Spaces:
Running
Running
| from toolbox import CatchException, update_ui, ProxyNetworkActivate | |
| from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything | |
| def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): | |
| """ | |
| txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径 | |
| llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行 | |
| plugin_kwargs 插件模型的参数，暂时没有用武之地 | |
| chatbot 聊天显示框的句柄，用于显示给用户 | |
| history 聊天历史，前情提要 | |
| system_prompt 给gpt的静默提醒 | |
| web_port 当前软件运行的端口号 | |
| """ | |
| history = [] # 清空历史，以免输入溢出 | |
| chatbot.append(("这是什么功能？", "[Local Message] 从一批文件(txt, md, tex)中读取数据构建知识库, 然后进行问答。")) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| # resolve deps | |
| try: | |
| from zh_langchain import construct_vector_store | |
| from langchain.embeddings.huggingface import HuggingFaceEmbeddings | |
| from .crazy_utils import knowledge_archive_interface | |
| except Exception as e: | |
| chatbot.append( | |
| ["依赖不足", | |
| "导入依赖失败。正在尝试自动安装，请查看终端的输出或耐心等待..."] | |
| ) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| from .crazy_utils import try_install_deps | |
| try_install_deps(['zh_langchain==0.2.1', 'pypinyin']) | |
| # < --------------------读取参数--------------- > | |
| if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg") | |
| kai_id = plugin_kwargs.get("advanced_arg", 'default') | |
| # < --------------------读取文件--------------- > | |
| file_manifest = [] | |
| spl = ["txt", "doc", "docx", "email", "epub", "html", "json", "md", "msg", "pdf", "ppt", "pptx", "rtf"] | |
| for sp in spl: | |
| _, file_manifest_tmp, _ = get_files_from_everything(txt, type=f'.{sp}') | |
| file_manifest += file_manifest_tmp | |
| if len(file_manifest) == 0: | |
| chatbot.append(["没有找到任何可读取文件", "当前支持的格式包括: txt, md, docx, pptx, pdf, json等"]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return | |
| # < -------------------预热文本向量化模组--------------- > | |
| chatbot.append(['<br/>'.join(file_manifest), "正在预热文本向量化模组, 如果是第一次运行, 将消耗较长时间下载中文向量化模型..."]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| print('Checking Text2vec ...') | |
| from langchain.embeddings.huggingface import HuggingFaceEmbeddings | |
| with ProxyNetworkActivate(): # 临时地激活代理网络 | |
| HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese") | |
| # < -------------------构建知识库--------------- > | |
| chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| print('Establishing knowledge archive ...') | |
| with ProxyNetworkActivate(): # 临时地激活代理网络 | |
| kai = knowledge_archive_interface() | |
| kai.feed_archive(file_manifest=file_manifest, id=kai_id) | |
| kai_files = kai.get_loaded_file() | |
| kai_files = '<br/>'.join(kai_files) | |
| # chatbot.append(['知识库构建成功', "正在将知识库存储至cookie中"]) | |
| # yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| # chatbot._cookies['langchain_plugin_embedding'] = kai.get_current_archive_id() | |
| # chatbot._cookies['lock_plugin'] = 'crazy_functions.Langchain知识库->读取知识库作答' | |
| # chatbot.append(['完成', "“根据知识库作答”函数插件已经接管问答系统, 提问吧! 但注意, 您接下来不能再使用其他插件了，刷新页面即可以退出知识库问答模式。"]) | |
| chatbot.append(['构建完成', f"当前知识库内的有效文件：\n\n---\n\n{kai_files}\n\n---\n\n请切换至“知识库问答”插件进行知识库访问, 或者使用此插件继续上传更多文件。"]) | |
| 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 | |
| def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port=-1): | |
| # resolve deps | |
| try: | |
| from zh_langchain import construct_vector_store | |
| from langchain.embeddings.huggingface import HuggingFaceEmbeddings | |
| from .crazy_utils import knowledge_archive_interface | |
| except Exception as e: | |
| chatbot.append(["依赖不足", "导入依赖失败。正在尝试自动安装，请查看终端的输出或耐心等待..."]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| from .crazy_utils import try_install_deps | |
| try_install_deps(['zh_langchain==0.2.1']) | |
| # < ------------------- --------------- > | |
| kai = knowledge_archive_interface() | |
| if 'langchain_plugin_embedding' in chatbot._cookies: | |
| resp, prompt = kai.answer_with_archive_by_id(txt, chatbot._cookies['langchain_plugin_embedding']) | |
| else: | |
| if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg") | |
| kai_id = plugin_kwargs.get("advanced_arg", 'default') | |
| resp, prompt = kai.answer_with_archive_by_id(txt, kai_id) | |
| chatbot.append((txt, '[Local Message] ' + prompt)) | |
| 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 | |
| gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| inputs=prompt, inputs_show_user=txt, | |
| llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], | |
| sys_prompt=system_prompt | |
| ) | |
| history.extend((prompt, gpt_say)) | |
| 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 | |