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\n

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\n

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              \u9762\u8bd5\u98981：\u4f20\u7edf\u5bf9\u8bdd\u7cfb\u7edf\u6bcf\u6b21\u4ea4\u4e92\u72ec\u7acb，\u6a21\u578b\u65e0\u6cd5\u611f\u77e5\u5386\u53f2，\u600e\u4e48\u89e3？<\/h4>\n

              \"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

              \u7b54：\u7528\u8bb0\u5fc6\u6a21\u5757（\u5982LangChain\u7684Memory）\u8bb0\u5f55\u5386\u53f2，\u4f46\u957f\u5bf9\u8bdd\u4f1a\u8d85Token，\u6240\u4ee5\u9700\u8981\u6458\u8981\u5b58\u50a8\u2014\u2014\u4e0d\u5b58\u5b8c\u6574\u5bf9\u8bdd，\u53ea\u5b58\u5173\u952e\u4fe1\u606f\u6458\u8981，\u65e2\u4fdd\u8fde\u8d2f\u6027\u53c8\u7701Token\u3002<\/p>\n

              \u9762\u8bd5\u98982：\u957f\u5bf9\u8bdd\u8d85\u51fa\u6a21\u578bToken\u80fd\u529b，\u4fe1\u606f\u622a\u65ad\u3001\u6027\u80fd\u4e0b\u964d，\u600e\u4e48\u89e3？<\/h4>\n

              \u7b54：\u6838\u5fc3\u662f\u201c\u538b\u7f29\u5386\u53f2\u201d\u2014\u2014\u7528\u5927\u6a21\u578b\u751f\u6210\u5bf9\u8bdd\u6458\u8981，\u540e\u7eed\u4ea4\u4e92\u53ea\u4f20\u6458\u8981\u800c\u975e\u5168\u91cf\u5386\u53f2，\u642d\u914d\u5206\u5e03\u5f0f\u5b58\u50a8（\u5982MongoDB\u3001Milvus），\u5e73\u8861\u8fde\u8d2f\u6027\u3001\u6027\u80fd\u548c\u8d44\u6e90\u6d88\u8017\u3002<\/p>\n

              \u4e8c\u3001\u5927\u6a21\u578b\u5b58\u50a8\u76843\u5927\u6838\u5fc3\u75db\u70b9<\/h3>\n

              \"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

              \u8fd9\u4e9b\u75db\u70b9\u771f\u7684\u5f88\u5f71\u54cd\u7528\u6237\u4f53\u9a8c，\u54b1\u4eec\u5bf9\u53f7\u5165\u5ea7：<\/p>\n\n\u75db\u70b9\u7c7b\u578b\u5177\u4f53\u8868\u73b0\u540e\u679c<\/tr>\n\n\n\n\n
              \u6280\u672f\u9650\u5236<\/td>\n\u7528\u6237\u804a10\u8f6e\u5c31\u8d854k Token\u9650\u5236<\/td>\n\u65e9\u671fQA\u4fe1\u606f\u4e22\u5931，\u56de\u7b54\u9a74\u5507\u4e0d\u5bf9\u9a6c\u5634<\/td>\n<\/tr>\n
              \u6548\u7387\u74f6\u9888<\/td>\n\u5168\u91cf\u5b58\u5386\u53f2，\u68c0\u7d22\u4e00\u6b21\u8981600ms+<\/td>\n\u56de\u590d\u6162，\u7528\u6237\u5410\u69fd\u201c\u53cd\u5e94\u8fdf\u949d\u201d<\/td>\n<\/tr>\n
              \u4e1a\u52a1&\u5408\u89c4\u98ce\u9669<\/td>\n\u5b58\u7528\u6237\u624b\u673a\u53f7\u3001\u9700\u6c42\u7b49\u654f\u611f\u4fe1\u606f\u539f\u6587<\/td>\n\u6709\u6570\u636e\u6cc4\u9732\u98ce\u9669，\u8d28\u68c0\u6eaf\u6e90\u96be<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u4e09\u3001\u6838\u5fc3\u89e3\u51b3\u65b9\u6848：\u6458\u8981\u5b58\u50a8+LangChain\u5b9e\u6218<\/h3>\n

              \"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

              \u89e3\u51b3\u601d\u8def\u5f88\u7b80\u5355：\u7528ConversationSummaryMemory\u751f\u6210\u5bf9\u8bdd\u6458\u8981，\u53ea\u5b58\u6458\u8981\u4e0d\u5b58\u5168\u91cf\u5386\u53f2\u3002\u4f18\u52bf\u7279\u522b\u660e\u663e：<\/p>\n

              \u6838\u5fc3\u76ee\u6807<\/h4>\n

              \u901a\u8fc7\u6458\u8981\u5b58\u50a8\u7ef4\u62a4\u957f\u671f\u4e0a\u4e0b\u6587，\u89e3\u51b3\u201cToken\u4e0d\u591f\u7528\u3001\u8d44\u6e90\u6d88\u8017\u5927\u3001\u8fde\u8d2f\u6027\u5dee\u201d\u4e09\u5927\u95ee\u9898\u3002<\/p>\n

              \u6280\u672f\u539f\u7406<\/h4>\n

              \u5c31\u50cf\u6211\u8bb0\u7b14\u8bb0\u2014\u2014\u4e0d\u6284\u8001\u5e08\u6bcf\u53e5\u8bdd，\u53ea\u8bb0\u91cd\u70b9\u3002\u6a21\u578b\u4e5f\u4e00\u6837：\u7528\u5927\u6a21\u578b（\u5982\u901a\u4e49\u5343\u95ee）\u628a\u5bf9\u8bdd\u751f\u6210\u6458\u8981，\u540e\u7eed\u4ea4\u4e92\u53ea\u4f20\u6458\u8981，\u76f8\u5f53\u4e8e\u201c\u5e26\u7740\u7b14\u8bb0\u804a\u5929\u201d，\u800c\u975e\u201c\u5e26\u7740\u6574\u672c\u4e66\u804a\u5929\u201d\u3002<\/p>\n

              \u4f18\u52bf<\/h4>\n
            • \u7701Token：\u6458\u8981\u6bd4\u5168\u91cf\u5386\u53f2\u5c0f80%，\u518d\u4e5f\u4e0d\u62c5\u5fc3\u8d85\u9650\u5236；<\/li>\n
            • \u4fdd\u8fde\u8d2f：\u6458\u8981\u542b\u5173\u952e\u4fe1\u606f，\u6a21\u578b\u77e5\u9053\u4e4b\u524d\u804a\u4e86\u5565；<\/li>\n
            • \u6613\u6269\u5c55：\u53ef\u5b58\u5728MongoDB\u3001Milvus，\u652f\u6301\u591a\u7528\u6237\u3001\u5927\u6570\u636e\u91cf\u3002<\/li>\n

              \u56db\u3001\u5e26\u6458\u8981\u5b58\u50a8\u7684\u5bf9\u8bdd\u7cfb\u7edf<\/h3>\n

              \u5b9e\u6218\u51c6\u5907<\/h4>\n

              \u5148\u5b89\u88c5\u4f9d\u8d56：<\/p>\n

              pip install<\/span> langchain langchain-openai langchain-core pymilvus # \u6309\u9700\u88c5\u5b58\u50a8\u4f9d\u8d56<\/span><\/p>\n

              \u5b9e\u62181：\u57fa\u7840\u7248\u2014\u2014\u751f\u6210\u5bf9\u8bdd\u6458\u8981<\/h4>\n

              \u8fd9\u662f\u6700\u57fa\u7840\u7684\u7528\u6cd5，\u6211\u7528\u6765\u6d4b\u8bd5\u6458\u8981\u6548\u679c，\u770b\u770b\u6a21\u578b\u80fd\u4e0d\u80fd\u6293\u5173\u952e\u4fe1\u606f：<\/p>\n

              from<\/span> langchain.<\/span>memory import<\/span> ConversationSummaryMemory
              \nfrom<\/span> langchain_openai import<\/span> ChatOpenAI<\/p>\n

              # \u521d\u59cb\u5316\u5927\u6a21\u578b（\u5de5\u85e4\u7528\u7684\u901a\u4e49\u5343\u95ee，\u5927\u5bb6\u66ff\u6362\u81ea\u5df1\u7684api_key）<\/span>
              \nllm =<\/span> ChatOpenAI(<\/span>
              \n model_name=<\/span>"qwen-plus"<\/span>,<\/span>
              \n base_url=<\/span>"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1"<\/span>,<\/span>
              \n api_key=<\/span>"\u4f60\u7684api_key"<\/span>,<\/span> # \u5de5\u85e4\u63d0\u793a：\u522b\u786c\u7f16\u7801，\u653e\u73af\u5883\u53d8\u91cf\u91cc\u66f4\u5b89\u5168<\/span>
              \n temperature=<\/span>0.7<\/span> # \u6458\u8981\u4e0d\u7528\u592a\u6b7b\u677f，0.7\u521a\u597d<\/span>
              \n)<\/span><\/p>\n

              # \u521d\u59cb\u5316\u6458\u8981\u8bb0\u5fc6（\u6838\u5fc3\u7ec4\u4ef6）<\/span>
              \nmemory =<\/span> ConversationSummaryMemory(<\/span>llm=<\/span>llm)<\/span><\/p>\n

              # \u6a21\u62df\u6211\u548c\u7528\u6237\u7684\u5bf9\u8bdd（\u5de5\u85e4\u9879\u76ee\u91cc\u7684\u771f\u5b9e\u5bf9\u8bdd\u7247\u6bb5）<\/span>
              \nmemory.<\/span>save_context(<\/span>
              \n {<\/span>"input"<\/span>:<\/span> "\u5de5\u85e4，AI\u5927\u6a21\u578b\u600e\u4e48\u5165\u95e8？"<\/span>}<\/span>,<\/span>
              \n {<\/span>"output"<\/span>:<\/span> "\u5148\u5b66\u57fa\u7840\u6982\u5ff5，\u518d\u8c03\u7528API，\u7136\u540e\u5b66LangChain\u3001RAG，\u6700\u540e\u5b9e\u6218\u505a\u9879\u76ee"<\/span>}<\/span>
              \n)<\/span>
              \nmemory.<\/span>save_context(<\/span>
              \n {<\/span>"input"<\/span>:<\/span> "\u6709\u6ca1\u6709\u9002\u5408\u96f6\u57fa\u7840\u7684\u8bfe\u7a0b？"<\/span>}<\/span>,<\/span>
              \n {<\/span>"output"<\/span>:<\/span> "\u53ef\u4ee5\u770b\u6211\u7684\u96f6\u57fa\u7840\u5b66AI\u5927\u6a21\u578b\u7cfb\u5217，\u4eceAPI\u8c03\u7528\u8bb2\u5230Agent\u5b9e\u6218"<\/span>}<\/span>
              \n)<\/span><\/p>\n

              # \u53d6\u6458\u8981\u2014\u2014\u770b\u770b\u6548\u679c<\/span>
              \nsummary =<\/span> memory.<\/span>load_memory_variables(<\/span>{<\/span>}<\/span>)<\/span>
              \nprint<\/span>(<\/span>"\u5de5\u85e4\u9879\u76ee\u5b9e\u6218：\u5bf9\u8bdd\u6458\u8981"<\/span>)<\/span>
              \nprint<\/span>(<\/span>summary[<\/span>"history"<\/span>]<\/span>)<\/span> # \u8f93\u51fa\u6458\u8981，\u53ea\u5b58\u5173\u952e\u4fe1\u606f<\/span><\/p>\n

              # \u5de5\u85e4\u8fd0\u884c\u7ed3\u679c：<\/span>
              \n# \u7528\u6237\u8be2\u95eeAI\u5927\u6a21\u578b\u96f6\u57fa\u7840\u5165\u95e8\u65b9\u6cd5，\u52a9\u624b\u5efa\u8bae\u5148\u5b66\u57fa\u7840\u6982\u5ff5\u3001\u8c03\u7528API\u3001\u5b66LangChain\u548cRAG，\u518d\u5b9e\u6218；\u7528\u6237\u53c8\u95ee\u9002\u5408\u96f6\u57fa\u7840\u7684\u8bfe\u7a0b，\u52a9\u624b\u63a8\u8350\u81ea\u5df1\u7684\u96f6\u57fa\u7840\u5b66AI\u5927\u6a21\u578b\u7cfb\u5217\u3002<\/span><\/p>\n

              \u5b9e\u62182：\u8fdb\u9636\u7248\u2014\u2014\u5e26\u6458\u8981\u5b58\u50a8\u7684\u5bf9\u8bdd\u94fe<\/h4>\n

              \u8fd9\u662f\u6211\u73b0\u5728\u9879\u76ee\u91cc\u7528\u7684\u6838\u5fc3\u4ee3\u7801，\u7528LCEL\u94fe\u5f0f\u7ed3\u6784，\u652f\u6301\u591a\u8f6e\u5bf9\u8bdd，\u81ea\u52a8\u66f4\u6458\u8981，\u7279\u522b\u7a33\u5b9a：<\/p>\n

              from<\/span> langchain.<\/span>memory import<\/span> ConversationSummaryMemory
              \nfrom<\/span> langchain_openai import<\/span> ChatOpenAI
              \nfrom<\/span> langchain_core.<\/span>runnables import<\/span> RunnablePassthrough
              \nfrom<\/span> langchain_core.<\/span>output_parsers import<\/span> StrOutputParser
              \nfrom<\/span> langchain_core.<\/span>prompts import<\/span> ChatPromptTemplate<\/p>\n

              # 1. \u521d\u59cb\u5316\u5927\u6a21\u578b（\u548c\u6211\u4e4b\u524d\u7684Agent\u9879\u76ee\u7528\u7684\u4e00\u6837）<\/span>
              \nllm =<\/span> ChatOpenAI(<\/span>
              \n model_name=<\/span>"qwen-plus"<\/span>,<\/span>
              \n base_url=<\/span>"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1"<\/span>,<\/span>
              \n api_key=<\/span>"\u4f60\u7684api_key"<\/span>,<\/span>
              \n temperature=<\/span>0.7<\/span>
              \n)<\/span><\/p>\n

              # 2. \u521d\u59cb\u5316\u6458\u8981\u8bb0\u5fc6（memory_key\u8981\u548cprompt\u91cc\u7684\u53d8\u91cf\u540d\u4e00\u81f4！）<\/span>
              \nmemory =<\/span> ConversationSummaryMemory(<\/span>
              \n llm=<\/span>llm,<\/span>
              \n memory_key=<\/span>"chat_history"<\/span>,<\/span> # \u5de5\u85e4\u8e29\u5751：\u8fd9\u91cc\u548c\u4e0b\u9762prompt\u7684{chat_history}\u8981\u540c\u540d<\/span>
              \n return_messages=<\/span>True<\/span> # \u8fd4\u56de\u6d88\u606f\u5bf9\u8c61，\u66f4\u7075\u6d3b<\/span>
              \n)<\/span><\/p>\n

              # 3. \u5b9a\u4e49prompt\u2014\u2014\u5fc5\u987b\u5305\u542b\u6458\u8981\u53d8\u91cf（chat_history）<\/span>
              \nprompt =<\/span> ChatPromptTemplate.<\/span>from_messages(<\/span>[<\/span>
              \n (<\/span>"system"<\/span>,<\/span> "\u4f60\u662f\u5de5\u85e4\u5b66\u7f16\u7a0b\u7684AI\u52a9\u624b，\u57fa\u4e8e\u5bf9\u8bdd\u6458\u8981\u56de\u7b54\u95ee\u9898，\u8bed\u6c14\u4eb2\u5207\u50cf\u804a\u5929"<\/span>)<\/span>,<\/span>
              \n (<\/span>"human"<\/span>,<\/span> "\u5bf9\u8bdd\u6458\u8981：{chat_history}\\\\n\u7528\u6237\u73b0\u5728\u95ee：{input}"<\/span>)<\/span>
              \n]<\/span>)<\/span><\/p>\n

              # 4. \u6784\u5efaLCEL\u94fe（\u5de5\u85e4\u63a8\u8350\u7528\u8fd9\u4e2a，\u6bd4LLMChain\u7075\u6d3b）<\/span>
              \nchain =<\/span> (<\/span>
              \n # \u6ce8\u5165\u8f93\u5165\u548c\u8bb0\u5fc6\u6458\u8981<\/span>
              \n RunnablePassthrough.<\/span>assign(<\/span>
              \n chat_history=<\/span>lambda<\/span> _<\/span>:<\/span> memory.<\/span>load_memory_variables(<\/span>{<\/span>}<\/span>)<\/span>[<\/span>"chat_history"<\/span>]<\/span>
              \n )<\/span>
              \n |<\/span> prompt # \u683c\u5f0f\u5316prompt<\/span>
              \n |<\/span> llm # \u8c03\u7528\u5927\u6a21\u578b<\/span>
              \n |<\/span> StrOutputParser(<\/span>)<\/span> # \u89e3\u6790\u8f93\u51fa<\/span>
              \n)<\/span><\/p>\n

              # 5. \u6a21\u62df\u7528\u6237\u591a\u8f6e\u5bf9\u8bdd（\u5de5\u85e4\u9879\u76ee\u91cc\u7684\u771f\u5b9e\u7528\u6237\u63d0\u95ee）<\/span>
              \nuser_inputs =<\/span> [<\/span>
              \n "\u5de5\u85e4，\u600e\u4e48\u7528LangChain\u505a\u8bb0\u5fc6\u529f\u80fd？"<\/span>,<\/span>
              \n "\u4e4b\u524d\u8bf4\u7684ConversationSummaryMemory，\u80fd\u5b58\u591a\u5c11\u8f6e\u5bf9\u8bdd？"<\/span>,<\/span>
              \n "\u5b83\u548cMilvus\u7ed3\u5408\u7684\u8bdd，\u600e\u4e48\u5b58\u6458\u8981？"<\/span> # \u4f9d\u8d56\u4e0a\u4e00\u8f6e\u7684\u8bb0\u5fc6<\/span>
              \n]<\/span><\/p>\n

              # 6. \u8fd0\u884c\u5bf9\u8bdd（\u5de5\u85e4\u91cd\u70b9\u6ce8\u91ca：LCEL\u9700\u8981\u624b\u52a8\u4fdd\u5b58\u4e0a\u4e0b\u6587！）<\/span>
              \nfor<\/span> query in<\/span> user_inputs:<\/span>
              \n print<\/span>(<\/span>f"\\\\n\u7528\u6237：<\/span>{<\/span>query}<\/span><\/span>"<\/span><\/span>)<\/span>
              \n # \u8c03\u7528\u94fe\u83b7\u53d6\u56de\u590d<\/span>
              \n response =<\/span> chain.<\/span>invoke(<\/span>{<\/span>"input"<\/span>:<\/span> query}<\/span>)<\/span>
              \n print<\/span>(<\/span>f"\u5de5\u85e4\u52a9\u624b：<\/span>{<\/span>response}<\/span><\/span>"<\/span><\/span>)<\/span><\/p>\n

              # \u624b\u52a8\u4fdd\u5b58\u4e0a\u4e0b\u6587\u5230\u8bb0\u5fc6（LLMChain\u4f1a\u81ea\u52a8\u5b58，LCEL\u8981\u624b\u52a8！）<\/span>
              \n memory.<\/span>save_context(<\/span>{<\/span>"input"<\/span>:<\/span> query}<\/span>,<\/span> {<\/span>"output"<\/span>:<\/span> response}<\/span>)<\/span><\/p>\n

              # \u67e5\u770b\u5f53\u524d\u6458\u8981（\u5de5\u85e4\u8c03\u8bd5\u65f6\u5fc5\u770b，\u786e\u4fdd\u6458\u8981\u6b63\u786e）<\/span>
              \n current_summary =<\/span> memory.<\/span>load_memory_variables(<\/span>{<\/span>}<\/span>)<\/span>[<\/span>"chat_history"<\/span>]<\/span>
              \n print<\/span>(<\/span>f"\u5f53\u524d\u5bf9\u8bdd\u6458\u8981：<\/span>{<\/span>current_summary}<\/span><\/span>"<\/span><\/span>)<\/span><\/p>\n

              \u5de5\u85e4\u5b9e\u6218\u8f93\u51fa\u6548\u679c（\u771f\u5b9e\u8fd0\u884c\u7ed3\u679c）<\/h4>\n

              \u7528\u6237：\u5de5\u85e4，\u600e\u4e48\u7528LangChain\u505a\u8bb0\u5fc6\u529f\u80fd？
              \n\u5de5\u85e4\u52a9\u624b：\u53ef\u4ee5\u7528LangChain\u7684Memory\u6a21\u5757，\u6bd4\u5982ConversationBufferMemory\u5b58\u5b8c\u6574\u5386\u53f2，ConversationSummaryMemory\u5b58\u6458\u8981，\u9002\u5408\u957f\u5bf9\u8bdd…
              \n\u5f53\u524d\u5bf9\u8bdd\u6458\u8981： \u7528\u6237\u8be2\u95ee\u5982\u4f55\u7528LangChain\u505a\u8bb0\u5fc6\u529f\u80fd，\u52a9\u624b\u5efa\u8bae\u4f7f\u7528Memory\u6a21\u5757，\u4e3e\u4f8bConversationBufferMemory\u548cConversationSummaryMemory，\u540e\u8005\u9002\u5408\u957f\u5bf9\u8bdd\u3002<\/p>\n

              \u7528\u6237：\u4e4b\u524d\u8bf4\u7684ConversationSummaryMemory，\u80fd\u5b58\u591a\u5c11\u8f6e\u5bf9\u8bdd？
              \n\u5de5\u85e4\u52a9\u624b：\u5b83\u6ca1\u6709\u56fa\u5b9a\u8f6e\u6570\u9650\u5236，\u56e0\u4e3a\u5b58\u7684\u662f\u6458\u8981，\u4e0d\u662f\u5168\u91cf\u5bf9\u8bdd，\u54ea\u6015100\u8f6e，\u6458\u8981\u4e5f\u4e0d\u4f1a\u8d85\u592a\u591aToken…
              \n\u5f53\u524d\u5bf9\u8bdd\u6458\u8981： \u7528\u6237\u5148\u95eeLangChain\u8bb0\u5fc6\u529f\u80fd\u505a\u6cd5，\u52a9\u624b\u63a8\u8350Memory\u6a21\u5757\u53ca\u4e24\u4e2a\u5b50\u7c7b；\u63a5\u7740\u7528\u6237\u95eeConversationSummaryMemory\u80fd\u5b58\u591a\u5c11\u8f6e，\u52a9\u624b\u79f0\u65e0\u56fa\u5b9a\u9650\u5236，\u56e0\u5b58\u50a8\u7684\u662f\u6458\u8981\u3002<\/p>\n

              \u7528\u6237：\u5b83\u548cMilvus\u7ed3\u5408\u7684\u8bdd，\u600e\u4e48\u5b58\u6458\u8981？
              \n\u5de5\u85e4\u52a9\u624b：\u53ef\u4ee5\u628a\u751f\u6210\u7684\u6458\u8981\u8f6c\u6210\u5411\u91cf，\u7528LangChain\u7684VectorStoreRetrieverMemory，\u628a\u6458\u8981\u5b58\u5728Milvus\u91cc，\u9700\u8981\u65f6\u68c0\u7d22\u76f8\u5173\u6458\u8981…
              \n\u5f53\u524d\u5bf9\u8bdd\u6458\u8981： \u7528\u6237\u95eeConversationSummaryMemory\u4e0eMilvus\u7ed3\u5408\u7684\u5b58\u6458\u8981\u65b9\u6cd5，\u52a9\u624b\u5efa\u8bae\u5c06\u6458\u8981\u8f6c\u5411\u91cf，\u7528VectorStoreRetrieverMemory\u5b58\u5165Milvus，\u9700\u7528\u65f6\u68c0\u7d22\u3002<\/p>\n

              \u770b！\u5c31\u7b97\u804a\u591a\u8f6e，\u6a21\u578b\u4e5f\u4e0d\u4f1a\u201c\u5931\u5fc6\u201d，\u6458\u8981\u91cc\u5168\u662f\u5173\u952e\u4fe1\u606f，Token\u6d88\u8017\u7279\u522b\u5c11～<\/p>\n

              \u56db\u3001\u5173\u952e\u77e5\u8bc6\u70b9：LCEL\u548cLLMChain\u600e\u4e48\u9009？<\/h3>\n\n\u7279\u6027LCEL\u94feLLMChain<\/tr>\n\n\n\n\n\n
              \u8bb0\u5fc6\u4fdd\u5b58<\/td>\n\u9700\u624b\u52a8\u8c03\u7528memory.save_context()<\/td>\n\u81ea\u52a8\u4fdd\u5b58，\u4e0d\u7528\u624b\u52a8\u5199<\/td>\n<\/tr>\n
              \u94fe\u5f0f\u7075\u6d3b\u6027<\/td>\n\u9ad8，\u53ef\u52a0\u8def\u7531\u3001\u65e5\u5fd7（\u6211\u52a0\u4e86\u9519\u8bef\u6355\u83b7）<\/td>\n\u56fa\u5b9a\u7ed3\u6784，\u7075\u6d3b\u5ea6\u4f4e<\/td>\n<\/tr>\n
              \u8c03\u8bd5&\u6269\u5c55<\/td>\n\u53ef\u63d2\u4e2d\u95f4\u4ef6，\u9002\u5408\u590d\u6742\u9879\u76ee（\u5982\u591a\u5de5\u5177\u8c03\u7528）<\/td>\n\u9760verbose=True\u8c03\u8bd5，\u9002\u5408\u5165\u95e8<\/td>\n<\/tr>\n
              \u5de5\u85e4\u4f7f\u7528\u573a\u666f<\/td>\n\u667a\u80fd\u52a9\u624b\u3001Agent\u9879\u76ee（\u590d\u6742\u573a\u666f）<\/td>\n\u7b80\u5355\u5bf9\u8bdddemo（\u5feb\u901f\u9a8c\u8bc1\u60f3\u6cd5）<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u4e94\u3001\u907f\u5751\u6307\u5357<\/h3>\n
            • \u53d8\u91cf\u540d\u8981\u4e00\u81f4：memory_key（\u5982"chat_history"）\u5fc5\u987b\u548cprompt\u91cc\u7684\u53d8\u91cf\u540d\u4e00\u6837，\u4e0d\u7136\u4f1a\u62a5\u201c\u53d8\u91cf\u672a\u5b9a\u4e49\u201d；<\/li>\n
            • \u6458\u8981\u6a21\u677f\u53ef\u5b9a\u5236：\u60f3\u8ba9\u6458\u8981\u5305\u542b\u66f4\u591aQA\u7ec6\u8282，\u53ef\u6539prompt，\u6bd4\u5982\u52a0\u4e00\u53e5\u201c\u6458\u8981\u8981\u5305\u542b\u7528\u6237\u95ee\u9898\u548c\u52a9\u624b\u6838\u5fc3\u56de\u7b54\u201d；<\/li>\n
            • \u654f\u611f\u4fe1\u606f\u8fc7\u6ee4：\u4fdd\u5b58\u6458\u8981\u524d，\u7528\u6b63\u5219\u66ff\u6362\u624b\u673a\u53f7\u3001\u90ae\u7bb1，\u907f\u514d\u5408\u89c4\u98ce\u9669；<\/li>\n
            • \u5b58\u50a8\u6269\u5c55：\u91cf\u5927\u65f6，\u628a\u6458\u8981\u5b58Milvus，\u7528VectorStoreRetrieverMemory，\u68c0\u7d22\u66f4\u5feb（\u4e4b\u524d\u8bb2\u8fc7Milvus\u5b9e\u6218，\u53ef\u56de\u5934\u770b）\u3002<\/li>\n

              \u603b\u7ed3<\/h3>\n

              \u5176\u5b9e\u89e3\u51b3\u5927\u91cfQA\u3001\u957f\u5bf9\u8bdd\u5b58\u50a8\u95ee\u9898，\u6838\u5fc3\u5c31\u662f\u201c\u6293\u91cd\u70b9\u201d\u2014\u2014\u7528ConversationSummaryMemory\u751f\u6210\u6458\u8981，\u53ea\u5b58\u5173\u952e\u4fe1\u606f，\u518d\u6839\u636e\u9879\u76ee\u590d\u6742\u5ea6\u9009LCEL\u6216LLMChain\u3002<\/p>\n

              \u6709\u7591\u95ee\u6b22\u8fce\u5728\u8bc4\u8bba\u533a\u4ea4\u6d41，\u54b1\u4eec\u4e0b\u671f\u518d\u89c1！👋<\/p>\n","protected":false},"excerpt":{"rendered":"

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