\u8f6c\u8f7d\uff1a\u5c0f\u7ea2\u4e66 AI\u4ea7\u54c1\u8d75\u54e5<\/p>\n\n\n\n
\u57fa\u4e8e LangChain \u7684\u67e5\u8be2\u8def\u7531 + \u5b50\u95ee\u9898\u62c6\u89e3\uff0c\u544a\u522b \u201cNaive RAG\u201d<\/p>\n\n\n\n
\u524d\u8a00\ud83d\udd16<\/strong><\/p>\n\n\n\n \u4e0a\u4e00\u7bc7\u54b1\u804a\u4e86\u5411\u91cf\u6570\u636e\u5e93\u7684\u9009\u578b\uff0c\u6709\u670b\u53cb\u56de\u53bb\u628a\u81ea\u5df1\u516c\u53f8\u7684\u6587\u6863\u5207\u7247\u5b58\u8fdb FAISS \u6216 Chroma \u4e4b\u540e\uff0c\u9a6c\u4e0a\u5c31\u9047\u5230\u4e86\u65b0\u7684\u5c0f\u95ee\u9898\u3002<\/p>\n\n\n\n \u8fd9\u4e5f\u662f\u76ee\u524d AI \u4ea7\u54c1\u7ecf\u7406\u4e0a\u624b LangChain \u6700\u5e38\u89c1\u7684\u4e00\u4e2a\u73b0\u8c61\uff1a\u201cDemo \u731b\u5982\u864e\uff0c\u5b9e\u6218\u4e8c\u767e\u4e94\u201d\u3002<\/p>\n\n\n\n \u8fd9\u5c31\u662f \u6734\u7d20 RAG\uff08Naive RAG\uff09\u7684\u5c40\u9650\u6027\u3002\u5b83\u53ea\u662f\u7b80\u5355\u7c97\u66b4\u5730\u6839\u636e\u76f8\u4f3c\u5ea6\u68c0\u7d22\uff0c\u4e0d\u7ba1\u4f60\u7684\u95ee\u9898\u662f\u4ec0\u4e48\u7c7b\u578b\uff0c\u4e5f\u4e0d\u7ba1\u4f60\u7684\u6570\u636e\u6709\u591a\u5c11\u4e2a\u9886\u57df\u3002\u5b83\u628a\u6240\u6709\u6570\u636e\u6df7\u5728\u4e00\u4e2a\u5927\u6c60\u5b50\u91cc\u635e\u9488\u3002<\/p>\n\n\n\n \u4eca\u5929\u54b1\u4eec\u6765\u804a\u7684\u662f\u4f01\u4e1a\u7ea7 RAG \u5fc5\u987b\u8de8\u8d8a\u7684\u95e8\u69db\uff1aAdvanced RAG\uff08\u9ad8\u7ea7 RAG\uff09<\/strong>\u3002<\/p>\n\n\n\n \u6211\u4eec\u5c06\u5229\u7528 LangChain \u5f3a\u5927\u7684\u7f16\u6392\u80fd\u529b\uff0c\u5b9e\u73b0\u4e24\u4e2a\u6838\u5fc3\u903b\u8f91\uff1a\u67e5\u8be2\u8def\u7531\uff08Routing\uff09\u548c\u5b50\u95ee\u9898\u62c6\u89e3\uff08Query Decomposition\uff09<\/strong>\u3002<\/p>\n\n\n\n \u8fd9\u7bc7\u7b14\u8bb0\u7a0d\u5fae\u6709\u70b9\u6280\u672f\u8303\u513f\uff0c\u6d89\u53ca\u67b6\u6784\u903b\u8f91\uff0c\u4f46\u5927\u5bb6\u4e0d\u8981\u62c5\u5fc3\uff0c\u62d4\u62d4\u9ad8\uff0c\u624d\u80fd\u66f4\u5f3a\u5927\u3002\u51c6\u5907\u597d\u4e86\u5417\uff1f\u54b1\u8d70\u7740\uff01<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u75db\u70b9\uff1a\u4e3a\u4ec0\u4e48 \u201c\u5927\u4e00\u7edf\u201d \u7684\u68c0\u7d22\u884c\u4e0d\u901a\uff1f\ud83d\udd16<\/strong><\/p>\n\n\n\n \u5728\u4f01\u4e1a\u73af\u5883\u91cc\uff0c\u77e5\u8bc6\u5e93\u901a\u5e38\u662f\u5f02\u6784\u7684\u3002<\/p>\n\n\n\n \u5982\u679c\u4f60\u628a\u8fd9\u4e9b\u90fd\u6254\u8fdb\u540c\u4e00\u4e2a Vector Store\uff0c\u7528\u540c\u4e00\u4e2a Prompt \u53bb\u5904\u7406\uff0c\u7ed3\u679c\u5fc5\u7136\u662f\u707e\u96be\u6027\u7684\u3002<\/p>\n\n\n\n LangChain \u7684\u89e3\u51b3\u601d\u8def\u662f\uff1a\u5206\u800c\u6cbb\u4e4b\u3002\u6211\u4eec\u8981\u6784\u5efa\u4e00\u4e2a\u667a\u80fd\u8c03\u5ea6\u5c42\uff0c\u5728\u68c0\u7d22\u4e4b\u524d\uff0c\u5148\u8ba9 LLM \u601d\u8003\uff1a\u201c\u8fd9\u4e2a\u95ee\u9898\u8be5\u53bb\u54ea\u91cc\u67e5\uff1f\u8be5\u600e\u4e48\u67e5\uff1f\u201d<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u6838\u5fc3\u6280\u672f\u4e00\uff1a\u67e5\u8be2\u8def\u7531\uff08Query Routing\uff09\ud83d\udd16<\/strong><\/p>\n\n\n\n \u8def\u7531\u7684\u6838\u5fc3\u601d\u60f3\u662f\uff1a\u4e13\u5e93\u4e13\u7528<\/strong>\u3002\u4e0e\u5176\u5efa\u7acb\u4e00\u4e2a\u5305\u542b\u4e07\u7269\u7684\u5de8\u5927\u7d22\u5f15\uff0c\u4e0d\u5982\u5efa\u7acb\u591a\u4e2a\u5c0f\u800c\u7cbe\u7684\u7d22\u5f15\u3002<\/p>\n\n\n\n \u5f53\u7528\u6237\u63d0\u95ee\u65f6\uff0c\u6211\u4eec\u5148\u7ecf\u8fc7\u4e00\u4e2a Router\uff08\u8def\u7531\u5668\uff09\uff0c\u5224\u65ad\u610f\u56fe\uff0c\u7136\u540e\u628a\u95ee\u9898\u5206\u53d1\u7ed9\u5bf9\u5e94\u7684\u7d22\u5f15\u3002<\/p>\n\n\n\n \ud83d\udd391\uff0e\u903b\u8f91\u67b6\u6784<\/strong><\/p>\n\n\n\n \u7528\u6237\u7684 Query \u2192\u2192 LLM \u8def\u7531\u5c42\uff08\u5206\u7c7b\u5668\uff09\u2192\u2192 \u547d\u4e2d\u5177\u4f53\u7684 Retriever \u2192\u2192 \u83b7\u53d6 Context \u2192\u2192 \u751f\u6210\u7b54\u6848\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \ud83d\udd392\uff0eLangChain \u5b9e\u73b0\u4ee3\u7801\uff08\u5177\u8c61\u5316\uff09<\/strong><\/p>\n\n\n\n LangChain \u63d0\u4f9b\u4e86\u975e\u5e38\u4f18\u96c5\u7684\u8def\u7531\u5b9e\u73b0\u65b9\u5f0f\u3002\u5373\u4f7f\u662f\u4ea7\u54c1\u7ecf\u7406\uff0c\u770b\u61c2\u4e0b\u9762\u7684\u903b\u8f91\u4e5f\u4e0d\u96be\u3002\u6211\u4eec\u5229\u7528 LLM \u7684 Function Calling<\/strong> \u80fd\u529b\u6765\u505a\u7cbe\u51c6\u5206\u7c7b\u3002<\/p>\n\n\n\n \u4ea7\u54c1\u7ecf\u7406 Insight:<\/strong><\/p>\n\n\n\n \u5728 PRD \u4e2d\uff0c\u4f60\u9700\u8981\u5b9a\u4e49\u6e05\u695a \u201c\u8def\u7531\u89c4\u5219\u201d\u3002\u4e5f\u5c31\u662f\u4e0a\u9762\u4ee3\u7801\u4e2d description<\/strong> \u7684\u90e8\u5206\u3002\u8fd9\u90e8\u5206\u63cf\u8ff0\u5199\u5f97\u8d8a\u6e05\u695a\uff0cAI \u5206\u7c7b\u5c31\u8d8a\u51c6\u3002\u4e0d\u8981\u53ea\u4f9d\u8d56\u5f00\u53d1\u53bb\u5199\uff0c\u4f5c\u4e3a PM\uff0c\u4f60\u8981\u68b3\u7406\u4e1a\u52a1\u8fb9\u754c\uff0c\u544a\u8bc9\u5f00\u53d1\uff1a\u201c\u6d89\u53ca\u5230\u62a5\u9500\u7684\uff0c\u5168\u90e8\u5206\u7ed9\u8d22\u52a1\u5e93\uff1b\u6d89\u53ca\u5230\u5408\u540c\u7684\uff0c\u5168\u90e8\u5206\u7ed9\u6cd5\u52a1\u5e93\u201d\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u6838\u5fc3\u6280\u672f\u4e8c\uff1a\u5b50\u95ee\u9898\u62c6\u89e3\uff08Query Decomposition\uff09\ud83d\udd16<\/strong><\/p>\n\n\n\n \u8def\u7531\u89e3\u51b3\u4e86 \u201c\u53bb\u54ea\u67e5\u201d \u7684\u95ee\u9898\uff0c\u4f46\u5b83\u89e3\u51b3\u4e0d\u4e86\u590d\u6742\u67e5\u8be2\u7684\u95ee\u9898\u3002<\/p>\n\n\n\n \u573a\u666f\u63cf\u8ff0\uff1a<\/strong><\/p>\n\n\n\n \u7528\u6237\u95ee\uff1a\u201c\u6bd4\u8f83\u4e00\u4e0b LangChain \u548c LlamaIndex \u5728 RAG \u5b9e\u73b0\u4e0a\u7684\u533a\u522b\u3002\u201d<\/p>\n\n\n\n \u6734\u7d20 RAG \u7684\u505a\u6cd5\uff1a<\/strong><\/p>\n\n\n\n \u76f4\u63a5\u62ff\u6574\u53e5\u8bdd\u53bb\u5411\u91cf\u5e93\u641c\u3002\u5411\u91cf\u5e93\u53ef\u80fd\u4f1a\u641c\u5230\u4ecb\u7ecd LangChain \u7684\u6587\u6863\uff0c\u4e5f\u53ef\u80fd\u641c\u5230\u4ecb\u7ecd LlamaIndex \u7684\u6587\u6863\u3002\u4f46\u5f88\u5c11\u6709\u4e00\u7bc7\u6587\u6863\u662f\u4e13\u95e8\u5199\u8fd9\u4fe9\u533a\u522b\u7684\u3002<\/p>\n\n\n\n \u7ed3\u679c\u5c31\u662f\uff1a<\/strong><\/p>\n\n\n\n \u68c0\u7d22\u56de\u6765\u7684\u788e\u7247\u4fe1\u606f\u62fc\u51d1\u4e0d\u8d77\u6765\uff0c\u56de\u7b54\u4e0d\u4ec5\u7f3a\u80f3\u818a\u5c11\u817f\uff0c\u8fd8\u5bb9\u6613\u778e\u7f16\u3002<\/p>\n\n\n\n LangChain \u7684\u89e3\u51b3\u601d\u8def\uff1a<\/strong><\/p>\n\n\n\n \u628a\u4e00\u4e2a\u5927\u95ee\u9898\uff0c\u62c6\u89e3\u6210\u591a\u4e2a\u53ef\u4ee5\u72ec\u7acb\u68c0\u7d22\u7684\u5c0f\u95ee\u9898\u3002<\/p>\n\n\n\n \ud83d\udd391. \u903b\u8f91\u67b6\u6784<\/strong><\/p>\n\n\n\n \u7528\u6237 Query \u2192\u2192 LLM \u62c6\u89e3\u5c42 \u2192\u2192 \u751f\u6210\u5b50\u95ee\u9898\u5217\u8868 [Q1, Q2] \u2192\u2192 \u5206\u522b\u68c0\u7d22 \u2192\u2192 \u6c47\u603b Context \u2192\u2192 \u751f\u6210\u6700\u7ec8\u7b54\u6848\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \ud83d\udd392. LangChain \u5b9e\u73b0\u4ee3\u7801\uff08MultiQueryRetriever\uff09<\/strong><\/p>\n\n\n\n \u8fd9\u91cc\u6211\u4eec\u4e0d\u9700\u8981\u624b\u5199\u590d\u6742\u7684\u5faa\u73af\uff0cLangChain \u6709\u4e00\u4e2a\u73b0\u6210\u7684\u7ec4\u4ef6\u53eb MultiQueryRetriever\uff0c\u4f46\u4e3a\u4e86\u8ba9\u5927\u5bb6\u770b\u61c2\u903b\u8f91\uff0c\u6211\u5c55\u793a\u4e00\u4e0b\u6838\u5fc3\u7684 Prompt \u9a71\u52a8\u62c6\u89e3\u8fc7\u7a0b\u3002<\/p>\n\n\n\n \u62ff\u5230\u8fd9\u4e2a\u5217\u8868\u540e\uff0c\u4ee3\u7801\u4f1a\u904d\u5386\u8fd9\u4e2a\u5217\u8868\uff0c\u5206\u522b\u53bb\u5411\u91cf\u5e93\u68c0\u7d22\uff0c\u628a\u627e\u56de\u6765\u7684 6 \u6bb5\u8bdd\uff08\u5047\u8bbe\u6bcf\u4e2a\u95ee\u9898\u627e 3 \u6bb5\uff09\u62fc\u5728\u4e00\u8d77\uff0c\u6700\u540e\u6254\u7ed9 llm \u8bf4\uff1a\u201c\u57fa\u4e8e\u4ee5\u4e0a\u4fe1\u606f\uff0c\u56de\u7b54\u7528\u6237\u5173\u4e8e\u4e24\u8005\u6bd4\u8f83\u7684\u95ee\u9898\u3002\u201d<\/p>\n\n\n\n \u4ea7\u54c1\u7ecf\u7406 Insight\uff1a<\/strong><\/p>\n\n\n\n \u5982\u679c\u4f60\u7684\u4ea7\u54c1\u6d89\u53ca\u5bf9\u6bd4\u5206\u6790\u3001\u591a\u6b65\u63a8\u7406\u3001\u957f\u6587\u603b\u7ed3\uff0c\u4e00\u5b9a\u8981\u5728\u6280\u672f\u65b9\u6848\u4e2d\u8981\u6c42\u52a0\u4e0a Decomposition \u7b56\u7565\u3002\u5426\u5219\uff0c\u9762\u5bf9\u590d\u6742\u95ee\u9898\uff0c\u4f60\u7684 AI \u9664\u4e86\u4f1a\u8bf4 \u201c\u62b1\u6b49\u6211\u4e0d\u77e5\u9053\u201d\uff0c\u5c31\u662f\u5728\u4e00\u672c\u6b63\u7ecf\u5730\u80e1\u8bf4\u516b\u9053\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u8fdb\u9636\u4e00\u4e0b\u5b50\uff1a\u81ea\u67e5\u8be2\u68c0\u7d22\u5668\uff08Self-Querying\uff09\ud83d\udd16<\/strong><\/p>\n\n\n\n \u9664\u4e86\u8def\u7531\u548c\u62c6\u89e3\uff0c\u8fd8\u6709\u4e00\u4e2a\u975e\u5e38\u9ad8\u9891\u7684\u573a\u666f\uff1a\u7ed3\u6784\u5316\u8fc7\u6ee4\u3002<\/p>\n\n\n\n \u573a\u666f\u63cf\u8ff0\uff1a<\/strong><\/p>\n\n\n\n \u7528\u6237\u95ee\uff1a\u201c\u627e\u4e00\u4e0b 2023 \u5e74\u7684\u8001\u738b\u5199\u7684\u5173\u4e8e AI \u7684\u6587\u7ae0\u3002\u201d<\/p>\n\n\n\n \u6734\u7d20 RAG\uff1a<\/strong><\/p>\n\n\n\n \u5411\u91cf\u641c\u7d22\u662f\u57fa\u4e8e\u8bed\u4e49\u7684\u3002\u5b83\u4f1a\u53bb\u5e93\u91cc\u627e\u548c \u201c2023 \u5e74\u201d\u3001\u201c\u8001\u738b\u201d \u8bed\u4e49\u76f8\u8fd1\u7684\u8bcd\u3002\u4f46\u5b9e\u9645\u4e0a\uff0c\u8fd9\u91cc\u7684 \u201c2023 \u5e74\u201d \u548c \u201c\u8001\u738b\u201d \u4e0d\u5e94\u8be5\u53c2\u4e0e\u5411\u91cf\u8ba1\u7b97\uff0c\u5b83\u4eec\u5e94\u8be5\u662f\u8fc7\u6ee4\u5668\uff08Filter\uff09\u3002<\/p>\n\n\n\n \u6b63\u786e\u7684 SQL \u903b\u8f91\u5e94\u8be5\u662f\uff1a<\/p>\n\n\n\n SELECT * FROM docs WHERE year=2023 AND author=’ \u8001\u738b ‘ AND semantic_match (‘AI’)\u3002<\/p>\n\n\n\n LangChain \u7684 SelfQueryRetriever\uff1a<\/strong><\/p>\n\n\n\n \u5b83\u80fd\u81ea\u52a8\u628a\u81ea\u7136\u8bed\u8a00\u628a\u5176\u4e2d\u7684 Metadata\uff08\u5143\u6570\u636e\uff09\u5265\u79bb\u51fa\u6765\u3002<\/p>\n\n\n\n \u8fd9\u5bf9\u5bf9\u4e8e\u5408\u540c\u68c0\u7d22\uff08\u6309\u91d1\u989d\u3001\u6309\u7b7e\u7f72\u65e5\u671f\uff09\u3001\u7b80\u5386\u5e93\uff08\u6309\u5b66\u5386\u3001\u6309\u5de5\u4f5c\u5e74\u9650\uff09\u7b49\u573a\u666f\u662f\u521a\u9700\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u4f01\u4e1a\u7ea7 RAG \u7684\u5b8c\u6574\u5f62\u6001\ud83d\udd16<\/strong><\/p>\n\n\n\n \u628a\u4e0a\u9762\u8bb2\u7684\u7ed3\u5408\u8d77\u6765\uff0c\u4e00\u4e2a\u80fd\u5728\u751f\u4ea7\u73af\u5883 \u201c\u8010\u6495\u201d \u7684 RAG \u7cfb\u7edf\uff0c\u5b83\u7684\u6570\u636e\u6d41\u8f6c\u5e94\u8be5\u662f\u8fd9\u6837\u7684\uff1a<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u843d\u5730\u5b9e\u6218\u4e2d\u7684 3 \u4e2a\u5751\ud83d\udd16<\/strong><\/p>\n\n\n\n \u4f5c\u4e3a\u4ea7\u54c1\u7ecf\u7406\uff0c\u5728\u63a8\u884c\u8fd9\u79cd\u9ad8\u7ea7\u67b6\u6784\u65f6\uff0c\u8981\u6ce8\u610f\u4ee5\u4e0b\u4ee3\u4ef7\uff1a<\/p>\n\n\n\n \ud83d\udd391\uff0e\u5ef6\u8fdf\uff08Latency\uff09\u7684\u589e\u52a0<\/strong><\/p>\n\n\n\n \u5751\u70b9\uff1a\u6734\u7d20 RAG \u53ea\u9700\u8981\u8bf7\u6c42\u4e00\u6b21 Embedding\uff0c\u67e5\u4e00\u6b21\u5e93\uff0c\u8bf7\u6c42\u4e00\u6b21 LLM\u3002\u901f\u5ea6\u5f88\u5feb\u3002\u9ad8\u7ea7 RAG\uff08\u8def\u7531 + \u62c6\u89e3\uff09\u53ef\u80fd\u9700\u8981\u8bf7\u6c42 3-4 \u6b21 LLM \u624d\u80fd\u751f\u6210\u7b54\u6848\u3002<\/p>\n\n\n\n \u89e3\u51b3\u65b9\u6848\uff1a\u5fc5\u987b\u4e0a\u6d41\u5f0f\u8f93\u51fa\uff08Streaming\uff09\u3002\u5728\u540e\u53f0\u8fdb\u884c\u62c6\u89e3\u548c\u68c0\u7d22\u65f6\uff0c\u524d\u7aef\u8981\u5c55\u793a \u201c\u6b63\u5728\u601d\u8003\u62c6\u89e3\u6b65\u9aa4\u2026\u2026\u201d\u3001\u201c\u6b63\u5728\u68c0\u7d22\u6280\u672f\u6587\u6863\u5e93\u2026\u2026\u201d\uff0c\u7f13\u89e3\u7528\u6237\u7126\u8651\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \ud83d\udd392\uff0eToken \u6210\u672c\u7684\u6fc0\u589e<\/strong><\/p>\n\n\n\n \u5751\u70b9\uff1a\u6bcf\u6b21\u62c6\u89e3\u3001\u6bcf\u6b21\u8def\u7531\uff0c\u90fd\u662f\u5728\u6d88\u8017 Token\u3002\u7279\u522b\u662f MultiQuery\uff0c\u628a\u4e00\u4e2a\u95ee\u9898\u62c6\u6210 3 \u4e2a\uff0c\u610f\u5473\u7740\u4f60\u8981\u505a 3 \u6b21\u68c0\u7d22\uff0c\u4e0a\u4e0b\u6587\u957f\u5ea6\u53ef\u80fd\u4f1a\u7ffb 3 \u500d\u3002<\/p>\n\n\n\n \u89e3\u51b3\u65b9\u6848\uff1a\u8def\u7531\u548c\u62c6\u89e3\u5c42\uff0c\u5c3d\u91cf\u4f7f\u7528\u4fbf\u5b9c\u7684\u5c0f\u6a21\u578b\uff08\u5982 gpt-4.1-nano\uff09\uff0c\u53ea\u6709\u6700\u540e\u7684\u751f\u6210\u5c42\u624d\u7528 GPT-5\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \ud83d\udd393\uff0e\u9519\u8bef\u7684\u8def\u7531\u6bd4\u4e0d\u8def\u7531\u66f4\u53ef\u6015<\/strong><\/p>\n\n\n\n \u5751\u70b9\uff1a\u5982\u679c Router \u628a\u4e00\u4e2a \u201c\u6280\u672f\u95ee\u9898\u201d \u9519\u8bef\u5730\u5206\u5230\u4e86 \u201cHR \u5e93\u201d\uff0c\u90a3\u7ed3\u679c\u5c31\u662f 0 \u5206\u3002<\/p>\n\n\n\n \u89e3\u51b3\u65b9\u6848\uff1a\u8bbe\u7f6e\u515c\u5e95\u94fe\uff08Default Chain\uff09\u3002\u5982\u679c Router \u89c9\u5f97\u8fd9\u95ee\u9898\u65e2\u4e0d\u50cf HR \u4e5f\u4e0d\u50cf\u6280\u672f\uff0c\u6216\u8005\u7f6e\u4fe1\u5ea6\u4f4e\uff0c\u5c31\u53bb\u67e5\u4e00\u4e2a\u901a\u7528\u7684\u5927\u7d22\u5f15\uff0c\u6216\u8005\u76f4\u63a5\u5229\u7528 LLM \u81ea\u8eab\u7684\u77e5\u8bc6\u5e93\u56de\u7b54\uff0c\u5e76\u6807\u6ce8 \u201c\u672a\u68c0\u7d22\u5230\u5185\u90e8\u6587\u6863\uff0c\u4ee5\u4e0b\u57fa\u4e8e\u901a\u7528\u77e5\u8bc6\u56de\u7b54\u201d\u3002<\/p>\n\n\n\n \u3000\u3000<\/p>\n\n\n\n \u6765\uff0c\u54b1\u4eec\u603b\u7ed3\u4e00\u4e0b\u5427\ud83d\udd16<\/strong><\/p>\n\n\n\n \u8fd9\u7bc7\u7b14\u8bb0\u7684\u6838\u5fc3\u5176\u5b9e\u5c31\u4e00\u53e5\u8bdd\uff1a\u4e0d\u8981\u8ba9 LLM \u50bb\u50bb\u5730\u53bb\u68c0\u7d22\uff0c\u8981\u5148\u8ba9\u5b83 \u201c\u601d\u8003\u201d \u4e00\u4e0b\u68c0\u7d22\u7b56\u7565\u3002<\/p>\n\n\n\n \u5f53\u4f60\u80fd\u8ddf\u5f00\u53d1\u56e2\u961f\u804a\u51fa\uff1a\u201c\u8fd9\u4e2a\u573a\u666f\u6211\u4eec\u9700\u8981\u52a0\u4e00\u4e2a Router Chain\uff0c\u7528 Function Calling \u505a\u5206\u7c7b\uff0c\u7136\u540e\u9488\u5bf9\u590d\u6742 Case \u4e0a\u4e00\u4e2a MultiQuery Retriever\u201d \u65f6\uff0c\u4f60\u5728\u56e2\u961f\u91cc\u7684\u6280\u672f\u8bdd\u8bed\u6743\u5c31\u7acb\u4f4f\u4e86\u3002<\/p>\n\n\n\n LangChain \u6700\u5f3a\u5927\u7684\u5730\u65b9\uff0c\u4e0d\u4ec5\u4ec5\u662f\u5b83\u5c01\u88c5\u4e86 API\uff0c\u800c\u662f\u5b83\u5c01\u88c5\u4e86\u8fd9\u4e9b Cognitive Architectures\uff08\u8ba4\u77e5\u67b6\u6784\uff09\u3002\u5b83\u8ba9\u5f00\u53d1\u4eba\u5458\u80fd\u591f\u50cf\u642d\u79ef\u6728\u4e00\u6837\uff0c\u628a\u8fd9\u4e9b\u9ad8\u7ea7\u7684\u63a8\u7406\u6a21\u5f0f\u7ec4\u88c5\u8fdb\u4ea7\u54c1\u91cc\u3002<\/p>\n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" \u8f6c\u8f7d\uff1a\u5c0f\u7ea2\u4e66 AI\u4ea7\u54c1\u8d75\u54e5 \u57fa\u4e8e LangChain \u7684\u67e5\u8be2\u8def\u7531 + \u5b50\u95ee\u9898\u62c6\u89e3\uff0c\u544a\u522b \u201cNaive RAG\u201d […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[48],"tags":[],"_links":{"self":[{"href":"https:\/\/92it.top\/index.php?rest_route=\/wp\/v2\/posts\/20281"}],"collection":[{"href":"https:\/\/92it.top\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/92it.top\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/92it.top\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/92it.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=20281"}],"version-history":[{"count":7,"href":"https:\/\/92it.top\/index.php?rest_route=\/wp\/v2\/posts\/20281\/revisions"}],"predecessor-version":[{"id":20352,"href":"https:\/\/92it.top\/index.php?rest_route=\/wp\/v2\/posts\/20281\/revisions\/20352"}],"wp:attachment":[{"href":"https:\/\/92it.top\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=20281"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/92it.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=20281"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/92it.top\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=20281"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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from typing import Literal\nfrom langchain_core.pydantic_v1 import BaseModel, Field\n\nfrom langchain_openai import ChatOpenAI\nfrom langchain_core.prompts import ChatPromptTemplate\n\n# 1. \u5b9a\u4e49\u8def\u7531\u7684\u6570\u636e\u7ed3\u6784\n# \u6211\u4eec\u544a\u8bc9 LLM\uff0c\u4f60\u5fc5\u987b\u4ece \"technical\" \u6216 \"hr\" \u4e2d\u9009\u4e00\u4e2a\nclass RouteQuery(BaseModel):\n \"\"\"\u6839\u636e\u7528\u6237\u7684\u95ee\u9898\uff0c\u5c06\u67e5\u8be2\u8def\u7531\u5230\u5408\u9002\u7684\u6570\u636e\u6e90\u3002\"\"\"\n datasource: Literal[\"technical\", \"hr\"] = Field(\n ...,\n description=\"\u5982\u679c\u662f\u6280\u672f\u95ee\u9898\u3001\u4ee3\u7801\u95ee\u9898\uff0c\u9009 technical\uff1b\u5982\u679c\u662f\u8bf7\u5047\u3001\u798f\u5229\u3001\u5165\u804c\u95ee\u9898\uff0c\u9009 hr\"\n )\n\n# 2. \u521d\u59cb\u5316\u5f3a\u529b\u6a21\u578b\uff08\u5efa\u8bae GPT-5 \u6216 GPT-4\uff09\nllm = ChatOpenAI(model=\"gpt-4\", temperature=0)\n\n# 3. \u7ed1\u5b9a\u5de5\u5177\uff08\u8ba9\u6a21\u578b\u5f3a\u5236\u8f93\u51fa\u7ed3\u6784\u5316\u5206\u7c7b\uff09\nstructured_llm_router = llm.with_structured_output(RouteQuery)\n\n# 4. \u5b9a\u4e49\u8def\u7531\u63d0\u793a\u8bcd\nsystem = \"\"\"\u4f60\u662f\u4e00\u4e2a\u4e13\u4e1a\u7684\u5206\u7c7b\u5458\u3002\u4f60\u7684\u4efb\u52a1\u662f\u5c06\u7528\u6237\u7684\u95ee\u9898\u8def\u7531\u5230\u6b63\u786e\u7684\u6570\u636e\u6e90\u3002\n\u4e0d\u8981\u56de\u7b54\u95ee\u9898\uff0c\u53ea\u8d1f\u8d23\u5206\u7c7b\u3002\"\"\"\nroute_prompt = ChatPromptTemplate.from_messages(\n [\n (\"system\", system),\n (\"human\", \"{question}\"),\n ]\n)\n\n# 5. \u6784\u5efa\u8def\u7531\u94fe\nrouter_chain = route_prompt | structured_llm_router\n\n--- \u6d4b\u8bd5\u6548\u679c ---\nCase A\nprint (router_chain.invoke ({\"question\": \"\u600e\u4e48\u5b89\u88c5 Python \u73af\u5883\uff1f\"}))\n\u8f93\u51fa: datasource='technical'\nCase B\nprint (router_chain.invoke ({\"question\": \"\u5e74\u5047\u6ca1\u4f11\u5b8c\u53ef\u4ee5\u6298\u73b0\u5417\uff1f\"}))\n\u8f93\u51fa: datasource='hr'<\/pre>\n\n\n\n
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from langchain_core.output_parsers import StrOutputParser\n\n# 1. \u5b9a\u4e49\u62c6\u89e3 Prompt\n# \u8fd9\u91cc\u7684\u6838\u5fc3\u6280\u5de7\u662f Few-Shot (\u5c11\u6837\u672c)\uff0c\u7ed9 AI \u51e0\u4e2a\u62c6\u89e3\u7684\u4f8b\u5b50\ntemplate = \"\"\"\u4f60\u662f\u4e00\u4e2a\u667a\u80fd\u52a9\u624b\u3002\u4f60\u7684\u4efb\u52a1\u662f\u6839\u636e\u7528\u6237\u7684\u95ee\u9898\uff0c\u751f\u6210\n\u901a\u5e38\u539f\u672c\u7684\u95ee\u9898\u592a\u590d\u6742\uff0c\u65e0\u6cd5\u76f4\u63a5\u68c0\u7d22\u3002\u8bf7\u628a\u5b83\u4eec\u62c6\u89e3\u6210\u66f4\u7b80\u5355\u7684\u95ee\u9898\u3002\n\u8bf7\u6bcf\u884c\u8f93\u51fa\u4e00\u4e2a\u5b50\u95ee\u9898\u3002\n\n\u793a\u4f8b 1\uff1a\n\u8f93\u5165\uff1a\u6bd4\u8f83 iPhone 15 \u548c \u534e\u4e3a Mate 60 \u7684\u5c4f\u5e55\u53c2\u6570\u3002\n\u8f93\u51fa\uff1a\niPhone 15 \u5c4f\u5e55\u53c2\u6570\u662f\u4ec0\u4e48\uff1f\n\u534e\u4e3a Mate 60 \u5c4f\u5e55\u53c2\u6570\u662f\u4ec0\u4e48\uff1f\n\n\u793a\u4f8b 2\uff1a\n\u8f93\u5165\uff1a{question}\n\u8f93\u51fa\uff1a\n\"\"\"\n\nprompt_decomposition = ChatPromptTemplate.from_template(\n\n# 2. \u6784\u5efa\u62c6\u89e3\u94fe\n# \u6a21\u578b -> \u89e3\u6790\u6210\u591a\u884c\u6587\u672c -> \u8f6c\u6362\u6210\u5217\u8868\ngenerate_queries_chain = (\n prompt_decomposition\n | ChatOpenAI(temperature=0)\n | StrOutputParser()\n | (lambda x: x.split(\"\\n\"))\n)\n\n# --- \u6d4b\u8bd5\u6548\u679c ---\nuser_question = \"LangChain \u548c Semantic Kernel \u54ea\u4e2a\u66f4\u9002\u5408\"\nsub_questions = generate_queries_chain.invoke({\"question\"\n\nprint(sub_questions)\n# \u8f93\u51fa\u7ed3\u679c\u5c06\u662f\u4e00\u4e2a\u5217\u8868:\n# [\n# \"LangChain \u5bf9 Java \u5f00\u53d1\u7684\u652f\u6301\u60c5\u51b5\u5982\u4f55?\",\n# \"Semantic Kernel \u5bf9 Java \u5f00\u53d1\u7684\u652f\u6301\u60c5\u51b5\u5982\u4f55?\"\n# ]\n<\/pre>\n\n\n\n
\n\n\n\n\u4f2a\u4ee3\u7801\u903b\u8f91\u5c55\u793a\nmetadata_field_info = [AttributeInfo (name=\"author\", description=\"\u6587\u6863\u7684\u4f5c\u8005\"),AttributeInfo (name=\"year\", description=\"\u6587\u6863\u53d1\u5e03\u7684\u5e74\u4efd\")]\n\n\u5f53\u7528\u6237\u95ee\uff1a\u627e\u4e00\u4e0b 2023 \u5e74\u8001\u738b\u7684\u6587\u7ae0\nSelfQueryRetriever \u4f1a\u81ea\u52a8\u5c06\u5176\u8f6c\u5316\u4e3a:\nfilter = {\n\"author\": {\"$eq\": \"\u8001\u738b\"},\n\"year\": { \"$eq\": 2023 }\n}\nquery = \"AI \u6587\u7ae0\"<\/pre>\n\n\n\n
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