langchain
This commit is contained in:
505030475
parent
6789d1fab4
commit
6d1ea643e9
80
colorful.py
80
colorful.py
@ -34,58 +34,28 @@ def print亮紫(*kw,**kargs):
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def print亮靛(*kw,**kargs):
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print("\033[1;36m",*kw,"\033[0m",**kargs)
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def print亮红(*kw,**kargs):
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print("\033[1;31m",*kw,"\033[0m",**kargs)
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def print亮绿(*kw,**kargs):
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print("\033[1;32m",*kw,"\033[0m",**kargs)
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def print亮黄(*kw,**kargs):
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print("\033[1;33m",*kw,"\033[0m",**kargs)
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def print亮蓝(*kw,**kargs):
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print("\033[1;34m",*kw,"\033[0m",**kargs)
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def print亮紫(*kw,**kargs):
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print("\033[1;35m",*kw,"\033[0m",**kargs)
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def print亮靛(*kw,**kargs):
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print("\033[1;36m",*kw,"\033[0m",**kargs)
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print_red = print红
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print_green = print绿
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print_yellow = print黄
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print_blue = print蓝
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print_purple = print紫
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print_indigo = print靛
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print_bold_red = print亮红
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print_bold_green = print亮绿
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print_bold_yellow = print亮黄
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print_bold_blue = print亮蓝
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print_bold_purple = print亮紫
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print_bold_indigo = print亮靛
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if not stdout.isatty():
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# redirection, avoid a fucked up log file
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print红 = print
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print绿 = print
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print黄 = print
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print蓝 = print
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print紫 = print
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print靛 = print
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print亮红 = print
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print亮绿 = print
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print亮黄 = print
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print亮蓝 = print
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print亮紫 = print
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print亮靛 = print
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print_red = print
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print_green = print
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print_yellow = print
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print_blue = print
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print_purple = print
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print_indigo = print
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print_bold_red = print
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print_bold_green = print
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print_bold_yellow = print
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print_bold_blue = print
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print_bold_purple = print
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print_bold_indigo = print
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# Do you like the elegance of Chinese characters?
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def sprint红(*kw):
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return "\033[0;31m"+' '.join(kw)+"\033[0m"
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def sprint绿(*kw):
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return "\033[0;32m"+' '.join(kw)+"\033[0m"
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def sprint黄(*kw):
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return "\033[0;33m"+' '.join(kw)+"\033[0m"
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def sprint蓝(*kw):
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return "\033[0;34m"+' '.join(kw)+"\033[0m"
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def sprint紫(*kw):
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return "\033[0;35m"+' '.join(kw)+"\033[0m"
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def sprint靛(*kw):
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return "\033[0;36m"+' '.join(kw)+"\033[0m"
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def sprint亮红(*kw):
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return "\033[1;31m"+' '.join(kw)+"\033[0m"
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def sprint亮绿(*kw):
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return "\033[1;32m"+' '.join(kw)+"\033[0m"
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def sprint亮黄(*kw):
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return "\033[1;33m"+' '.join(kw)+"\033[0m"
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def sprint亮蓝(*kw):
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return "\033[1;34m"+' '.join(kw)+"\033[0m"
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def sprint亮紫(*kw):
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return "\033[1;35m"+' '.join(kw)+"\033[0m"
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def sprint亮靛(*kw):
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return "\033[1;36m"+' '.join(kw)+"\033[0m"
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@ -295,5 +295,17 @@ def get_crazy_functions():
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except:
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print('Load function plugin failed')
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try:
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from crazy_functions.Langchain知识库 import 知识库问答
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function_plugins.update({
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"构建知识库（请先上传文件素材）": {
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"Color": "stop",
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"AsButton": False,
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"Function": HotReload(知识库问答)
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}
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})
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except:
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print('Load function plugin failed')
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###################### 第n组插件 ###########################
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return function_plugins
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88
crazy_functions/Langchain知识库.py
Normal file
88
crazy_functions/Langchain知识库.py
Normal file
@ -0,0 +1,88 @@
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from toolbox import CatchException, update_ui, ProxyNetworkActivate
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
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@CatchException
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def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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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
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llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
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plugin_kwargs 插件模型的参数，暂时没有用武之地
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chatbot 聊天显示框的句柄，用于显示给用户
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history 聊天历史，前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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history = [] # 清空历史，以免输入溢出
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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。"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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try:
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import zh_langchain
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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from .crazy_utils import knowledge_archive_interface
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except Exception as e:
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chatbot.append(
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["依赖不足",
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"导入依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade langchain zh_langchain```。"]
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)
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# < --------------------读取文件--------------- >
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file_manifest = []
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spl = ["doc", "docx", "email", "epub", "html", "image", "json", "md", "msg", "odt", "pdf", "ppt", "pptx", "rtf", "text"]
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for sp in spl:
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_, file_manifest_tmp, _ = get_files_from_everything(txt, type=f'.{sp}')
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file_manifest += file_manifest_tmp
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if len(file_manifest) == 0:
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chatbot.append(["没有找到任何可读取文件", "当前支持的格式包括: txt, md, tex"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# < -------------------预热文本向量化模组--------------- >
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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..."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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print('Checking Text2vec ...')
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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with ProxyNetworkActivate(): # 临时地激活代理网络
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HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese", model_kwargs={'device': 'cpu'})
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# < -------------------构建知识库--------------- >
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chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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print('Establishing knowledge archive ...')
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with ProxyNetworkActivate(): # 临时地激活代理网络
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kai = knowledge_archive_interface()
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kai.feed_archive(file_manifest=file_manifest, id="default")
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chatbot.append(['知识库构建成功', "正在将知识库存储至cookie中"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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chatbot._cookies['langchain_plugin_embedding'] = kai.get_current_archive_id()
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chatbot._cookies['lock_plugin'] = 'crazy_functions.Langchain知识库->读取知识库作答'
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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。"])
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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
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@CatchException
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def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port=-1):
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# < ------------------- --------------- >
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from .crazy_utils import knowledge_archive_interface
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kai = knowledge_archive_interface()
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if 'langchain_plugin_embedding' in chatbot._cookies:
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resp, prompt = kai.answer_with_archive_by_id(txt, chatbot._cookies['langchain_plugin_embedding'])
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else:
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if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
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kai_id = plugin_kwargs.get("advanced_arg", 'default')
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resp, prompt = kai.answer_with_archive_by_id(txt, kai_id)
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chatbot.append((txt, '[Local Message] ' + prompt))
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=prompt, inputs_show_user=txt,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt=system_prompt
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)
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history.extend((prompt, gpt_say))
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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
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@ -3,6 +3,8 @@
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这个文件用于函数插件的单元测试
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运行方法 python crazy_functions/crazy_functions_test.py
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"""
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# ==============================================================================================================================
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def validate_path():
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import os, sys
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@ -10,10 +12,16 @@ def validate_path():
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root_dir_assume = os.path.abspath(os.path.dirname(__file__) + '/..')
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os.chdir(root_dir_assume)
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sys.path.append(root_dir_assume)
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validate_path() # validate path so you can run from base directory
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# ==============================================================================================================================
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from colorful import *
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from toolbox import get_conf, ChatBotWithCookies
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import contextlib
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import os
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import sys
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from functools import wraps
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proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \
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get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
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@ -30,7 +38,43 @@ history = []
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system_prompt = "Serve me as a writing and programming assistant."
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web_port = 1024
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# ==============================================================================================================================
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def silence_stdout(func):
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@wraps(func)
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def wrapper(*args, **kwargs):
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_original_stdout = sys.stdout
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sys.stdout = open(os.devnull, 'w')
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for q in func(*args, **kwargs):
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sys.stdout = _original_stdout
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yield q
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sys.stdout = open(os.devnull, 'w')
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sys.stdout.close()
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sys.stdout = _original_stdout
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return wrapper
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class CLI_Printer():
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def __init__(self) -> None:
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self.pre_buf = ""
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def print(self, buf):
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bufp = ""
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for index, chat in enumerate(buf):
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a, b = chat
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bufp += sprint亮靛('[Me]:' + a) + '\n'
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bufp += '[GPT]:' + b
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if index < len(buf)-1:
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bufp += '\n'
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if self.pre_buf!="" and bufp.startswith(self.pre_buf):
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print(bufp[len(self.pre_buf):], end='')
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else:
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print('\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n'+bufp, end='')
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self.pre_buf = bufp
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return
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cli_printer = CLI_Printer()
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# ==============================================================================================================================
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def test_解析一个Python项目():
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from crazy_functions.解析项目源代码 import 解析一个Python项目
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txt = "crazy_functions/test_project/python/dqn"
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@ -116,6 +160,25 @@ def test_Markdown多语言():
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for cookies, cb, hist, msg in Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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print(cb)
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def test_Langchain知识库():
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from crazy_functions.Langchain知识库 import 知识库问答
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txt = "README.md"
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chatbot = ChatBotWithCookies(llm_kwargs)
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for cookies, cb, hist, msg in silence_stdout(知识库问答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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cli_printer.print(cb) # print(cb)
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chatbot = ChatBotWithCookies(cookies)
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from crazy_functions.Langchain知识库 import 读取知识库作答
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txt = "摘要？"
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for cookies, cb, hist, msg in silence_stdout(读取知识库作答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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cli_printer.print(cb) # print(cb)
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def test_Langchain知识库读取():
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from crazy_functions.Langchain知识库 import 读取知识库作答
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txt = "远程云服务器部署？"
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for cookies, cb, hist, msg in silence_stdout(读取知识库作答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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cli_printer.print(cb) # print(cb)
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# test_解析一个Python项目()
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@ -129,7 +192,8 @@ def test_Markdown多语言():
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# test_联网回答问题()
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# test_解析ipynb文件()
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# test_数学动画生成manim()
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test_Markdown多语言()
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test_Langchain知识库()
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# test_Langchain知识库读取()
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input("程序完成，回车退出。")
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print("退出。")
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@ -1,4 +1,5 @@
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from toolbox import update_ui, get_conf, trimmed_format_exc
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import threading
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def input_clipping(inputs, history, max_token_limit):
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import numpy as np
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@ -606,3 +607,87 @@ def get_files_from_everything(txt, type): # type='.md'
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success = False
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return success, file_manifest, project_folder
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def Singleton(cls):
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_instance = {}
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def _singleton(*args, **kargs):
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if cls not in _instance:
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_instance[cls] = cls(*args, **kargs)
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return _instance[cls]
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return _singleton
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@Singleton
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class knowledge_archive_interface():
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def __init__(self) -> None:
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self.threadLock = threading.Lock()
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self.current_id = ""
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self.kai_path = None
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self.qa_handle = None
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self.text2vec_large_chinese = None
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def get_chinese_text2vec(self):
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if self.text2vec_large_chinese is None:
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# < -------------------预热文本向量化模组--------------- >
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from toolbox import ProxyNetworkActivate
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print('Checking Text2vec ...')
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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with ProxyNetworkActivate(): # 临时地激活代理网络
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self.text2vec_large_chinese = HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese", model_kwargs={'device': 'cpu'})
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return self.text2vec_large_chinese
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def feed_archive(self, file_manifest, id="default"):
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self.threadLock.acquire()
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# import uuid
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self.current_id = id
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from zh_langchain import construct_vector_store
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self.qa_handle, self.kai_path = construct_vector_store(
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vs_id=self.current_id,
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files=file_manifest,
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sentence_size=100,
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history=[],
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one_conent="",
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one_content_segmentation="",
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text2vec = self.get_chinese_text2vec(),
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)
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self.threadLock.release()
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def get_current_archive_id(self):
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return self.current_id
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def answer_with_archive_by_id(self, txt, id):
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self.threadLock.acquire()
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if not self.current_id == id:
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self.current_id = id
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from zh_langchain import construct_vector_store
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self.qa_handle, self.kai_path = construct_vector_store(
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vs_id=self.current_id,
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files=[],
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sentence_size=100,
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history=[],
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one_conent="",
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one_content_segmentation="",
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text2vec = self.get_chinese_text2vec(),
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)
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VECTOR_SEARCH_SCORE_THRESHOLD = 0
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VECTOR_SEARCH_TOP_K = 4
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CHUNK_SIZE = 512
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resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
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query = txt,
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vs_path = self.kai_path,
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score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
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vector_search_top_k=VECTOR_SEARCH_TOP_K,
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chunk_conent=True,
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chunk_size=CHUNK_SIZE,
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text2vec = self.get_chinese_text2vec(),
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)
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self.threadLock.release()
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return resp, prompt
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12
toolbox.py
12
toolbox.py
@ -59,7 +59,15 @@ def ArgsGeneralWrapper(f):
|
||||
}
|
||||
chatbot_with_cookie = ChatBotWithCookies(cookies)
|
||||
chatbot_with_cookie.write_list(chatbot)
|
||||
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
|
||||
if 'lock_plugin' in cookies and cookies['lock_plugin'] is not None:
|
||||
# 处理插件锁定状态
|
||||
module, fn_name = cookies['lock_plugin'].split('->')
|
||||
f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
|
||||
yield from HotReload(f_hot_reload)(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
else:
|
||||
# 正常状态
|
||||
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
return decorated
|
||||
|
||||
|
||||
@ -83,7 +91,7 @@ def CatchException(f):
|
||||
"""
|
||||
|
||||
@wraps(f)
|
||||
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT=-1):
|
||||
try:
|
||||
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||||
except Exception as e:
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user