\n| RAG\u79bb\u7ebf\u8fd0\u884c\u811a\u672c<\/td>\n | \u672c\u6587\u4f18\u5316\u7248<\/td>\n | \u590d\u5236\u672c\u6587\u6700\u540e\u7684\u5b8c\u6574\u811a\u672c，\u4fdd\u5b58\u4e3arag_offline.py<\/td>\n | \u6838\u5fc3\u4e1a\u52a1\u903b\u8f91，\u5168\u79bb\u7ebf\u65e0\u5916\u90e8\u4f9d\u8d56<\/td>\n | \u79bb\u7ebf\u73af\u5883\u5de5\u4f5c\u76ee\u5f55，\u5982\/opt\/rag-offline\/<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\u3010\u6709\u7f51\u73af\u5883\u5fc5\u505a\u3011Docker\u955c\u50cf\u5bfc\u51fa\u547d\u4ee4<\/h4>\n\u5728\u6709\u7f51\u8bbe\u5907\u4e0a\u62c9\u53d6\u5b8c\u955c\u50cf\u540e，\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4\u5bfc\u51fa\u955c\u50cf\u6587\u4ef6，\u62f7\u8d1d\u5230\u79bb\u7ebf\u73af\u5883：<\/p>\n # \u5bfc\u51faES 9.1.3\u955c\u50cf
\ndocker save -o es-9.1.3.tar docker.elastic.co\/elasticsearch\/elasticsearch:9.1.3
\n# \u5bfc\u51faLocalAI CPU\u955c\u50cf
\ndocker save -o localai-cpu.tar localai\/localai:latest-cpu<\/p>\n \u6267\u884c\u5b8c\u6210\u540e，\u5f53\u524d\u76ee\u5f55\u4f1a\u751f\u6210es-9.1.3.tar\u548clocalai-cpu.tar\u4e24\u4e2a\u6587\u4ef6，\u5fc5\u987b\u548c\u5176\u4ed6\u7269\u6599\u4e00\u8d77\u62f7\u8d1d\u5230\u79bb\u7ebf\u73af\u5883\u3002<\/p>\n
\n\u4e09\u3001\u7b2c\u4e8c\u6b65：\u79bb\u7ebf\u73af\u5883\u57fa\u7840\u73af\u5883\u90e8\u7f72<\/h3>\n\u6240\u6709\u64cd\u4f5c\u5747\u5728\u79bb\u7ebf\u73af\u5883\u7684\u670d\u52a1\u5668\/\u7535\u8111\u4e0a\u6267\u884c，\u5168\u7a0b\u65e0\u9700\u8054\u7f51<\/p>\n 3.1 \u5b89\u88c5Docker（\u5bb9\u5668\u8fd0\u884c\u73af\u5883）<\/h4>\n\u539f\u7406\u5927\u767d\u8bdd<\/h5>\nDocker\u5c31\u50cf\u4e00\u4e2a\u201c\u9694\u79bb\u7684\u76d2\u5b50\u201d，\u6211\u4eec\u628aES\u548cLocalAI\u5206\u522b\u88c5\u5728\u4e24\u4e2a\u72ec\u7acb\u7684\u76d2\u5b50\u91cc，\u4e0d\u4f1a\u548c\u8bbe\u5907\u4e0a\u7684\u5176\u4ed6\u8f6f\u4ef6\u51b2\u7a81，\u79bb\u7ebf\u73af\u5883\u65e0\u9700\u89e3\u51b3\u590d\u6742\u7684\u4f9d\u8d56\u95ee\u9898，\u5bfc\u5165\u955c\u50cf\u5373\u53ef\u76f4\u63a5\u8fd0\u884c\u3002<\/p>\n Linux\u79bb\u7ebf\u5b89\u88c5\u6b65\u9aa4<\/h5>\n\u8fdb\u5165Docker\u5b89\u88c5\u5305\u5b58\u653e\u76ee\u5f55，\u89e3\u538b\u5e76\u5b89\u88c5：<\/li>\n# \u8fdb\u5165Docker\u5b89\u88c5\u5305\u76ee\u5f55
\ncd \/opt\/offline-packages\/docker\/
\n# \u89e3\u538b\u5b89\u88c5\u5305
\ntar -zxvf docker-20.10.24.tgz
\n# \u5c06Docker\u4e8c\u8fdb\u5236\u6587\u4ef6\u590d\u5236\u5230\u7cfb\u7edfPATH，\u5b9e\u73b0\u5168\u5c40\u8c03\u7528
\ncp docker\/* \/usr\/bin\/<\/p>\n \u914d\u7f6eDocker\u7cfb\u7edf\u670d\u52a1，\u5b9e\u73b0\u5f00\u673a\u81ea\u542f：<\/li>\n# \u521b\u5efaDocker\u670d\u52a1\u914d\u7f6e\u6587\u4ef6
\ncat > \/etc\/systemd\/system\/docker.service <<EOF
\n[Unit]
\nDescription=Docker Application Container Engine
\nDocumentation=https:\/\/docs.docker.com
\nAfter=network-online.target firewalld.service
\nWants=network-online.target<\/p>\n [Service]
\nType=notify
\nExecStart=\/usr\/bin\/dockerd
\nExecReload=\/bin\/kill -s HUP $MAINPID
\nTimeoutSec=0
\nRestartSec=2
\nRestart=always<\/p>\n LimitNOFILE=infinity
\nLimitNPROC=infinity
\nLimitCORE=infinity<\/p>\n TasksMax=infinity
\nDelegate=yes
\nKillMode=process<\/p>\n [Install]
\nWantedBy=multi-user.target
\nEOF<\/p>\n \u542f\u52a8Docker\u5e76\u8bbe\u7f6e\u5f00\u673a\u81ea\u542f：<\/li>\n# \u91cd\u8f7d\u7cfb\u7edf\u670d\u52a1\u914d\u7f6e
\nsystemctl daemon-reload
\n# \u542f\u52a8Docker\u670d\u52a1
\nsystemctl start docker
\n# \u8bbe\u7f6e\u5f00\u673a\u81ea\u542f
\nsystemctl enable docker<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011\u6267\u884cdocker version，\u80fd\u6b63\u5e38\u8f93\u51fa\u7248\u672c\u53f7，\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/li>\nWindows\u79bb\u7ebf\u5b89\u88c5\u6b65\u9aa4<\/h5>\n\u76f4\u63a5\u53cc\u51fbDocker Desktop\u79bb\u7ebf\u5b89\u88c5\u5305，\u8ddf\u968f\u5411\u5bfc\u5b8c\u6210\u5b89\u88c5，\u5b89\u88c5\u5b8c\u6210\u540e\u542f\u52a8Docker Desktop，\u53f3\u4e0b\u89d2Docker\u56fe\u6807\u663e\u793arunning，\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/p>\n \u79bb\u7ebf\u73af\u5883\u5e38\u89c1\u62a5\u9519\u5904\u7406<\/h5>\n\n- \n
\u62a5\u9519permission denied：\u4f7f\u7528root\u7528\u6237\u6267\u884c，\u6216\u7ed9\u5f53\u524d\u7528\u6237\u914d\u7f6esudo\u6743\u9650<\/p>\n<\/li>\n - \n
\u62a5\u9519docker\u670d\u52a1\u542f\u52a8\u5931\u8d25：\u68c0\u67e5\u9632\u706b\u5899\u662f\u5426\u5173\u95ed，\u7cfb\u7edf\u5185\u6838\u7248\u672c\u662f\u5426\u7b26\u5408Docker\u8981\u6c42（3.10+）<\/p>\n<\/li>\n<\/ul>\n 3.2 \u5bfc\u5165\u79bb\u7ebfDocker\u955c\u50cf<\/h4>\n\u539f\u7406\u5927\u767d\u8bdd<\/h5>\n\u6211\u4eec\u5728\u6709\u7f51\u73af\u5883\u628aES\u548cLocalAI\u7684\u201c\u5b8c\u6574\u5b89\u88c5\u5305\u201d\u5bfc\u51fa\u6210\u4e86tar\u6587\u4ef6，\u73b0\u5728\u628a\u8fd9\u4e9b\u6587\u4ef6\u5bfc\u5165\u5230\u79bb\u7ebf\u73af\u5883\u7684Docker\u4e2d，\u5c31\u50cf\u624b\u673a\u5b89\u88c5APK\u6587\u4ef6\u4e00\u6837，\u65e0\u9700\u8054\u7f51\u5373\u53ef\u5b8c\u6210\u5b89\u88c5\u3002<\/p>\n \u64cd\u4f5c\u6b65\u9aa4<\/h5>\n# \u8fdb\u5165\u955c\u50cftar\u6587\u4ef6\u5b58\u653e\u76ee\u5f55
\ncd \/opt\/offline-packages\/images\/
\n# \u5bfc\u5165ES 9.1.3\u955c\u50cf
\ndocker load -i es-9.1.3.tar
\n# \u5bfc\u5165LocalAI CPU\u955c\u50cf
\ndocker load -i localai-cpu.tar<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011<\/h5>\n\u6267\u884cdocker images，\u80fd\u770b\u5230docker.elastic.co\/elasticsearch\/elasticsearch:9.1.3\u548clocalai\/localai:latest-cpu\u4e24\u4e2a\u955c\u50cf，\u8bf4\u660e\u5bfc\u5165\u6210\u529f\u3002<\/p>\n 3.3 \u5b89\u88c5Python\u4e0e\u79bb\u7ebf\u4f9d\u8d56\u5305<\/h4>\n\u539f\u7406\u5927\u767d\u8bdd<\/h5>\nRAG\u6838\u5fc3\u811a\u672c\u57fa\u4e8ePython\u5f00\u53d1，\u9700\u8981\u5b89\u88c5Python\u73af\u5883\u548c\u5bf9\u5e94\u7684\u4f9d\u8d56\u5e93\u3002\u79bb\u7ebf\u73af\u5883\u65e0\u6cd5\u4f7f\u7528pip install\u5728\u7ebf\u5b89\u88c5，\u56e0\u6b64\u6211\u4eec\u63d0\u524d\u628a\u6240\u6709\u4f9d\u8d56\u5305\u7684\u79bb\u7ebf\u5b89\u88c5\u6587\u4ef6（whl\u683c\u5f0f）\u4e0b\u8f7d\u5b8c\u6210，\u76f4\u63a5\u672c\u5730\u5b89\u88c5\u5373\u53ef\u3002<\/p>\n \u64cd\u4f5c\u6b65\u9aa4<\/h5>\n - \n
\u5b89\u88c5Python 3.10<\/p>\n \n- \n
Linux：\u6267\u884crpm -ivh python-3.10.14.rpm（\u5bf9\u5e94\u7cfb\u7edf\u7248\u672c），\u6216\u901a\u8fc7\u89e3\u538b\u5305\u7f16\u8bd1\u5b89\u88c5<\/p>\n<\/li>\n - \n
Windows：\u53cc\u51fbPython\u79bb\u7ebf\u5b89\u88c5\u5305，\u52fe\u9009\u201cAdd Python to PATH\u201d，\u8ddf\u968f\u5411\u5bfc\u5b8c\u6210\u5b89\u88c5<\/p>\n<\/li>\n<\/ul>\n<\/li>\n - \n
\u3010\u6210\u529f\u6821\u9a8cPython\u3011\u6267\u884cpython3 –version（Linux）\u6216python –version（Windows），\u8f93\u51fa\u7248\u672c\u53f73.10.14，\u8bf4\u660e\u5b89\u88c5\u6210\u529f<\/p>\n<\/li>\n - \n
\u79bb\u7ebf\u5b89\u88c5Python\u4f9d\u8d56\u5305（\u590d\u5236\u5373\u7528）<\/p>\n<\/li>\n # \u8fdb\u5165whl\u5305\u5b58\u653e\u76ee\u5f55
\ncd \/opt\/offline-packages\/whl\/
\n# \u672c\u5730\u5b89\u88c5\u6240\u6709\u4f9d\u8d56\u5305，\u5b8c\u5168\u79bb\u7ebf，\u65e0\u5916\u7f51\u8c03\u7528
\npip install –no-index –find-links=.\/ elasticsearch requests openai<\/p>\n - \u3010\u6210\u529f\u6821\u9a8c\u4f9d\u8d56\u3011\u6267\u884cpip list，\u80fd\u770b\u5230elasticsearch\u3001requests\u3001openai\u4e09\u4e2a\u5305，\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/li>\n
\n\u56db\u3001\u7b2c\u4e09\u6b65：Elasticsearch 9.x \u79bb\u7ebf\u90e8\u7f72<\/h3>\n4.1 \u63d0\u524d\u89c4\u5212：ES\u79bb\u7ebf\u73af\u5883\u76ee\u5f55<\/h4>\n\u6240\u6709\u6570\u636e\u3001\u914d\u7f6e\u3001\u6a21\u578b\u5747\u5b58\u50a8\u5728\u5bbf\u4e3b\u673a\u76ee\u5f55，\u5bb9\u5668\u91cd\u542f\u4e0d\u4f1a\u4e22\u5931\u6570\u636e，\u79bb\u7ebf\u73af\u5883\u5fc5\u987b\u505a\u6301\u4e45\u5316\u914d\u7f6e<\/p>\n # \u521b\u5efaES\u5de5\u4f5c\u76ee\u5f55，\u6240\u6709\u6570\u636e\u5747\u5b58\u50a8\u5728\u6b64\u5904
\nmkdir -p \/opt\/rag-offline\/es\/{data,logs,config,models}
\n# \u7ed9\u76ee\u5f55\u8d4b\u8bfb\u5199\u6743\u9650，ES\u5bb9\u5668\u5185\u90e8\u7528\u6237\u4e3a1000，\u5fc5\u987b\u5f00\u653e\u6743\u9650\u5426\u5219\u542f\u52a8\u5931\u8d25
\nchmod -R 777 \/opt\/rag-offline\/es\/<\/p>\n 4.2 \u542f\u52a8ES 9.x \u79bb\u7ebf\u5355\u8282\u70b9\u5bb9\u5668<\/h4>\n\u539f\u7406\u5927\u767d\u8bdd<\/h5>\n\u6211\u4eec\u901a\u8fc7Docker\u542f\u52a8ES，\u6240\u6709\u914d\u7f6e\u5747\u9002\u914d\u79bb\u7ebf\u5355\u8282\u70b9\u73af\u5883，\u5173\u95ed\u4e86\u6240\u6709\u9700\u8981\u8054\u7f51\u7684\u529f\u80fd，\u5f00\u542f\u4e86\u5b89\u5168\u8ba4\u8bc1，\u540c\u65f6\u628a\u6570\u636e\u3001\u914d\u7f6e\u6301\u4e45\u5316\u5230\u5bbf\u4e3b\u673a，\u5373\u4f7f\u5bb9\u5668\u5220\u9664，\u6570\u636e\u4e5f\u4e0d\u4f1a\u4e22\u5931\u3002<\/p>\n \u542f\u52a8\u547d\u4ee4<\/h5>\ndocker run -d \\\\
\n –name es-rag-offline \\\\
\n –restart=always \\\\
\n -p 9200:9200 \\\\
\n -p 9300:9300 \\\\
\n -e "discovery.type=single-node" \\\\ # \u5355\u8282\u70b9\u6a21\u5f0f，\u79bb\u7ebf\u73af\u5883\u65e0\u9700\u96c6\u7fa4\u914d\u7f6e
\n -e "ES_JAVA_OPTS=-Xms2g -Xmx2g" \\\\ # \u5806\u5185\u5b58\u8bbe\u7f6e，\u5efa\u8bae\u4e3a\u8bbe\u5907\u5185\u5b58\u76841\/4，\u6700\u4f4e2G
\n -e "xpack.security.enabled=true" \\\\ # \u5f00\u542f\u5b89\u5168\u8ba4\u8bc1，\u7b26\u5408\u5185\u7f51\u5408\u89c4\u8981\u6c42
\n -e "xpack.security.authc.api_key.enabled=true" \\\\ # \u5f00\u542fAPI\u5bc6\u94a5\u8ba4\u8bc1，\u811a\u672c\u8c03\u7528\u4f7f\u7528
\n -e "xpack.ml.enabled=true" \\\\ # \u5f00\u542f\u673a\u5668\u5b66\u4e60\u529f\u80fd，\u7528\u4e8e\u52a0\u8f7d\u5d4c\u5165\u6a21\u578b
\n -e "xpack.ml.model_repository.file.enabled=true" \\\\ # \u5f00\u542f\u672c\u5730\u6a21\u578b\u5bfc\u5165，\u79bb\u7ebf\u73af\u5883\u6838\u5fc3\u914d\u7f6e
\n -v \/opt\/rag-offline\/es\/data:\/usr\/share\/elasticsearch\/data \\\\
\n -v \/opt\/rag-offline\/es\/logs:\/usr\/share\/elasticsearch\/logs \\\\
\n -v \/opt\/rag-offline\/es\/config:\/usr\/share\/elasticsearch\/config \\\\
\n -v \/opt\/rag-offline\/es\/models:\/usr\/share\/elasticsearch\/models \\\\ # \u6302\u8f7d\u79bb\u7ebf\u6a21\u578b\u76ee\u5f55
\n docker.elastic.co\/elasticsearch\/elasticsearch:9.1.3<\/p>\n Windows\u73af\u5883\u9002\u914d<\/h5>\n\u5c06\u76ee\u5f55\u66ff\u6362\u4e3aWindows\u8def\u5f84，\u6bd4\u5982D:\\\\rag-offline\\\\es\\\\data，\u547d\u4ee4\u4fee\u6539\u4e3a：<\/p>\n docker run -d ^
\n –name es-rag-offline ^
\n –restart=always ^
\n -p 9200:9200 ^
\n -p 9300:9300 ^
\n -e "discovery.type=single-node" ^
\n -e "ES_JAVA_OPTS=-Xms2g -Xmx2g" ^
\n -e "xpack.security.enabled=true" ^
\n -e "xpack.security.authc.api_key.enabled=true" ^
\n -e "xpack.ml.enabled=true" ^
\n -e "xpack.ml.model_repository.file.enabled=true" ^
\n -v D:\\\\rag-offline\\\\es\\\\data:\/usr\/share\/elasticsearch\/data ^
\n -v D:\\\\rag-offline\\\\es\\\\logs:\/usr\/share\/elasticsearch\/logs ^
\n -v D:\\\\rag-offline\\\\es\\\\config:\/usr\/share\/elasticsearch\/config ^
\n -v D:\\\\rag-offline\\\\es\\\\models:\/usr\/share\/elasticsearch\/models ^
\n docker.elastic.co\/elasticsearch\/elasticsearch:9.1.3<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011<\/h5>\n - \n
\u6267\u884cdocker ps，\u770b\u5230ES\u5bb9\u5668\u7684STATUS\u4e3aUp X seconds (healthy)，\u8bf4\u660e\u542f\u52a8\u6210\u529f（\u5fc5\u987b\u663e\u793ahealthy，\u4ec5Up\u4e0d\u4ee3\u8868\u5b8c\u5168\u542f\u52a8）<\/p>\n<\/li>\n - \n
\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4，\u80fd\u8fd4\u56deES\u7684\u7248\u672c\u4fe1\u606f，\u8bf4\u660eAPI\u53ef\u6b63\u5e38\u8bbf\u95ee：<\/p>\n<\/li>\n curl -X GET "http:\/\/localhost:9200\/" -u "elastic:\u4f60\u7684elastic\u5bc6\u7801"<\/p>\n \u8865\u5145\u8bf4\u660e：ES\u9996\u6b21\u542f\u52a8\u4f1a\u81ea\u52a8\u751f\u6210elastic\u7528\u6237\u7684\u5bc6\u7801，\u6267\u884cdocker logs es-rag-offline | grep "Password for the elastic user is"\u5373\u53ef\u83b7\u53d6，\u52a1\u5fc5\u59a5\u5584\u4fdd\u5b58\u3002<\/p>\n 4.3 \u79bb\u7ebf\u5bfc\u5165multilingual-e5-small\u5d4c\u5165\u6a21\u578b\u5230ES<\/h4>\n\u539f\u7406\u5927\u767d\u8bdd<\/h5>\n\u5728\u7ebf\u73af\u5883\u4e2d，ES\u4f1a\u81ea\u52a8\u4ece\u5b98\u7f51\u4e0b\u8f7d\u8be5\u5d4c\u5165\u6a21\u578b，\u4f46\u79bb\u7ebf\u73af\u5883\u65e0\u6cd5\u8054\u7f51，\u56e0\u6b64\u6211\u4eec\u9700\u8981\u63d0\u524d\u628a\u6a21\u578b\u6587\u4ef6\u4e0b\u8f7d\u597d，\u653e\u5230ES\u7684\u6a21\u578b\u76ee\u5f55\u4e2d，\u8ba9ES\u79bb\u7ebf\u52a0\u8f7d\u8be5\u6a21\u578b，\u624d\u80fd\u5728\u65e0\u5916\u7f51\u7684\u73af\u5883\u4e0b\u751f\u6210\u8bed\u4e49\u5411\u91cf\u3002<\/p>\n \u64cd\u4f5c\u6b65\u9aa4<\/h5>\n - \n
\u628a\u63d0\u524d\u4e0b\u8f7d\u597d\u7684multilingual-e5-small\u6a21\u578b\u538b\u7f29\u5305，\u89e3\u538b\u5230\/opt\/rag-offline\/es\/models\/\u76ee\u5f55，\u786e\u4fdd\u89e3\u538b\u540e\u7684\u6a21\u578b\u6587\u4ef6\u76f4\u63a5\u5728\u8be5\u76ee\u5f55\u4e0b<\/p>\n<\/li>\n - \n
\u7ed9\u6a21\u578b\u6587\u4ef6\u8d4b\u6743\u9650：chmod -R 777 \/opt\/rag-offline\/es\/models\/<\/p>\n<\/li>\n - \n
\u91cd\u542fES\u5bb9\u5668，\u8ba9ES\u52a0\u8f7d\u672c\u5730\u6a21\u578b：docker restart es-rag-offline<\/p>\n<\/li>\n - \n
\u7b49\u5f85ES\u91cd\u542f\u5b8c\u6210（STATUS\u53d8\u4e3ahealthy），\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4，\u9a8c\u8bc1\u6a21\u578b\u662f\u5426\u52a0\u8f7d\u6210\u529f：<\/p>\n<\/li>\n curl -X GET "http:\/\/localhost:9200\/_ml\/trained_models\/.multilingual-e5-small" -u "elastic:\u4f60\u7684elastic\u5bc6\u7801"<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011<\/h5>\n\u547d\u4ee4\u8fd4\u56de\u6a21\u578b\u7684\u8be6\u7ec6\u4fe1\u606f，\u65e0\u62a5\u9519，\u8bf4\u660e\u6a21\u578b\u79bb\u7ebf\u52a0\u8f7d\u6210\u529f，ES\u53ef\u5728\u79bb\u7ebf\u73af\u5883\u4f7f\u7528\u8be5\u6a21\u578b\u751f\u6210\u8bed\u4e49\u5411\u91cf\u3002<\/p>\n 4.4 \u751f\u6210ES API\u5bc6\u94a5<\/h4>\n\u64cd\u4f5c\u6b65\u9aa4<\/h5>\ncurl -X POST "http:\/\/localhost:9200\/_security\/api_key" \\\\
\n -u "elastic:\u4f60\u7684elastic\u5bc6\u7801" \\\\
\n -H "Content-Type: application\/json" \\\\
\n -d '{
\n "name": "rag-offline-api-key",
\n "expiration": "10y",
\n "role_descriptors": {
\n "rag-admin": {
\n "cluster": ["all"],
\n "index": [
\n {
\n "names": ["*"],
\n "privileges": ["all"]
\n }
\n ]
\n }
\n }
\n }'<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011<\/h5>\n\u8fd4\u56de\u7ed3\u679c\u4e2d\u7684encoded\u5b57\u6bb5，\u5c31\u662f\u4f60\u7684API\u5bc6\u94a5，\u52a1\u5fc5\u590d\u5236\u4fdd\u5b58，\u540e\u7eed\u811a\u672c\u9700\u8981\u4f7f\u7528，\u683c\u5f0f\u793a\u4f8b：MTk0NVRwa0IxRGRjVmVKSGl2ZFc6dUFaNkZTUHVXRzEzVjdrejQzSUNxZw==<\/p>\n
\n\u4e94\u3001\u7b2c\u56db\u6b65：LocalAI+\u5927\u6a21\u578b \u5b8c\u5168\u79bb\u7ebf\u90e8\u7f72<\/h3>\n5.1 \u63d0\u524d\u89c4\u5212：LocalAI\u79bb\u7ebf\u73af\u5883\u76ee\u5f55<\/h4>\n# \u521b\u5efaLocalAI\u5de5\u4f5c\u76ee\u5f55，\u5b58\u653e\u5927\u6a21\u578b\u6587\u4ef6
\nmkdir -p \/opt\/rag-offline\/localai\/models
\n# \u7ed9\u76ee\u5f55\u8d4b\u8bfb\u5199\u6743\u9650
\nchmod -R 777 \/opt\/rag-offline\/localai\/<\/p>\n 5.2 \u653e\u7f6e\u5927\u6a21\u578b\u6587\u4ef6<\/h4>\n\u628a\u63d0\u524d\u4e0b\u8f7d\u597d\u7684dolphin3.0-qwen2.5-0.5b-instruct.Q4_K_M.gguf\u6587\u4ef6，\u62f7\u8d1d\u5230\/opt\/rag-offline\/localai\/models\u76ee\u5f55\u4e2d，LocalAI\u542f\u52a8\u65f6\u4f1a\u81ea\u52a8\u52a0\u8f7d\u8be5\u6a21\u578b，\u5b8c\u5168\u79bb\u7ebf，\u65e0\u9700\u901a\u8fc7API\u4e0b\u8f7d\u3002<\/p>\n 5.3 \u542f\u52a8LocalAI\u79bb\u7ebf\u5bb9\u5668<\/h4>\n\u539f\u7406\u5927\u767d\u8bdd<\/h5>\nLocalAI\u5c31\u50cf\u4e00\u4e2a\u672c\u5730\u7684OpenAI\u670d\u52a1，\u6211\u4eec\u628a\u5927\u6a21\u578b\u6587\u4ef6\u6302\u8f7d\u5230\u5bb9\u5668\u4e2d，\u5b83\u542f\u52a8\u65f6\u4f1a\u81ea\u52a8\u52a0\u8f7d，\u5bf9\u5916\u63d0\u4f9b\u548cOpenAI\u5b8c\u5168\u517c\u5bb9\u7684API\u63a5\u53e3，RAG\u811a\u672c\u65e0\u9700\u4fee\u6539\u4efb\u4f55\u4ee3\u7801，\u5373\u53ef\u8c03\u7528\u672c\u5730\u5927\u6a21\u578b，\u5168\u7a0b\u65e0\u5916\u7f51\u8c03\u7528\u3002<\/p>\n \u542f\u52a8\u547d\u4ee4<\/h5>\ndocker run -d \\\\
\n –name localai-rag-offline \\\\
\n –restart=always \\\\
\n -p 8080:8080 \\\\
\n -v \/opt\/rag-offline\/localai\/models:\/models \\\\ # \u6302\u8f7d\u672c\u5730\u6a21\u578b\u76ee\u5f55
\n -e DEBUG=false \\\\
\n -e MODELS_PATH=\/models \\\\
\n -e THREADS=4 \\\\ # \u6539\u4e3a\u4f60\u7684CPU\u7269\u7406\u6838\u5fc3\u6570，\u6838\u5fc3\u8d8a\u591a\u751f\u6210\u901f\u5ea6\u8d8a\u5feb
\n -e CONTEXT_SIZE=2048 \\\\ # \u4e0a\u4e0b\u6587\u7a97\u53e3，\u5e73\u8861\u5185\u5b58\u5360\u7528\u548c\u957f\u6587\u672c\u652f\u6301
\n -e PRELOAD_MODELS=dolphin3.0-qwen2.5-0.5b-instruct.Q4_K_M.gguf \\\\ # \u542f\u52a8\u65f6\u9884\u52a0\u8f7d\u6a21\u578b，\u65e0\u9700\u7b49\u5f85\u8c03\u7528\u518d\u52a0\u8f7d
\n localai\/localai:latest-cpu<\/p>\n Windows\u73af\u5883\u9002\u914d<\/h5>\n\u5c06\u76ee\u5f55\u66ff\u6362\u4e3aWindows\u8def\u5f84，\u6bd4\u5982D:\\\\rag-offline\\\\localai\\\\models，\u4fee\u6539\u4e3a\u5bf9\u5e94Windows\u683c\u5f0f\u5373\u53ef\u3002<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011<\/h5>\n - \n
\u6267\u884cdocker ps，\u770b\u5230LocalAI\u5bb9\u5668STATUS\u4e3aUp，\u8bf4\u660e\u542f\u52a8\u6210\u529f<\/p>\n<\/li>\n - \n
\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4，\u9a8c\u8bc1\u6a21\u578b\u662f\u5426\u52a0\u8f7d\u6210\u529f，\u53ef\u6b63\u5e38\u751f\u6210\u5185\u5bb9：<\/p>\n<\/li>\n curl -X POST http:\/\/localhost:8080\/v1\/chat\/completions \\\\
\n -H "Content-Type: application\/json" \\\\
\n -d '{
\n "model": "dolphin3.0-qwen2.5-0.5b-instruct.Q4_K_M.gguf",
\n "messages": [{"role": "user", "content": "\u4f60\u597d"}],
\n "stream": false
\n }'<\/p>\n - \u547d\u4ee4\u8fd4\u56de\u5927\u6a21\u578b\u751f\u6210\u7684\u56de\u590d，\u65e0\u62a5\u9519，\u8bf4\u660eLocalAI\u79bb\u7ebf\u90e8\u7f72\u6210\u529f\u3002<\/li>\n
\n\u516d\u3001\u7b2c\u4e94\u6b65：RAG\u6838\u5fc3\u914d\u7f6e\u4e0e\u79bb\u7ebf\u811a\u672c\u90e8\u7f72<\/h3>\n6.1 \u539f\u7406\u5927\u767d\u8bdd<\/h4>\n\u8fd9\u4e2a\u811a\u672c\u662f\u6574\u4e2a\u7cfb\u7edf\u7684\u201c\u603b\u6307\u6325\u201d，\u5168\u7a0b\u65e0\u5916\u7f51\u8c03\u7528，\u81ea\u52a8\u5b8c\u6210\u4ee5\u4e0b\u5de5\u4f5c：<\/p>\n - \n
\u5728ES\u4e2d\u521b\u5efa\u79bb\u7ebf\u63a8\u7406\u7aef\u70b9，\u7528\u4e8e\u751f\u6210\u8bed\u4e49\u5411\u91cf<\/p>\n<\/li>\n - \n
\u521b\u5efa\u77e5\u8bc6\u5e93\u7d22\u5f15，\u7528\u4e8e\u5b58\u50a8\u6587\u6863\u548c\u8bed\u4e49\u6807\u7b7e<\/p>\n<\/li>\n - \n
\u6279\u91cf\u5bfc\u5165\u6307\u5b9a\u6587\u4ef6\u5939\u4e2d\u7684\u6587\u6863\u5230ES\u77e5\u8bc6\u5e93<\/p>\n<\/li>\n - \n
\u8f93\u5165\u95ee\u9898\u540e，\u81ea\u52a8\u5728ES\u4e2d\u6267\u884c\u8bed\u4e49\u68c0\u7d22，\u5339\u914d\u76f8\u5173\u6587\u6863<\/p>\n<\/li>\n - \n
\u628a\u68c0\u7d22\u5230\u7684\u5185\u5bb9\u53d1\u9001\u7ed9\u672c\u5730\u5927\u6a21\u578b，\u751f\u6210\u5e26\u5f15\u6587\u7684\u7cbe\u51c6\u7b54\u6848<\/p>\n<\/li>\n - \n
\u8f93\u51fa\u6700\u7ec8\u7ed3\u679c\u548c\u6027\u80fd\u6570\u636e<\/p>\n<\/li>\n 6.2 \u51c6\u5907\u77e5\u8bc6\u5e93\u6587\u6863<\/h4>\n\u5728\u79bb\u7ebf\u73af\u5883\u4e2d，\u521b\u5efa\/opt\/rag-offline\/dataset\u76ee\u5f55，\u628a\u6240\u6709txt\u683c\u5f0f\u7684\u6587\u6863（\u4f1a\u8bae\u7eaa\u8981\u3001\u62a5\u544a\u3001\u5236\u5ea6\u6587\u4ef6\u7b49）\u653e\u5165\u8be5\u76ee\u5f55，\u811a\u672c\u4f1a\u81ea\u52a8\u8bfb\u53d6\u6240\u6709txt\u6587\u4ef6\u3002<\/p>\n 6.3 \u5b8c\u6574\u79bb\u7ebfRAG\u811a\u672c<\/h4>\n\u628a\u4ee5\u4e0b\u811a\u672c\u4fdd\u5b58\u4e3a\/opt\/rag-offline\/rag_offline.py，\u4ec5\u9700\u4fee\u6539\u5f00\u5934\u76843\u4e2a\u914d\u7f6e\u9879（ES_API_KEY\u3001AI_MODEL_NAME\u3001DATASET_FOLDER），\u5176\u4f59\u5185\u5bb9\u65e0\u9700\u4fee\u6539\u3002<\/p>\n import os
\nimport time
\nfrom elasticsearch import Elasticsearch, helpers
\nfrom openai import OpenAI<\/p>\n # ===================== \u3010\u4ec5\u9700\u4fee\u6539\u8fd9\u91cc\u7684\u914d\u7f6e，\u5176\u4ed6\u5185\u5bb9\u65e0\u9700\u6539\u52a8\u3011=====================
\n# \u66ff\u6362\u4e3a\u4e4b\u524d\u751f\u6210\u7684ES API\u5bc6\u94a5
\nES_API_KEY = "\u4f60\u7684ES API\u5bc6\u94a5"
\n# \u66ff\u6362\u4e3a\u653e\u5165models\u76ee\u5f55\u7684\u5927\u6a21\u578b\u6587\u4ef6\u540d，\u5fc5\u987b\u548c\u6587\u4ef6\u540d\u5b8c\u5168\u4e00\u81f4
\nAI_MODEL_NAME = "dolphin3.0-qwen2.5-0.5b-instruct.Q4_K_M.gguf"
\n# \u77e5\u8bc6\u5e93\u6587\u6863\u5b58\u653e\u76ee\u5f55
\nDATASET_FOLDER = "\/opt\/rag-offline\/dataset"
\n# ==============================================================================<\/p>\n # \u56fa\u5b9a\u914d\u7f6e，\u79bb\u7ebf\u73af\u5883\u65e0\u9700\u4fee\u6539
\nES_URL = "http:\/\/localhost:9200"
\nINDEX_NAME = "offline-rag-knowledge-base"
\nLOCAL_AI_URL = "http:\/\/localhost:8080\/v1"<\/p>\n # \u521d\u59cb\u5316\u5ba2\u6237\u7aef，\u5168\u7a0b\u65e0\u5916\u7f51\u8c03\u7528
\nes_client = Elasticsearch(ES_URL, api_key=ES_API_KEY)
\nai_client = OpenAI(base_url=LOCAL_AI_URL, api_key="sk-offline-rag") # API key\u586b\u5199\u4efb\u610f\u975e\u7a7a\u5b57\u7b26\u4e32\u5373\u53ef，\u65e0\u9700\u771f\u5b9e\u5bc6\u94a5<\/p>\n def check_es_connect():
\n """\u68c0\u67e5ES\u8fde\u63a5\u662f\u5426\u6b63\u5e38，\u79bb\u7ebf\u73af\u5883\u7b2c\u4e00\u6b65\u5fc5\u505a"""
\n try:
\n if not es_client.ping():
\n print("\u274c \u65e0\u6cd5\u8fde\u63a5\u5230Elasticsearch，\u8bf7\u68c0\u67e5\u670d\u52a1\u662f\u5426\u542f\u52a8\u3001API\u5bc6\u94a5\u662f\u5426\u6b63\u786e")
\n exit(1)
\n es_info = es_client.info()
\n print(f"\u2705 \u6210\u529f\u8fde\u63a5Elasticsearch，\u7248\u672c：{es_info['version']['number']}")
\n return True
\n except Exception as e:
\n print(f"\u274c ES\u8fde\u63a5\u5931\u8d25，\u9519\u8bef\u4fe1\u606f：{str(e)}")
\n exit(1)<\/p>\n def setup_embedding_inference():
\n """\u521b\u5efa\u79bb\u7ebf\u5d4c\u5165\u63a8\u7406\u7aef\u70b9，\u4f7f\u7528\u63d0\u524d\u5bfc\u5165\u7684e5-small\u6a21\u578b，\u65e0\u5916\u7f51\u8c03\u7528"""
\n inference_id = "offline-e5-small-embedding"
\n # \u5148\u68c0\u67e5\u63a8\u7406\u7aef\u70b9\u662f\u5426\u5df2\u5b58\u5728，\u5b58\u5728\u5219\u65e0\u9700\u91cd\u590d\u521b\u5efa
\n try:
\n es_client.inference.get(inference_id=inference_id)
\n print(f"\u2705 \u5d4c\u5165\u63a8\u7406\u7aef\u70b9 {inference_id} \u5df2\u5b58\u5728，\u65e0\u9700\u91cd\u590d\u521b\u5efa")
\n return
\n except Exception:
\n pass<\/p>\n # \u521b\u5efa\u63a8\u7406\u7aef\u70b9，\u5b8c\u5168\u9002\u914d\u79bb\u7ebf\u73af\u5883，\u65e0\u5916\u90e8\u8c03\u7528
\n try:
\n es_client.inference.put(
\n inference_id=inference_id,
\n task_type="text_embedding",
\n body={
\n "service": "elasticsearch",
\n "service_settings": {
\n "num_allocations": 1,
\n "num_threads": 1,
\n "model_id": ".multilingual-e5-small", # \u4f7f\u7528\u63d0\u524d\u79bb\u7ebf\u5bfc\u5165\u7684\u6a21\u578b
\n },
\n "chunking_settings": {
\n "strategy": "sentence",
\n "max_chunk_size": 250,
\n "sentence_overlap": 2
\n }
\n }
\n )
\n print(f"\u2705 \u5d4c\u5165\u63a8\u7406\u7aef\u70b9 {inference_id} \u521b\u5efa\u6210\u529f")
\n except Exception as e:
\n print(f"\u274c \u5d4c\u5165\u63a8\u7406\u7aef\u70b9\u521b\u5efa\u5931\u8d25，\u9519\u8bef\u4fe1\u606f：{str(e)}")
\n exit(1)<\/p>\n def setup_knowledge_index():
\n """\u521b\u5efa\u77e5\u8bc6\u5e93\u7d22\u5f15，\u4f7f\u7528ES9.x\u539f\u751fsemantic_text\u5b57\u6bb5，\u81ea\u52a8\u5904\u7406\u5411\u91cf，\u65e0\u9700\u624b\u52a8\u7f16\u7801"""
\n try:
\n if es_client.indices.exists(index=INDEX_NAME):
\n print(f"\u2705 \u77e5\u8bc6\u5e93\u7d22\u5f15 {INDEX_NAME} \u5df2\u5b58\u5728，\u65e0\u9700\u91cd\u590d\u521b\u5efa")
\n return False<\/p>\n print(f"📦 \u6b63\u5728\u521b\u5efa\u77e5\u8bc6\u5e93\u7d22\u5f15 {INDEX_NAME}…")
\n es_client.indices.create(
\n index=INDEX_NAME,
\n body={
\n # \u79bb\u7ebf\u5355\u8282\u70b9\u73af\u5883\u4e13\u5c5e\u914d\u7f6e，\u907f\u514d\u7d22\u5f15\u9ec4\u6807，\u63d0\u5347\u6027\u80fd
\n "settings": {
\n "number_of_shards": 1,
\n "number_of_replicas": 0,
\n "refresh_interval": "1s"
\n },
\n # \u7d22\u5f15\u6620\u5c04，\u6838\u5fc3\u4e3asemantic_text\u8bed\u4e49\u5b57\u6bb5，\u81ea\u52a8\u5904\u7406\u5411\u91cf\u751f\u6210\u548c\u68c0\u7d22
\n "mappings": {
\n "properties": {
\n "file_name": {
\n "type": "text",
\n "copy_to": "semantic_content" # \u628a\u6587\u4ef6\u540d\u590d\u5236\u5230\u8bed\u4e49\u5b57\u6bb5，\u652f\u6301\u6309\u6587\u4ef6\u540d\u68c0\u7d22
\n },
\n "file_content": {
\n "type": "text",
\n "copy_to": "semantic_content" # \u628a\u6587\u4ef6\u5185\u5bb9\u590d\u5236\u5230\u8bed\u4e49\u5b57\u6bb5，\u652f\u6301\u6309\u5185\u5bb9\u68c0\u7d22
\n },
\n "semantic_content": {
\n "type": "semantic_text",
\n "inference_id": "offline-e5-small-embedding" # \u7ed1\u5b9a\u521b\u5efa\u7684\u79bb\u7ebf\u63a8\u7406\u7aef\u70b9
\n }
\n }
\n }
\n }
\n )
\n print(f"\u2705 \u77e5\u8bc6\u5e93\u7d22\u5f15 {INDEX_NAME} \u521b\u5efa\u6210\u529f")
\n return True
\n except Exception as e:
\n print(f"\u274c \u77e5\u8bc6\u5e93\u7d22\u5f15\u521b\u5efa\u5931\u8d25，\u9519\u8bef\u4fe1\u606f：{str(e)}")
\n exit(1)<\/p>\n def load_documents_from_folder():
\n """\u4ece\u672c\u5730\u6587\u4ef6\u5939\u52a0\u8f7d\u6240\u6709txt\u6587\u6863，\u751f\u6210ES\u6279\u91cf\u5199\u5165\u6570\u636e，\u5b8c\u5168\u79bb\u7ebf"""
\n if not os.path.exists(DATASET_FOLDER):
\n print(f"\u274c \u77e5\u8bc6\u5e93\u76ee\u5f55 {DATASET_FOLDER} \u4e0d\u5b58\u5728，\u8bf7\u5148\u521b\u5efa\u76ee\u5f55\u5e76\u653e\u5165txt\u6587\u6863")
\n exit(1)<\/p>\n file_count = 0
\n for filename in os.listdir(DATASET_FOLDER):
\n if filename.endswith(".txt"):
\n file_path = os.path.join(DATASET_FOLDER, filename)
\n # \u7528UTF-8\u7f16\u7801\u8bfb\u53d6，\u907f\u514d\u4e2d\u6587\u4e71\u7801
\n with open(file_path, "r", encoding="utf-8") as f:
\n file_content = f.read()<\/p>\n yield {
\n "_index": INDEX_NAME,
\n "_source": {
\n "file_name": filename,
\n "file_content": file_content
\n }
\n }
\n file_count += 1<\/p>\n if file_count == 0:
\n print(f"\u274c \u77e5\u8bc6\u5e93\u76ee\u5f55 {DATASET_FOLDER} \u4e2d\u6ca1\u6709\u627e\u5230\u4efb\u4f55txt\u6587\u6863，\u8bf7\u5148\u653e\u5165\u6587\u6863")
\n exit(1)
\n print(f"📄 \u627e\u5230 {file_count} \u4e2a\u6587\u6863，\u51c6\u5907\u5bfc\u5165ES")<\/p>\n def bulk_index_documents():
\n """\u6279\u91cf\u628a\u6587\u6863\u5bfc\u5165ES\u77e5\u8bc6\u5e93，\u4f7f\u7528bulk API\u63d0\u5347\u5bfc\u5165\u901f\u5ea6"""
\n try:
\n success_count, failed_count = helpers.bulk(
\n es_client,
\n load_documents_from_folder()
\n )
\n if failed_count:
\n print(f"\u26a0\ufe0f {failed_count} \u4e2a\u6587\u6863\u5bfc\u5165\u5931\u8d25")
\n print(f"\u2705 \u6210\u529f\u5bfc\u5165 {success_count} \u4e2a\u6587\u6863\u5230\u77e5\u8bc6\u5e93")
\n return success_count
\n except Exception as e:
\n print(f"\u274c \u6587\u6863\u5bfc\u5165\u5931\u8d25，\u9519\u8bef\u4fe1\u606f：{str(e)}")
\n exit(1)<\/p>\n def semantic_search(user_query, top_n=3):
\n """ES\u539f\u751f\u8bed\u4e49\u68c0\u7d22，\u81ea\u52a8\u628a\u7528\u6237\u95ee\u9898\u8f6c\u6210\u5411\u91cf，\u5339\u914d\u6700\u76f8\u5173\u7684\u6587\u6863，\u5168\u7a0b\u79bb\u7ebf"""
\n start_time = time.time()
\n # \u8bed\u4e49\u68c0\u7d22\u67e5\u8be2，\u4e00\u884c\u4ee3\u7801\u5b8c\u6210，\u65e0\u9700\u624b\u52a8\u751f\u6210\u5411\u91cf
\n search_query = {
\n "query": {
\n "semantic": {
\n "field": "semantic_content",
\n "query": user_query
\n }
\n },
\n "size": top_n,
\n "_source": ["file_name", "file_content"]
\n }<\/p>\n response = es_client.search(index=INDEX_NAME, body=search_query)
\n search_latency = (time.time() – start_time) * 1000 # \u8f6c\u6362\u4e3a\u6beb\u79d2
\n return response["hits"]["hits"], search_latency<\/p>\n def call_local_llm(prompt):
\n """\u8c03\u7528\u672c\u5730\u79bb\u7ebf\u5927\u6a21\u578b\u751f\u6210\u7b54\u6848，\u5168\u7a0b\u65e0\u5916\u7f51\u8c03\u7528"""
\n start_time = time.time()
\n try:
\n response = ai_client.chat.completions.create(
\n model=AI_MODEL_NAME,
\n messages=[{"role": "user", "content": prompt}],
\n temperature=0.3, # RAG\u573a\u666f\u4f7f\u7528\u4f4e\u6e29\u5ea6，\u51cf\u5c11\u5e7b\u89c9，\u786e\u4fdd\u7b54\u6848\u4ec5\u6765\u81ea\u6587\u6863
\n stream=False
\n )
\n # \u8ba1\u7b97\u8017\u65f6\u548c\u751f\u6210\u901f\u5ea6
\n llm_latency = (time.time() – start_time) * 1000
\n answer = response.choices[0].message.content
\n tokens_per_second = 0<\/p>\n # \u8ba1\u7b97token\u751f\u6210\u901f\u5ea6
\n if hasattr(response, "usage") and response.usage:
\n completion_tokens = response.usage.completion_tokens
\n if llm_latency > 0:
\n tokens_per_second = (completion_tokens \/ llm_latency) * 1000<\/p>\n return answer, llm_latency, tokens_per_second
\n except Exception as e:
\n llm_latency = (time.time() – start_time) * 1000
\n return f"\u5927\u6a21\u578b\u8c03\u7528\u5931\u8d25，\u9519\u8bef\u4fe1\u606f：{str(e)}", llm_latency, 0<\/p>\n def build_rag_prompt(user_query, search_results):
\n """\u6784\u5efaRAG\u63d0\u793a\u8bcd，\u5f3a\u5236\u5927\u6a21\u578b\u4ec5\u4f7f\u7528\u68c0\u7d22\u5230\u7684\u6587\u6863\u5185\u5bb9，\u51cf\u5c11\u5e7b\u89c9，\u5e26\u5f15\u6587\u6807\u6ce8"""
\n context = ""
\n citations = []
\n for idx, hit in enumerate(search_results, 1):
\n source = hit["_source"]
\n context += f"[{idx}] \u6587\u6863\u540d\u79f0：{source['file_name']}\\\\n\u6587\u6863\u5185\u5bb9：{source['file_content']}\\\\n\\\\n"
\n citations.append(f"[{idx}] {source['file_name']}")<\/p>\n # \u4e2d\u6587\u63d0\u793a\u8bcd，\u9002\u914d\u4e2d\u6587\u5927\u6a21\u578b，\u660e\u786e\u89c4\u5219\u51cf\u5c11\u5e7b\u89c9
\n prompt = f"""
\n \u8bf7\u4e25\u683c\u57fa\u4e8e\u4e0b\u9762\u63d0\u4f9b\u7684\u53c2\u8003\u6587\u6863，\u56de\u7b54\u7528\u6237\u7684\u95ee\u9898，\u5fc5\u987b\u9075\u5b88\u4ee5\u4e0b\u89c4\u5219：
\n 1. \u53ea\u4f7f\u7528\u53c2\u8003\u6587\u6863\u91cc\u7684\u5185\u5bb9\u56de\u7b54\u95ee\u9898，\u7edd\u5bf9\u4e0d\u80fd\u7f16\u9020\u53c2\u8003\u6587\u6863\u91cc\u6ca1\u6709\u7684\u4fe1\u606f
\n 2. \u6bcf\u5f15\u7528\u4e00\u53e5\u53c2\u8003\u6587\u6863\u7684\u5185\u5bb9，\u5fc5\u987b\u5728\u540e\u9762\u6807\u6ce8\u6765\u6e90，\u683c\u5f0f\u4e3a [1][2] \u8fd9\u6837\u7684\u7f16\u53f7
\n 3. \u56de\u7b54\u6761\u7406\u6e05\u6670，\u5206\u70b9\u8bf4\u660e\u6838\u5fc3\u5185\u5bb9，\u8bed\u8a00\u7b80\u6d01\u51c6\u786e
\n 4. \u5982\u679c\u53c2\u8003\u6587\u6863\u91cc\u6ca1\u6709\u548c\u95ee\u9898\u76f8\u5173\u7684\u5185\u5bb9，\u76f4\u63a5\u56de\u7b54\u201c\u672a\u5728\u77e5\u8bc6\u5e93\u4e2d\u627e\u5230\u76f8\u5173\u4fe1\u606f\u201d<\/p>\n \u53c2\u8003\u6587\u6863：
\n {context}<\/p>\n \u7528\u6237\u95ee\u9898：{user_query}
\n """
\n return prompt, citations<\/p>\n if __name__ == "__main__":
\n print("="*60)
\n print("🚀 \u3010\u5b8c\u5168\u79bb\u7ebf\u7248\u3011RAG\u4e2a\u4eba\u77e5\u8bc6\u5e93\u52a9\u624b \u542f\u52a8")
\n print("="*60)<\/p>\n # 1. \u68c0\u67e5ES\u8fde\u63a5
\n print("\\\\n===== 1. \u68c0\u67e5Elasticsearch\u8fde\u63a5 =====")
\n check_es_connect()<\/p>\n # 2. \u521b\u5efa\u79bb\u7ebf\u5d4c\u5165\u63a8\u7406\u7aef\u70b9
\n print("\\\\n===== 2. \u521d\u59cb\u5316\u79bb\u7ebf\u5d4c\u5165\u6a21\u578b =====")
\n setup_embedding_inference()<\/p>\n # 3. \u521b\u5efa\u77e5\u8bc6\u5e93\u7d22\u5f15
\n print("\\\\n===== 3. \u521d\u59cb\u5316\u77e5\u8bc6\u5e93\u7d22\u5f15 =====")
\n is_new_index = setup_knowledge_index()<\/p>\n # 4. \u65b0\u521b\u5efa\u7684\u7d22\u5f15\u81ea\u52a8\u5bfc\u5165\u6587\u6863
\n if is_new_index:
\n print("\\\\n===== 4. \u5bfc\u5165\u77e5\u8bc6\u5e93\u6587\u6863 =====")
\n import_count = bulk_index_documents()
\n if import_count == 0:
\n exit(1)
\n time.sleep(1) # \u7b49\u5f85\u7d22\u5f15\u5237\u65b0，\u786e\u4fdd\u6587\u6863\u53ef\u88ab\u68c0\u7d22<\/p>\n # 5. \u6267\u884cRAG\u95ee\u7b54
\n print("\\\\n===== 5. \u6267\u884cRAG\u667a\u80fd\u95ee\u7b54 =====")
\n # \u6b64\u5904\u53ef\u4fee\u6539\u4e3a\u4f60\u8981\u63d0\u95ee\u7684\u95ee\u9898，\u652f\u6301\u4e2d\u6587
\n USER_QUESTION = "\u8bf7\u603b\u7ed3API\u5b58\u5728\u7684\u6027\u80fd\u95ee\u9898"
\n print(f"🔍 \u7528\u6237\u95ee\u9898：{USER_QUESTION}")<\/p>\n # \u8bed\u4e49\u68c0\u7d22
\n search_results, search_latency = semantic_search(USER_QUESTION, top_n=3)
\n if not search_results:
\n print("\u274c \u672a\u5728\u77e5\u8bc6\u5e93\u4e2d\u627e\u5230\u76f8\u5173\u6587\u6863")
\n exit(0)
\n print(f"\u2705 \u627e\u5230 {len(search_results)} \u4e2a\u76f8\u5173\u6587\u6863，\u68c0\u7d22\u8017\u65f6：{search_latency:.0f}ms")<\/p>\n # \u6784\u5efaRAG\u63d0\u793a\u8bcd
\n rag_prompt, citations = build_rag_prompt(USER_QUESTION, search_results)<\/p>\n # \u8c03\u7528\u672c\u5730\u5927\u6a21\u578b\u751f\u6210\u7b54\u6848
\n print(f"\\\\n🤖 \u6b63\u5728\u8c03\u7528\u672c\u5730\u5927\u6a21\u578b {AI_MODEL_NAME} \u751f\u6210\u7b54\u6848…")
\n answer, llm_latency, tokens_per_second = call_local_llm(rag_prompt)<\/p>\n # \u8f93\u51fa\u6700\u7ec8\u7ed3\u679c
\n print("\\\\n" + "="*60)
\n print(f"💡 \u95ee\u9898：{USER_QUESTION}")
\n print(f"📝 \u7b54\u6848：\\\\n{answer}")
\n print("\\\\n📚 \u5f15\u7528\u6765\u6e90：")
\n for cite in citations:
\n print(f" {cite}")
\n print("\\\\n" + "="*60)
\n print(f"🔍 \u8bed\u4e49\u68c0\u7d22\u8017\u65f6：{search_latency:.0f}ms")
\n print(f"🤖 \u5927\u6a21\u578b\u751f\u6210\u8017\u65f6：{llm_latency:.0f}ms | \u751f\u6210\u901f\u5ea6：{tokens_per_second:.1f} tokens\/s")
\n print("\u2705 \u79bb\u7ebfRAG\u95ee\u7b54\u6267\u884c\u5b8c\u6210")<\/p>\n 6.4 \u8fd0\u884c\u811a\u672c<\/h4>\n# \u8fdb\u5165\u811a\u672c\u6240\u5728\u76ee\u5f55
\ncd \/opt\/rag-offline\/
\n# \u8fd0\u884c\u811a\u672c
\npython3 rag_offline.py<\/p>\n \u3010\u6210\u529f\u6821\u9a8c\u6807\u51c6\u3011<\/h5>\n\u811a\u672c\u6b63\u5e38\u6267\u884c，\u8f93\u51fa\u6700\u7ec8\u7684\u7b54\u6848\u3001\u5f15\u7528\u6765\u6e90\u548c\u6027\u80fd\u6570\u636e，\u65e0\u62a5\u9519，\u8bf4\u660e\u6574\u4e2a\u79bb\u7ebfRAG\u7cfb\u7edf\u90e8\u7f72\u6210\u529f！<\/p>\n
\n\u4e03\u3001\u79bb\u7ebf\u73af\u5883\u5e38\u89c1\u62a5\u9519\u4e0e\u7ec8\u6781\u89e3\u51b3\u65b9\u6848<\/h3>\n\n\u62a5\u9519\u73b0\u8c61\u6839\u56e0\u5206\u6790\u89e3\u51b3\u65b9\u6848<\/tr>\n \n\n| ES\u5bb9\u5668\u542f\u52a8\u540e，STATUS\u4e00\u76f4\u663e\u793aunhealthy<\/td>\n | \u76ee\u5f55\u6743\u9650\u4e0d\u8db3，ES\u5bb9\u5668\u5185\u90e8\u7528\u6237\u65e0\u6cd5\u8bfb\u5199\u5bbf\u4e3b\u673a\u76ee\u5f55<\/td>\n | \u6267\u884cchmod -R 777 \/opt\/rag-offline\/es\/，\u91cd\u542f\u5bb9\u5668<\/td>\n<\/tr>\n | \n| ES\u6a21\u578b\u52a0\u8f7d\u5931\u8d25，\u62a5\u9519model not found<\/td>\n | \u6a21\u578b\u6587\u4ef6\u672a\u653e\u5165\u6b63\u786e\u76ee\u5f55，\u6216\u6743\u9650\u4e0d\u8db3<\/td>\n | \u786e\u4fdd\u6a21\u578b\u6587\u4ef6\u89e3\u538b\u5230\/opt\/rag-offline\/es\/models\/\u76ee\u5f55，\u8d4b777\u6743\u9650，\u91cd\u542fES<\/td>\n<\/tr>\n | \n| LocalAI\u8c03\u7528\u62a5\u9519model not found<\/td>\n | \u5927\u6a21\u578b\u6587\u4ef6\u540d\u548c\u811a\u672c\u91cc\u7684AI_MODEL_NAME\u4e0d\u4e00\u81f4，\u6216\u672a\u653e\u5165\u6b63\u786e\u76ee\u5f55<\/td>\n | \u68c0\u67e5\u6587\u4ef6\u540d，\u5fc5\u987b\u5b8c\u5168\u4e00\u81f4（\u5305\u62ec.gguf\u540e\u7f00），\u653e\u5165\/opt\/rag-offline\/localai\/models\/\u76ee\u5f55<\/td>\n<\/tr>\n | \n| \u811a\u672c\u6267\u884c\u62a5\u9519ES\u8fde\u63a5\u5931\u8d25<\/td>\n | API\u5bc6\u94a5\u9519\u8bef\u3001ES\u670d\u52a1\u672a\u542f\u52a8\u3001\u7aef\u53e3\u88ab\u5360\u7528<\/td>\n | \u68c0\u67e5ES\u5bb9\u5668\u662f\u5426\u6b63\u5e38\u8fd0\u884c\u3001API\u5bc6\u94a5\u662f\u5426\u6b63\u786e\u30019200\u7aef\u53e3\u662f\u5426\u88ab\u5360\u7528<\/td>\n<\/tr>\n | \n| \u4e2d\u6587\u6587\u6863\u4e71\u7801<\/td>\n | \u6587\u6863\u975eUTF-8\u7f16\u7801，\u6216\u8bfb\u53d6\u65f6\u672a\u6307\u5b9a\u7f16\u7801<\/td>\n | \u7528\u8bb0\u4e8b\u672c\u6253\u5f00\u6587\u6863，\u53e6\u5b58\u4e3aUTF-8\u7f16\u7801，\u811a\u672c\u5df2\u6307\u5b9aencoding=\u201cutf-8\u201d<\/td>\n<\/tr>\n | \n| \u5927\u6a21\u578b\u751f\u6210\u7684\u7b54\u6848\u4e0e\u6587\u6863\u65e0\u5173\u3001\u51ed\u7a7a\u7f16\u9020<\/td>\n | \u6e29\u5ea6\u8bbe\u7f6e\u8fc7\u9ad8，\u6216\u63d0\u793a\u8bcd\u65e0\u6709\u6548\u7ea6\u675f<\/td>\n | \u5c06temperature\u6539\u4e3a0.1~0.3，\u786e\u4fdd\u63d0\u793a\u8bcd\u660e\u786e\u8981\u6c42\u4ec5\u4f7f\u7528\u53c2\u8003\u6587\u6863\u5185\u5bb9<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
\n\u516b\u3001\u79bb\u7ebf\u73af\u5883\u8fdb\u9636\u4f18\u5316<\/h3>\n- \n
\u591a\u683c\u5f0f\u6587\u6863\u652f\u6301：\u6269\u5c55\u811a\u672c，\u652f\u6301PDF\u3001Word\u3001Excel\u7b49\u683c\u5f0f，\u901a\u8fc7PyPDF2\u3001python-docx\u7b49\u5e93\u7684\u79bb\u7ebfwhl\u5305\u5b89\u88c5，\u63d0\u53d6\u6587\u672c\u540e\u5bfc\u5165ES<\/p>\n<\/li>\n - \n
Web\u53ef\u89c6\u5316\u754c\u9762：\u901a\u8fc7Streamlit\u79bb\u7ebf\u90e8\u7f72\u53ef\u89c6\u5316\u754c\u9762，\u5b9e\u73b0\u6587\u6863\u4e0a\u4f20\u3001\u95ee\u7b54\u4ea4\u4e92\u3001\u68c0\u7d22\u7ed3\u679c\u67e5\u770b，\u5168\u7a0b\u65e0\u5916\u7f51\u4f9d\u8d56<\/p>\n<\/li>\n - \n
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