{"id":49932,"date":"2025-07-30T20:37:07","date_gmt":"2025-07-30T12:37:07","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/49932.html"},"modified":"2025-07-30T20:37:07","modified_gmt":"2025-07-30T12:37:07","slug":"%e4%b8%80%e6%96%87%e8%af%bb%e6%87%82lightrag%ef%bc%9a%e4%b8%93%e4%b8%ba%e4%b8%ad%e5%b0%8f%e4%bc%81%e4%b8%9a%e6%89%93%e9%80%a0%e7%9a%84%e8%bd%bb%e9%87%8f%e7%ba%a7rag%e8%a7%a3%e5%86%b3%e6%96%b9%e6%a1%88","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/49932.html","title":{"rendered":"\u4e00\u6587\u8bfb\u61c2LightRAG\uff1a\u4e13\u4e3a\u4e2d\u5c0f\u4f01\u4e1a\u6253\u9020\u7684\u8f7b\u91cf\u7ea7RAG\u89e3\u51b3\u65b9\u6848"},"content":{"rendered":"<p>\u5728\u5927\u6a21\u578b\u98de\u901f\u53d1\u5c55\u7684\u5f53\u4e0b&#xff0c;RAG&#xff08;Retrieval-Augmented Generation&#xff09;\u5df2\u7ecf\u6210\u4e3a\u8bb8\u591aAI\u7cfb\u7edf\u7684\u6807\u914d\u201c\u5916\u6302\u5927\u8111\u201d\u3002\u5b83\u8ba9\u6a21\u578b\u4e0d\u518d\u201c\u6b7b\u8bb0\u786c\u80cc\u201d&#xff0c;\u800c\u662f\u80fd\u201c\u67e5\u8d44\u6599\u518d\u7b54\u9898\u201d&#xff0c;\u6781\u5927\u5730\u63d0\u5347\u4e86\u751f\u6210\u51c6\u786e\u6027\u548c\u65f6\u6548\u6027\u3002<\/p>\n<p>\u4f46&#xff01;<br \/>\n\u4f20\u7edf\u7684RAG\u67b6\u6784\u52a8\u8f84\u8981\u51e0\u767eGB\u7684\u77e5\u8bc6\u5e93\u3001\u6210\u5806\u7684GPU\u8d44\u6e90\u3001\u590d\u6742\u7684\u94fe\u8def\u8bbe\u8ba1&#xff0c;\u5bf9\u5f88\u591a\u4e2d\u5c0f\u4f01\u4e1a\u3001\u4e2a\u4eba\u5f00\u53d1\u8005\u6765\u8bf4&#xff1a;\u201c\u4e0d\u662f\u4e0d\u80fd\u7528&#xff0c;\u662f\u7528\u4e0d\u8d77\u3002\u201d<\/p>\n<p>\u4e8e\u662f&#xff0c;LightRAG\u6765\u4e86\u3002<br \/>\n\u5b83\u5c31\u50cf\u662fRAG\u7684\u201c\u7cbe\u7b80\u7248\u201d\u4eb2\u5144\u5f1f&#xff0c;\u4e3b\u6253\u8f7b\u91cf\u3001\u5feb\u901f\u3001\u6613\u90e8\u7f72&#xff0c;\u8ba9\u66f4\u591a\u4eba\u4e5f\u80fd\u62e5\u6709\u5c5e\u4e8e\u81ea\u5df1\u7684\u667a\u80fd\u95ee\u7b54\u7cfb\u7edf\u3002<\/p>\n<p>\u4eca\u5929\u6211\u4eec\u5c31\u4e00\u8d77\u6765\u62c6\u89e3\u4e00\u4e0b\u2014\u2014<br \/>\nLightRAG\u5230\u5e95\u662f\u4ec0\u4e48&#xff1f;\u80fd\u505a\u4ec0\u4e48&#xff1f;\u600e\u4e48\u7528&#xff1f;\u672a\u6765\u53c8\u80fd\u8d70\u5230\u54ea&#xff1f;<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/07\/20250730123657-688a11e922d49.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h2>\u4e00\u3001\u4ec0\u4e48\u662fLightRAG&#xff1f;<\/h2>\n<p>\u6211\u4eec\u5148\u590d\u4e60\u4e00\u4e0b\u5927\u54e5 RAG \u7684\u6982\u5ff5&#xff1a;<\/p>\n<p>RAG &#061; \u201c\u68c0\u7d22 &#043; \u751f\u6210\u201d\u67b6\u6784\u3002<br \/>\n\u6a21\u578b\u5728\u56de\u7b54\u95ee\u9898\u65f6&#xff0c;\u5148\u4ece\u77e5\u8bc6\u5e93\u4e2d\u68c0\u7d22\u51fa\u76f8\u5173\u5185\u5bb9&#xff0c;\u7136\u540e\u518d\u751f\u6210\u56de\u7b54\u3002<\/p>\n<p>\u800c LightRAG&#xff08;Lightweight Retrieval-Augmented Generation&#xff09;&#xff0c;\u5219\u662f\u5728\u4fdd\u7559RAG\u6838\u5fc3\u4f18\u52bf\u7684\u57fa\u7840\u4e0a&#xff1a;<\/p>\n<li>\n<p>\u7cbe\u7b80\u6a21\u578b\u4f53\u79ef<\/p>\n<\/li>\n<li>\n<p>\u964d\u4f4e\u786c\u4ef6\u4f9d\u8d56<\/p>\n<\/li>\n<li>\n<p>\u7b80\u5316\u90e8\u7f72\u6d41\u7a0b<\/p>\n<\/li>\n<li>\n<p>\u63d0\u4f9b\u5f00\u7bb1\u5373\u7528\u7684\u7ec4\u4ef6\u7ec4\u5408<\/p>\n<\/li>\n<p>\u4f60\u53ef\u4ee5\u7406\u89e3\u4e3a\u5b83\u662f\u300cRAG \u7684\u8f7b\u88c5\u65c5\u884c\u7248\u300d&#xff0c;\u4f46\u4f9d\u7136\u80fd\u641e\u5b9a\u65e5\u5e38\u5927\u591a\u6570\u5e94\u7528\u573a\u666f\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/07\/20250730123657-688a11e9c1184.png\" alt=\"LightRAG: Retrieval-Augmented Generation with Graph-Based Insights | by  Sahin Ahmed, Data Scientist | Medium\" \/><\/p>\n<h2>\u4e8c\u3001\u54ea\u91cc\u53ef\u4ee5\u7528LightRAG&#xff1f;<\/h2>\n<p>\u867d\u7136LightRAG\u662f\u201c\u8f7b\u91cf\u7ea7\u201d\u7684&#xff0c;\u4f46\u5b83\u53ef\u4e00\u70b9\u90fd\u4e0d\u201c\u8f7b\u6d6e\u201d\u3002\u4ee5\u4e0b\u8fd9\u4e9b\u771f\u5b9e\u573a\u666f&#xff0c;\u90fd\u80fd\u7528\u5b83\u641e\u5b9a&#xff1a;<\/p>\n<h4>1. \u4f01\u4e1a\u77e5\u8bc6\u5e93\u95ee\u7b54<\/h4>\n<p>\u4e0a\u4f20\u516c\u53f8\u624b\u518c\u3001\u6d41\u7a0bPDF&#xff0c;LightRAG \u53ef\u56de\u7b54\u201c\u8bf7\u95ee\u8bf7\u5047\u6d41\u7a0b\u600e\u4e48\u8d70&#xff1f;\u201d\u3001\u201c\u67d0\u5c97\u4f4d\u7684KPI\u662f\u4ec0\u4e48&#xff1f;\u201d<\/p>\n<h4>2.\u533b\u7597\u6587\u732e\u67e5\u8be2\u52a9\u624b<\/h4>\n<p>\u5bfc\u5165\u4e34\u5e8a\u6307\u5357\u6216\u533b\u5b66\u6587\u732e&#xff0c;\u533b\u751f\u53ef\u76f4\u63a5\u95ee\u201c\u67d0\u75c5\u75c7\u7684\u4e00\u7ebf\u6cbb\u7597\u65b9\u6cd5\u6709\u54ea\u4e9b&#xff1f;\u201d<\/p>\n<h4>3.\u7535\u5546\u4ea7\u54c1\u5ba2\u670d<\/h4>\n<p>\u5bf9\u63a5\u5546\u54c1FAQ\u6587\u6863&#xff0c;\u7528\u6237\u53ef\u63d0\u95ee\u201c\u8fd9\u4e2a\u6d17\u8863\u673a\u80fd\u6d17\u7f8a\u6bdb\u5417&#xff1f;\u201d LightRAG\u81ea\u52a8\u67e5\u627e\u76f8\u5173\u95ee\u7b54\u8fd4\u56de\u3002<\/p>\n<h4>4.\u6559\u5b66\u8d44\u6599\u95ee\u7b54<\/h4>\n<p>\u4e0a\u4f20\u5b66\u751f\u6559\u6750\u6216\u8bb2\u4e49&#xff0c;\u5b66\u751f\u95ee\u201c\u725b\u987f\u7b2c\u4e09\u5b9a\u5f8b\u7684\u6838\u5fc3\u89c2\u70b9\u662f&#xff1f;\u201d&#xff0c;\u5b83\u80fd\u76f4\u63a5\u7ed9\u51fa\u6559\u6750\u4e2d\u7684\u539f\u8bdd\u3002<\/p>\n<h4>5.\u4e2a\u4eba\u77e5\u8bc6\u52a9\u624b<\/h4>\n<p>\u4f60\u4e5f\u53ef\u4ee5\u4e0a\u4f20\u4f60\u81ea\u5df1\u7684\u5b66\u4e60\u7b14\u8bb0\u3001\u4e66\u6458\u3001\u6587\u7ae0\u8d44\u6599&#xff0c;\u6253\u9020\u4f60\u7684\u4e13\u5c5e\u201c\u77e5\u8bc6\u5927\u8111\u201d\u3002<\/p>\n<h2>\u4e09\u3001LightRAG\u67b6\u6784\u5206\u6790\u548cDemo\u90e8\u7f72<\/h2>\n<h4>LightRAG\u57fa\u672c\u7ec4\u6210<\/h4>\n<p>LightRAG\u6574\u4f53\u7ed3\u6784\u6bd4\u4f20\u7edfRAG\u66f4\u6e05\u723d&#xff0c;\u6838\u5fc3\u7ec4\u4ef6\u5982\u4e0b&#xff1a;<\/p>\n<li>Embedding\u6a21\u578b&#xff08;\u7528\u4e8e\u6587\u672c\u5411\u91cf\u5316&#xff09;<\/li>\n<li>\u8f7b\u91cf\u7ea7\u68c0\u7d22\u5e93&#xff08;\u5982 FAISS\u3001\u672c\u5730sqlite\/Chroma&#xff09;<\/li>\n<li>\u5c0f\u578b\u8bed\u8a00\u6a21\u578b&#xff08;\u5982 MiniLM, Qwen1.5-0.5B, Mistral&#xff09;<\/li>\n<li>\u4e0a\u4e0b\u6587\u62fc\u63a5\u7b56\u7565&#xff08;\u5c06\u68c0\u7d22\u5230\u7684\u4fe1\u606f\u52a0\u8fdbprompt&#xff09;<\/li>\n<p>\u6d41\u7a0b\u7b80\u56fe\u5982\u4e0b&#xff1a;<br \/>\n\u7528\u6237\u95ee\u9898 \u2192 \u6587\u672c\u5411\u91cf\u5316 \u2192 \u76f8\u4f3c\u6587\u6863Top-k \u2192 \u62fc\u63a5\u4e0a\u4e0b\u6587 \u2192 \u9001\u8fdbLLM\u751f\u6210\u7b54\u6848<\/p>\n<h4>\u5feb\u901f\u4e0a\u624b&#xff1a;\u4ee3\u7801\u5b9e\u6218&#xff08;Python&#xff09;<\/h4>\n<p>\u4ee5\u4e0b\u662f\u7528 LangChain &#043; FAISS &#043; MiniLM \u6784\u5efa LightRAG \u7684\u7b80\u5316\u7248\u4ee3\u7801&#xff1a;<\/p>\n<p>from langchain.embeddings import HuggingFaceEmbeddingsfrom langchain.vectorstores import FAISSfrom langchain.llms import HuggingFacePipelinefrom langchain.chains import RetrievalQAfrom transformers import pipeline# 1. \u5411\u91cf\u5316\u6a21\u578b&#xff08;MiniLM&#xff09;embedding_model &#061; HuggingFaceEmbeddings(model_name&#061;&#034;sentence-transformers\/all-MiniLM-L6-v2&#034;)# 2. \u6784\u5efa\u77e5\u8bc6\u5e93docs &#061; [&#034;\u5458\u5de5\u53ef\u4ee5\u8bf7\u5e26\u85aa\u5e74\u5047&#xff0c;\u6bcf\u5e74\u6700\u591a10\u5929\u3002&#034;, &#034;\u9500\u552e\u9700\u6bcf\u5b63\u5ea6\u63d0\u4ea4\u4e00\u6b21\u5ba2\u6237\u62dc\u8bbf\u8bb0\u5f55\u3002&#034;]vector_db &#061; FAISS.from_texts(docs, embedding_model)# 3. \u642d\u5efaLLMqa_pipeline &#061; pipeline(&#034;text-generation&#034;, model&#061;&#034;Qwen\/Qwen1.5-0.5B&#034;, device&#061;0)llm &#061; HuggingFacePipeline(pipeline&#061;qa_pipeline)# 4. \u7ec4\u88c5\u6210LightRAGqa &#061; RetrievalQA.from_chain_type(llm&#061;llm, retriever&#061;vector_db.as_retriever(), chain_type&#061;&#034;stuff&#034;)# 5. \u4f53\u9a8c\u95ee\u7b54question &#061; &#034;\u8bf7\u95ee\u5458\u5de5\u5e74\u5047\u6709\u51e0\u5929&#xff1f;&#034;print(qa.run(question))<\/p>\n<h4>\u90e8\u7f72\u65b9\u5f0f\u5efa\u8bae&#xff1a;<\/h4>\n<ul>\n<li>\u672c\u5730\u90e8\u7f72&#xff1a;\u4f7f\u7528 Gradio\/Streamlit \u6784\u5efa\u7b80\u5355\u754c\u9762\u5373\u53ef<\/li>\n<li>\u4e91\u7aef\u90e8\u7f72&#xff1a;\u901a\u8fc7 Docker \u5bb9\u5668 &#043; FastAPI \u63d0\u4f9b\u670d\u52a1\u63a5\u53e3<\/li>\n<li>\u652f\u6301\u91cf\u5316\u6a21\u578b&#xff1a;\u53ef\u4f7f\u7528 INT8 \u7248\u672c LLM \u6a21\u578b\u8282\u7701\u663e\u5b58\u8d44\u6e90<\/li>\n<\/ul>\n<h2>\u56db\u3001LightRAG\u7684\u4f18\u7f3a\u70b9\u4e0e\u53d1\u5c55\u8d8b\u52bf<\/h2>\n<h4>1.\u4f18\u70b9\u4eae\u70b9&#xff1a;<\/h4>\n<table>\n<tr>\u4f18\u70b9\u8bf4\u660e<\/tr>\n<tbody>\n<tr>\n<td>\u8f7b\u91cf\u9ad8\u6548<\/td>\n<td>\u4f4e\u8d44\u6e90\u8fd0\u884c&#xff0c;\u7b14\u8bb0\u672c\u4e5f\u80fd\u7528<\/td>\n<\/tr>\n<tr>\n<td>\u6613\u90e8\u7f72<\/td>\n<td>\u6a21\u5757\u7ec4\u5408\u7075\u6d3b&#xff0c;\u65e0\u9700\u590d\u6742\u5fae\u8c03<\/td>\n<\/tr>\n<tr>\n<td>\u5f00\u6e90\u751f\u6001\u4e30\u5bcc<\/td>\n<td>\u652f\u6301 HuggingFace \/ LangChain \/ Chroma \/ FAISS \u7b49\u7ec4\u4ef6<\/td>\n<\/tr>\n<tr>\n<td>\u6210\u672c\u53ef\u63a7<\/td>\n<td>\u514d\u8d39\u6a21\u578b&#043;\u672c\u5730\u90e8\u7f72&#061;\u4e2d\u5c0f\u4f01\u4e1a\u53cb\u597d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4>2.\u4ecd\u6709\u4e0d\u8db3&#xff1a;<\/h4>\n<table>\n<tr>\u7f3a\u70b9\u8bf4\u660e<\/tr>\n<tbody>\n<tr>\n<td>\u274c \u4e0a\u4e0b\u6587\u62fc\u63a5\u9650\u5236<\/td>\n<td>Token \u9650\u5236&#xff0c;\u957f\u6587\u672c\u8986\u76d6\u6709\u9650<\/td>\n<\/tr>\n<tr>\n<td>\u274c \u65e0\u6cd5\u5904\u7406\u590d\u6742\u63a8\u7406\u94fe\u6761<\/td>\n<td>\u4e0d\u652f\u6301\u591a\u8f6e\u201c\u641c\u7d22-\u6574\u5408-\u5206\u6790\u201d\u7684\u957f\u94fe\u5f0f\u63a8\u7406<\/td>\n<\/tr>\n<tr>\n<td>\u274c \u5bf9\u6587\u6863\u7ed3\u6784\u8981\u6c42\u8f83\u9ad8<\/td>\n<td>\u683c\u5f0f\u6742\u4e71\u6587\u6863\u53ef\u80fd\u5bfc\u81f4\u68c0\u7d22\u4e0d\u51c6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4>3.\u672a\u6765\u53d1\u5c55\u8d8b\u52bf&#xff1a;<\/h4>\n<li>\u6a21\u5757\u5316\u4f18\u5316&#xff1a;\u5d4c\u5165\u66f4\u5f3a\u201c\u6587\u6863\u7ed3\u6784\u7406\u89e3\u201d\u548c\u201c\u6458\u8981\u538b\u7f29\u6a21\u5757\u201d<\/li>\n<li>\u672c\u5730\u591a\u6a21\u6001\u652f\u6301&#xff1a;\u672a\u6765LightRAG\u5c06\u652f\u6301\u56fe\u6587\u5e76\u5b58\u7684\u77e5\u8bc6\u5e93&#xff08;\u56fe\u50cf&#043;PDF&#xff09;<\/li>\n<li>\u94fe\u5f0f\u5de5\u5177\u8c03\u7528&#xff1a;\u7ed3\u5408 Agent \u7cfb\u7edf&#xff0c;\u81ea\u52a8\u8fdb\u884c\u201c\u67e5\u2192\u8bfb\u2192\u7b54\u2192\u5f15\u7528\u201d\u5168\u8fc7\u7a0b<\/li>\n<li>\u4f01\u4e1a\u5b9a\u5236\u5316\u6a21\u677f&#xff1a;\u4e3aHR\u3001\u5ba2\u670d\u3001\u6cd5\u52a1\u3001\u533b\u836f\u7b49\u884c\u4e1a\u5b9a\u5236\u4e13\u5c5e\u95ee\u7b54\u6a21\u7248<\/li>\n<h2>\u4e94\u3001LightRAG&#xff0c;\u662f\u4eba\u4eba\u53ef\u7528\u7684\u201c\u77e5\u8bc6\u578bAI\u5c0f\u52a9\u7406\u201d<\/h2>\n<p>\u4f20\u7edfRAG\u662f\u201c\u5168\u526f\u6b66\u88c5\u201d\u7684\u4fe1\u606f\u6218\u58eb&#xff0c;\u800cLightRAG\u662f\u201c\u7075\u6d3b\u8fc5\u6377\u201d\u7684\u65a5\u5019&#xff0c;\u6ca1\u6709GPU\u4f60\u4e5f\u80fd\u7528&#xff0c;\u4fe1\u606f\u7ed3\u6784\u4e0d\u5b8c\u7f8e\u4e5f\u80fd\u8dd1&#xff0c;\u5f00\u53d1\u8005\u5c11\u4e5f\u80fd\u90e8\u7f72\u3002<\/p>\n<p>\u5728\u201cAI\u5e73\u6c11\u5316\u201d\u7684\u6d6a\u6f6e\u91cc&#xff0c;LightRAG\u7684\u5b58\u5728\u6b63\u662f\u4e3a\u4e86&#xff1a;<\/p>\n<p>\u8ba9\u66f4\u591a\u4f01\u4e1a\u548c\u4e2a\u4eba&#xff0c;\u4e5f\u62e5\u6709\u5c5e\u4e8e\u81ea\u5df1\u7684AI\u77e5\u8bc6\u5927\u8111\u3002<\/p>\n<p>\u4f60\u53ef\u4ee5\u7528\u5b83\u505a\u5458\u5de5\u624b\u518c\u52a9\u624b\u3001\u505a\u8bba\u6587\u7b14\u8bb0\u52a9\u6559\u3001\u505aFAQ\u5ba2\u670d\u5de5\u5177\u2026\u2026<br 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decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/07\/20250730123658-688a11ea7fceb.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u968f\u7740AI\u5927\u6a21\u578b\u6280\u672f\u7684\u8fc5\u901f\u53d1\u5c55&#xff0c;\u76f8\u5173\u5c97\u4f4d\u7684\u9700\u6c42\u4e5f\u65e5\u76ca\u589e\u52a0\u3002\u5927\u6a21\u578b\u4ea7\u4e1a\u94fe\u50ac\u751f\u4e86\u4e00\u6279\u9ad8\u85aa\u65b0\u804c\u4e1a&#xff1a;<br \/>\n<img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/07\/20250730123659-688a11eb62343.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" 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