{"id":48530,"date":"2024-04-28T16:26:03","date_gmt":"2024-04-28T08:26:03","guid":{"rendered":"https:\/\/wx.kaifamiao.info\/?p=48530"},"modified":"2024-05-10T17:15:44","modified_gmt":"2024-05-10T09:15:44","slug":"langchain-ru-menben-de-hua-bu-shujie-ru-da-mo-xing","status":"publish","type":"post","link":"http:\/\/wx.kaifamiao.info\/index.php\/2024\/04\/28\/langchain-ru-menben-de-hua-bu-shujie-ru-da-mo-xing\/","title":{"rendered":"LangChain\uff1a\u5165\u95e8-\u672c\u5730\u5316\u90e8\u7f72-\u63a5\u5165\u5927\u6a21\u578b\uff088\uff09"},"content":{"rendered":"<h1><a id=\"langchain%EF%BC%9A%E5%85%A5%E9%97%A8%E6%9C%AC%E5%9C%B0%E5%8C%96%E9%83%A8%E7%BD%B2%E6%8E%A5%E5%85%A5%E5%A4%A7%E6%A8%A1%E5%9E%8B%EF%BC%88-8%EF%BC%89\" class=\"anchor\" aria-hidden=\"true\"><span class=\"octicon octicon-link\"><\/span><\/a>LangChain\uff1a\u5165\u95e8-\u672c\u5730\u5316\u90e8\u7f72-\u63a5\u5165\u5927\u6a21\u578b\uff088\uff09<\/h1>\n<h2><a id=\"langchain%E6%A0%B8%E5%BF%83%E6%A8%A1%E5%9D%97\" class=\"anchor\" aria-hidden=\"true\"><span class=\"octicon octicon-link\"><\/span><\/a>LangChain\u6838\u5fc3\u6a21\u5757<\/h2>\n<ul>\n<li>\n\u6a21\u578b\uff08models\uff09 : LangChain \u652f\u6301\u7684\u5404\u79cd\u6a21\u578b\u7c7b\u578b\u548c\u6a21\u578b\u96c6\u6210\u3002\n<\/li>\n<li>\n\u63d0\u793a\uff08prompts\uff09 : \u5305\u62ec\u63d0\u793a\u7ba1\u7406\u3001\u63d0\u793a\u4f18\u5316\u548c\u63d0\u793a\u5e8f\u5217\u5316\u3002\n<\/li>\n<li>\n\u94fe\uff08chains\uff09 : \u94fe\u4e0d\u4ec5\u4ec5\u662f\u5355\u4e2a LLM \u8c03\u7528\uff0c\u8fd8\u5305\u62ec\u4e00\u7cfb\u5217\u8c03\u7528\uff08\u65e0\u8bba\u662f\u8c03\u7528 LLM \u8fd8\u662f\u4e0d\u540c\u7684\u5b9e\u7528\u5de5\u5177\uff09\u3002LangChain \u63d0\u4f9b\u4e86\u4e00\u79cd\u6807\u51c6\u7684\u94fe\u63a5\u53e3\u3001\u8bb8\u591a\u4e0e\u5176\u4ed6\u5de5\u5177\u7684\u96c6\u6210\u3002LangChain \u63d0\u4f9b\u4e86\u7528\u4e8e\u5e38\u89c1\u5e94\u7528\u7a0b\u5e8f\u7684\u7aef\u5230\u7aef\u7684\u94fe\u8c03\u7528\u3002\n<\/li>\n<li>\n\u7d22\u5f15\uff08indexes\uff09 : \u4e0e\u60a8\u81ea\u5df1\u7684\u6587\u672c\u6570\u636e\u7ed3\u5408\u4f7f\u7528\u65f6\uff0c\u8bed\u8a00\u6a21\u578b\u5f80\u5f80\u66f4\u52a0\u5f3a\u5927\u2014\u2014\u6b64\u6a21\u5757\u6db5\u76d6\u4e86\u6267\u884c\u6b64\u64cd\u4f5c\u7684\u6700\u4f73\u5b9e\u8df5\u3002\n<\/li>\n<li>\n\u4ee3\u7406\uff08agents\uff09 : \u4ee3\u7406\u6d89\u53ca LLM \u505a\u51fa\u884c\u52a8\u51b3\u7b56\u3001\u6267\u884c\u8be5\u884c\u52a8\u3001\u67e5\u770b\u4e00\u4e2a\u89c2\u5bdf\u7ed3\u679c\uff0c\u5e76\u91cd\u590d\u8be5\u8fc7\u7a0b\u76f4\u5230\u5b8c\u6210\u3002LangChain \u63d0\u4f9b\u4e86\u4e00\u4e2a\u6807\u51c6\u7684\u4ee3\u7406\u63a5\u53e3\uff0c\u4e00\u7cfb\u5217\u53ef\u4f9b\u9009\u62e9\u7684\u4ee3\u7406\uff0c\u4ee5\u53ca\u7aef\u5230\u7aef\u4ee3\u7406\u7684\u793a\u4f8b\u3002\n<\/li>\n<li>\n\u5185\u5b58\uff08memory\uff09\u4e5f\u53eb\u8bb0\u5fc6\u5b58\u50a8 : \u5185\u5b58\u662f\u5728\u94fe\/\u4ee3\u7406\u8c03\u7528\u4e4b\u95f4\u4fdd\u6301\u72b6\u6001\u7684\u6982\u5ff5\u3002LangChain\u63d0\u4f9b\u4e86\u4e00\u4e2a\u6807\u51c6\u7684\u5185\u5b58\u63a5\u53e3\u3001\u4e00\u7ec4\u5185\u5b58\u5b9e\u73b0\u53ca\u4f7f\u7528\u5185\u5b58\u7684\u94fe\/\u4ee3\u7406\u793a\u4f8b\u3002\n<\/li>\n<\/ul>\n<p>\u4e3a\u4e86\u8ba9\u80fd\u591f\u66f4\u597d\u7684\u7406\u89e3\u8fd9\u516d\u4e2a\u6838\u5fc3\u6a21\u5757\uff0c\u4e3e\u4e2a\u4f8b\u5b50\uff1a<\/p>\n<p>\u6211\u4eec\u5728\u4f7f\u7528\u4f7f\u7528\u5927\u6a21\u578b\uff0c\u9996\u5148\u5c31\u8981\u4f7f\u7528\u6a21\u578b\u5bf9\u63a5\u3002\u5bf9\u63a5\u597d\u4e86\uff0c\u6211\u4eec\u600e\u4e48\u5f00\u59cb\u60f3\u600e\u4e48\u95ee\u5927\u6a21\u578b\u7684\u95ee\u9898\uff08\u63d0\u793a\u8bcd\uff09\uff0c\u63a5\u7740\u60f3\u597d\u600e\u4e48\u95ee\u4ed6\uff0c\u6211\u4eec\u9700\u8981\u7a7f\u8d77\u6765(\u94fe)\u3002\u73b0\u5728\u8981\u5f3a\u5927\u6211\u4eec\u7684\u5927\u6a21\u578b\uff0c\u9700\u8981\u8ba9\u4ed6\u62e5\u6709\u989d\u5916\u77e5\u8bc6(\u7d22\u5f15)\u548c\u4ee3\u66ff\u6211\u4eec\u505a\u4e00\u4e9b\u5de5\u4f5c(\u4ee3\u7406).\u518d\u95ee\u95ee\u7684\u65f6\u5019\u6211\u5e0c\u671b\u4ed6\u62e5\u6709\u8bb0\u5fc6(\u5185\u5b58)<\/p>\n<h2><a id=\"%E5%A6%82%E4%BD%95%E6%8E%A5%E5%85%A5%E5%A4%A7%E6%A8%A1%E5%9E%8B\" class=\"anchor\" aria-hidden=\"true\"><span class=\"octicon octicon-link\"><\/span><\/a>\u5982\u4f55\u63a5\u5165\u5927\u6a21\u578b<\/h2>\n<h3><a id=\"%E5%8E%9F%E7%94%9Fopenai%E8%B0%83%E7%94%A8%E5%A4%A7%E6%A8%A1%E5%9E%8B\" class=\"anchor\" aria-hidden=\"true\"><span class=\"octicon octicon-link\"><\/span><\/a>\u539f\u751fopenai\u8c03\u7528\u5927\u6a21\u578b<\/h3>\n<p>\u5f53\u4f60\u6709\u4e86openai\u7684key\uff0c\u4f60\u5c31\u53ef\u4ee5\u4f7f\u7528opanai\u7684\u6a21\u5757\u8fdb\u884c\u8c03\u7528<\/p>\n<pre><code class=\"language-sh\">pip install openai==0.28\n<\/code><\/pre>\n<pre><code class=\"language-python\">import os\nimport openai\n\ndef get_completion(prompt,model=\"gpt-3.5-turbo\"):\n    messages=[{\"role\":\"user\",\"content\":prompt}]\n\n    response=openai.ChatCompletion.create(\n        model=model,\n        messages=messages,\n        temperature=0,\n    )\n    return response.choices[0].message[\"content\"]\n\n\nif __name__ == \"__main__\":\n    # import your OpenAI key (put in your .env file)\n    # \u4ece.env\u6587\u4ef6\u4e2d\u5bfc\u5165OpenAI\u7684API\u5bc6\u94a5\n\n    with open(\".env\", \"r\") as f:\n        env_file = f.readlines()\n    envs_dict = {\n        key.strip(\"'\"): value.strip(\"\\n\")\n        for key, value in [(i.split(\"=\")) for i in env_file]\n    }\n    os.environ[\"OPENAI_API_KEY\"] = envs_dict[\"OPENAI_API_KEY\"]\n\n    # \u7b2c\u4e00\u6b65\u8fd9\u662fopenai\u7684key\n    openai.api_key = os.environ[\"OPENAI_API_KEY\"]\n    print(get_completion(\"\u4f60\u597d\"))\n<\/code><\/pre>\n<p>\u8fd4\u56de\u7ed3\u679c<\/p>\n<pre><code class=\"language-plain_text\">\u60a8\u597d\uff01\u6709\u4ec0\u4e48\u53ef\u4ee5\u5e2e\u52a9\u60a8\u7684\u5417\n<\/code><\/pre>\n<h4><a id=\"%E4%BD%BF%E7%94%A8langchain%E5%B0%81%E8%A3%85%E7%9A%84openai%E6%A8%A1%E5%9D%97\" class=\"anchor\" aria-hidden=\"true\"><span class=\"octicon octicon-link\"><\/span><\/a>\u4f7f\u7528LangChain\u5c01\u88c5\u7684OpenAI\u6a21\u5757<\/h4>\n<p><strong>\u73af\u5883\u51c6\u5907<\/strong><\/p>\n<p>\u9996\u5148\u4f60\u9700\u8981\u4e0b\u8f7d\u4f60\u7684\u5927\u6a21\u578b\uff0c\u8fd9\u91cc\u7528\u901a\u4e49\u5343\u95ee7B\u4e3e\u4f8b\uff1a<br \/>\n<a href=\"https:\/\/www.modelscope.cn\/models\/qwen\/Qwen-7B-Chat\/files\">https:\/\/www.modelscope.cn\/models\/qwen\/Qwen-7B-Chat\/files<\/a><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/1YsWjRu9BZe7lDT.png\" alt=\"image-20240428161744694\" \/><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/G1CyYjZMfNnsUIz.png\" alt=\"image-20240428161847122\" \/><\/p>\n<p>\u5728\u4e0b\u8f7d\u4e4b\u524d\u4f60\u9700\u8981\u5b89\u88c5\u73af\u5883<\/p>\n<pre><code class=\"language-python\">pip install openai==0.28\npip install transformers==4.32.0 accelerate tiktoken einops scipy transformers_stream_generator==0.0.4 peft deepspeed\n\n\npip install transformers_stream_generator\n\n\npip3 install -U modelscope\n# \u5bf9\u4e8e\u56fd\u5185\u7684\u7528\u6237\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a\n# pip3 install -U modelscope -i https:\/\/mirror.sjtu.edu.cn\/pypi\/web\/simple\n<\/code><\/pre>\n<p>\u9ed8\u8ba4\u662f\u5728\/root\/.cache\u6587\u4ef6\u5939\uff0c\u8fd9\u91cc\u53ef\u4ee5local_dir_root \u6307\u5b9a\u4e0b\u8f7d\u4f4d\u7f6e<\/p>\n<pre><code class=\"language-sh\">from modelscope.hub.snapshot_download import snapshot_download\nlocal_dir_root = \"\/root\/autodl-tmp\/models_from_modelscope\"\nsnapshot_download('qwen\/Qwen-7B-Chat', cache_dir=local_dir_root)\n<\/code><\/pre>\n<p><strong>\u542f\u52a8\u6a21\u578b<\/strong><\/p>\n<p>\u62c9\u53bb\u5b98\u65b9\u7684demo,\u4e00\u822c\u6a21\u578b\u90fd\u6709\u81ea\u5df1\u7684demo,\u5927\u5bb6\u53ef\u4ee5\u53bb\u770b\u770b<img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/6pIHFsXxVS5Mw4O.png\" alt=\"image-20240428162035967\" \/><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/VjZdoz3r9PK4bwN.png\" alt=\"image-20240428162147645\" \/><\/p>\n<pre><code class=\"language-sh\">git clone https:\/\/github.com\/QwenLM\/Qwen.git\n<\/code><\/pre>\n<p>\u4fee\u6539Qwen\u91cc\u9762\u7684openai_api\u5730\u5740\u4e3a\u771f\u5b9e\u7684\u5730\u5740<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/32EkxeBpfJKusFG.png\" alt=\"image-20240428162225410\" \/><\/p>\n<p>\u7136\u540e\u5c31\u53ef\u4ee5\u6b63\u5e38\u542f\u52a8\u4e86<\/p>\n<pre><code class=\"language-sh\">pip install openai==0.28\npip install -r requirements.txt\npip install fastapi uvicorn openai pydantic sse_starlette\npython openai_api.py\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/ofZ5vAy2imcWODE.png\" alt=\"image-20240428162314307\" \/><\/p>\n<p>\u53ef\u4ee5\u643a\u5e26\u81ea\u5df1\u5b9a\u4e49\u7684\u53c2\u6570<\/p>\n<pre><code class=\"language-plain_text\">--checkpoint-path \u589e\u91cf\u6a21\u578b\u5730\u5740\n--cpu-only cpu\u542f\u52a8\n--server-port \u670d\u52a1\u7aef\u53e3\u9ed8\u8ba48000\n--server-name \u670d\u52a1ip\u9ed8\u8ba4127.0.0.1\n---disable-gc\u5728\u751f\u6210\u6bcf\u4e2a\u54cd\u5e94\u540e\u7981\u7528GC\u3002\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/EsxeDfrWLNMuvUl.png\" alt=\"image-20240428162421991\" \/><\/p>\n<p><strong>\u4f7f\u7528\u6a21\u578b<\/strong><\/p>\n<p>\u5f53\u7136\u6b64\u65f6\u6211\u4eec\u8fd8\u662f\u53ef\u4ee5\u4f7f\u7528openai\u7684\u6a21\u5757\u8fdb\u884c\u8c03\u7528<\/p>\n<pre><code class=\"language-python\">import openai\nopenai.api_base = \"http:\/\/localhost:8000\/v1\"\nopenai.api_key = \"none\"\n\n# \u4f7f\u7528\u6d41\u5f0f\u56de\u590d\u7684\u8bf7\u6c42\nfor chunk in openai.ChatCompletion.create(\n    model=\"Qwen\",\n    messages=[\n        {\"role\": \"user\", \"content\": \"\u4f60\u597d\"}\n    ],\n    stream=True\n    # \u6d41\u5f0f\u8f93\u51fa\u7684\u81ea\u5b9a\u4e49stopwords\u529f\u80fd\u5c1a\u672a\u652f\u6301\uff0c\u6b63\u5728\u5f00\u53d1\u4e2d\n):\n    if hasattr(chunk.choices[0].delta, \"content\"):\n        print(chunk.choices[0].delta.content, end=\"\", flush=True)\n\n# \u4e0d\u4f7f\u7528\u6d41\u5f0f\u56de\u590d\u7684\u8bf7\u6c42\nresponse = openai.ChatCompletion.create(\n    model=\"Qwen\",\n    messages=[\n        {\"role\": \"user\", \"content\": \"\u4f60\u597d\"}\n    ],\n    stream=False,\n    stop=[] # \u5728\u6b64\u5904\u6dfb\u52a0\u81ea\u5b9a\u4e49\u7684stop words \u4f8b\u5982ReAct prompting\u65f6\u9700\u8981\u589e\u52a0\uff1a stop=[\"Observation:\"]\u3002\n)\nprint(response.choices[0].message.content)\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/3IwcxJUnrQtXuiv.png\" alt=\"image-20240428162513615\" \/><\/p>\n<p>\u5f53\u7136\u5e94\u4e3a\u6211\u4eec\u9009\u62e9LangChain\u6700\u4e3a\u6211\u4eec\u7684\u4e2d\u95f4\u4ef6\uff0c\u6211\u4eec\u4e5f\u53ef\u4ee5\u4f7f\u7528LangChain\u5c01\u88c5\u7684\u6a21\u5757\u4f7f\u7528<\/p>\n<pre><code class=\"language-sh\">pip install langchain\n<\/code><\/pre>\n<pre><code class=\"language-python\">from langchain.chat_models import ChatOpenAI\n\nfrom langchain.schema import HumanMessage\n\nllm = ChatOpenAI(\n    streaming=True,\n    verbose=True,\n    # callbacks=[callback],\n    openai_api_key=\"none\",\n    openai_api_base=\"http:\/\/127.0.0.1:8000\/v1\",\n    model_name=\"Qwen-7B-Chat\"\n)\ninstructions = \"\"\"\n\u4f60\u5c06\u5f97\u5230\u4e00\u4e2a\u5e26\u6709\u6c34\u679c\u540d\u79f0\u7684\u53e5\u5b50,\u63d0\u53d6\u8fd9\u4e9b\u6c34\u679c\u540d\u79f0\u5e76\u4e3a\u5176\u5206\u914d\u4e00\u4e2a\u8868\u60c5\u7b26\u53f7\n\u5728 python \u5b57\u5178\u4e2d\u8fd4\u56de\u6c34\u679c\u540d\u79f0\u548c\u8868\u60c5\u7b26\u53f7\n\"\"\"\n\nfruit_names = \"\"\"\n\u82f9\u679c,\u68a8,\u8fd9\u662f\u5947\u5f02\u679c\n\"\"\"\n\n# \u5236\u4f5c\u7ed3\u5408\u8bf4\u660e\u548c\u6c34\u679c\u540d\u79f0\u7684\u63d0\u793a\nprompt = (instructions + fruit_names)\n\n# Call the LLM\noutput = llm([HumanMessage(content=prompt)])\n\nprint (output.content)\nprint(\"========\")\nprint (type(output.content))\n# \u82f9\u679c: \ud83c\udf4e\u68a8: \ud83e\udd50\u5947\u5f02\u679c: \ud83c\udf53\n# ========\n# <class 'str'>\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/s2.loli.net\/2024\/04\/28\/TIMeJj5V9hEHZnq.png\" alt=\"image-20240428162553959\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>LangChain\uff1a\u5165\u95e8-\u672c\u5730\u5316\u90e8\u7f72-\u63a5\u5165\u5927\u6a21\u578b\uff088\uff09 LangChain\u6838\u5fc3\u6a21\u5757 \u6a21\u578b\uff08models\uff09 :  [&hellip;]<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[99],"tags":[],"class_list":["post-48530","post","type-post","status-publish","format-standard","hentry","category-javabase"],"_links":{"self":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts\/48530","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/comments?post=48530"}],"version-history":[{"count":1,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts\/48530\/revisions"}],"predecessor-version":[{"id":48531,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/posts\/48530\/revisions\/48531"}],"wp:attachment":[{"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/media?parent=48530"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/categories?post=48530"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/wx.kaifamiao.info\/index.php\/wp-json\/wp\/v2\/tags?post=48530"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}