本课程专为希望掌握LangChain技术的开发者和企业设计，涵盖从基础安装到高级应用的全面技能。通过23个实战模块，学员将学习如何构建智能问答系统、优化模型输出、使用链和代理进行复杂任务处理等。课程还包括如何利用LangChain进行数据库连接、异步通信机制的应用，以及如何部署和优化AI驱动的电商解决方案。无论您是AI新手还是希望提升现有技能的专业人士，本课程都将为您提供宝贵的知识和实践经验。
以下云资源目录树快照生成于[10个月前]，该学习资料由夸克云用户[端庄*白猫]分享（只展示大部分文件和目录）
LangChain实战：23项核心技能，从入门到企业级应用641.81 MB(png、jpg图片214张；pdf文档26个；)
开篇词｜带你亲证AI应用开发的“奇点”时刻.pdf5.29MB
开篇词｜带你亲证AI应用开发的“奇点”时刻.mp315.87MB
开篇词｜带你亲证AI应用开发的“奇点”时刻.md15.73KB结束语｜人生的价值就在于创造.pdf6.13MB结束语｜人生的价值就在于创造.mp35.64MB结束语｜人生的价值就在于创造.md4.46KB结课测试｜来赴一场满分之约.pdf391.42KB结课测试｜来赴一场满分之约.md495Byte23｜易速鲜花聊天客服机器人的开发（下）.pdf2.66MB23｜易速鲜花聊天客服机器人的开发（下）.mp313.89MB23｜易速鲜花聊天客服机器人的开发（下）.md16.15KB22｜易速鲜花聊天客服机器人的开发（上）.pdf4.05MB22｜易速鲜花聊天客服机器人的开发（上）.mp39.82MB22｜易速鲜花聊天客服机器人的开发（上）.md15.31KB21｜部署一个鲜花网络电商的人脉工具（下）.pdf8.73MB21｜部署一个鲜花网络电商的人脉工具（下）.mp39.5MB21｜部署一个鲜花网络电商的人脉工具（下）.md17.12KB20｜部署一个鲜花网络电商的人脉工具（上）.pdf11.06MB20｜部署一个鲜花网络电商的人脉工具（上）.mp313.98MB20｜部署一个鲜花网络电商的人脉工具（上）.md21.62KB19｜BabyAGI：根据气候变化自动制定鲜花存储策略.pdf3.13MB19｜BabyAGI：根据气候变化自动制定鲜花存储策略.mp314.1MB19｜BabyAGI：根据气候变化自动制定鲜花存储策略.md32.61KB18｜CAMEL：通过角色扮演脑暴一个鲜花营销方案.pdf6.2MB18｜CAMEL：通过角色扮演脑暴一个鲜花营销方案.mp316.64MB18｜CAMEL：通过角色扮演脑暴一个鲜花营销方案.md22.06KB17｜回调函数：在AI应用中引入异步通信机制.pdf2.13MB17｜回调函数：在AI应用中引入异步通信机制.mp312.26MB17｜回调函数：在AI应用中引入异步通信机制.md17.33KB16｜连接数据库：通过链和代理查询鲜花信息.pdf4.53MB16｜连接数据库：通过链和代理查询鲜花信息.mp313.47MB16｜连接数据库：通过链和代理查询鲜花信息.md14.08KB15｜检索增强生成：通过RAG助力鲜花运营.pdf7.39MB15｜检索增强生成：通过RAG助力鲜花运营.mp324.13MB15｜检索增强生成：通过RAG助力鲜花运营.md22.55KB14｜工具和工具箱：LangChain中的Tool和Toolkits一览.pdf6.87MB14｜工具和工具箱：LangChain中的Tool和Toolkits一览.mp316.9MB14｜工具和工具箱：LangChain中的Tool和Toolkits一览.md19.4KB13｜代理（下）：结构化工具对话、Self-AskwithSearch以及Planandexecute代理.pdf6.14MB13｜代理（下）：结构化工具对话、Self-AskwithSearch以及Planandexecute代理.mp317.66MB13｜代理（下）：结构化工具对话、Self-AskwithSearch以及Planandexecute代理.md19.29KB12｜代理（中）：AgentExecutor究竟是怎样驱动模型和工具完成任务的？.pdf19.3MB12｜代理（中）：AgentExecutor究竟是怎样驱动模型和工具完成任务的？.mp320.62MB12｜代理（中）：AgentExecutor究竟是怎样驱动模型和工具完成任务的？.md25.53KB11｜代理（上）：ReAct框架，推理与行动的协同.pdf4.21MB11｜代理（上）：ReAct框架，推理与行动的协同.mp313.27MB11｜代理（上）：ReAct框架，推理与行动的协同.md13.17KB10｜记忆：通过Memory记住客户上次买花时的对话细节.pdf4.07MB10｜记忆：通过Memory记住客户上次买花时的对话细节.mp316.02MB10｜记忆：通过Memory记住客户上次买花时的对话细节.md21.41KB09｜链（下）：想学“育花”还是“插花”？用RouterChain确定客户意图.pdf1.98MB09｜链（下）：想学“育花”还是“插花”？用RouterChain确定客户意图.mp316.77MB09｜链（下）：想学“育花”还是“插花”？用RouterChain确定客户意图.md16.69KB08｜链（上）：写一篇完美鲜花推文？用SequencialChain链接不同的组件.pdf3.62MB08｜链（上）：写一篇完美鲜花推文？用SequencialChain链接不同的组件.mp39.99MB08｜链（上）：写一篇完美鲜花推文？用SequencialChain链接不同的组件.md14.67KB07｜输出解析：用OutputParser生成鲜花推荐列表.pdf2.8MB07｜输出解析：用OutputParser生成鲜花推荐列表.mp321.3MB07｜输出解析：用OutputParser生成鲜花推荐列表.md27.61KB06｜调用模型：使用OpenAIAPI还是微调开源Llama2-ChatGLM？.pdf11.88MB06｜调用模型：使用OpenAIAPI还是微调开源Llama2-ChatGLM？.mp319.83MB06｜调用模型：使用OpenAIAPI还是微调开源Llama2-ChatGLM？.md22.45KB05｜提示工程（下）：用思维链和思维树提升模型思考质量.pdf3.17MB05｜提示工程（下）：用思维链和思维树提升模型思考质量.mp313.3MB05｜提示工程（下）：用思维链和思维树提升模型思考质量.md18.42KB04｜提示工程（上）：用少样本FewShotTemplate和ExampleSelector创建应景文案.pdf3.82MB04｜提示工程（上）：用少样本FewShotTemplate和ExampleSelector创建应景文案.mp318.7MB04｜提示工程（上）：用少样本FewShotTemplate和ExampleSelector创建应景文案.md24.8KB03｜模型I-O：输入提示、调用模型、解析输出.pdf2.8MB03｜模型I-O：输入提示、调用模型、解析输出.mp316.9MB03｜模型I-O：输入提示、调用模型、解析输出.md21.86KB02｜用LangChain快速构建基于“易速鲜花”本地知识库的智能问答系统.pdf4.85MB02｜用LangChain快速构建基于“易速鲜花”本地知识库的智能问答系统.mp315.48MB02｜用LangChain快速构建基于“易速鲜花”本地知识库的智能问答系统.md18.26KB01｜LangChain系统安装和快速入门.pdf10.68MB01｜LangChain系统安装和快速入门.mp325.33MB01｜LangChain系统安装和快速入门.md21.56KBimages
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