Merge remote-tracking branch 'origin/master' into multi_language

.gitignore

@@ -147,4 +147,5 @@ private*
 crazy_functions/test_project/pdf_and_word
 crazy_functions/test_samples
 request_llm/jittorllms
-multi-language
+multi-language
+request_llm/moss

README.md

@@ -267,6 +267,12 @@ Tip：不指定文件直接点击 `载入对话历史存档` 可以查看历史h
 <img src="https://github.com/binary-husky/gpt_academic/assets/96192199/bc7ab234-ad90-48a0-8d62-f703d9e74665" width="500" >
 </div>
 
+9. OpenAI音频解析与总结
+<div align="center">
+<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/709ccf95-3aee-498a-934a-e1c22d3d5d5b" width="500" >
+</div>
+
+
 
 ## 版本:
 - version 3.5(Todo): 使用自然语言调用本项目的所有函数插件（高优先级）

config.py

@@ -44,9 +44,10 @@ WEB_PORT = -1
 # 如果OpenAI不响应（网络卡顿、代理失败、KEY失效），重试的次数限制
 MAX_RETRY = 2
 
-# OpenAI模型选择是（gpt4现在只对申请成功的人开放，体验gpt-4可以试试api2d）
+# 模型选择是
 LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing"]
+AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
+# P.S. 其他可用的模型还包括 ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
 
 # 本地LLM模型如ChatGLM的执行方式 CPU/GPU
 LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
@@ -75,3 +76,7 @@ NEWBING_STYLE = "creative"  # ["creative", "balanced", "precise"]
 NEWBING_COOKIES = """
 your bing cookies here
 """
+
+# 如果需要使用Slack Claude，使用教程详情见 request_llm/README.md
+SLACK_CLAUDE_BOT_ID = ''   
+SLACK_CLAUDE_USER_TOKEN = ''

core_functional.py

@@ -68,4 +68,11 @@ def get_core_functions():
             "Prefix":   r"请解释以下代码：" + "\n```\n",
             "Suffix":   "\n```\n",
         },
+        "参考文献转Bib": {
+            "Prefix":   r"Here are some bibliography items, please transform them into bibtex style." +
+                        r"Note that, reference styles maybe more than one kind, you should transform each item correctly." +
+                        r"Items need to be transformed:",
+            "Suffix":   r"",
+            "Visible": False,
+        }
     }

crazy_functional.py

@@ -246,5 +246,15 @@ def get_crazy_functions():
             "Function": HotReload(图片生成)
         },
     })
+    from crazy_functions.总结音视频 import 总结音视频
+    function_plugins.update({
+        "批量总结音视频（输入路径或上传压缩包）": {
+            "Color": "stop",
+            "AsButton": False,
+            "AdvancedArgs": True,
+            "ArgsReminder": "调用openai api 使用whisper-1模型, 目前支持的格式:mp4, m4a, wav, mpga, mpeg, mp3。此处可以输入解析提示，例如：解析为简体中文（默认）。",
+            "Function": HotReload(总结音视频)
+        }
+    })
     ###################### 第n组插件 ###########################
     return function_plugins

crazy_functions/图片生成.py

@@ -55,6 +55,7 @@ def 图片生成(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
     history = []    # 清空历史，以免输入溢出
     chatbot.append(("这是什么功能？", "[Local Message] 生成图像, 请先把模型切换至gpt-xxxx或者api2d-xxxx。如果中文效果不理想, 尝试Prompt。正在处理中 ....."))
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
+    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
     resolution = plugin_kwargs.get("advanced_arg", '256x256')
     image_url, image_path = gen_image(llm_kwargs, prompt, resolution)
     chatbot.append([prompt,  

crazy_functions/总结音视频.py

@@ -0,0 +1,184 @@
+from toolbox import CatchException, report_execption, select_api_key, update_ui, write_results_to_file, get_conf
+from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+
+def split_audio_file(filename, split_duration=1000):
+    """
+    根据给定的切割时长将音频文件切割成多个片段。
+
+    Args:
+        filename (str): 需要被切割的音频文件名。
+        split_duration (int, optional): 每个切割音频片段的时长（以秒为单位）。默认值为1000。
+
+    Returns:
+        filelist (list): 一个包含所有切割音频片段文件路径的列表。
+
+    """
+    from moviepy.editor import AudioFileClip
+    import os
+    os.makedirs('gpt_log/mp3/cut/', exist_ok=True)  # 创建存储切割音频的文件夹
+
+    # 读取音频文件
+    audio = AudioFileClip(filename)
+
+    # 计算文件总时长和切割点
+    total_duration = audio.duration
+    split_points = list(range(0, int(total_duration), split_duration))
+    split_points.append(int(total_duration))
+    filelist = []
+
+    # 切割音频文件
+    for i in range(len(split_points) - 1):
+        start_time = split_points[i]
+        end_time = split_points[i + 1]
+        split_audio = audio.subclip(start_time, end_time)
+        split_audio.write_audiofile(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3")
+        filelist.append(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3")
+
+    audio.close()
+    return filelist
+
+def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
+    import os, requests
+    from moviepy.editor import AudioFileClip
+    from request_llm.bridge_all import model_info
+
+    # 设置OpenAI密钥和模型
+    api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
+    chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
+
+    whisper_endpoint = chat_endpoint.replace('chat/completions', 'audio/transcriptions')
+    url = whisper_endpoint
+    headers = {
+        'Authorization': f"Bearer {api_key}"
+    }
+
+    os.makedirs('gpt_log/mp3/', exist_ok=True)
+    for index, fp in enumerate(file_manifest):
+        audio_history = []
+        # 提取文件扩展名
+        ext = os.path.splitext(fp)[1]
+        # 提取视频中的音频
+        if ext not in [".mp3", ".wav", ".m4a", ".mpga"]:
+            audio_clip = AudioFileClip(fp)
+            audio_clip.write_audiofile(f'gpt_log/mp3/output{index}.mp3')
+            fp = f'gpt_log/mp3/output{index}.mp3'
+        # 调用whisper模型音频转文字
+        voice = split_audio_file(fp)
+        for j, i in enumerate(voice):
+            with open(i, 'rb') as f:
+                file_content = f.read()  # 读取文件内容到内存
+                files = {
+                    'file': (os.path.basename(i), file_content),
+                }
+                data = {
+                    "model": "whisper-1",
+                    "prompt": parse_prompt,
+                    'response_format': "text"
+                }
+
+            chatbot.append([f"将 {i} 发送到openai音频解析终端 (whisper)，当前参数：{parse_prompt}", "正在处理 ..."])
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+            proxies, = get_conf('proxies')
+            response = requests.post(url, headers=headers, files=files, data=data, proxies=proxies).text
+
+            chatbot.append(["音频解析结果", response])
+            history.extend(["音频解析结果", response])
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+            i_say = f'请对下面的音频片段做概述，音频内容是 ```{response}```'
+            i_say_show_user = f'第{index + 1}段音频的第{j + 1} / {len(voice)}片段。'
+            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=i_say,
+                inputs_show_user=i_say_show_user,
+                llm_kwargs=llm_kwargs,
+                chatbot=chatbot,
+                history=[],
+                sys_prompt=f"总结音频。音频文件名{fp}"
+            )
+
+            chatbot[-1] = (i_say_show_user, gpt_say)
+            history.extend([i_say_show_user, gpt_say])
+            audio_history.extend([i_say_show_user, gpt_say])
+
+        # 已经对该文章的所有片段总结完毕，如果文章被切分了
+        result = "".join(audio_history)
+        if len(audio_history) > 1:
+            i_say = f"根据以上的对话，使用中文总结音频“{result}”的主要内容。"
+            i_say_show_user = f'第{index + 1}段音频的主要内容：'
+            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=i_say,
+                inputs_show_user=i_say_show_user,
+                llm_kwargs=llm_kwargs,
+                chatbot=chatbot,
+                history=audio_history,
+                sys_prompt="总结文章。"
+            )
+
+            history.extend([i_say, gpt_say])
+            audio_history.extend([i_say, gpt_say])
+
+        res = write_results_to_file(history)
+        chatbot.append((f"第{index + 1}段音频完成了吗？", res))
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+    # 删除中间文件夹
+    import shutil
+    shutil.rmtree('gpt_log/mp3')
+    res = write_results_to_file(history)
+    chatbot.append(("所有音频都总结完成了吗？", res))
+    yield from update_ui(chatbot=chatbot, history=history)
+
+
+@CatchException
+def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, WEB_PORT):
+    import glob, os
+
+    # 基本信息：功能、贡献者
+    chatbot.append([
+        "函数插件功能？",
+        "总结音视频内容，函数插件贡献者: dalvqw & BinaryHusky"])
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+    try:
+        from moviepy.editor import AudioFileClip
+    except:
+        report_execption(chatbot, history,
+                         a=f"解析项目: {txt}",
+                         b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade moviepy```。")
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        return
+
+    # 清空历史，以免输入溢出
+    history = []
+
+    # 检测输入参数，如没有给定输入参数，直接退出
+    if os.path.exists(txt):
+        project_folder = txt
+    else:
+        if txt == "": txt = '空空如也的输入栏'
+        report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        return
+
+    # 搜索需要处理的文件清单
+    extensions = ['.mp4', '.m4a', '.wav', '.mpga', '.mpeg', '.mp3', '.avi', '.mkv', '.flac', '.aac']
+
+    if txt.endswith(tuple(extensions)):
+        file_manifest = [txt]
+    else:
+        file_manifest = []
+        for extension in extensions:
+            file_manifest.extend(glob.glob(f'{project_folder}/**/*{extension}', recursive=True))
+
+    # 如果没找到任何文件
+    if len(file_manifest) == 0:
+        report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何音频或视频文件: {txt}")
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        return
+
+    # 开始正式执行任务
+    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
+    parse_prompt = plugin_kwargs.get("advanced_arg", '将音频解析为简体中文')
+    yield from AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history)
+
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面

crazy_functions/解析JupyterNotebook.py

@@ -67,6 +67,7 @@ def parseNotebook(filename, enable_markdown=1):
 def ipynb解释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
     from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
 
+    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
     enable_markdown = plugin_kwargs.get("advanced_arg", "1")
     try:
         enable_markdown = int(enable_markdown)

crazy_functions/询问多个大语言模型.py

@@ -45,6 +45,7 @@ def 同时问询_指定模型(txt, llm_kwargs, plugin_kwargs, chatbot, history,
     chatbot.append((txt, "正在同时咨询ChatGPT和ChatGLM……"))
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
 
+    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
     # llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
     llm_kwargs['llm_model'] = plugin_kwargs.get("advanced_arg", 'chatglm&gpt-3.5-turbo') # 'chatglm&gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
     gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(

main.py

@@ -74,6 +74,7 @@ def main():
                 with gr.Accordion("基础功能区", open=True) as area_basic_fn:
                     with gr.Row():
                         for k in functional:
+                            if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
                             variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
                             functional[k]["Button"] = gr.Button(k, variant=variant)
                 with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
@@ -144,6 +145,7 @@ def main():
         clearBtn2.click(lambda: ("",""), None, [txt, txt2])
         # 基础功能区的回调函数注册
         for k in functional:
+            if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
             click_handle = functional[k]["Button"].click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(k)], outputs=output_combo)
             cancel_handles.append(click_handle)
         # 文件上传区，接收文件后与chatbot的互动

request_llm/README.md

@@ -13,6 +13,31 @@ LLM_MODEL = "chatglm"
 `python main.py`
 ``` 
 
+## Claude-Stack
+
+- 请参考此教程获取  https://zhuanlan.zhihu.com/p/627485689
+    - 1、SLACK_CLAUDE_BOT_ID 
+    - 2、SLACK_CLAUDE_USER_TOKEN
+
+- 把token加入config.py
+
+## Newbing
+
+- 使用cookie editor获取cookie（json）
+- 把cookie（json）加入config.py （NEWBING_COOKIES）
+
+## Moss
+- 使用docker-compose
+
+## RWKV
+- 使用docker-compose
+
+## LLAMA
+- 使用docker-compose
+
+## 盘古
+- 使用docker-compose
+
 
 ---
 ## Text-Generation-UI (TGUI，调试中，暂不可用)

request_llm/bridge_all.py

@@ -130,6 +130,7 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+
 }
 
 
@@ -186,8 +187,20 @@ if "moss" in AVAIL_LLM_MODELS:
             "token_cnt": get_token_num_gpt35,
         },
     })
-
+if "stack-claude" in AVAIL_LLM_MODELS:
-
+    from .bridge_stackclaude import predict_no_ui_long_connection as claude_noui
+    from .bridge_stackclaude import predict as claude_ui
+    # claude
+    model_info.update({
+        "stack-claude": {
+            "fn_with_ui": claude_ui,
+            "fn_without_ui": claude_noui,
+            "endpoint": None,
+            "max_token": 8192,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        }
+    })
 
 
 def LLM_CATCH_EXCEPTION(f):

request_llm/bridge_newbing.py

@@ -153,7 +153,7 @@ class NewBingHandle(Process):
             # 进入任务等待状态
             asyncio.run(self.async_run())
         except Exception:
-            tb_str = '```\n' + trimmed_format_exc() + '```'
+            tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
             self.child.send(f'[Local Message] Newbing失败 {tb_str}.')
             self.child.send('[Fail]')
             self.child.send('[Finish]')

request_llm/bridge_stackclaude.py

@@ -0,0 +1,296 @@
+from .bridge_newbing import preprocess_newbing_out, preprocess_newbing_out_simple
+from multiprocessing import Process, Pipe
+from toolbox import update_ui, get_conf, trimmed_format_exc
+import threading
+import importlib
+import logging
+import time
+from toolbox import get_conf
+import asyncio
+load_message = "正在加载Claude组件，请稍候..."
+
+try:
+    """
+    ========================================================================
+    第一部分：Slack API Client
+    https://github.com/yokonsan/claude-in-slack-api
+    ========================================================================
+    """
+
+    from slack_sdk.errors import SlackApiError
+    from slack_sdk.web.async_client import AsyncWebClient
+
+    class SlackClient(AsyncWebClient):
+        """SlackClient类用于与Slack API进行交互，实现消息发送、接收等功能。
+
+            属性：
+            - CHANNEL_ID：str类型，表示频道ID。
+
+            方法：
+            - open_channel()：异步方法。通过调用conversations_open方法打开一个频道，并将返回的频道ID保存在属性CHANNEL_ID中。
+            - chat(text: str)：异步方法。向已打开的频道发送一条文本消息。
+            - get_slack_messages()：异步方法。获取已打开频道的最新消息并返回消息列表，目前不支持历史消息查询。
+            - get_reply()：异步方法。循环监听已打开频道的消息，如果收到"Typing…_"结尾的消息说明Claude还在继续输出，否则结束循环。
+
+        """
+        CHANNEL_ID = None
+
+        async def open_channel(self):
+            response = await self.conversations_open(users=get_conf('SLACK_CLAUDE_BOT_ID')[0])
+            self.CHANNEL_ID = response["channel"]["id"]
+
+        async def chat(self, text):
+            if not self.CHANNEL_ID:
+                raise Exception("Channel not found.")
+
+            resp = await self.chat_postMessage(channel=self.CHANNEL_ID, text=text)
+            self.LAST_TS = resp["ts"]
+
+        async def get_slack_messages(self):
+            try:
+                # TODO：暂时不支持历史消息，因为在同一个频道里存在多人使用时历史消息渗透问题
+                resp = await self.conversations_history(channel=self.CHANNEL_ID, oldest=self.LAST_TS, limit=1)
+                msg = [msg for msg in resp["messages"]
+                    if msg.get("user") == get_conf('SLACK_CLAUDE_BOT_ID')[0]]
+                return msg
+            except (SlackApiError, KeyError) as e:
+                raise RuntimeError(f"获取Slack消息失败。")
+        
+        async def get_reply(self):
+            while True:
+                slack_msgs = await self.get_slack_messages()
+                if len(slack_msgs) == 0:
+                    await asyncio.sleep(0.5)
+                    continue
+                
+                msg = slack_msgs[-1]
+                if msg["text"].endswith("Typing…_"):
+                    yield False, msg["text"]
+                else:
+                    yield True, msg["text"]
+                    break
+except:
+    pass
+
+"""
+========================================================================
+第二部分：子进程Worker（调用主体）
+========================================================================
+"""
+
+
+class ClaudeHandle(Process):
+    def __init__(self):
+        super().__init__(daemon=True)
+        self.parent, self.child = Pipe()
+        self.claude_model = None
+        self.info = ""
+        self.success = True
+        self.local_history = []
+        self.check_dependency()
+        if self.success: 
+            self.start()
+            self.threadLock = threading.Lock()
+
+    def check_dependency(self):
+        try:
+            self.success = False
+            import slack_sdk
+            self.info = "依赖检测通过，等待Claude响应。注意目前不能多人同时调用Claude接口（有线程锁），否则将导致每个人的Claude问询历史互相渗透。调用Claude时，会自动使用已配置的代理。"
+            self.success = True
+        except:
+            self.info = "缺少的依赖，如果要使用Claude，除了基础的pip依赖以外，您还需要运行`pip install -r request_llm/requirements_slackclaude.txt`安装Claude的依赖，然后重启程序。"
+            self.success = False
+
+    def ready(self):
+        return self.claude_model is not None    
+    
+    async def async_run(self):
+        await self.claude_model.open_channel()
+        while True:
+            # 等待
+            kwargs = self.child.recv()
+            question = kwargs['query']
+            history = kwargs['history']
+            # system_prompt=kwargs['system_prompt']
+
+            # 是否重置
+            if len(self.local_history) > 0 and len(history) == 0:
+                # await self.claude_model.reset()
+                self.local_history = []
+
+            # 开始问问题
+            prompt = ""
+            # Slack API最好不要添加系统提示
+            # if system_prompt not in self.local_history:
+            #     self.local_history.append(system_prompt)
+            #     prompt += system_prompt + '\n'
+
+            # 追加历史
+            for ab in history:
+                a, b = ab
+                if a not in self.local_history:
+                    self.local_history.append(a)
+                    prompt += a + '\n'
+                # if b not in self.local_history:
+                #     self.local_history.append(b)
+                #     prompt += b + '\n'
+
+            # 问题
+            prompt += question
+            self.local_history.append(question)
+            print('question:', prompt)
+            # 提交
+            await self.claude_model.chat(prompt)
+            # 获取回复
+            # async for final, response in self.claude_model.get_reply():
+            #     await self.handle_claude_response(final, response)
+            async for final, response in self.claude_model.get_reply():                
+                if not final:
+                    print(response)
+                    self.child.send(str(response))
+                else:
+                    # 防止丢失最后一条消息
+                    slack_msgs = await self.claude_model.get_slack_messages()
+                    last_msg = slack_msgs[-1]["text"] if slack_msgs and len(slack_msgs) > 0 else ""
+                    if last_msg:
+                        self.child.send(last_msg)
+                    print('-------- receive final ---------')
+                    self.child.send('[Finish]')
+                    
+    def run(self):
+        """
+        这个函数运行在子进程
+        """
+        # 第一次运行，加载参数
+        self.success = False
+        self.local_history = []
+        if (self.claude_model is None) or (not self.success):
+            # 代理设置
+            proxies, = get_conf('proxies')
+            if proxies is None:
+                self.proxies_https = None
+            else:
+                self.proxies_https = proxies['https']
+
+            try:
+                SLACK_CLAUDE_USER_TOKEN, = get_conf('SLACK_CLAUDE_USER_TOKEN')
+                self.claude_model = SlackClient(token=SLACK_CLAUDE_USER_TOKEN, proxy=self.proxies_https)
+                print('Claude组件初始化成功。')
+            except:
+                self.success = False
+                tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
+                self.child.send(f'[Local Message] 不能加载Claude组件。{tb_str}')
+                self.child.send('[Fail]')
+                self.child.send('[Finish]')
+                raise RuntimeError(f"不能加载Claude组件。")
+
+        self.success = True
+        try:
+            # 进入任务等待状态
+            asyncio.run(self.async_run())
+        except Exception:
+            tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
+            self.child.send(f'[Local Message] Claude失败 {tb_str}.')
+            self.child.send('[Fail]')
+            self.child.send('[Finish]')
+
+    def stream_chat(self, **kwargs):
+        """
+        这个函数运行在主进程
+        """
+        self.threadLock.acquire()
+        self.parent.send(kwargs)    # 发送请求到子进程
+        while True:
+            res = self.parent.recv()    # 等待Claude回复的片段
+            if res == '[Finish]':
+                break       # 结束
+            elif res == '[Fail]':
+                self.success = False
+                break
+            else:
+                yield res   # Claude回复的片段
+        self.threadLock.release()
+
+
+"""
+========================================================================
+第三部分：主进程统一调用函数接口
+========================================================================
+"""
+global claude_handle
+claude_handle = None
+
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+    """
+        多线程方法
+        函数的说明请见 request_llm/bridge_all.py
+    """
+    global claude_handle
+    if (claude_handle is None) or (not claude_handle.success):
+        claude_handle = ClaudeHandle()
+        observe_window[0] = load_message + "\n\n" + claude_handle.info
+        if not claude_handle.success:
+            error = claude_handle.info
+            claude_handle = None
+            raise RuntimeError(error)
+
+    # 没有 sys_prompt 接口，因此把prompt加入 history
+    history_feedin = []
+    for i in range(len(history)//2):
+        history_feedin.append([history[2*i], history[2*i+1]])
+
+    watch_dog_patience = 5  # 看门狗 (watchdog) 的耐心, 设置5秒即可
+    response = ""
+    observe_window[0] = "[Local Message]: 等待Claude响应中 ..."
+    for response in claude_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=sys_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+        observe_window[0] = preprocess_newbing_out_simple(response)
+        if len(observe_window) >= 2:
+            if (time.time()-observe_window[1]) > watch_dog_patience:
+                raise RuntimeError("程序终止。")
+    return preprocess_newbing_out_simple(response)
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None):
+    """
+        单线程方法
+        函数的说明请见 request_llm/bridge_all.py
+    """
+    chatbot.append((inputs, "[Local Message]: 等待Claude响应中 ..."))
+
+    global claude_handle
+    if (claude_handle is None) or (not claude_handle.success):
+        claude_handle = ClaudeHandle()
+        chatbot[-1] = (inputs, load_message + "\n\n" + claude_handle.info)
+        yield from update_ui(chatbot=chatbot, history=[])
+        if not claude_handle.success:
+            claude_handle = None
+            return
+
+    if additional_fn is not None:
+        import core_functional
+        importlib.reload(core_functional)    # 热更新prompt
+        core_functional = core_functional.get_core_functions()
+        if "PreProcess" in core_functional[additional_fn]:
+            inputs = core_functional[additional_fn]["PreProcess"](
+                inputs)  # 获取预处理函数（如果有的话）
+        inputs = core_functional[additional_fn]["Prefix"] + \
+            inputs + core_functional[additional_fn]["Suffix"]
+
+    history_feedin = []
+    for i in range(len(history)//2):
+        history_feedin.append([history[2*i], history[2*i+1]])
+
+    chatbot[-1] = (inputs, "[Local Message]: 等待Claude响应中 ...")
+    response = "[Local Message]: 等待Claude响应中 ..."
+    yield from update_ui(chatbot=chatbot, history=history, msg="Claude响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
+    for response in claude_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=system_prompt):
+        chatbot[-1] = (inputs, preprocess_newbing_out(response))
+        yield from update_ui(chatbot=chatbot, history=history, msg="Claude响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
+    if response == "[Local Message]: 等待Claude响应中 ...":
+        response = "[Local Message]: Claude响应异常，请刷新界面重试 ..."
+    history.extend([inputs, response])
+    logging.info(f'[raw_input] {inputs}')
+    logging.info(f'[response] {response}')
+    yield from update_ui(chatbot=chatbot, history=history, msg="完成全部响应，请提交新问题。")

request_llm/requirements_slackclaude.txt

@@ -0,0 +1 @@
+slack-sdk==3.21.3

version

@@ -1,5 +1,5 @@
 {
-  "version": 3.34,
+  "version": 3.35,
   "show_feature": true,
-  "new_feature": "修复新版gradio(3.28.3)的暗色主题适配 <-> 提供复旦MOSS模型适配（启用需额外依赖） <-> 提供docker-compose方案兼容LLAMA盘古RWKV等模型的后端 <-> 新增Live2D WAIFU装饰 <-> 完善对话历史的保存/载入/删除 <-> ChatGLM加线程锁提高并发稳定性 <-> 支持NewBing <-> Markdown翻译功能支持直接输入Readme文件网址 <-> 保存对话功能 <-> 解读任意语言代码+同时询问任意的LLM组合 <-> 添加联网（Google）回答问题插件"
+  "new_feature": "添加了OpenAI图片生成插件 <-> 添加了OpenAI音频转文本总结插件 <-> 通过Slack添加对Claude的支持 <-> 提供复旦MOSS模型适配（启用需额外依赖） <-> 提供docker-compose方案兼容LLAMA盘古RWKV等模型的后端 <-> 新增Live2D装饰 <-> 完善对话历史的保存/载入/删除 <-> 保存对话功能"
 }