMModel):
         self.image_path = None
         self.xm_history = []
         self.url = "https://xmbot.net/web"
+        self.last_conv_id = None
 
     def reset(self):
         self.session_id = str(uuid.uuid4())
+        self.last_conv_id = None
         return [], "已重置"
 
-    def try_read_image(self, filepath):
-        import base64
+    def image_to_base64(self, image_path):
+        # 打开并加载图片
+        img = Image.open(image_path)
+
+        # 获取图片的宽度和高度
+        width, height = img.size
+
+        # 计算压缩比例，以确保最长边小于4096像素
+        max_dimension = 2048
+        scale_ratio = min(max_dimension / width, max_dimension / height)
+
+        if scale_ratio < 1:
+            # 按压缩比例调整图片大小
+            new_width = int(width * scale_ratio)
+            new_height = int(height * scale_ratio)
+            img = img.resize((new_width, new_height), Image.ANTIALIAS)
 
+        # 将图片转换为jpg格式的二进制数据
+        buffer = BytesIO()
+        if img.mode == "RGBA":
+            img = img.convert("RGB")
+        img.save(buffer, format='JPEG')
+        binary_image = buffer.getvalue()
+
+        # 对二进制数据进行Base64编码
+        base64_image = base64.b64encode(binary_image).decode('utf-8')
+
+        return base64_image
+
+    def try_read_image(self, filepath):
         def is_image_file(filepath):
             # 判断文件是否为图片
             valid_image_extensions = [".jpg", ".jpeg", ".png", ".bmp", ".gif", ".tiff"]
             file_extension = os.path.splitext(filepath)[1].lower()
             return file_extension in valid_image_extensions
 
-        def read_image_as_bytes(filepath):
-            # 读取图片文件并返回比特流
-            with open(filepath, "rb") as f:
-                image_bytes = f.read()
-            return image_bytes
-
         if is_image_file(filepath):
             logging.info(f"读取图片文件: {filepath}")
-            image_bytes = read_image_as_bytes(filepath)
-            base64_encoded_image = base64.b64encode(image_bytes).decode()
-            self.image_bytes = base64_encoded_image
+            self.image_bytes = self.image_to_base64(filepath)
             self.image_path = filepath
         else:
             self.image_bytes = None
             self.image_path = None
 
+    def like(self):
+        if self.last_conv_id is None:
+            return "点赞失败，你还没发送过消息"
+        data = {
+            "uuid": self.last_conv_id,
+            "appraise": "good"
+        }
+        response = requests.post(self.url, json=data)
+        return "👍点赞成功，，感谢反馈～"
+
+    def dislike(self):
+        if self.last_conv_id is None:
+            return "点踩失败，你还没发送过消息"
+        data = {
+            "uuid": self.last_conv_id,
+            "appraise": "bad"
+        }
+        response = requests.post(self.url, json=data)
+        return "👎点踩成功，感谢反馈～"
+
     def prepare_inputs(self, real_inputs, use_websearch, files, reply_language, chatbot):
         fake_inputs = real_inputs
         display_append = ""
@@ -448,6 +485,8 @@ class XMBot_Client(BaseLLMModel):
                 chatbot = chatbot + [((self.image_path,), None)]
             if self.image_bytes is not None:
                 logging.info("使用图片作为输入")
+                # XMChat的一轮对话中实际上只能处理一张图片
+                self.reset()
                 conv_id = str(uuid.uuid4())
                 data = {
                     "user_id": self.api_key,
@@ -464,6 +503,7 @@ class XMBot_Client(BaseLLMModel):
     def get_answer_at_once(self):
         question = self.history[-1]["content"]
         conv_id = str(uuid.uuid4())
+        self.last_conv_id = conv_id
         data = {
             "user_id": self.api_key,
             "session_id": self.session_id,
@@ -528,8 +568,10 @@ def get_model(
             else:
                 msg += f" + {lora_model_path}"
             model = LLaMA_Client(model_name, lora_model_path)
-        elif model_type == ModelType.XMBot:
-            model = XMBot_Client(api_key=access_key)
+        elif model_type == ModelType.XMChat:
+            if os.environ.get("XMCHAT_API_KEY") != "":
+                access_key = os.environ.get("XMCHAT_API_KEY")
+            model = XMChat(api_key=access_key)
         elif model_type == ModelType.Unknown:
             raise ValueError(f"未知模型: {model_name}")
         logging.info(msg)

modules/presets.py

@@ -67,7 +67,7 @@ ONLINE_MODELS = [
     "gpt-4-0314",
     "gpt-4-32k",
     "gpt-4-32k-0314",
-    "xmbot",
+    "xmchat",
 ]
 
 LOCAL_MODELS = [
@@ -75,12 +75,8 @@ LOCAL_MODELS = [
     "chatglm-6b-int4",
     "chatglm-6b-int4-qe",
     "llama-7b-hf",
-    "llama-7b-hf-int4",
-    "llama-7b-hf-int8",
     "llama-13b-hf",
-    "llama-13b-hf-int4",
     "llama-30b-hf",
-    "llama-30b-hf-int4",
     "llama-65b-hf"
 ]
 

modules/utils.py

@@ -113,6 +113,12 @@ def set_single_turn(current_model, *args):
 def handle_file_upload(current_model, *args):
     return current_model.handle_file_upload(*args)
 
+def like(current_model, *args):
+    return current_model.like(*args)
+
+def dislike(current_model, *args):
+    return current_model.dislike(*args)
+
 
 def count_token(message):
     encoding = tiktoken.get_encoding("cl100k_base")
@@ -451,11 +457,11 @@ Error code: {result.returncode}""")
     result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True, env=os.environ if custom_env is None else custom_env)
     if result.returncode != 0:
         message = f"""{errdesc or 'Error running command'}.
-Command: {command}
-Error code: {result.returncode}
-stdout: {result.stdout.decode(encoding="utf8", errors="ignore") if len(result.stdout)>0 else '<empty>'}
-stderr: {result.stderr.decode(encoding="utf8", errors="ignore") if len(result.stderr)>0 else '<empty>'}
-"""
+            Command: {command}
+            Error code: {result.returncode}
+            stdout: {result.stdout.decode(encoding="utf8", errors="ignore") if len(result.stdout)>0 else '<empty>'}
+            stderr: {result.stderr.decode(encoding="utf8", errors="ignore") if len(result.stderr)>0 else '<empty>'}
+            """
         raise RuntimeError(message)
     return result.stdout.decode(encoding="utf8", errors="ignore")
 
@@ -472,12 +478,12 @@ def versions_html():
     else:
         commit_info = "unknown \U0001F615"
     return f"""
-Python: <span title="{sys.version}">{python_version}</span>
- • 
-Gradio: {gr.__version__}
- • 
-Commit: {commit_info}
-"""
+        Python: <span title="{sys.version}">{python_version}</span>
+         • 
+        Gradio: {gr.__version__}
+         • 
+        Commit: {commit_info}
+        """
 
 def add_source_numbers(lst, source_name = "Source", use_source = True):
     if use_source:
@@ -531,3 +537,12 @@ def get_last_day_of_month(any_day):
 def get_model_source(model_name, alternative_source):
     if model_name == "gpt2-medium":
         return "https://huggingface.co/gpt2-medium"
+
+def refresh_ui_elements_on_load(current_model, selected_model_name):
+    return current_model.billing_info(), toggle_like_btn_visibility(selected_model_name)
+
+def toggle_like_btn_visibility(selected_model_name):
+    if selected_model_name == "xmchat":
+        return gr.update(visible=True)
+    else:
+        return gr.update(visible=False)

modules/webui_locale.py

@@ -9,8 +9,8 @@ class I18nAuto:
                 config = json.load(f)
         else:
             config = {}
-        language = config.get("language", "auto") # 在这里输入你的 API 密钥
-        language = os.environ.get("LANGUAGE", language)
+        lang_config = config.get("language", "auto")
+        language = os.environ.get("default_ui_lang", lang_config)
         if language == "auto":
             language = locale.getdefaultlocale()[0] # get the language code of the system (ex. zh_CN)
         self.language_map = {}

readme/README_en.md

@@ -122,6 +122,6 @@ More information could be found in our [wiki](https://github.com/GaiZhenbiao/Chu
 
 🐯 If you find this project helpful, feel free to buy me a coke or a cup of coffee~
 
-<a href="https://www.buymeacoffee.com/ChuanhuChat" target="_blank"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=ChuanhuChat&button_colour=1aae59&font_colour=ffffff&font_family=Poppins&outline_colour=ffffff&coffee_colour=FFDD00" alt="Buy Me A Coffee" width="250"></a>
+<a href="https://www.buymeacoffee.com/ChuanhuChat" ><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=ChuanhuChat&button_colour=219d53&font_colour=ffffff&font_family=Poppins&outline_colour=ffffff&coffee_colour=FFDD00" alt="Buy Me A Coffee" width="250"></a>
 
 <img width="250" alt="image" src="https://user-images.githubusercontent.com/51039745/226920291-e8ec0b0a-400f-4c20-ac13-dafac0c3aeeb.JPG">

readme/README_ja.md

@@ -121,6 +121,6 @@ python ChuanhuChatbot.py
 
 🐯 この企画が役に立ったら、遠慮なくコーラかコーヒーでもおごってください〜。
 
-<a href="https://www.buymeacoffee.com/ChuanhuChat" target="_blank"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=ChuanhuChat&button_colour=1aae59&font_colour=ffffff&font_family=Poppins&outline_colour=ffffff&coffee_colour=FFDD00" alt="Buy Me A Coffee" width="250"></a>
+<a href="https://www.buymeacoffee.com/ChuanhuChat" ><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=ChuanhuChat&button_colour=219d53&font_colour=ffffff&font_family=Poppins&outline_colour=ffffff&coffee_colour=FFDD00" alt="Buy Me A Coffee" width="250"></a>
 
 <img width="250" alt="image" src="https://user-images.githubusercontent.com/51039745/226920291-e8ec0b0a-400f-4c20-ac13-dafac0c3aeeb.JPG">