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尚硅谷-26年7月完 Agent智能体极速版 (零基础推荐)
FastAPI与SQLAlchemy深度结合，构建高效API
编辑点评
系统学习FastAPI框架，掌握SQLAlchemy数据库操作，构建高效后端服务。
⭐ 编辑推荐
从零基础开始，深入FastAPI框架与SQLAlchemy库的结合，学习构建现代Web API。
课程亮点
• FastAPI框架深度解析
• SQLAlchemy数据库操作
• 高效API构建实践
课程目录
📁 阶段03：FastAPI（2026年4月开始）
📁 1.笔记
尚硅谷大模型技术之FastAPI&SQLAlchemy1.0.docx [1.3 MB]
📁 4.视频
02-协程概述.mp4 [53.6 MB]
19-FastAPI和SQLAlchemy结合案例.mp4 [32.5 MB]
03-async和await.mp4 [31.2 MB]
16-SQLAlchemy环境准备.mp4 [64.8 MB]
18-通过表生成模型类.mp4 [37.8 MB]
09-FastAPI概述以及入门案例.mp4 [102.2 MB]
15-SQLAlchemy概述.mp4 [32.8 MB]
day01.torrent [21.7 KB]
12-FastAPI之查询参数.mp4 [84.4 MB]
08-WSGI和ASGI.mp4 [38.9 MB]
07-协程案例.mp4 [54.5 MB]
17-SQLAlchemy功能测试.mp4 [84.2 MB]
05-时间循环概述.mp4 [60.8 MB]
01-回顾.mp4 [24.5 MB]
11-FastAPI之路径参数.mp4 [39.3 MB]
10-FastAPI交互式API文档.mp4 [50.9 MB]
04-启动协程实现同步效果.mp4 [21.1 MB]
06-协程实现并发.mp4 [47.9 MB]
13-FastAPI之请求体参数.mp4 [37.1 MB]
14-FastAPI之路由分发.mp4 [43.7 MB]
📁 2.资料
📁 3.代码
📁 代码
📁 fastapi_project
📁 __pycache__
main.cpython-312.pyc [879.0 B]
📁 routers
📁 __pycache__
user.cpython-312.pyc [732.0 B]
item.cpython-312.pyc [732.0 B]
user.py [271.0 B]
item.py [271.0 B]
main.py [391.0 B]
📁 myproject
📁 __pycache__
fastapi_sqlalchemy.cpython-312.pyc [2.4 KB]
table_2_models.cpython-312.pyc [2.6 KB]
database.cpython-312.pyc [493.0 B]
database.py [683.0 B]
table_2_models.py [1.6 KB]
base.py [130.0 B]
fastapi_sqlalchemy.py [1.5 KB]
📁 fastapi_test
📁 __pycache__
main.cpython-312.pyc [4.5 KB]
main.py [3.7 KB]
📁 sqlalchemy_test
📁 __pycache__
models.cpython-312.pyc [1.6 KB]
base.cpython-312.pyc [263.0 B]
database.cpython-312.pyc [499.0 B]
table_2_models.cpython-312.pyc [2.6 KB]
base.py [130.0 B]
gen.py [2.5 KB]
main.py [3.6 KB]
database.py [683.0 B]
table_2_models.py [1.6 KB]
models.py [1.8 KB]
📁 async_await_test
test_one.py [219.0 B]
test_three.py [1.1 KB]
test_two.py [957.0 B]
阶段03：FastAPI（2026年4月开始）必看.zip [1.8 MB]
📁 阶段12：大模型部署、调优、评估
📁 课件
📁 部署
📁 images
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image-20260331144704905.png [27.3 KB]
image-20260515203836477.png [115.3 KB]
image-20260515203214085.png [291.7 KB]
GPU模型部署.md [34.7 KB]
应用服务部署.md [20.7 KB]
📁 评估与优化
📁 media
image1.png [211.8 KB]
image4.png [267.2 KB]
image8.png [24.2 KB]
image9.png [164.9 KB]
image3.png [48.5 KB]
image10.png [226.6 KB]
image11.png [103.5 KB]
image5.png [156.0 KB]
image7.png [135.4 KB]
image2.png [16.7 KB]
尚硅谷人工智能之知识库的评估与优化.md [33.7 KB]
课件资料.zip [1.8 MB]
课堂随笔.pptx [66.2 KB]
课堂随笔_0630202652.pptx [88.9 KB]
📁 资料
万用表RS-12的使用.pdf [1.4 MB]
hak180产品安全手册_new.md [14.8 KB]
万用表RS-12的使用_new.md [14.0 KB]
eval_bak.py [17.3 KB]
qa.csv [1.2 KB]
hak180产品安全手册.pdf [627.8 KB]
📁 视频
📁 day3 vibe coding
4 几个要点.mp4 [113.7 MB]
1 、spec coding流程.mp4 [304.6 MB]
3 pencil插件.mp4 [94.4 MB]
5 解决pencil连接的问题.mp4 [12.5 MB]
2 关于项目中使用skill.mp4 [166.0 MB]
📁 day2 部署
11 qwen3工具提示词.mp4 [121.3 MB]
15 下载镜像问题.mp4 [17.3 MB]
4 vllm发布qwen8b模型.mp4 [105.8 MB]
1 模型部署方案.mp4 [127.1 MB]
12 所有模型远端调用验证.mp4 [31.2 MB]
14 准备部署应用的材料.mp4 [168.4 MB]
13 部署应用要做的事.mp4 [209.0 MB]
2 服务部署架构.mp4 [51.8 MB]
16 关于部署的网络问题和图片问题.mp4 [103.1 MB]
6 reranker发布.mp4 [444.8 MB]
8 代码改动分析.mp4 [92.9 MB]
9 编写生成新的工具类的提示词.mp4 [76.2 MB]
5 bgem3发布.mp4 [216.9 MB]
3 在autodl上租服务器.mp4 [105.5 MB]
7 qwen远程测试.mp4 [98.2 MB]
10 m3和reranker测试通过.mp4 [156.0 MB]
📁 day1 评估优化
6 跑评估程序观察答案.mp4 [185.4 MB]
11 关于图谱的优化.mp4 [90.5 MB]
12 关于性能优化.mp4 [111.1 MB]
8 知识图谱原理.mp4 [248.0 MB]
9 展示问题.mp4 [46.3 MB]
7 解决切片丢失和提示词的问题.mp4 [520.8 MB]
5 生成评估程序.mp4 [173.4 MB]
2 ragas评估过程.mp4 [66.6 MB]
4 生成问题集.mp4 [110.6 MB]
3 ragas 的指标.mp4 [128.4 MB]
1 评估的目的和意义.mp4 [75.9 MB]
10 关于仓库地址.mp4 [10.2 MB]
📁 代码
eval.py [17.3 KB]
代码地址.txt [116.0 B]
📁 阶段15：大模型微调LLM
📁 3.视频
10_LLamaFactory安装&几个重要参数的设置经验.mp4 [173.8 MB]
09_PEFT_QLora原理2.mp4 [29.7 MB]
00_微调的价值.mp4 [78.5 MB]
15_LLamaFactory流程跑通.mp4 [151.5 MB]
01_微调流程1.mp4 [102.2 MB]
08_PEFT_QLora原理.mp4 [19.3 MB]
12_LLamaFactory其他参数解析.mp4 [40.7 MB]
16_LLamaFactory后续处理.mp4 [31.5 MB]
GPT-1架构-细节-情感分析任务架构图.svg [2.2 MB]
11_LLamaFacotry启动&训练参数解析.mp4 [98.3 MB]
02_微调流程2.mp4 [52.0 MB]
14_LLamaFactory指定本地模型.mp4 [54.1 MB]
13_LLamaFactory模型选择和下载.mp4 [15.3 MB]
03_显存估算&影响体验.mp4 [83.4 MB]
04_单GPU训练优化.mp4 [22.7 MB]
17_其他练习方式.mp4 [46.8 MB]
课堂随笔.txt [3.4 KB]
07_PEFT_Lora原理.mp4 [42.6 MB]
06_分布式训练介绍.mp4 [67.0 MB]
05_补充.mp4 [12.4 MB]
📁 2.资料
keywords_data_sharegpt.jsonl [35.7 MB]
keywords_data_sharegpt_small.jsonl [1.4 MB]
📁 4.微调实战
项目实战-微调.md [6.5 KB]
📁 1.课件
尚硅谷大模型极速版之模型微调-V1.0.docx [3.1 MB]
阶段15：大模型微调LLM说明.zip [1.8 MB]
📁 阶段11：AI智能客服（2026年6月）
📁 4.视频
📁 day09
📁 课堂笔记
📁 images
08-动作注册表.png [303.2 KB]
08-本节流程.png [1.1 MB]
05-七个字段总览.png [1.1 MB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
07-当前有活跃任务（打断场景）.png [1.1 MB]
03-YAML的嵌套层次.png [1.1 MB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
01-expire_on_commit参数.png [87.0 KB]
06-task 轨道的四重校验.png [1.1 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
01-expire_on_commit参数2.png [28.8 KB]
02-state的四个类关系.png [2.5 MB]
02-pending_turn完整流程图.png [3.7 MB]
02-一次对话轮次.png [3.8 MB]
06-SetSlotsCommand统一入口.png [751.3 KB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
06-生成回复.png [477.7 KB]
06-能否填槽的判断.png [1.1 MB]
06-校验的职责.png [1.1 MB]
05-把这一节串起来.png [1.1 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
04-读取状态.png [1.2 MB]
07-把五个分支汇成一张图：.png [1.2 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
06-场景C.png [1.0 MB]
06-场景B.png [1.1 MB]
03-边、节点、容器之间关系.png [4.6 MB]
01-组件关系.png [1.3 MB]
04-搭建三层.png [718.8 KB]
06-场景 A.png [1.1 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
06-校验以及对象消息流程.png [1.2 MB]
02-任务被另一个任务打断.png [3.7 MB]
06-完整流程.png [1.1 MB]
02-单任务正常完成.png [3.1 MB]
08-三种模式总览.png [1.1 MB]
05-predict.png [438.0 KB]
05-流程.png [1.1 MB]
06-validate 入口.png [1.1 MB]
05-对话处理流程.png [1.1 MB]
08-四个概念的协作.png [1.2 MB]
05-决策中枢.png [1.2 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
08-Action 在整个系统里的位置.png [344.5 KB]
03-加载流程全景.png [1.1 MB]
05-消息处理五步.png [1.1 MB]
02-三个会话方法的协作.png [3.9 MB]
07-TaskHandler 的两个阶段.png [357.0 KB]
04-整条链路.png [1.2 MB]
07-恢复与挂起全景.png [1.2 MB]
06-三分支.png [1.1 MB]
07-run 与 _apply.png [1.2 MB]
07-退款流程续接.png [1.2 MB]
02-DialogueState聚合根.png [3.8 MB]
04-三步编排.png [388.3 KB]
04-Web 层的本质.png [1.1 MB]
01-创建项目.png [75.3 KB]
06-ClarifyResponder 全貌.png [1.1 MB]
04-核心交互转换.png [331.7 KB]
04【电商小二】三层架构.md [27.5 KB]
07【电商小二】TaskHandler与CommandProcessor.md [26.3 KB]
08【电商小二】Action实现.md [28.5 KB]
02【电商小二】领域模型domain.md [66.6 KB]
05【电商小二】DialogueEngine 与 TurnPlanner的LLM调用.md [38.0 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
03【电商小二】流程数据模型与加载.md [62.3 KB]
06【电商小二】防幻觉校验与对象消息处理.md [43.6 KB]
05-尚硅谷-电商小二-resume流程中档有激活任务的时候系统过场的修改.mp4 [15.5 MB]
17-尚硅谷-电商小二-ActionResponse-自定义action的实现.mp4 [90.3 MB]
04-尚硅谷-电商小二-resume流程的实现.mp4 [186.9 MB]
customer-service-backend-day09.zip [136.7 KB]
16-尚硅谷-电商小二-ActionResponse-http中台api接口调用的通用方法的定义-shared.mp4 [5.5 MB]
11-尚硅谷-电商小二-ActionResponse-static分支的实现.mp4 [83.0 MB]
18-尚硅谷-电商小二-ActionResponse-注册action和依赖注入.mp4 [178.5 MB]
13-尚硅谷-电商小二-ActionResponse-llm处理.mp4 [85.6 MB]
06-尚硅谷-电商小二-resume流程中的场景测试.mp4 [38.8 MB]
08-尚硅谷-电商小二-上午总结.mp4 [78.7 MB]
09-尚硅谷-电商小二-ActionListen的实现.mp4 [15.3 MB]
14-尚硅谷-电商小二-ActionResponse-去黄.mp4 [25.9 MB]
09-尚硅谷-电商小二-Action模块各部分组件的作用.mp4 [107.4 MB]
03-尚硅谷-电商小二-resume流程的分支分析.mp4 [69.9 MB]
10-尚硅谷-电商小二-ActionResponse的分析.mp4 [79.3 MB]
01-尚硅谷-电商小二-day08回顾和_handle_cancel_flow方法的修改.mp4 [265.1 MB]
07-尚硅谷-电商小二-Action-介绍以及整体框架搭建1.mp4 [132.4 MB]
02-尚硅谷-电商小二-开启任务的五个分支.mp4 [168.2 MB]
12-尚硅谷-电商小二-ActionResponse-rephrase分支和generate分支分支的实现.mp4 [28.1 MB]
15-尚硅谷-电商小二-ActionResponse-http中台api接口调用的通用方法的定义.mp4 [157.4 MB]
📁 day04
📁 课堂笔记
📁 images
02-pending_turn完整流程图.png [3.7 MB]
03-加载流程全景.png [1.1 MB]
01-expire_on_commit参数.png [87.0 KB]
01-expire_on_commit参数2.png [28.8 KB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
04-三步编排.png [388.3 KB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
02-state的四个类关系.png [2.5 MB]
02-单任务正常完成.png [3.1 MB]
04-搭建三层.png [718.8 KB]
02-三个会话方法的协作.png [3.9 MB]
02-DialogueState聚合根.png [3.8 MB]
02-一次对话轮次.png [3.8 MB]
01-组件关系.png [1.3 MB]
04-整条链路.png [1.2 MB]
01-创建项目.png [75.3 KB]
04-读取状态.png [1.2 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
03-YAML的嵌套层次.png [1.1 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
04-Web 层的本质.png [1.1 MB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
04-核心交互转换.png [331.7 KB]
03-边、节点、容器之间关系.png [3.9 MB]
02-任务被另一个任务打断.png [3.7 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
03【电商小二】流程数据模型与加载.md [62.2 KB]
02【电商小二】领域模型domain.md [66.3 KB]
04【电商小二】三层架构.md [27.4 KB]
03-尚硅谷-电商小二-yml文件的加载和解析-slots的重复校验和多文件合并.mp4 [171.0 MB]
07-尚硅谷-电商小二-三层架构-两套模型的说明.mp4 [31.5 MB]
21-尚硅谷-电商小二-三层架构-程序的生命周期和数据库资源的初始化.mp4 [32.3 MB]
05-尚硅谷-电商小二-yml文件的加载和解析-flow中slots的的封装.mp4 [131.8 MB]
14-尚硅谷-电商小二-三层架构-持久层-数据插入.mp4 [68.6 MB]
customer-service-backend-day04.zip [78.3 KB]
11-尚硅谷-电商小二-三层架构-DDD领域驱动设计.mp4 [147.2 MB]
02-尚硅谷-电商小二-yml文件的加载和解析-现有yml文件加载流程的梳理.mp4 [76.3 MB]
08-尚硅谷-电商小二-三层架构-补充领域模型并定义接口模型.mp4 [89.8 MB]
10-尚硅谷-电商小二-上午总结.mp4 [24.3 MB]
20-尚硅谷-电商小二-三层架构-依赖注入.mp4 [128.7 MB]
22-尚硅谷-电商小二-三层架构-程序的运行和debug.mp4 [113.1 MB]
06-尚硅谷-电商小二-三层架构-什么是职责分离.mp4 [58.0 MB]
04-尚硅谷-电商小二-yml文件的加载和解析-flows的封装.mp4 [135.5 MB]
01-尚硅谷-电商小二-day03回顾.mp4 [115.2 MB]
13-尚硅谷-电商小二-三层架构-持久层-数据查询.mp4 [86.7 MB]
15-尚硅谷-电商小二-三层架构-引擎层.mp4 [34.5 MB]
09-尚硅谷-电商小二-三层架构-定义ORM模型.mp4 [53.1 MB]
16-尚硅谷-电商小二-三层架构-业务层.mp4 [46.9 MB]
17-尚硅谷-电商小二-三层架构-持久层和引擎层的存算分离思想.mp4 [35.4 MB]
图.drawio [11.5 KB]
12-尚硅谷-电商小二-三层架构-数据库基础设施层以及其他辅助模块总结.mp4 [34.1 MB]
18-尚硅谷-电商小二-三层架构-web层.mp4 [155.3 MB]
19-尚硅谷-电商小二-三层架构-到目前为止的总结.mp4 [39.1 MB]
📁 day07
📁 课堂笔记
📁 images
02-InterruptedSystemContext场景模拟.png [3.7 MB]
05-决策中枢.png [1.2 MB]
07-把五个分支汇成一张图：.png [1.2 MB]
01-expire_on_commit参数.png [87.0 KB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
1、对话处理流程.png [1.1 MB]
02-三个会话方法的协作.png [3.9 MB]
06-场景B.png [1.1 MB]
02-任务被另一个任务打断.png [3.7 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
05-七个字段总览.png [1.1 MB]
05-流程.png [1.1 MB]
06-场景 A.png [1.1 MB]
04-搭建三层.png [718.8 KB]
02-DialogueState聚合根.png [3.8 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
05-消息处理五步.png [1.1 MB]
06-场景C.png [1.0 MB]
05-把这一节串起来.png [1.1 MB]
06-validate 入口.png [1.1 MB]
07-恢复与挂起全景.png [1.2 MB]
07-run 与 _apply.png [1.2 MB]
02-pending_turn完整流程图.png [3.7 MB]
03-YAML的嵌套层次.png [1.1 MB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
04-整条链路.png [1.2 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
06-校验的职责.png [1.1 MB]
05-predict.png [438.0 KB]
07-TaskHandler 的两个阶段.png [357.0 KB]
02-一次对话轮次.png [3.8 MB]
01-expire_on_commit参数2.png [28.8 KB]
06-能否填槽的判断.png [1.1 MB]
04-Web 层的本质.png [1.1 MB]
03-加载流程全景.png [1.1 MB]
02-state的四个类关系.png [2.5 MB]
01-创建项目.png [75.3 KB]
06-校验以及对象消息流程.png [1.2 MB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
02-单任务正常完成.png [3.1 MB]
06-三分支.png [1.1 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
06-task 轨道的四重校验.png [1.1 MB]
03-边、节点、容器之间关系.png [4.6 MB]
04-读取状态.png [1.2 MB]
06-生成回复.png [477.7 KB]
04-三步编排.png [388.3 KB]
06-完整流程.png [1.1 MB]
04-核心交互转换.png [331.7 KB]
01-组件关系.png [1.3 MB]
06-SetSlotsCommand统一入口.png [751.3 KB]
06-ClarifyResponder 全貌.png [1.1 MB]
06【电商小二】防幻觉校验与对象消息处理.md [43.6 KB]
05【电商小二】DialogueEngine 与 TurnPlanner的LLM调用.md [38.0 KB]
02【电商小二】领域模型domain.md [66.6 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
04【电商小二】三层架构.md [27.5 KB]
07【电商小二】TaskHandler与CommandProcessor.md [24.4 KB]
03【电商小二】流程数据模型与加载.md [62.3 KB]
📁 prompts
clarify_respond.jinja2 [477.0 B]
08-尚硅谷-电商小二-knowledge_intentsz在业务流程中的使用.mp4 [53.9 MB]
06-尚硅谷-电商小二-创建和初始化KnowledgeHandler以及TurnPlanValidator.mp4 [105.4 MB]
05-尚硅谷-电商小二-上午总结.mp4 [57.0 MB]
07-尚硅谷-电商小二-组装提示词中的knowledge_intents_json.mp4 [103.4 MB]
12-尚硅谷-电商小二-加载和渲染提示词模版.mp4 [212.3 MB]
13-尚硅谷-电商小二-澄清结果实现流程梳理.mp4 [89.1 MB]
14-尚硅谷-电商小二-澄清结果测试.mp4 [107.8 MB]
02-尚硅谷-电商小二-turn_plan结果的合法性校验-业务流程校验.mp4 [233.2 MB]
03-尚硅谷-电商小二-KnowledgeIntent信息检索注册表.mp4 [83.0 MB]
17-尚硅谷-电商小二-对象消息的结果澄清.mp4 [171.7 MB]
09-尚硅谷-电商小二-文本消息类型-幻觉校验（合法性校验）不通过时的处理.mp4 [25.8 MB]
customer-service-backend-day07.zip [117.6 KB]
04-尚硅谷-电商小二-turn_plan结果的合法性校验-用户意图校验.mp4 [233.1 MB]
11-尚硅谷-电商小二-ClarifyResponder依赖注入.mp4 [15.3 MB]
16-尚硅谷-电商小二-传递对象消息以及前后端流程梳理.mp4 [122.7 MB]
10-尚硅谷-电商小二-澄清结果方法的定义.mp4 [135.4 MB]
01-尚硅谷-电商小二-节前内容梳理.mp4 [314.9 MB]
15-尚硅谷-电商小二-澄清结果测试2.mp4 [41.2 MB]
📁 day02
📁 课堂笔记
📁 images
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
02-state的四个类关系.png [2.5 MB]
02-pending_turn完整流程图.png [3.7 MB]
02-三个会话方法的协作.png [3.9 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
01-组件关系.png [1.3 MB]
02-任务被另一个任务打断.png [3.7 MB]
01-创建项目.png [75.3 KB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
01-expire_on_commit参数2.png [28.8 KB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
02-一次对话轮次.png [3.8 MB]
02-DialogueState聚合根.png [3.8 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
02-单任务正常完成.png [3.1 MB]
01-expire_on_commit参数.png [87.0 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
02【电商小二】领域模型domain.md [66.3 KB]
11-尚硅谷-电商小二-领域模型的设计-业务任务的流程推进和上下文的快照分析.mp4 [34.2 MB]
20-尚硅谷-电商小二-领域模型的设计-系统流程-任务恢复-场景2.mp4 [22.5 MB]
17-尚硅谷-电商小二-领域模型的设计-系统流程-任务取消-场景1.mp4 [37.2 MB]
12-尚硅谷-电商小二-领域模型的设计-系统流程的理解.mp4 [67.4 MB]
24-尚硅谷-电商小二-领域模型的设计-会话状态.mp4 [25.0 MB]
06-尚硅谷-电商小二-领域模型的设计-序列化和反序列化.mp4 [26.9 MB]
09-尚硅谷-电商小二-领域模型的设计-业务任务和系统流程.mp4 [68.8 MB]
32-尚硅谷-电商小二-领域模型的设计-会话状态-会话方法的协作.mp4 [20.9 MB]
23-尚硅谷-电商小二-领域模型的设计-区分联合类型.mp4 [63.4 MB]
33-尚硅谷-电商小二-领域模型的设计-会话状态-轮次相关方法.mp4 [69.7 MB]
21-尚硅谷-电商小二-领域模型的设计-系统流程-信息收集.mp4 [79.7 MB]
16-尚硅谷-电商小二-上午总结.mp4 [78.4 MB]
10-尚硅谷-电商小二-领域模型的设计-业务任务的上下文.mp4 [49.8 MB]
27-尚硅谷-电商小二-领域模型的设计-会话状态-所有属性的定义.mp4 [15.4 MB]
30-尚硅谷-电商小二-领域模型的设计-会话状态-会话相关的方法实现1.mp4 [44.2 MB]
13-尚硅谷-电商小二-领域模型的设计-系统流程-流程开始.mp4 [48.0 MB]
19-尚硅谷-电商小二-领域模型的设计-系统流程-任务恢复-场景1.mp4 [52.7 MB]
14-尚硅谷-电商小二-领域模型的设计-系统流程-任务中断-场景1.mp4 [52.7 MB]
34-尚硅谷-电商小二-领域模型的设计-会话状态-聚焦对象相关.mp4 [14.3 MB]
15-尚硅谷-电商小二-领域模型的设计-系统流程-任务中断-场景2.mp4 [66.3 MB]
01-尚硅谷-电商小二-day01总结和今日内容.mp4 [38.1 MB]
28-尚硅谷-电商小二-领域模型的设计-会话状态-任务相关的方法实现.mp4 [129.5 MB]
31-尚硅谷-电商小二-领域模型的设计-会话状态-会话相关的方法实现2.mp4 [29.9 MB]
26-尚硅谷-电商小二-领域模型的设计-会话状态-session和sessions.mp4 [23.6 MB]
customer-service-backend-day02.zip [25.0 KB]
18-尚硅谷-电商小二-领域模型的设计-系统流程-任务取消-场景2.mp4 [55.9 MB]
08-尚硅谷-电商小二-今天的目标的说明.mp4 [34.2 MB]
03-尚硅谷-电商小二-关于产品原型中的图片生成.mp4 [93.0 MB]
02-尚硅谷-电商小二-领域模型的设计-FocusedObject.mp4 [114.8 MB]
25-尚硅谷-电商小二-领域模型的设计-会话状态-会话轮次.mp4 [15.0 MB]
04-尚硅谷-电商小二-领域模型的设计-消息的枚举.mp4 [13.8 MB]
07-尚硅谷-电商小二-UML统一建模语言.mp4 [129.4 MB]
29-尚硅谷-电商小二-领域模型的设计-会话状态-槽位相关的方法实现.mp4 [15.8 MB]
05-尚硅谷-电商小二-领域模型的设计-用户消息和机器人消息.mp4 [21.0 MB]
22-尚硅谷-电商小二-领域模型的设计-序列化和反序列化的现有问题.mp4 [88.6 MB]
📁 day10
📁 课堂笔记
📁 images
02-三个会话方法的协作.png [3.9 MB]
09-整条链路.png [594.1 KB]
02-StartedSystemContext场景模拟.png [3.6 MB]
06-三分支.png [1.1 MB]
04-整条链路.png [1.2 MB]
03-加载流程全景.png [1.1 MB]
06-校验的职责.png [1.1 MB]
06-场景B.png [1.1 MB]
05-消息处理五步.png [1.1 MB]
06-场景 A.png [1.1 MB]
06-task 轨道的四重校验.png [1.1 MB]
09-外层循环.png [3.9 MB]
04-三步编排.png [388.3 KB]
02-一次对话轮次.png [3.8 MB]
01-expire_on_commit参数2.png [28.8 KB]
02-单任务正常完成.png [3.1 MB]
06-校验以及对象消息流程.png [1.2 MB]
06-validate 入口.png [1.1 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
05-对话处理流程.png [1.1 MB]
09-顺序为什么重要.png [3.8 MB]
08-三种模式总览.png [1.1 MB]
04-Web 层的本质.png [1.1 MB]
07-把五个分支汇成一张图：.png [1.2 MB]
09-尝试自动补槽.png [1.1 MB]
08-四个概念的协作.png [1.2 MB]
05-决策中枢.png [1.2 MB]
06-生成回复.png [477.7 KB]
04-搭建三层.png [718.8 KB]
03-YAML的嵌套层次.png [1.1 MB]
07-当前有活跃任务（打断场景）.png [1.1 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
06-场景C.png [1.0 MB]
04-读取状态.png [1.2 MB]
09-内层循环流程图.png [1.1 MB]
07-run 与 _apply.png [1.2 MB]
08-Action 在整个系统里的位置.png [344.5 KB]
01-创建项目.png [75.3 KB]
07-退款流程续接.png [1.2 MB]
08-动作注册表.png [303.2 KB]
01-组件关系.png [1.3 MB]
05-把这一节串起来.png [1.1 MB]
07-恢复与挂起全景.png [1.2 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
08-本节流程.png [1.1 MB]
06-能否填槽的判断.png [1.1 MB]
01-expire_on_commit参数.png [87.0 KB]
06-ClarifyResponder 全貌.png [1.1 MB]
02-DialogueState聚合根.png [3.8 MB]
04-核心交互转换.png [331.7 KB]
07-TaskHandler 的两个阶段.png [357.0 KB]
10-全貌.png [555.5 KB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
10-闲聊轨道全貌.png [427.5 KB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
09-FlowExecutor位置.png [565.9 KB]
09-3整体流程.png [3.9 MB]
06-完整流程.png [1.1 MB]
02-任务被另一个任务打断.png [3.7 MB]
05-predict.png [438.0 KB]
06-SetSlotsCommand统一入口.png [751.3 KB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
05-流程.png [1.1 MB]
05-七个字段总览.png [1.1 MB]
02-state的四个类关系.png [2.5 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
02-pending_turn完整流程图.png [3.7 MB]
03-边、节点、容器之间关系.png [4.6 MB]
04【电商小二】三层架构.md [27.5 KB]
10【电商小二】信息检索与闲聊.md [18.6 KB]
06【电商小二】防幻觉校验与对象消息处理.md [43.6 KB]
08【电商小二】Action实现.md [29.0 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
11【电商小二】历史对话实现.md [7.4 KB]
09【电商小二】FlowExecutor执行器.md [23.2 KB]
05【电商小二】DialogueEngine 与 TurnPlanner的LLM调用.md [38.0 KB]
07【电商小二】TaskHandler与CommandProcessor.md [26.3 KB]
02【电商小二】领域模型domain.md [66.6 KB]
03【电商小二】流程数据模型与加载.md [62.3 KB]
📁 prompts
chitchat_respond.jinja2 [560.0 B]
knowledge_respond.jinja2 [544.0 B]
19-尚硅谷-电商小二-知识库-整合和测试.mp4 [121.3 MB]
18-尚硅谷-电商小二-知识库-知识检索处理器.mp4 [102.8 MB]
09-尚硅谷-电商小二-FlowExecutor-使用eval计算ConditionalLink的表达式结果.mp4 [40.9 MB]
11-尚硅谷-电商小二-FlowExecutor_步骤end.mp4 [34.8 MB]
08-尚硅谷-电商小二-FlowExecutor-安全的eval.mp4 [56.6 MB]
04-尚硅谷-电商小二-FlowExecutor的外层循环.mp4 [90.1 MB]
13-尚硅谷-电商小二-FlowExecutor_步骤collect.mp4 [222.7 MB]
03-尚硅谷-电商小二-FlowExecutor的创建和初始化.mp4 [89.0 MB]
05-尚硅谷-电商小二-FlowExecutor的内层循环.mp4 [78.4 MB]
12-尚硅谷-电商小二-FlowExecutor_步骤action.mp4 [170.8 MB]
06-尚硅谷-电商小二-FlowExecutor的内执行流程的推进以及步骤start.mp4 [267.6 MB]
customer-service-backend-day10.zip [185.1 KB]
20-尚硅谷-电商小二-知识库-一个api.product案例测试.mp4 [20.5 MB]
02-尚硅谷-电商小二-FlowExecutor的作用.mp4 [31.4 MB]
14-尚硅谷-电商小二-一轮会话的完整测试.mp4 [464.7 MB]
15-尚硅谷-电商小二-闲聊功能的实现.mp4 [140.8 MB]
21-尚硅谷-电商小二-知识库-关于http_client的引入.mp4 [45.0 MB]
07-尚硅谷-电商小二-FlowExecutor-步骤推进中的ConditionalLink.mp4 [17.8 MB]
10-尚硅谷-电商小二-上午总结.mp4 [120.7 MB]
17-尚硅谷-电商小二-知识库-知识库提供者-注册表-回复生成器.mp4 [184.8 MB]
16-尚硅谷-电商小二-知识库-信息检索的意图.mp4 [19.5 MB]
01-尚硅谷-电商小二-day09总结.mp4 [214.6 MB]
📁 day06
📁 课堂笔记
📁 images
01-组件关系.png [1.3 MB]
04-读取状态.png [1.2 MB]
05-把这一节串起来.png [1.1 MB]
06-场景B.png [1.1 MB]
06-ClarifyResponder 全貌.png [1.1 MB]
05-流程.png [1.1 MB]
04-Web 层的本质.png [1.1 MB]
03-YAML的嵌套层次.png [1.1 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
04-整条链路.png [1.2 MB]
02-任务被另一个任务打断.png [3.7 MB]
04-三步编排.png [388.3 KB]
06-完整流程.png [1.1 MB]
06-场景 A.png [1.1 MB]
1、对话处理流程.png [1.1 MB]
06-场景C.png [1.0 MB]
05-决策中枢.png [1.2 MB]
06-SetSlotsCommand统一入口.png [1.0 MB]
05-predict.png [438.0 KB]
02-三个会话方法的协作.png [3.9 MB]
04-核心交互转换.png [331.7 KB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
06-三分支.png [1.1 MB]
01-expire_on_commit参数.png [87.0 KB]
06-生成回复.png [1.1 MB]
02-单任务正常完成.png [3.1 MB]
05-消息处理五步.png [1.1 MB]
06-validate 入口.png [1.1 MB]
04-搭建三层.png [718.8 KB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
02-state的四个类关系.png [2.5 MB]
06-task 轨道的四重校验.png [1.1 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
02-pending_turn完整流程图.png [3.7 MB]
05-七个字段总览.png [1.1 MB]
06-能否填槽的判断.png [1.1 MB]
01-创建项目.png [75.3 KB]
06-校验以及对象消息流程.png [1.2 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
02-一次对话轮次.png [3.8 MB]
03-加载流程全景.png [1.1 MB]
06-校验的职责.png [1.1 MB]
02-DialogueState聚合根.png [3.8 MB]
03-边、节点、容器之间关系.png [4.6 MB]
01-expire_on_commit参数2.png [28.8 KB]
02【电商小二】领域模型domain.md [66.3 KB]
06【电商小二】防幻觉校验与对象消息处理.md [37.0 KB]
05【电商小二】DialogueEngine 与 TurnPlanner的LLM调用.md [38.0 KB]
04【电商小二】三层架构.md [27.5 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
03【电商小二】流程数据模型与加载.md [62.3 KB]
09-尚硅谷-电商小二-校验结果模型的封装和九中原因码.mp4 [62.3 MB]
01-尚硅谷-电商小二-会话流程总结和梳理.mp4 [128.0 MB]
03-尚硅谷-电商小二-先执行一个发送请求的测试.mp4 [17.5 MB]
07-尚硅谷-电商小二-本章任务说明.mp4 [24.1 MB]
10-尚硅谷-电商小二-上午总结以及关于测试标准.mp4 [76.6 MB]
11-尚硅谷-电商小二-放幻觉校验以及原因码总结.mp4 [31.9 MB]
图.drawio [3.8 KB]
13-尚硅谷-电商小二-TurnPlanValidator校验主流程.mp4 [114.8 MB]
06-尚硅谷-电商小二-执行测试查看TurnPlan的三种情况.mp4 [125.7 MB]
02-尚硅谷-电商小二-程序运行前的两个问题的解决.mp4 [102.1 MB]
customer-service-backend-day06.zip [112.4 KB]
电商小二的面试指南.md [90.6 KB]
14-尚硅谷-电商小二-四重校验.mp4 [51.7 MB]
08-尚硅谷-电商小二-对话处理的关键流程（校验和澄清分离）.mp4 [40.6 MB]
05-尚硅谷-电商小二-关于关闭会话方法的修改.mp4 [4.4 MB]
15-尚硅谷-电商小二-四重校验的编码实现.mp4 [128.7 MB]
12-尚硅谷-电商小二-校验结果数据模型的定义.mp4 [32.6 MB]
04-尚硅谷-电商小二-一次会话执行的细节梳理.mp4 [263.3 MB]
📁 day08
📁 课堂笔记
📁 images
04-核心交互转换.png [331.7 KB]
06-三分支.png [1.1 MB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
01-组件关系.png [1.3 MB]
05-predict.png [438.0 KB]
06-场景C.png [1.0 MB]
02-state的四个类关系.png [2.5 MB]
06-完整流程.png [1.1 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
06-场景B.png [1.1 MB]
03-加载流程全景.png [1.1 MB]
02-DialogueState聚合根.png [3.8 MB]
02-任务被另一个任务打断.png [3.7 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
05-七个字段总览.png [1.1 MB]
05-流程.png [1.1 MB]
06-validate 入口.png [1.1 MB]
01-创建项目.png [75.3 KB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
02-一次对话轮次.png [3.8 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
06-场景 A.png [1.1 MB]
07-把五个分支汇成一张图：.png [1.2 MB]
04-搭建三层.png [718.8 KB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
01-expire_on_commit参数.png [87.0 KB]
06-校验以及对象消息流程.png [1.2 MB]
07-恢复与挂起全景.png [1.2 MB]
03-边、节点、容器之间关系.png [4.6 MB]
05-把这一节串起来.png [1.1 MB]
04-三步编排.png [388.3 KB]
06-校验的职责.png [1.1 MB]
04-整条链路.png [1.2 MB]
04-Web 层的本质.png [1.1 MB]
05-决策中枢.png [1.2 MB]
06-ClarifyResponder 全貌.png [1.1 MB]
05-消息处理五步.png [1.1 MB]
01-expire_on_commit参数2.png [28.8 KB]
02-pending_turn完整流程图.png [3.7 MB]
04-读取状态.png [1.2 MB]
06-生成回复.png [477.7 KB]
02-三个会话方法的协作.png [3.9 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
07-TaskHandler 的两个阶段.png [357.0 KB]
07-run 与 _apply.png [1.2 MB]
06-SetSlotsCommand统一入口.png [751.3 KB]
03-YAML的嵌套层次.png [1.1 MB]
06-能否填槽的判断.png [1.1 MB]
06-task 轨道的四重校验.png [1.1 MB]
02-单任务正常完成.png [3.1 MB]
1、对话处理流程.png [1.1 MB]
03【电商小二】流程数据模型与加载.md [62.3 KB]
06【电商小二】防幻觉校验与对象消息处理.md [43.6 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
02【电商小二】领域模型domain.md [66.6 KB]
07【电商小二】TaskHandler与CommandProcessor.md [25.0 KB]
05【电商小二】DialogueEngine 与 TurnPlanner的LLM调用.md [38.0 KB]
04【电商小二】三层架构.md [27.5 KB]
基于对象消息的业务流程的扩展步骤.txt [269.0 B]
08-尚硅谷-电商小二-上午总结.mp4 [87.7 MB]
11-尚硅谷-电商小二-创建命令处理器-四个辅助方法.mp4 [216.2 MB]
06-尚硅谷-电商小二-本章目标-流程推进-会话状态设置.mp4 [94.0 MB]
12-尚硅谷-电商小二-创建命令处理器-开启一个任务（普通版）.mp4 [65.6 MB]
03-尚硅谷-电商小二-对象消息-将对象消息转换成command-2 和 流程恰好需要订单号的场景.mp4 [182.4 MB]
07-尚硅谷-电商小二-重构DialogueState的resumed_active_task方法.mp4 [91.2 MB]
14-尚硅谷-电商小二-创建命令处理器-开启一个任务（完整版）-情况一.mp4 [252.9 MB]
15-尚硅谷-电商小二-创建命令处理器-填槽.mp4 [7.8 MB]
04-尚硅谷-电商小二-对象消息-场景2（没有流程需要澄清）和场景3（槽位已搜集或者槽位不匹配）.mp4 [154.4 MB]
13-尚硅谷-电商小二-创建命令处理器-开启一个任务（完整版）-情况二.mp4 [60.3 MB]
18-尚硅谷-电商小二-创建命令处理器-开启一个新任务（优化校验）.mp4 [18.8 MB]
02-尚硅谷-电商小二-对象消息-将对象消息转换成command-1.mp4 [271.5 MB]
09-尚硅谷-电商小二-TaskHandler 的两个阶段.mp4 [15.0 MB]
17-尚硅谷-电商小二-创建命令处理器-取消一个任务.mp4 [110.2 MB]
16-尚硅谷-电商小二-创建命令处理器-关于active_task是否被修改的补充.mp4 [22.8 MB]
05-尚硅谷-电商小二-对象消息-上节课总结.mp4 [21.5 MB]
10-尚硅谷-电商小二-创建命令处理器-CommandProcessor.mp4 [91.0 MB]
customer-service-backend-day08.zip [120.8 KB]
01-尚硅谷-电商小二-day07总结.mp4 [203.5 MB]
📁 day03
📁 课堂笔记
📁 images
01-expire_on_commit参数.png [87.0 KB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
01-组件关系.png [1.3 MB]
02-三个会话方法的协作.png [3.9 MB]
02-单任务正常完成.png [3.1 MB]
03-YAML的嵌套层次.png [1.1 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
01-创建项目.png [75.3 KB]
02-任务被另一个任务打断.png [3.7 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
02-DialogueState聚合根.png [3.8 MB]
02-pending_turn完整流程图.png [3.7 MB]
02-state的四个类关系.png [2.5 MB]
03- 加载流程全景.png [1.1 MB]
02-一次对话轮次.png [3.8 MB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
01-expire_on_commit参数2.png [28.8 KB]
03-边、节点、容器之间关系.png [3.9 MB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
03【电商小二】流程数据模型与加载.md [61.0 KB]
02【电商小二】领域模型domain.md [66.3 KB]
14-尚硅谷-电商小二-yml业务规则-next节点和yml业务定义的总结.mp4 [44.2 MB]
04-?????-????????-yml????????-???????.mp4 [25.6 MB]
08-尚硅谷-电商小二-yml业务规则-flow和step的定义.mp4 [52.3 MB]
22-尚硅谷-电商小二-yml文件相关模型的定义-step的base_fields方法的定义.mp4 [113.6 MB]
18-尚硅谷-电商小二-yml文件相关模型的定义-steps1.mp4 [155.7 MB]
09-尚硅谷-电商小二-yml业务规则-action.mp4 [54.0 MB]
26-尚硅谷-电商小二-yml文件相关模型的定义-flows中的模型的定义.mp4 [89.3 MB]
10-尚硅谷-电商小二-yml业务规则-action_response.mp4 [62.6 MB]
23-尚硅谷-电商小二-yml文件相关模型的定义-step的build_links方法的定义.mp4 [88.6 MB]
19-尚硅谷-电商小二-yml文件相关模型的定义-为什么要定义手动的dict to object的方法.mp4 [94.8 MB]
28-尚硅谷-电商小二-yml文件的加载和解析-加载两个文件.mp4 [109.9 MB]
06-尚硅谷-电商小二-yml业务规则-slots和slot的定义.mp4 [22.3 MB]
02-尚硅谷-电商小二-三种格式的配置文件.mp4 [44.8 MB]
11-尚硅谷-电商小二-yml业务规则-action_responsed的占位符.mp4 [7.8 MB]
29-尚硅谷-电商小二-yml文件的加载和解析-加载slots.mp4 [37.4 MB]
24-尚硅谷-电商小二-yml文件相关模型的定义-step中的ActionFlowStep的完善.mp4 [85.9 MB]
图.drawio [7.3 KB]
27-尚硅谷-电商小二-yml文件相关模型的定义-flows中的方法定义.mp4 [22.9 MB]
13-尚硅谷-电商小二-yml业务规则-其他的system_flow.mp4 [63.7 MB]
customer-service-backend-day03.zip [39.2 KB]
20-尚硅谷-电商小二-yml文件相关模型的定义-step的from_dict方法的定义.mp4 [61.9 MB]
25-尚硅谷-电商小二-yml文件相关模型的定义-step中的CollectFlowStep的完善.mp4 [41.9 MB]
07-尚硅谷-电商小二-yml业务规则-flows列表的定义.mp4 [15.5 MB]
17-尚硅谷-电商小二-上午总结.mp4 [68.4 MB]
15-尚硅谷-电商小二-yml文件的加载-目标说明.mp4 [25.7 MB]
12-尚硅谷-电商小二-yml业务规则-collect以及system_flows中的system_collect_information.mp4 [93.2 MB]
03-?????-????????-yml????????-???????.mp4 [28.7 MB]
21-尚硅谷-电商小二-yml文件相关模型的定义-上节课总结.mp4 [47.4 MB]
01-尚硅谷-电商小二-回顾和今日内容.mp4 [19.9 MB]
05-尚硅谷-电商小二-使用python读取yml文件.mp4 [47.3 MB]
16-尚硅谷-电商小二-yml文件相关模型的定义-links.mp4 [45.3 MB]
📁 day05
📁 课堂笔记
📁 images
02-任务被另一个任务打断.png [3.7 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
01-创建项目.png [75.3 KB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
02-单任务正常完成.png [3.1 MB]
05-七个字段总览.png [1.1 MB]
05-消息处理五步.png [1.1 MB]
03-加载流程全景.png [1.1 MB]
02-三个会话方法的协作.png [3.9 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
05-predict.png [438.0 KB]
04-三步编排.png [388.3 KB]
01-组件关系.png [1.3 MB]
04-Web 层的本质.png [1.1 MB]
03-YAML的嵌套层次.png [1.1 MB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
04-搭建三层.png [718.8 KB]
02-一次对话轮次.png [3.8 MB]
01-expire_on_commit参数2.png [28.8 KB]
04-核心交互转换.png [331.7 KB]
03-边、节点、容器之间关系.png [4.6 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
04-读取状态.png [1.2 MB]
02-state的四个类关系.png [2.5 MB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
05-流程.png [1.1 MB]
05-决策中枢.png [1.2 MB]
02-DialogueState聚合根.png [3.8 MB]
04-整条链路.png [1.2 MB]
05-把这一节串起来.png [1.1 MB]
01-expire_on_commit参数.png [87.0 KB]
02-pending_turn完整流程图.png [3.7 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
02【电商小二】领域模型domain.md [66.3 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
03【电商小二】流程数据模型与加载.md [62.3 KB]
05【电商小二】DialogueEngine 与 TurnPlanner的LLM调用.md [36.3 KB]
04【电商小二】三层架构.md [27.4 KB]
📁 prompts
📁 jinja2
__init__.py
turn_plan.jinja2 [2.1 KB]
__init__.py
16-尚硅谷-电商小二-提示词模板分析.mp4 [75.3 MB]
10-尚硅谷-电商小二-文本消息的处理-TurnPlan模型和Command模型的定义2.mp4 [55.2 MB]
23-尚硅谷-电商小二-组装TaskHandler和turn_planner.mp4 [74.7 MB]
13-尚硅谷-电商小二-模型处理-XxxTurnPlan的dict转模型.mp4 [89.1 MB]
24-尚硅谷-电商小二-组装提示词模板.mp4 [350.2 MB]
15-尚硅谷-电商小二-接下来要做的事情分析.mp4 [19.0 MB]
19-尚硅谷-电商小二-提示词模板分析-渲染一个基于磁盘的模板.mp4 [63.3 MB]
customer-service-backend-day05.zip [99.4 KB]
03-尚硅谷-电商小二-消息处理的主流程.mp4 [14.7 MB]
04-尚硅谷-电商小二-消息处理的主流程-引擎代码的编写.mp4 [63.7 MB]
18-尚硅谷-电商小二-提示词模板分析-渲染一个基于内存的模板.mp4 [14.0 MB]
22-尚硅谷-电商小二-提示词各部分总结.mp4 [30.4 MB]
17-尚硅谷-电商小二-提示词模板分析-模板引擎.mp4 [75.1 MB]
05-尚硅谷-电商小二-消息处理的主流程-开启新会话.mp4 [44.6 MB]
21-尚硅谷-电商小二-组织历史会话记录字符串.mp4 [195.9 MB]
02-尚硅谷-电商小二-引擎的主要任务.mp4 [76.8 MB]
01-尚硅谷-电商小二-day04总结.mp4 [121.5 MB]
06-尚硅谷-电商小二-消息处理的主流程-开启新轮次.mp4 [11.4 MB]
08-尚硅谷-电商小二-文本消息的处理-主流程实现.mp4 [110.0 MB]
12-尚硅谷-电商小二-模型处理-Command的dict转模型.mp4 [47.6 MB]
09-尚硅谷-电商小二-文本消息的处理-TurnPlan模型和Command模型的定义1.mp4 [37.5 MB]
14-尚硅谷-电商小二-模型处理-上午总结以及Turn的模型转换.mp4 [163.7 MB]
11-尚硅谷-电商小二-文本消息的处理-TurnPlan模型和Command模型的定义3.mp4 [110.8 MB]
20-尚硅谷-电商小二-加载程序中的模板文件.mp4 [37.9 MB]
07-尚硅谷-电商小二-消息处理的主流程-上节课总结.mp4 [19.4 MB]
📁 day01
📁 课堂笔记
📁 images
02-三个会话方法的协作.png [3.9 MB]
02-一次对话轮次.png [3.8 MB]
02-CanceledSystemContext场景模拟.png [2.9 MB]
02-DialogueState聚合根.png [3.8 MB]
02-pending_turn完整流程图.png [3.7 MB]
01-expire_on_commit参数.png [87.0 KB]
02-CollectSystemContext：收集槽位场景模拟.png [3.6 MB]
02-StartedSystemContext场景模拟.png [3.6 MB]
01-expire_on_commit参数2.png [28.8 KB]
01-组件关系.png [1.3 MB]
02-InterruptedSystemContext 打断两个任务(连环打断).png [4.2 MB]
02-InterruptedSystemContext场景模拟.png [3.7 MB]
02-任务被另一个任务打断.png [3.7 MB]
02-ResumedSystemContext LIFO 默认恢复(用户没指明恢复哪个).png [3.4 MB]
02-state的四个类关系.png [2.5 MB]
01-创建项目.png [75.3 KB]
02-单任务正常完成.png [3.1 MB]
02-ResumedSystemContext 精确恢复 (用户明确指明).png [4.4 MB]
02-CanceledSystemContext 取消挂起的任务场景模拟.png [3.6 MB]
02【电商小二】领域模型domain.md [65.9 KB]
01【电商小二】项目概述与整体架构.md [31.9 KB]
05-尚硅谷-电商小二-docker容器启动的常见问题和解决方案.mp4 [11.3 MB]
22-2-尚硅谷-电商小二-异步httpx包引入的问题.mp4 [3.1 MB]
24-尚硅谷-电商小二-访问数据库-同步测试2.mp4 [41.2 MB]
13-尚硅谷-电商小二-服务功能的数理.mp4 [47.1 MB]
26-尚硅谷-电商小二-访问数据库-异步工具的定义1.mp4 [92.5 MB]
21-尚硅谷-电商小二-llm客户端创建.mp4 [10.2 MB]
customer-service-backend-day01.zip [120.1 KB]
10-尚硅谷-电商小二-AI客服的三大能力-1流程类.mp4 [68.7 MB]
03-尚硅谷-电商小二-在widnows中还原MySQL脚本.mp4 [41.3 MB]
16-尚硅谷-电商小二-创建AI客服项目.mp4 [62.8 MB]
27-尚硅谷-电商小二-访问数据库-异步工具的定义2.mp4 [85.4 MB]
图.drawio [5.5 KB]
02-尚硅谷-电商小二-项目整体环境.mp4 [6.7 MB]
12-尚硅谷-电商小二-AI客服的三大能力-3闲聊以及三条轨道之间的关系.mp4 [8.1 MB]
06-尚硅谷-电商小二-中台项目的启动和测试.mp4 [130.4 MB]
01-尚硅谷-电商小二-项目介绍.mp4 [14.4 MB]
17-尚硅谷-电商小二-上午总结和下午内容.mp4 [79.5 MB]
19-尚硅谷-电商小二-pydantic-settings读取配置的实现.mp4 [81.7 MB]
25-尚硅谷-电商小二-访问数据库-异步方式访问.mp4 [123.3 MB]
07-尚硅谷-电商小二-前端项目的启动和测试.mp4 [32.9 MB]
04-尚硅谷-电商小二-在docker中运行MySQL服务.mp4 [67.2 MB]
14-尚硅谷-电商小二-系统架构设计.mp4 [25.9 MB]
09-尚硅谷-电商小二-项目开发的背景.mp4 [17.6 MB]
08-尚硅谷-电商小二-代理和反向代理的概念以及组件之间的关系.mp4 [150.8 MB]
18-尚硅谷-电商小二-pydantic-settings的作用.mp4 [32.1 MB]
11-尚硅谷-电商小二-AI客服的三大能力-2信息检索.mp4 [20.1 MB]
23-尚硅谷-电商小二-访问数据库-同步测试1.mp4 [87.9 MB]
15-尚硅谷-电商小二-一轮会话的完整流程以及项目分层结构.mp4 [42.1 MB]
22-1-尚硅谷-电商小二-异步http远程访问.mp4 [118.4 MB]
20-尚硅谷-电商小二-环境变量误删还原.mp4 [9.9 MB]
📁 1.笔记
10-DialogueEngine实现.md [12.3 KB]
此处课件仅为参考，上课课件内容见 视频目录 每天的文件夹的 课堂笔记.txt
09-TurnPlanner实现.md [23.1 KB]
07-KnowledgeHandler实现.md [10.9 KB]
02-对话状态设计.md [9.8 KB]
01-尚硅谷大模型项目之电商小二.md [11.8 KB]
客服后端接口文档.md [2.9 KB]
04-TaskHandler设计.md [33.9 KB]
03-DialogueEngine设计.md [7.6 KB]
08-ChitChatHandler实现.md [2.9 KB]
11-FastAPI依赖注入和生命周期.md [1.6 KB]
05-KnowledgeHandler&ChitChatHandler设计.md [4.4 KB]
06-TaskHandler实现.md [40.6 KB]
📁 3.代码
📁 2.资料
📁 前端、中台项目
📁 ecommerce-service-backend
📁 app
📁 __pycache__
models.cpython-312.pyc [7.8 KB]
app.cpython-312.pyc [977.0 B]
schemas.cpython-312.pyc [4.4 KB]
__init__.cpython-312.pyc [225.0 B]
database.cpython-312.pyc [978.0 B]
config.cpython-312.pyc [950.0 B]
api.cpython-312.pyc [15.4 KB]
models.py [5.2 KB]
schemas.py [1.9 KB]
__init__.py [41.0 B]
config.py [331.0 B]
app.py [830.0 B]
api.py [10.7 KB]
database.py [531.0 B]
README.md [1.0 KB]
.env.example [115.0 B]
pyproject.toml [388.0 B]
uv.lock [88.0 KB]
main.py [652.0 B]
📁 customer-service-frontend
📁 src
📁 assets
xiaoer.png [3.7 MB]
userProfileAvatar.svg [5.2 KB]
logo.webp [11.6 KB]
App.vue [57.7 KB]
main.js [90.0 B]
package.json [321.0 B]
vite.config.js [556.0 B]
package-lock.json [42.3 KB]
index.html [305.0 B]
📁 customer-service-backend
📁 flow_config
__init__.py
user_flows.yml [4.9 KB]
system_flows.yml [5.6 KB]
uv.lock [326.6 KB]
pyproject.toml [461.0 B]
.env.example [276.0 B]
📁 docker
📁 mysql
📁 initdb
001_init_customer_service.sql [520.0 B]
002_init_commerce.sql [13.6 KB]
📁 windows
📁 initdb
001_init_customer_service.sql [438.0 B]
002_init_commerce.sql [13.5 KB]
docker-compose.yml [471.0 B]
阶段11：AI智能客服（2026年6月）文档.zip [1.8 MB]
📁 阶段09：智能体项目：Agent单智能体智数
📁 day04
📁 视频
13-尚硅谷-掌柜问数-语言模型初始化.mp4 [38.6 MB]
15-尚硅谷-掌柜问数-召回字段信息.mp4 [218.8 MB]
11-尚硅谷-掌柜问数-langgraph流演示.mp4 [61.1 MB]
03-尚硅谷-掌柜问数-保存指标信息.mp4 [100.8 MB]
01-尚硅谷-掌柜问数-内容回顾概述.mp4 [32.6 MB]
08-尚硅谷-掌柜问数-构建智能体节点.mp4 [65.7 MB]
14-尚硅谷-掌柜问数-提取关键字实现.mp4 [115.6 MB]
12-尚硅谷-掌柜问数-提示词加载定义.mp4 [25.7 MB]
02-尚硅谷-掌柜问数-取值全文索引.mp4 [232.7 MB]
07-尚硅谷-掌柜问数-Node节点Runtime.mp4 [94.0 MB]
06-尚硅谷-掌柜问数-智能体概述.mp4 [50.0 MB]
05-尚硅谷-掌柜问数-整体调整测试.mp4 [127.4 MB]
09-尚硅谷-掌柜问数-构建langgraph图.mp4 [164.7 MB]
10-尚硅谷-掌柜问数-langgraph流概念.mp4 [54.1 MB]
04-尚硅谷-掌柜问数-保存指标向量.mp4 [186.7 MB]
📁 课件
📁 assets
image-20260302164313014.png [254.0 KB]
image-20260121215240284.png [34.4 KB]
image-20260207161919313.png [88.2 KB]
image-20260121184748743.png [51.2 KB]
image-20260121204009373.png [54.5 KB]
掌柜问数项目-问数智能体.drawio.svg [274.8 KB]
wps4.jpg [73.4 KB]
image-20260303152708134.png [56.2 KB]
image-20260121202229381.png [34.2 KB]
image-20260121223015280.png [49.2 KB]
image-20260311204041206.png [34.0 KB]
image-20260207140320440.png [21.8 KB]
image-20260302193512226.png [36.1 KB]
image-20260302160651463.png [43.4 KB]
image-20260302145219771.png [37.5 KB]
wps7.jpg [130.8 KB]
image-20260121201903693.png [47.5 KB]
image-20260302164430508.png [20.8 KB]
image-20260312164049033.png [89.1 KB]
image-20260301202214037.png [26.0 KB]
image-20260207140352763.png [65.8 KB]
wps6.png [626.0 KB]
image-20260302193437126.png [35.3 KB]
image-20260311204011515.png [34.7 KB]
image-20260207142744497.png [48.0 KB]
wps2.jpg [48.0 KB]
image-20260302192049010.png [43.8 KB]
image-20260312162206045.png [69.2 KB]
image-20260121203227857.png [24.3 KB]
wps3.png [26.8 KB]
wps5.jpg [112.5 KB]
image-20260301202052447.png [31.7 KB]
image-20260302193422656.png [35.7 KB]
wps1.jpg [48.0 KB]
image-20260121202402103.png [76.9 KB]
image-20260302165403928.png [48.5 KB]
image-20260302144433733.png [66.1 KB]
image-20260312185315752.png [102.1 KB]
尚硅谷大模型项目之掌柜问数.md [243.4 KB]
📁 代码
📁 data-agent
📁 conf
app_config.yaml [674.0 B]
text_config.yaml [72.0 B]
meta_config.yaml [4.8 KB]
📁 prompts
filter_table_info.prompt [2.1 KB]
plan_sql.prompt [2.5 KB]
correct_sql.prompt [1.9 KB]
generate_sql.prompt [1.2 KB]
filter_metric_info.prompt [2.2 KB]
extend_keywords_for_column_recall.prompt [1.9 KB]
extend_keywords_for_metric_recall.prompt [2.2 KB]
extend_keywords_for_value_recall.prompt [1.6 KB]
📁 app
📁 agent
📁 __pycache__
__init__.cpython-311.pyc [173.0 B]
context.cpython-311.pyc [785.0 B]
llm.cpython-311.pyc [759.0 B]
state.cpython-311.pyc [746.0 B]
📁 nodes
📁 __pycache__
filter_table.cpython-311.pyc [843.0 B]
execute_sql.cpython-311.pyc [833.0 B]
recall_metric.cpython-311.pyc [841.0 B]
extract_keywords.cpython-311.pyc [1.7 KB]
filter_metric.cpython-311.pyc [840.0 B]
__init__.cpython-311.pyc [179.0 B]
validata_sql.cpython-311.pyc [1.3 KB]
recall_column.cpython-311.pyc [2.9 KB]
recall_value.cpython-311.pyc [846.0 B]
add_extra_context.cpython-311.pyc [932.0 B]
generate_sql.cpython-311.pyc [836.0 B]
correct_sql.cpython-311.pyc [833.0 B]
merge_retrieved_info.cpython-311.pyc [862.0 B]
__init__.py
generate_sql.py [379.0 B]
add_extra_context.py [459.0 B]
execute_sql.py [390.0 B]
merge_retrieved_info.py [396.0 B]
validata_sql.py [705.0 B]
recall_column.py [2.6 KB]
filter_table.py [387.0 B]
extract_keywords.py [1.6 KB]
correct_sql.py [390.0 B]
filter_metric.py [395.0 B]
recall_metric.py [385.0 B]
recall_value.py [390.0 B]
📁 logs
app.log [3.7 KB]
llm.py [361.0 B]
context.py [328.0 B]
__init__.py
graph.py [3.9 KB]
state.py [234.0 B]
📁 prompt
📁 __pycache__
prompt_loader.cpython-311.pyc [810.0 B]
__init__.cpython-311.pyc [174.0 B]
__init__.py
prompt_loader.py [312.0 B]
📁 repositories
📁 __pycache__
__init__.cpython-311.pyc [180.0 B]
📁 qdrant
📁 __pycache__
column_qdrant_repository.cpython-311.pyc [4.0 KB]
__init__.cpython-311.pyc [187.0 B]
metric_qdrant_repository.cpython-311.pyc [3.3 KB]
__init__.py
metric_qdrant_repository.py [2.1 KB]
column_qdrant_repository.py [2.5 KB]
📁 es
📁 __pycache__
value_es_repository.cpython-311.pyc [2.7 KB]
__init__.cpython-311.pyc [183.0 B]
value_es_repository.py [2.0 KB]
__init__.py
📁 mysql
📁 __pycache__
__init__.cpython-311.pyc [186.0 B]
meta_mysql_repository.cpython-311.pyc [2.7 KB]
dw_mysql_repository.cpython-311.pyc [2.4 KB]
__init__.py
dw_mysql_repository.py [1.2 KB]
meta_mysql_repository.py [1.4 KB]
__init__.py
📁 conf
📁 __pycache__
app_config.cpython-311.pyc [3.7 KB]
meta_config.cpython-311.pyc [1.9 KB]
__init__.cpython-311.pyc [172.0 B]
text_config.cpython-311.pyc [1.2 KB]
text_config.py [844.0 B]
app_config.py [1.2 KB]
meta_config.py [574.0 B]
__init__.py
📁 core
📁 __pycache__
context.cpython-311.pyc [306.0 B]
log.cpython-311.pyc [3.8 KB]
__init__.cpython-311.pyc [172.0 B]
📁 logs
app.log [188.0 B]
context.py [86.0 B]
file_2026-05-29_09-04-20_477303.log [293.0 B]
log.py [3.6 KB]
__init__.py
📁 __pycache__
__init__.cpython-311.pyc [167.0 B]
📁 models
📁 qdrant
📁 __pycache__
column_info_qdrant.cpython-311.pyc [727.0 B]
__init__.cpython-311.pyc [181.0 B]
metric_info_qdrant.cpython-311.pyc [659.0 B]
column_info_qdrant.py [196.0 B]
metric_info_qdrant.py [158.0 B]
__init__.py
📁 es
📁 __pycache__
__init__.cpython-311.pyc [177.0 B]
value_info_es.cpython-311.pyc [689.0 B]
__init__.py
value_info_es.py [182.0 B]
📁 mysql
📁 __pycache__
column_info_mysql.cpython-311.pyc [2.1 KB]
column_metric_mysql.cpython-311.pyc [1.1 KB]
table_info_mysql.cpython-311.pyc [1.4 KB]
base.cpython-311.pyc [469.0 B]
metric_info_mysql.cpython-311.pyc [1.6 KB]
__init__.cpython-311.pyc [180.0 B]
metric_info_mysql.py [807.0 B]
column_metric_mysql.py [457.0 B]
base.py [86.0 B]
__init__.py
column_info_mysql.py [1.1 KB]
table_info_mysql.py [640.0 B]
📁 __pycache__
__init__.cpython-311.pyc [174.0 B]
__init__.py
📁 services
📁 __pycache__
__init__.cpython-311.pyc [176.0 B]
meta_knowledge_service.cpython-311.pyc [14.6 KB]
__init__.py
meta_knowledge_service.py [13.4 KB]
📁 clients
📁 __pycache__
es_client_manager.cpython-311.pyc [3.2 KB]
qdrant_client_manager.cpython-311.pyc [3.6 KB]
mysql_client_manager.cpython-311.pyc [3.7 KB]
__init__.cpython-311.pyc [175.0 B]
embedding_client_manager.cpython-311.pyc [2.1 KB]
__init__.py
mysql_client_manager.py [2.0 KB]
qdrant_client_manager.py [2.4 KB]
es_client_manager.py [4.2 KB]
embedding_client_manager.py [1.3 KB]
📁 scripts
📁 __pycache__
__init__.cpython-311.pyc [175.0 B]
build_meta_knowledge.cpython-311.pyc [4.0 KB]
📁 logs
app.log [1.4 KB]
build_meta_knowledge.py [2.6 KB]
__init__.py
__init__.py
📁 .idea
📁 dataSources
📁 0deae914-40e2-4145-9ff2-eeba6054ba72
📁 storage_v2
📁 _src_
📁 schema
information_schema.FNRwLQ.meta [76.0 B]
performance_schema.kIw0nw.meta [76.0 B]
0deae914-40e2-4145-9ff2-eeba6054ba72.xml [46.3 KB]
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
modules.xml [279.0 B]
dataSources.xml [530.0 B]
workspace.xml [14.7 KB]
sqldialects.xml [296.0 B]
dataSources.local.xml [1.1 KB]
data_agent.iml [404.0 B]
.gitignore [238.0 B]
misc.xml [300.0 B]
📁 docker
📁 mysql
dw.sql [15.5 KB]
meta.sql [1.5 KB]
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
📁 embedding
📁 bge-large-zh-v1.5
📁 1_Pooling
config.json [191.0 B]
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
…（层级过深，已停止）
config_sentence_transformers.json.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
special_tokens_map.json.metadata [104.0 B]
config.json.metadata [104.0 B]
modules.json.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
pytorch_model.bin.metadata [127.0 B]
tokenizer_config.json.metadata [103.0 B]
tokenizer.json.metadata [104.0 B]
README.md.metadata [104.0 B]
.gitignore [1.0 B]
vocab.txt [107.0 KB]
sentence_bert_config.json [52.0 B]
tokenizer_config.json [394.0 B]
modules.json [349.0 B]
config.json [1000.0 B]
tokenizer.json [428.8 KB]
pytorch_model.bin [1.2 GB]
README.md [29.7 KB]
.gitattributes [1.5 KB]
special_tokens_map.json [125.0 B]
config_sentence_transformers.json [124.0 B]
📁 .venv
📁 Scripts
python.exe [256.0 KB]
activate.bat [2.6 KB]
deactivate.bat [1.7 KB]
activate.fish [4.1 KB]
activate_this.py [2.3 KB]
activate.nu [3.7 KB]
activate.csh [2.6 KB]
activate.ps1 [2.7 KB]
pydoc.bat [1.2 KB]
pythonw.exe [244.0 KB]
activate [4.0 KB]
📁 Lib
📁 site-packages
_virtualenv.py [4.2 KB]
_virtualenv.pth [18.0 B]
pyvenv.cfg [198.0 B]
.gitignore [1.0 B]
CACHEDIR.TAG [43.0 B]
docker-compose.yaml [1.6 KB]
📁 logs
app.log [11.4 KB]
pyproject.toml [566.0 B]
main.py [544.0 B]
uv.lock [767.7 KB]
📁 截图
01-提过过期处理.png [126.1 KB]
02-智能题体流式输出.png [57.4 KB]
📁 资料
📁 prompts
plan_sql.prompt [2.5 KB]
filter_metric_info.prompt [2.2 KB]
generate_sql.prompt [1.2 KB]
correct_sql.prompt [1.9 KB]
extend_keywords_for_value_recall.prompt [1.6 KB]
filter_table_info.prompt [2.1 KB]
extend_keywords_for_metric_recall.prompt [2.2 KB]
extend_keywords_for_column_recall.prompt [1.9 KB]
day04说明.png [493.5 KB]
📁 day05
📁 视频
04-尚硅谷-掌柜问数-召回字段取值.mp4 [153.0 MB]
10-尚硅谷-掌柜问数-过滤表信息模型处理.mp4 [105.7 MB]
05-尚硅谷-掌柜问数-合并召回信息分析.mp4 [113.0 MB]
12-尚硅谷-掌柜问数-过滤指标信息实现.mp4 [42.5 MB]
09-尚硅谷-掌柜问数-最终表数据和指标数据封装.mp4 [206.8 MB]
07-尚硅谷-掌柜问数-补充字段取值对应信息.mp4 [41.3 MB]
01-尚硅谷-掌柜问数-课程内容概述.mp4 [16.7 MB]
13-尚硅谷-掌柜问数-添加额外上下文信息.mp4 [134.3 MB]
11-尚硅谷-掌柜问数-过滤表信息数据处理.mp4 [105.8 MB]
03-尚硅谷-掌柜问数-召回指标测试.mp4 [44.6 MB]
14-尚硅谷-掌柜问数-生成sql语句功能实现.mp4 [73.9 MB]
06-尚硅谷-掌柜问数-补充指标对应字段.mp4 [105.8 MB]
02-尚硅谷-掌柜问数-召回指标实现.mp4 [139.0 MB]
08-尚硅谷-掌柜问数-补充表中主外键字段.mp4 [168.4 MB]
📁 资料
解决docker端口占用问题.txt [38.0 B]
📁 截图
02-季度数据计算.png [39.0 KB]
01-合并召回信息.png [152.8 KB]
📁 课件
📁 assets
wps2.jpg [48.0 KB]
image-20260302192049010.png [43.8 KB]
image-20260302164313014.png [254.0 KB]
image-20260302144433733.png [66.1 KB]
掌柜问数项目-问数智能体.drawio.svg [274.8 KB]
image-20260312164049033.png [89.1 KB]
image-20260302145219771.png [37.5 KB]
wps4.jpg [73.4 KB]
image-20260302193512226.png [36.1 KB]
image-20260302193422656.png [35.7 KB]
image-20260121202229381.png [34.2 KB]
image-20260301202052447.png [31.7 KB]
image-20260121223015280.png [49.2 KB]
image-20260121201903693.png [47.5 KB]
image-20260207140320440.png [21.8 KB]
wps5.jpg [112.5 KB]
image-20260303152708134.png [56.2 KB]
wps6.png [626.0 KB]
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wps7.jpg [130.8 KB]
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尚硅谷大模型项目之掌柜问数.md [243.8 KB]
📁 代码
📁 data-agent
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
📁 dataSources
📁 0deae914-40e2-4145-9ff2-eeba6054ba72
📁 storage_v2
📁 _src_
📁 schema
information_schema.FNRwLQ.meta [76.0 B]
performance_schema.kIw0nw.meta [76.0 B]
0deae914-40e2-4145-9ff2-eeba6054ba72.xml [46.3 KB]
sqldialects.xml [296.0 B]
modules.xml [279.0 B]
.gitignore [238.0 B]
misc.xml [300.0 B]
dataSources.local.xml [1.1 KB]
dataSources.xml [530.0 B]
data_agent.iml [404.0 B]
workspace.xml [15.9 KB]
📁 conf
text_config.yaml [72.0 B]
meta_config.yaml [4.8 KB]
app_config.yaml [674.0 B]
📁 prompts
extend_keywords_for_value_recall.prompt [1.6 KB]
filter_metric_info.prompt [2.2 KB]
correct_sql.prompt [1.9 KB]
extend_keywords_for_metric_recall.prompt [2.2 KB]
plan_sql.prompt [2.5 KB]
filter_table_info.prompt [2.1 KB]
generate_sql.prompt [1.2 KB]
extend_keywords_for_column_recall.prompt [1.9 KB]
📁 app
📁 scripts
📁 __pycache__
build_meta_knowledge.cpython-311.pyc [4.0 KB]
__init__.cpython-311.pyc [175.0 B]
📁 logs
app.log [1.4 KB]
build_meta_knowledge.py [2.6 KB]
__init__.py
📁 repositories
📁 mysql
📁 __pycache__
meta_mysql_repository.cpython-311.pyc [4.4 KB]
__init__.cpython-311.pyc [186.0 B]
dw_mysql_repository.cpython-311.pyc [3.0 KB]
meta_mysql_repository.py [2.7 KB]
__init__.py
dw_mysql_repository.py [1.6 KB]
📁 es
📁 __pycache__
value_es_repository.cpython-311.pyc [3.5 KB]
__init__.cpython-311.pyc [183.0 B]
__init__.py
value_es_repository.py [2.5 KB]
📁 qdrant
📁 __pycache__
metric_qdrant_repository.cpython-311.pyc [4.1 KB]
__init__.cpython-311.pyc [187.0 B]
column_qdrant_repository.cpython-311.pyc [4.0 KB]
__init__.py
column_qdrant_repository.py [2.5 KB]
metric_qdrant_repository.py [2.5 KB]
📁 __pycache__
__init__.cpython-311.pyc [180.0 B]
__init__.py
📁 services
📁 __pycache__
meta_knowledge_service.cpython-311.pyc [14.6 KB]
__init__.cpython-311.pyc [176.0 B]
__init__.py
meta_knowledge_service.py [13.4 KB]
📁 test
__init__.py
test001.py [25.0 B]
📁 conf
📁 __pycache__
__init__.cpython-311.pyc [172.0 B]
meta_config.cpython-311.pyc [1.9 KB]
app_config.cpython-311.pyc [3.7 KB]
text_config.cpython-311.pyc [1.2 KB]
__init__.py
meta_config.py [574.0 B]
text_config.py [844.0 B]
app_config.py [1.2 KB]
📁 clients
📁 __pycache__
embedding_client_manager.cpython-311.pyc [2.1 KB]
es_client_manager.cpython-311.pyc [3.2 KB]
mysql_client_manager.cpython-311.pyc [3.7 KB]
__init__.cpython-311.pyc [175.0 B]
qdrant_client_manager.cpython-311.pyc [3.8 KB]
__init__.py
es_client_manager.py [4.2 KB]
qdrant_client_manager.py [2.4 KB]
embedding_client_manager.py [1.3 KB]
mysql_client_manager.py [2.0 KB]
📁 core
📁 __pycache__
context.cpython-311.pyc [306.0 B]
log.cpython-311.pyc [3.8 KB]
__init__.cpython-311.pyc [172.0 B]
📁 logs
app.log [188.0 B]
log.py [3.6 KB]
__init__.py
context.py [86.0 B]
file_2026-05-29_09-04-20_477303.log [293.0 B]
📁 prompt
📁 __pycache__
prompt_loader.cpython-311.pyc [810.0 B]
__init__.cpython-311.pyc [174.0 B]
__init__.py
prompt_loader.py [312.0 B]
📁 __pycache__
__init__.cpython-311.pyc [167.0 B]
📁 agent
📁 nodes
📁 __pycache__
recall_value.cpython-311.pyc [2.6 KB]
recall_column.cpython-311.pyc [2.9 KB]
validata_sql.cpython-311.pyc [1.3 KB]
generate_sql.cpython-311.pyc [2.5 KB]
add_extra_context.cpython-311.pyc [2.0 KB]
filter_table.cpython-311.pyc [2.6 KB]
merge_retrieved_info.cpython-311.pyc [6.3 KB]
filter_metric.cpython-311.pyc [2.3 KB]
execute_sql.cpython-311.pyc [833.0 B]
__init__.cpython-311.pyc [179.0 B]
recall_metric.cpython-311.pyc [3.0 KB]
extract_keywords.cpython-311.pyc [1.7 KB]
correct_sql.cpython-311.pyc [833.0 B]
recall_column.py [2.6 KB]
execute_sql.py [390.0 B]
add_extra_context.py [1.5 KB]
__init__.py
filter_metric.py [1.9 KB]
extract_keywords.py [1.6 KB]
recall_value.py [2.2 KB]
recall_metric.py [2.7 KB]
filter_table.py [2.7 KB]
generate_sql.py [2.0 KB]
correct_sql.py [390.0 B]
merge_retrieved_info.py [7.1 KB]
validata_sql.py [705.0 B]
📁 __pycache__
__init__.cpython-311.pyc [173.0 B]
llm.cpython-311.pyc [759.0 B]
context.cpython-311.pyc [1.4 KB]
state.cpython-311.pyc [2.8 KB]
📁 logs
app.log [114.0 KB]
graph.py [5.3 KB]
llm.py [361.0 B]
context.py [822.0 B]
state.py [1.2 KB]
__init__.py
📁 models
📁 mysql
📁 __pycache__
metric_info_mysql.cpython-311.pyc [1.6 KB]
column_metric_mysql.cpython-311.pyc [1.1 KB]
base.cpython-311.pyc [469.0 B]
__init__.cpython-311.pyc [180.0 B]
table_info_mysql.cpython-311.pyc [1.4 KB]
column_info_mysql.cpython-311.pyc [2.1 KB]
metric_info_mysql.py [807.0 B]
base.py [86.0 B]
column_info_mysql.py [1.1 KB]
__init__.py
column_metric_mysql.py [457.0 B]
table_info_mysql.py [640.0 B]
📁 qdrant
📁 __pycache__
__init__.cpython-311.pyc [181.0 B]
column_info_qdrant.cpython-311.pyc [727.0 B]
metric_info_qdrant.cpython-311.pyc [659.0 B]
metric_info_qdrant.py [158.0 B]
__init__.py
column_info_qdrant.py [196.0 B]
📁 es
📁 __pycache__
__init__.cpython-311.pyc [177.0 B]
value_info_es.cpython-311.pyc [689.0 B]
__init__.py
value_info_es.py [182.0 B]
📁 __pycache__
__init__.cpython-311.pyc [174.0 B]
__init__.py
__init__.py
📁 logs
app.log [11.4 KB]
📁 docker
📁 embedding
📁 bge-large-zh-v1.5
📁 1_Pooling
config.json [191.0 B]
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
…（层级过深，已停止）
config.json.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
special_tokens_map.json.metadata [104.0 B]
tokenizer_config.json.metadata [103.0 B]
sentence_bert_config.json.metadata [104.0 B]
pytorch_model.bin.metadata [127.0 B]
README.md.metadata [104.0 B]
config_sentence_transformers.json.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
modules.json.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
.gitignore [1.0 B]
vocab.txt [107.0 KB]
README.md [29.7 KB]
tokenizer.json [428.8 KB]
config_sentence_transformers.json [124.0 B]
config.json [1000.0 B]
pytorch_model.bin [1.2 GB]
.gitattributes [1.5 KB]
sentence_bert_config.json [52.0 B]
special_tokens_map.json [125.0 B]
tokenizer_config.json [394.0 B]
modules.json [349.0 B]
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
📁 .venv
📁 Lib
📁 site-packages
_virtualenv.pth [18.0 B]
_virtualenv.py [4.2 KB]
📁 Scripts
activate.nu [3.7 KB]
python.exe [256.0 KB]
activate.fish [4.1 KB]
activate.ps1 [2.7 KB]
pydoc.bat [1.2 KB]
pythonw.exe [244.0 KB]
activate.bat [2.6 KB]
deactivate.bat [1.7 KB]
activate [4.0 KB]
activate.csh [2.6 KB]
activate_this.py [2.3 KB]
CACHEDIR.TAG [43.0 B]
pyvenv.cfg [198.0 B]
.gitignore [1.0 B]
📁 mysql
meta.sql [1.5 KB]
dw.sql [15.5 KB]
docker-compose.yaml [1.6 KB]
uv.lock [767.7 KB]
pyproject.toml [566.0 B]
main.py [544.0 B]
day05文档.zip [1.8 MB]
📁 day03
📁 视频
07-尚硅谷-掌柜问数-加载配置文件.mp4 [37.5 MB]
12-尚硅谷-掌柜问数-确保字段集合存在.mp4 [74.6 MB]
13-尚硅谷-掌柜问数-为字段构建向量索引.mp4 [261.2 MB]
06-尚硅谷-掌柜问数-构建业务层实现.mp4 [42.8 MB]
02-尚硅谷-掌柜问数-日志管理搭建.mp4 [241.0 MB]
08-尚硅谷-掌柜问数-保存表信息实现一.mp4 [158.8 MB]
14-尚硅谷-掌柜问数-确保字段取值索引存在.mp4 [105.9 MB]
11-尚硅谷-掌柜问数-构建字段和取值分析.mp4 [22.7 MB]
01-尚硅谷-掌柜问数-今日内容概述.mp4 [11.3 MB]
05-尚硅谷-掌柜问数-命令参数解析.mp4 [102.0 MB]
04-尚硅谷-掌柜问数-入口脚本构建.mp4 [66.3 MB]
09-尚硅谷-掌柜问数-上午内容总结.mp4 [20.2 MB]
10-尚硅谷-掌柜问数-保存表信息实现二.mp4 [139.1 MB]
03-尚硅谷-掌柜问数-代码组织规划.mp4 [60.1 MB]
📁 课件
📁 assets
image-20260121223015280.png [49.2 KB]
wps7.jpg [130.8 KB]
image-20260312164049033.png [89.1 KB]
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wps2.jpg [48.0 KB]
image-20260311204011515.png [34.7 KB]
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wps1.jpg [48.0 KB]
image-20260303152708134.png [56.2 KB]
image-20260302193512226.png [36.1 KB]
掌柜问数项目-问数智能体.drawio.svg [274.8 KB]
image-20260207140352763.png [65.8 KB]
image-20260121184748743.png [51.2 KB]
wps6.png [626.0 KB]
image-20260302144433733.png [66.1 KB]
image-20260121202402103.png [76.9 KB]
image-20260301202052447.png [31.7 KB]
尚硅谷大模型项目之掌柜问数.md [243.4 KB]
📁 代码
📁 data-agent
📁 conf
app_config.yaml [657.0 B]
text_config.yaml [72.0 B]
meta_config.yaml [4.8 KB]
📁 docker
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
📁 .venv
📁 Scripts
python.exe [256.0 KB]
activate.fish [4.1 KB]
pythonw.exe [244.0 KB]
pydoc.bat [1.2 KB]
deactivate.bat [1.7 KB]
activate.nu [3.7 KB]
activate_this.py [2.3 KB]
activate.csh [2.6 KB]
activate.ps1 [2.7 KB]
activate.bat [2.6 KB]
activate [4.0 KB]
📁 Lib
📁 site-packages
_virtualenv.py [4.2 KB]
_virtualenv.pth [18.0 B]
CACHEDIR.TAG [43.0 B]
.gitignore [1.0 B]
pyvenv.cfg [198.0 B]
📁 embedding
📁 bge-large-zh-v1.5
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
…（层级过深，已停止）
vocab.txt.metadata [104.0 B]
modules.json.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
README.md.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
pytorch_model.bin.metadata [127.0 B]
config_sentence_transformers.json.metadata [104.0 B]
tokenizer_config.json.metadata [103.0 B]
config.json.metadata [104.0 B]
special_tokens_map.json.metadata [104.0 B]
.gitignore [1.0 B]
📁 1_Pooling
config.json [191.0 B]
README.md [29.7 KB]
config_sentence_transformers.json [124.0 B]
modules.json [349.0 B]
config.json [1000.0 B]
.gitattributes [1.5 KB]
special_tokens_map.json [125.0 B]
vocab.txt [107.0 KB]
pytorch_model.bin [1.2 GB]
tokenizer_config.json [394.0 B]
tokenizer.json [428.8 KB]
sentence_bert_config.json [52.0 B]
📁 mysql
dw.sql [15.5 KB]
meta.sql [1.5 KB]
docker-compose.yaml [1.6 KB]
📁 logs
app.log [5.3 KB]
📁 .idea
📁 dataSources
📁 0deae914-40e2-4145-9ff2-eeba6054ba72
📁 storage_v2
📁 _src_
📁 schema
information_schema.FNRwLQ.meta [76.0 B]
performance_schema.kIw0nw.meta [76.0 B]
0deae914-40e2-4145-9ff2-eeba6054ba72.xml [46.3 KB]
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
workspace.xml [13.4 KB]
sqldialects.xml [296.0 B]
dataSources.xml [530.0 B]
misc.xml [300.0 B]
dataSources.local.xml [1.1 KB]
.gitignore [238.0 B]
modules.xml [279.0 B]
data_agent.iml [404.0 B]
📁 app
📁 models
📁 mysql
📁 __pycache__
table_info_mysql.cpython-311.pyc [1.4 KB]
column_info_mysql.cpython-311.pyc [2.1 KB]
base.cpython-311.pyc [469.0 B]
__init__.cpython-311.pyc [180.0 B]
column_metric_mysql.py [457.0 B]
base.py [86.0 B]
column_info_mysql.py [1.1 KB]
__init__.py
table_info_mysql.py [640.0 B]
metric_info_mysql.py [807.0 B]
📁 qdrant
📁 __pycache__
column_info_qdrant.cpython-311.pyc [727.0 B]
__init__.cpython-311.pyc [181.0 B]
__init__.py
column_info_qdrant.py [196.0 B]
📁 __pycache__
__init__.cpython-311.pyc [174.0 B]
📁 es
__init__.py
__init__.py
📁 services
📁 __pycache__
__init__.cpython-311.pyc [176.0 B]
meta_knowledge_service.cpython-311.pyc [7.3 KB]
__init__.py
meta_knowledge_service.py [7.1 KB]
📁 clients
📁 __pycache__
es_client_manager.cpython-311.pyc [3.2 KB]
mysql_client_manager.cpython-311.pyc [3.7 KB]
__init__.cpython-311.pyc [175.0 B]
embedding_client_manager.cpython-311.pyc [2.1 KB]
qdrant_client_manager.cpython-311.pyc [3.4 KB]
es_client_manager.py [4.2 KB]
__init__.py
mysql_client_manager.py [2.0 KB]
qdrant_client_manager.py [2.1 KB]
embedding_client_manager.py [1.3 KB]
📁 __pycache__
__init__.cpython-311.pyc [167.0 B]
📁 conf
📁 __pycache__
__init__.cpython-311.pyc [172.0 B]
app_config.cpython-311.pyc [3.7 KB]
meta_config.cpython-311.pyc [1.9 KB]
text_config.cpython-311.pyc [1.2 KB]
meta_config.py [574.0 B]
__init__.py
text_config.py [844.0 B]
app_config.py [1.2 KB]
📁 scripts
📁 __pycache__
__init__.cpython-311.pyc [175.0 B]
build_meta_knowledge.cpython-311.pyc [3.8 KB]
📁 logs
app.log [131.0 B]
build_meta_knowledge.py [2.4 KB]
__init__.py
📁 repositories
📁 mysql
📁 __pycache__
meta_mysql_repository.cpython-311.pyc [1.7 KB]
__init__.cpython-311.pyc [186.0 B]
dw_mysql_repository.cpython-311.pyc [2.4 KB]
dw_mysql_repository.py [1.2 KB]
__init__.py
meta_mysql_repository.py [757.0 B]
📁 qdrant
📁 __pycache__
__init__.cpython-311.pyc [187.0 B]
column_qdrant_repository.cpython-311.pyc [3.2 KB]
__init__.py
column_qdrant_repository.py [2.0 KB]
📁 __pycache__
__init__.cpython-311.pyc [180.0 B]
📁 es
📁 __pycache__
value_es_repository.cpython-311.pyc [1.7 KB]
__init__.cpython-311.pyc [183.0 B]
value_es_repository.py [1.1 KB]
__init__.py
__init__.py
📁 core
📁 __pycache__
log.cpython-311.pyc [3.8 KB]
context.cpython-311.pyc [306.0 B]
__init__.cpython-311.pyc [172.0 B]
📁 logs
app.log [188.0 B]
__init__.py
log.py [3.6 KB]
context.py [86.0 B]
file_2026-05-29_09-04-20_477303.log [293.0 B]
__init__.py
uv.lock [766.1 KB]
main.py [544.0 B]
pyproject.toml [545.0 B]
📁 截图
03-构建脚本向量结构.png [103.1 KB]
02-脚本构建知识库.png [58.3 KB]
01-协程上下文变量.png [96.9 KB]
day03说明.png [493.5 KB]
📁 day06
📁 视频
02-尚硅谷-掌柜问数-检验sql思路.mp4 [75.3 MB]
17-尚硅谷-掌柜问数-前后端联调测试.mp4 [57.9 MB]
03-尚硅谷-掌柜问数-校验sql实现.mp4 [67.7 MB]
05-尚硅谷-掌柜问数-执行sql实现.mp4 [69.3 MB]
08-尚硅谷-掌柜问数-fastapi的基础定义.mp4 [79.6 MB]
06-尚硅谷-掌柜问数-优化思路分析.mp4 [65.6 MB]
01-尚硅谷-掌柜问数-内容回顾概述.mp4 [19.3 MB]
10-尚硅谷-掌柜问数-中间件的讲解.mp4 [64.3 MB]
18-尚硅谷-掌柜问数-学习方式分享.mp4 [40.9 MB]
14-尚硅谷-掌柜问数-智能体依赖项整合.mp4 [94.5 MB]
13-尚硅谷-掌柜问数-智能体服务封装.mp4 [93.7 MB]
15-尚硅谷-掌柜问数-智能体声明周期组件整合.mp4 [21.1 MB]
04-尚硅谷-掌柜问数-校正sql实现.mp4 [57.1 MB]
09-尚硅谷-掌柜问数-自定义流式响应.mp4 [132.4 MB]
12-尚硅谷-掌柜问数-依赖项讲解.mp4 [61.8 MB]
07-尚硅谷-掌柜问数-api接口概述.mp4 [57.8 MB]
11-尚硅谷-掌柜问数-声明周期事件 .mp4 [64.0 MB]
16-尚硅谷-掌柜问数-智能体整合调试.mp4 [124.3 MB]
📁 截图
02-sql验证分析.png [185.7 KB]
01-mysql流程讲解.png [237.7 KB]
03-智能体三层整合.png [99.6 KB]
05-学习方式.png [70.2 KB]
04-fastapi中间件.png [56.3 KB]
📁 代码
📁 data-agent
📁 prompts
extend_keywords_for_value_recall.prompt [1.6 KB]
extend_keywords_for_column_recall.prompt [1.9 KB]
plan_sql.prompt [2.5 KB]
correct_sql.prompt [1.9 KB]
filter_table_info.prompt [2.1 KB]
generate_sql.prompt [1.2 KB]
extend_keywords_for_metric_recall.prompt [2.2 KB]
filter_metric_info.prompt [2.2 KB]
📁 __pycache__
main.cpython-311.pyc [1.0 KB]
📁 logs
app.log [44.6 KB]
📁 conf
text_config.yaml [72.0 B]
meta_config.yaml [4.8 KB]
app_config.yaml [674.0 B]
📁 .idea
📁 dataSources
📁 0deae914-40e2-4145-9ff2-eeba6054ba72
📁 storage_v2
📁 _src_
📁 schema
performance_schema.kIw0nw.meta [76.0 B]
information_schema.FNRwLQ.meta [76.0 B]
0deae914-40e2-4145-9ff2-eeba6054ba72.xml [46.3 KB]
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
data_agent.iml [404.0 B]
sqldialects.xml [296.0 B]
misc.xml [300.0 B]
.gitignore [238.0 B]
modules.xml [279.0 B]
workspace.xml [15.8 KB]
dataSources.xml [530.0 B]
dataSources.local.xml [1.1 KB]
📁 docker
📁 .venv
📁 Lib
📁 site-packages
_virtualenv.py [4.2 KB]
_virtualenv.pth [18.0 B]
📁 Scripts
activate.fish [4.1 KB]
pythonw.exe [244.0 KB]
activate_this.py [2.3 KB]
activate.bat [2.6 KB]
activate [4.0 KB]
pydoc.bat [1.2 KB]
activate.nu [3.7 KB]
activate.ps1 [2.7 KB]
activate.csh [2.6 KB]
deactivate.bat [1.7 KB]
python.exe [256.0 KB]
CACHEDIR.TAG [43.0 B]
pyvenv.cfg [198.0 B]
.gitignore [1.0 B]
📁 mysql
dw.sql [15.5 KB]
meta.sql [1.5 KB]
📁 embedding
📁 bge-large-zh-v1.5
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
…（层级过深，已停止）
special_tokens_map.json.metadata [104.0 B]
modules.json.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
config_sentence_transformers.json.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
config.json.metadata [104.0 B]
tokenizer_config.json.metadata [103.0 B]
pytorch_model.bin.metadata [127.0 B]
README.md.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
.gitignore [1.0 B]
📁 1_Pooling
config.json [191.0 B]
vocab.txt [107.0 KB]
README.md [29.7 KB]
tokenizer.json [428.8 KB]
pytorch_model.bin [1.2 GB]
sentence_bert_config.json [52.0 B]
tokenizer_config.json [394.0 B]
modules.json [349.0 B]
config_sentence_transformers.json [124.0 B]
.gitattributes [1.5 KB]
config.json [1000.0 B]
special_tokens_map.json [125.0 B]
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
docker-compose.yaml [1.6 KB]
📁 app
📁 conf
📁 __pycache__
text_config.cpython-311.pyc [1.2 KB]
meta_config.cpython-311.pyc [1.9 KB]
app_config.cpython-311.pyc [3.7 KB]
__init__.cpython-311.pyc [172.0 B]
app_config.py [1.2 KB]
meta_config.py [574.0 B]
__init__.py
text_config.py [844.0 B]
📁 services
📁 __pycache__
meta_knowledge_service.cpython-311.pyc [14.6 KB]
query_service.cpython-311.pyc [2.9 KB]
__init__.cpython-311.pyc [176.0 B]
query_service.py [2.3 KB]
meta_knowledge_service.py [13.4 KB]
__init__.py
📁 core
📁 __pycache__
__init__.cpython-311.pyc [172.0 B]
context.cpython-311.pyc [306.0 B]
lifespan.cpython-311.pyc [1.5 KB]
log.cpython-311.pyc [3.8 KB]
📁 logs
app.log [188.0 B]
context.py [86.0 B]
__init__.py
lifespan.py [860.0 B]
file_2026-05-29_09-04-20_477303.log [293.0 B]
log.py [3.6 KB]
📁 repositories
📁 mysql
📁 __pycache__
__init__.cpython-311.pyc [186.0 B]
dw_mysql_repository.cpython-311.pyc [4.2 KB]
meta_mysql_repository.cpython-311.pyc [4.4 KB]
meta_mysql_repository.py [2.7 KB]
__init__.py
dw_mysql_repository.py [2.2 KB]
📁 qdrant
📁 __pycache__
metric_qdrant_repository.cpython-311.pyc [4.1 KB]
__init__.cpython-311.pyc [187.0 B]
column_qdrant_repository.cpython-311.pyc [4.0 KB]
metric_qdrant_repository.py [2.5 KB]
__init__.py
column_qdrant_repository.py [2.5 KB]
📁 es
📁 __pycache__
value_es_repository.cpython-311.pyc [3.5 KB]
__init__.cpython-311.pyc [183.0 B]
__init__.py
value_es_repository.py [2.5 KB]
📁 __pycache__
__init__.cpython-311.pyc [180.0 B]
__init__.py
📁 __pycache__
__init__.cpython-311.pyc [167.0 B]
📁 agent
📁 __pycache__
context.cpython-311.pyc [1.4 KB]
graph.cpython-311.pyc [7.2 KB]
__init__.cpython-311.pyc [173.0 B]
llm.cpython-311.pyc [759.0 B]
state.cpython-311.pyc [2.9 KB]
📁 nodes
📁 __pycache__
correct_sql.cpython-311.pyc [2.5 KB]
validata_sql.cpython-311.pyc [1.4 KB]
filter_table.cpython-311.pyc [2.6 KB]
recall_metric.cpython-311.pyc [3.0 KB]
execute_sql.cpython-311.pyc [1.4 KB]
filter_metric.cpython-311.pyc [2.3 KB]
add_extra_context.cpython-311.pyc [2.0 KB]
__init__.cpython-311.pyc [179.0 B]
extract_keywords.cpython-311.pyc [1.7 KB]
merge_retrieved_info.cpython-311.pyc [6.3 KB]
recall_column.cpython-311.pyc [2.9 KB]
recall_value.cpython-311.pyc [2.6 KB]
generate_sql.cpython-311.pyc [2.5 KB]
merge_retrieved_info.py [7.1 KB]
__init__.py
recall_metric.py [2.7 KB]
filter_metric.py [1.9 KB]
filter_table.py [2.7 KB]
generate_sql.py [2.3 KB]
extract_keywords.py [1.6 KB]
add_extra_context.py [1.5 KB]
execute_sql.py [853.0 B]
recall_value.py [2.2 KB]
validata_sql.py [847.0 B]
recall_column.py [2.6 KB]
correct_sql.py [2.2 KB]
📁 logs
app.log [218.6 KB]
state.py [1.2 KB]
llm.py [361.0 B]
graph.py [5.4 KB]
context.py [822.0 B]
__init__.py
📁 clients
📁 __pycache__
es_client_manager.cpython-311.pyc [3.2 KB]
embedding_client_manager.cpython-311.pyc [2.1 KB]
__init__.cpython-311.pyc [175.0 B]
mysql_client_manager.cpython-311.pyc [3.7 KB]
qdrant_client_manager.cpython-311.pyc [3.8 KB]
es_client_manager.py [4.2 KB]
__init__.py
embedding_client_manager.py [1.3 KB]
qdrant_client_manager.py [2.4 KB]
mysql_client_manager.py [2.0 KB]
📁 test
__init__.py
test001.py [25.0 B]
📁 prompt
📁 __pycache__
__init__.cpython-311.pyc [174.0 B]
prompt_loader.cpython-311.pyc [810.0 B]
__init__.py
prompt_loader.py [312.0 B]
📁 models
📁 __pycache__
__init__.cpython-311.pyc [174.0 B]
📁 qdrant
📁 __pycache__
metric_info_qdrant.cpython-311.pyc [659.0 B]
__init__.cpython-311.pyc [181.0 B]
column_info_qdrant.cpython-311.pyc [727.0 B]
column_info_qdrant.py [196.0 B]
metric_info_qdrant.py [158.0 B]
__init__.py
📁 mysql
📁 __pycache__
column_info_mysql.cpython-311.pyc [2.1 KB]
base.cpython-311.pyc [469.0 B]
__init__.cpython-311.pyc [180.0 B]
column_metric_mysql.cpython-311.pyc [1.1 KB]
metric_info_mysql.cpython-311.pyc [1.6 KB]
table_info_mysql.cpython-311.pyc [1.4 KB]
column_info_mysql.py [1.1 KB]
column_metric_mysql.py [457.0 B]
table_info_mysql.py [640.0 B]
base.py [86.0 B]
metric_info_mysql.py [807.0 B]
__init__.py
📁 es
📁 __pycache__
__init__.cpython-311.pyc [177.0 B]
value_info_es.cpython-311.pyc [689.0 B]
__init__.py
value_info_es.py [182.0 B]
__init__.py
📁 api
📁 routers
📁 __pycache__
__init__.cpython-311.pyc [179.0 B]
query_router.cpython-311.pyc [1.1 KB]
query_router.py [861.0 B]
__init__.py
📁 schemas
📁 __pycache__
__init__.cpython-311.pyc [179.0 B]
query_schema.cpython-311.pyc [522.0 B]
__init__.py
query_schema.py [83.0 B]
📁 __pycache__
dependencies.cpython-311.pyc [4.3 KB]
__init__.cpython-311.pyc [171.0 B]
dependencies.py [2.7 KB]
__init__.py
📁 scripts
📁 __pycache__
__init__.cpython-311.pyc [175.0 B]
build_meta_knowledge.cpython-311.pyc [4.0 KB]
📁 logs
app.log [1.4 KB]
build_meta_knowledge.py [2.6 KB]
__init__.py
__init__.py
uv.lock [767.7 KB]
main.py [603.0 B]
pyproject.toml [566.0 B]
📁 资料
📁 date-agent-frontend
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
.gitignore [238.0 B]
date-agent-frontend.iml [414.0 B]
modules.xml [297.0 B]
workspace.xml [4.2 KB]
misc.xml [284.0 B]
📁 src
📁 assets
vue.svg [496.0 B]
📁 components
HelloWorld.vue [847.0 B]
main.js [111.0 B]
App.vue [7.3 KB]
style.css [1.2 KB]
📁 dist
📁 assets
index-D8n9f6Di.js [63.0 KB]
index-b680BBEF.css [3.4 KB]
vite.svg [1.5 KB]
index.html [465.0 B]
📁 public
vite.svg [1.5 KB]
README.md [385.0 B]
vite.config.js [584.0 B]
index.html [366.0 B]
package-lock.json [42.6 KB]
.gitignore [253.0 B]
package.json [324.0 B]
📁 22_尚硅谷大模型项目实战之掌柜问数实战
📁 2.资料
📁 教育
📁 edu-data
📁 docker
docker-compose.yaml [402.0 B]
📁 seeds
📁 2_course
series_course.csv [106.8 KB]
series.csv [76.8 KB]
📁 3_question
question.csv [666.4 KB]
question_bank.csv [50.0 KB]
📁 1_foundation
dim_learning_goal.csv [847.0 B]
dim_question_type.csv [2.1 KB]
org_campus.csv [3.5 KB]
dim_channel.csv [2.0 KB]
org_department.csv [14.2 KB]
dim_course_category.csv [9.9 KB]
dim_learner_identity.csv [348.0 B]
dim_grade.csv [2.3 KB]
dim_education_level.csv [442.0 B]
org_institution.csv [1.1 KB]
📁 generate
📁 layers
validations.py [100.9 KB]
seed_importer.py [6.2 KB]
layer7.py [377.0 B]
layer1.py [23.2 KB]
layer3.py [29.3 KB]
layer5.py [48.0 KB]
layer2.py [38.4 KB]
base.py [1.3 KB]
layer6.py [33.5 KB]
__init__.py [25.0 B]
layer4.py [30.2 KB]
main.py [2.2 KB]
__init__.py [48.0 B]
config.py [5.3 KB]
db.py [3.2 KB]
insert_support.py [2.6 KB]
progress.py [3.8 KB]
📁 tests
test_conversion.py [4.8 KB]
test_tickets.py [3.3 KB]
test_users_and_courses.py [2.5 KB]
conftest.py [16.3 KB]
test_learning_and_interactions.py [5.6 KB]
test_orders_and_payments.py [10.7 KB]
📁 app
📁 routers
payments.py [18.8 KB]
courses.py [9.8 KB]
tickets.py [11.9 KB]
enrollments.py [9.3 KB]
orders.py [15.6 KB]
cart.py [4.4 KB]
favorites.py [4.6 KB]
users.py [5.7 KB]
interactions.py [5.8 KB]
study.py [19.4 KB]
consultations.py [4.8 KB]
coupons.py [8.7 KB]
__init__.py [26.0 B]
utils.py [2.4 KB]
database.py [1.6 KB]
main.py [3.1 KB]
errors.py [926.0 B]
response.py [308.0 B]
__init__.py [56.0 B]
dependencies.py [1.4 KB]
config.py [614.0 B]
📁 sql
.sqlfluff [26.0 B]
edu.sql [60.0 KB]
Makefile [875.0 B]
README.md [186.8 KB]
pyproject.toml [410.0 B]
uv.lock [72.7 KB]
.env [194.0 B]
.python-version [5.0 B]
.gitignore [108.0 B]
init_db.py [7.1 KB]
需求说明.md [2.8 KB]
📁 旅游
📁 travel-data
📁 .venv
📁 Scripts
py.test.exe [45.5 KB]
uvicorn.exe [45.5 KB]
activate.csh [2.7 KB]
activate.fish [4.2 KB]
pythonw.exe [257.4 KB]
pygmentize.exe [45.5 KB]
httpx.exe [45.5 KB]
pytest.exe [45.5 KB]
pydoc.bat [1.2 KB]
sqlacodegen.exe [45.5 KB]
deactivate.bat [1.7 KB]
activate.nu [3.8 KB]
activate.ps1 [2.7 KB]
python.exe [268.0 KB]
fastapi.exe [45.5 KB]
activate [4.1 KB]
activate.bat [2.7 KB]
activate_this.py [2.3 KB]
dotenv.exe [45.5 KB]
markdown-it.exe [45.5 KB]
📁 Lib
📁 site-packages
📁 annotated_doc-0.0.4.dist-info
…（层级过深，已停止）
📁 sqlacodegen-4.0.3.dist-info
…（层级过深，已停止）
📁 greenlet
…（层级过深，已停止）
📁 anyio-4.13.0.dist-info
…（层级过深，已停止）
📁 iniconfig-2.3.0.dist-info
…（层级过深，已停止）
📁 python_dotenv-1.2.2.dist-info
…（层级过深，已停止）
📁 markdown_it_py-4.0.0.dist-info
…（层级过深，已停止）
📁 typeguard
…（层级过深，已停止）
📁 markdown_it
…（层级过深，已停止）
📁 h11-0.16.0.dist-info
…（层级过深，已停止）
📁 pydantic-2.12.5.dist-info
…（层级过深，已停止）
📁 sqlalchemy-2.0.49.dist-info
…（层级过深，已停止）
📁 fastapi
…（层级过深，已停止）
📁 loguru
…（层级过深，已停止）
📁 asyncmy-0.2.11.dist-info
…（层级过深，已停止）
📁 fastapi-0.136.0.dist-info
…（层级过深，已停止）
📁 loguru-0.7.3.dist-info
…（层级过深，已停止）
📁 typeguard-4.5.1.dist-info
…（层级过深，已停止）
📁 pydantic_core-2.41.5.dist-info
…（层级过深，已停止）
📁 uvicorn
…（层级过深，已停止）
📁 mdurl
…（层级过深，已停止）
📁 colorama
…（层级过深，已停止）
📁 certifi-2026.4.22.dist-info
…（层级过深，已停止）
📁 more_itertools-11.0.2.dist-info
…（层级过深，已停止）
📁 annotated_types
…（层级过深，已停止）
📁 pytest
…（层级过深，已停止）
📁 click-8.3.2.dist-info
…（层级过深，已停止）
📁 annotated_doc
…（层级过深，已停止）
📁 httpcore
…（层级过深，已停止）
📁 rich
…（层级过深，已停止）
📁 pymysql
…（层级过深，已停止）
📁 iniconfig
…（层级过深，已停止）
📁 click
…（层级过深，已停止）
📁 packaging-26.1.dist-info
…（层级过深，已停止）
📁 starlette-1.0.0.dist-info
…（层级过深，已停止）
📁 pytest-9.0.3.dist-info
…（层级过深，已停止）
📁 mdurl-0.1.2.dist-info
…（层级过深，已停止）
📁 dotenv
…（层级过深，已停止）
📁 httpx-0.28.1.dist-info
…（层级过深，已停止）
📁 pydantic
…（层级过深，已停止）
📁 pluggy-1.6.0.dist-info
…（层级过深，已停止）
📁 sqlalchemy
…（层级过深，已停止）
📁 win32_setctime
…（层级过深，已停止）
📁 rich-15.0.0.dist-info
…（层级过深，已停止）
📁 annotated_types-0.7.0.dist-info
…（层级过深，已停止）
📁 anyio
…（层级过深，已停止）
📁 typing_inspection-0.4.2.dist-info
…（层级过深，已停止）
📁 pygments
…（层级过深，已停止）
📁 pygments-2.20.0.dist-info
…（层级过深，已停止）
📁 typing_extensions-4.15.0.dist-info
…（层级过深，已停止）
📁 pydantic_core
…（层级过深，已停止）
📁 typing_inspection
…（层级过深，已停止）
📁 inflect
…（层级过深，已停止）
📁 win32_setctime-1.2.0.dist-info
…（层级过深，已停止）
📁 h11
…（层级过深，已停止）
📁 asyncmy
…（层级过深，已停止）
📁 more_itertools
…（层级过深，已停止）
📁 pymysql-1.1.2.dist-info
…（层级过深，已停止）
📁 starlette
…（层级过深，已停止）
📁 httpcore-1.0.9.dist-info
…（层级过深，已停止）
📁 httpx
…（层级过深，已停止）
📁 colorama-0.4.6.dist-info
…（层级过深，已停止）
📁 idna
…（层级过深，已停止）
📁 inflect-7.5.0.dist-info
…（层级过深，已停止）
📁 certifi
…（层级过深，已停止）
📁 greenlet-3.4.0.dist-info
…（层级过深，已停止）
📁 __pycache__
…（层级过深，已停止）
📁 packaging
…（层级过深，已停止）
📁 idna-3.11.dist-info
…（层级过深，已停止）
📁 uvicorn-0.44.0.dist-info
…（层级过深，已停止）
📁 _pytest
…（层级过深，已停止）
📁 pluggy
…（层级过深，已停止）
📁 sqlacodegen
…（层级过深，已停止）
typing_extensions.py [156.7 KB]
py.py [329.0 B]
_virtualenv.py [4.2 KB]
_virtualenv.pth [18.0 B]
📁 include
📁 site
📁 python3.12
…（层级过深，已停止）
.gitignore [1.0 B]
pyvenv.cfg [148.0 B]
CACHEDIR.TAG [43.0 B]
.lock
📁 seeds
📁 5_marketing
promotions.csv [2.2 KB]
coupon_templates.csv [2.8 KB]
promotion_bindings.csv [2.4 KB]
promotion_rules.csv [1.6 KB]
📁 2_product
scenic_ticket_types.csv [11.5 KB]
scenic_spots.csv [11.2 KB]
train_routes.csv [3.3 KB]
transfer_service_area_rules.csv [3.3 KB]
transfer_services.csv [2.9 KB]
hotel_booking_rules.csv [4.6 KB]
hotel_room_types.csv [10.9 KB]
hotels.csv [11.3 KB]
flight_routes.csv [3.5 KB]
bus_routes.csv [4.4 KB]
scenic_booking_rules.csv [4.8 KB]
📁 1_dimension
areas.csv [245.3 KB]
channels.csv [112.0 B]
transport_hubs.csv [16.4 KB]
currencies.csv [135.0 B]
suppliers.csv [17.7 KB]
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
modules.xml [281.0 B]
travel-data.iml [562.0 B]
workspace.xml [4.0 KB]
misc.xml [194.0 B]
📁 generate
📁 layers
layer3.py [17.3 KB]
layer4.py [8.3 KB]
base.py [1013.0 B]
layer1.py [504.0 B]
validations.py [39.0 KB]
layer5.py [6.5 KB]
__init__.py
layer6.py [40.0 KB]
layer2.py [935.0 B]
seed_importer.py [4.2 KB]
__init__.py
db.py [3.2 KB]
main.py [2.0 KB]
config.py [3.0 KB]
progress.py [3.8 KB]
generator_support.py [7.5 KB]
📁 sql
.sqlfluff [26.0 B]
travel.sql [48.5 KB]
📁 docker
docker-compose.yaml [402.0 B]
📁 app
📁 routers
products.py [50.9 KB]
__init__.py [19.0 B]
users.py [15.2 KB]
orders.py [70.0 KB]
marketing.py [9.7 KB]
refunds.py [10.1 KB]
main.py [1.3 KB]
database.py [1.4 KB]
utils.py [2.4 KB]
dependencies.py [1.1 KB]
__init__.py [35.0 B]
config.py [541.0 B]
errors.py [568.0 B]
📁 tests
test_marketing.py [1.4 KB]
test_users.py [2.8 KB]
test_orders_and_refunds.py [7.8 KB]
conftest.py [8.7 KB]
test_products.py [6.3 KB]
.gitignore [108.0 B]
Makefile [875.0 B]
.env [197.0 B]
.python-version [5.0 B]
pyrightconfig.json [114.0 B]
pyproject.toml [437.0 B]
README.md [149.7 KB]
init_db.py [7.1 KB]
uv.lock [72.6 KB]
需求说明.md [3.1 KB]
项目实战说明.txt [198.0 B]
Apifox-2.8.32.exe [193.7 MB]
复盘.rar [224.9 KB]
📁 课件
📁 assets
image-20260301202052447.png [31.7 KB]
image-20260207140320440.png [21.8 KB]
image-20260302160651463.png [43.4 KB]
image-20260302164430508.png [20.8 KB]
image-20260121202402103.png [76.9 KB]
image-20260302165403928.png [48.5 KB]
image-20260312164049033.png [89.1 KB]
image-20260207161919313.png [88.2 KB]
wps7.jpg [130.8 KB]
image-20260301202214037.png [26.0 KB]
image-20260303152708134.png [56.2 KB]
image-20260121223015280.png [49.2 KB]
wps5.jpg [112.5 KB]
image-20260312185315752.png [102.1 KB]
image-20260302164313014.png [254.0 KB]
image-20260121203227857.png [24.3 KB]
image-20260121184748743.png [51.2 KB]
wps4.jpg [73.4 KB]
wps1.jpg [48.0 KB]
image-20260311204011515.png [34.7 KB]
image-20260207140352763.png [65.8 KB]
image-20260302193512226.png [36.1 KB]
image-20260121215240284.png [34.4 KB]
掌柜问数项目-问数智能体.drawio.svg [274.8 KB]
image-20260302193422656.png [35.7 KB]
image-20260121202229381.png [34.2 KB]
image-20260207142744497.png [48.0 KB]
wps3.png [26.8 KB]
wps6.png [626.0 KB]
image-20260312162206045.png [69.2 KB]
image-20260121201903693.png [47.5 KB]
image-20260302145219771.png [37.5 KB]
image-20260311204041206.png [34.0 KB]
image-20260121204009373.png [54.5 KB]
image-20260302192049010.png [43.8 KB]
image-20260302193437126.png [35.3 KB]
image-20260302144433733.png [66.1 KB]
wps2.jpg [48.0 KB]
尚硅谷大模型项目之掌柜问数.md [241.7 KB]
📁 day01
📁 视频
02-尚硅谷-掌柜问数-项目业务概述.mp4 [51.5 MB]
04-尚硅谷-掌柜问数-项目构建分析.mp4 [84.7 MB]
16-尚硅谷-掌柜问数-三层架构讲解.mp4 [40.4 MB]
08-尚硅谷-掌柜问数-全文索引概述.mp4 [45.6 MB]
14-尚硅谷-掌柜问数-项目配置管理.mp4 [112.3 MB]
10-尚硅谷-掌柜问数-项目创建演示.mp4 [105.4 MB]
17-尚硅谷-掌柜问数-ORM关系映射.mp4 [24.9 MB]
05-尚硅谷-掌柜问数-数据仓库分析.mp4 [91.7 MB]
13-尚硅谷-掌柜问数-项目目录结构.mp4 [37.9 MB]
01-尚硅谷-掌柜问数-项目整体介绍.mp4 [32.5 MB]
11-尚硅谷-掌柜问数-项目依赖说明.mp4 [38.9 MB]
06-尚硅谷-掌柜问数-元数据知识库.mp4 [102.0 MB]
07-尚硅谷-掌柜问数-向量索引概述.mp4 [84.9 MB]
09-尚硅谷-掌柜问数-智能体结构概述.mp4 [39.3 MB]
15-尚硅谷-掌柜问数-问数全局配置.mp4 [30.3 MB]
12-尚硅谷-掌柜问数-搭建开发环境.mp4 [110.5 MB]
03-尚硅谷-掌柜问数-项目演示说明.mp4 [62.0 MB]
📁 资料
📁 models
base.py [88.0 B]
column_metric_mysql.py [459.0 B]
column_info_mysql.py [1.0 KB]
metric_info_mysql.py [807.0 B]
table_info_mysql.py [644.0 B]
📁 docker
📁 embedding
📁 bge-large-zh-v1.5
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
config.json.metadata [104.0 B]
tokenizer_config.json.metadata [103.0 B]
modules.json.metadata [104.0 B]
README.md.metadata [104.0 B]
pytorch_model.bin.metadata [127.0 B]
config_sentence_transformers.json.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
special_tokens_map.json.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
config.json.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
.gitignore [1.0 B]
📁 1_Pooling
config.json [191.0 B]
README.md [29.7 KB]
pytorch_model.bin [1.2 GB]
.gitattributes [1.5 KB]
tokenizer.json [428.8 KB]
special_tokens_map.json [125.0 B]
tokenizer_config.json [394.0 B]
modules.json [349.0 B]
sentence_bert_config.json [52.0 B]
vocab.txt [107.0 KB]
config_sentence_transformers.json [124.0 B]
config.json [1000.0 B]
📁 mysql
dw.sql [15.5 KB]
meta.sql [1.5 KB]
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
docker-compose.yaml [1.6 KB]
meta_config.yaml [4.8 KB]
meta_config.py [601.0 B]
pycharm-2025.3.2.1.exe [848.5 MB]
app_config.yaml [657.0 B]
Docker Desktop Installer.exe [598.8 MB]
log.py [2.0 KB]
📁 截图
03-智能体流程分析.png [148.1 KB]
04-uv缓存说明.png [32.2 KB]
07-ORM讲解.png [65.1 KB]
01-字段指标关系分析.png [46.5 KB]
02-掌柜问数分析.png [155.8 KB]
05-json和yaml结构.png [90.1 KB]
06-三层架构讲解.png [115.2 KB]
📁 代码
📁 data-agent
📁 app
📁 conf
📁 __pycache__
app_config.cpython-311.pyc [3.7 KB]
__init__.cpython-311.pyc [172.0 B]
text_config.cpython-311.pyc [1.2 KB]
__init__.py
app_config.py [1.2 KB]
text_config.py [844.0 B]
📁 __pycache__
__init__.cpython-311.pyc [167.0 B]
__init__.py
📁 conf
app_config.yaml [657.0 B]
text_config.yaml [72.0 B]
📁 docker
📁 embedding
📁 bge-large-zh-v1.5
📁 1_Pooling
config.json [191.0 B]
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
…（层级过深，已停止）
modules.json.metadata [104.0 B]
config.json.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
pytorch_model.bin.metadata [127.0 B]
config_sentence_transformers.json.metadata [104.0 B]
README.md.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
tokenizer_config.json.metadata [103.0 B]
special_tokens_map.json.metadata [104.0 B]
.gitignore [1.0 B]
config_sentence_transformers.json [124.0 B]
tokenizer.json [428.8 KB]
modules.json [349.0 B]
.gitattributes [1.5 KB]
tokenizer_config.json [394.0 B]
sentence_bert_config.json [52.0 B]
pytorch_model.bin [1.2 GB]
special_tokens_map.json [125.0 B]
README.md [29.7 KB]
vocab.txt [107.0 KB]
config.json [1000.0 B]
📁 mysql
meta.sql [1.5 KB]
dw.sql [15.5 KB]
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
docker-compose.yaml [1.6 KB]
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
modules.xml [279.0 B]
.gitignore [238.0 B]
data_agent.iml [404.0 B]
workspace.xml [6.3 KB]
sqldialects.xml [296.0 B]
misc.xml [300.0 B]
uv.lock [766.1 KB]
main.py [544.0 B]
pyproject.toml [545.0 B]
掌柜问数.rar [723.0 MB]
📁 课件
📁 assets
image-20260302193512226.png [36.1 KB]
wps7.jpg [130.8 KB]
image-20260301202052447.png [31.7 KB]
wps3.png [26.8 KB]
image-20260302165403928.png [48.5 KB]
image-20260302164313014.png [254.0 KB]
image-20260312185315752.png [102.1 KB]
image-20260311204041206.png [34.0 KB]
image-20260302145219771.png [37.5 KB]
image-20260207161919313.png [88.2 KB]
image-20260302144433733.png [66.1 KB]
wps6.png [626.0 KB]
image-20260121202402103.png [76.9 KB]
wps4.jpg [73.4 KB]
image-20260207142744497.png [48.0 KB]
image-20260303152708134.png [56.2 KB]
image-20260121215240284.png [34.4 KB]
image-20260312164049033.png [89.1 KB]
image-20260302193437126.png [35.3 KB]
image-20260302160651463.png [43.4 KB]
image-20260207140320440.png [21.8 KB]
image-20260311204011515.png [34.7 KB]
image-20260121184748743.png [51.2 KB]
wps5.jpg [112.5 KB]
image-20260302164430508.png [20.8 KB]
image-20260312162206045.png [69.2 KB]
image-20260121223015280.png [49.2 KB]
image-20260302192049010.png [43.8 KB]
image-20260301202214037.png [26.0 KB]
image-20260302193422656.png [35.7 KB]
image-20260121203227857.png [24.3 KB]
wps1.jpg [48.0 KB]
image-20260121202229381.png [34.2 KB]
image-20260121201903693.png [47.5 KB]
image-20260207140352763.png [65.8 KB]
wps2.jpg [48.0 KB]
image-20260121204009373.png [54.5 KB]
掌柜问数项目-问数智能体.drawio.svg [274.8 KB]
尚硅谷大模型项目之掌柜问数.md [240.4 KB]
📁 day02
📁 视频
11-尚硅谷-掌柜问数-Elasticsearch-分词器概念讲解.mp4 [44.3 MB]
09-尚硅谷-掌柜问数-Elasticsaerch-倒排索引全文检索.mp4 [36.3 MB]
14-尚硅谷-掌柜问数-Elasticsaerch-DSL查询单条件.mp4 [74.3 MB]
15-尚硅谷-掌柜问数-Elastcisaerch-DSL查询多条件.mp4 [30.2 MB]
10-尚硅谷-掌柜问数-Elasticsearch-核心概念讲解.mp4 [96.1 MB]
06-尚硅谷-掌柜问数-Qdrant客户端封装实现.mp4 [101.8 MB]
01-尚硅谷-掌柜问数-内容概述和回顾.mp4 [42.1 MB]
05-尚硅谷-掌柜问数-SqlAIchemy模型封装讲解.mp4 [47.1 MB]
13-尚硅谷-掌柜问数-Elasticsearch-动态和静态映射.mp4 [57.0 MB]
18-尚硅谷-掌柜问数-Elasticsearch向量客户端封装.mp4 [73.0 MB]
16-尚硅谷-掌柜问数-Elasticsearch-DSL排序和分页.mp4 [24.2 MB]
17-尚硅谷-掌柜问数-Elastcisearch客户端封装.mp4 [179.1 MB]
02-尚硅谷-掌柜问数-SqlAIchemy客户端基础封装.mp4 [198.8 MB]
04-尚硅谷-掌柜问数-SqlAIchemy客户端最终封装.mp4 [147.7 MB]
07-尚硅谷-掌柜问数-Qdrant客户端操作实现.mp4 [81.1 MB]
08-尚硅谷-掌柜问数-Elasticsearch-概述特性场景.mp4 [108.5 MB]
03-尚硅谷-掌柜问数-SqlAIchemy客户端engine参数.mp4 [54.0 MB]
12-尚硅谷-掌柜问数-Elasticsearch-文档和索引操作.mp4 [65.3 MB]
📁 课件
📁 assets
image-20260302193512226.png [36.1 KB]
image-20260303152708134.png [56.2 KB]
image-20260121202402103.png [76.9 KB]
image-20260311204041206.png [34.0 KB]
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wps5.jpg [112.5 KB]
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wps2.jpg [48.0 KB]
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wps6.png [626.0 KB]
image-20260301202052447.png [31.7 KB]
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wps7.jpg [130.8 KB]
wps1.jpg [48.0 KB]
image-20260302193422656.png [35.7 KB]
image-20260121184748743.png [51.2 KB]
image-20260302160651463.png [43.4 KB]
image-20260302164313014.png [254.0 KB]
image-20260311204011515.png [34.7 KB]
image-20260207161919313.png [88.2 KB]
wps4.jpg [73.4 KB]
image-20260121201903693.png [47.5 KB]
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image-20260312162206045.png [69.2 KB]
image-20260121223015280.png [49.2 KB]
image-20260302165403928.png [48.5 KB]
image-20260121202229381.png [34.2 KB]
image-20260121203227857.png [24.3 KB]
image-20260207140352763.png [65.8 KB]
掌柜问数项目-问数智能体.drawio.svg [274.8 KB]
image-20260312185315752.png [102.1 KB]
image-20260301202214037.png [26.0 KB]
image-20260302145219771.png [37.5 KB]
image-20260302144433733.png [66.1 KB]
尚硅谷大模型项目之掌柜问数.md [241.4 KB]
ElasticSearch入门.pdf [1.2 MB]
📁 截图
02-pool_pre_ping说明.png [44.3 KB]
03-autoflush讲解.png [95.8 KB]
01-sqlaichemy分析.png [69.8 KB]
05-es客户端说明.png [39.7 KB]
04-expire_on_commit讲解.png [84.0 KB]
📁 资料
📁 assets
tingshu034-1696666009361.png [48.4 KB]
image-20240603183546629.png [24.6 KB]
1710126225027.png [45.6 KB]
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检索-热度搜索.gif [2.8 MB]
image-20231001115629519.png [56.6 KB]
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image-20231007101258763.png [133.9 KB]
1591212819.bmp [7.5 MB]
image-20231128215831068.png [48.4 KB]
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订单-VIP购买入口.gif [830.4 KB]
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声音-声音修改.gif [1.1 MB]
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1690338814304.png [146.0 KB]
image-20231030102130401.png [68.9 KB]
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docker001.png [41.4 KB]
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个人git心得.docx [4.7 MB]
Cursor应用.pdf [12.3 MB]
ElasticSearch入门.md [23.5 KB]
📁 代码
📁 data-agent
📁 conf
text_config.yaml [72.0 B]
app_config.yaml [657.0 B]
📁 docker
📁 embedding
📁 bge-large-zh-v1.5
📁 1_Pooling
config.json [191.0 B]
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
…（层级过深，已停止）
modules.json.metadata [104.0 B]
README.md.metadata [104.0 B]
pytorch_model.bin.metadata [127.0 B]
special_tokens_map.json.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
tokenizer_config.json.metadata [103.0 B]
config_sentence_transformers.json.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
config.json.metadata [104.0 B]
.gitignore [1.0 B]
tokenizer.json [428.8 KB]
config.json [1000.0 B]
sentence_bert_config.json [52.0 B]
tokenizer_config.json [394.0 B]
vocab.txt [107.0 KB]
modules.json [349.0 B]
.gitattributes [1.5 KB]
config_sentence_transformers.json [124.0 B]
README.md [29.7 KB]
special_tokens_map.json [125.0 B]
pytorch_model.bin [1.2 GB]
📁 elasticsearch
📁 plugins
elasticsearch-analysis-ik-8.19.10.zip [4.4 MB]
Dockerfile [330.0 B]
📁 .venv
📁 Lib
📁 site-packages
_virtualenv.py [4.2 KB]
_virtualenv.pth [18.0 B]
📁 Scripts
activate [4.0 KB]
pythonw.exe [244.0 KB]
activate.fish [4.1 KB]
activate.nu [3.7 KB]
python.exe [256.0 KB]
pydoc.bat [1.2 KB]
activate.bat [2.6 KB]
activate.csh [2.6 KB]
activate.ps1 [2.7 KB]
deactivate.bat [1.7 KB]
activate_this.py [2.3 KB]
.gitignore [1.0 B]
CACHEDIR.TAG [43.0 B]
pyvenv.cfg [198.0 B]
📁 mysql
dw.sql [15.5 KB]
meta.sql [1.5 KB]
docker-compose.yaml [1.6 KB]
📁 app
📁 models
📁 qdrant
__init__.py
📁 mysql
table_info_mysql.py [640.0 B]
metric_info_mysql.py [807.0 B]
column_info_mysql.py [1.1 KB]
base.py [86.0 B]
column_metric_mysql.py [457.0 B]
__init__.py
📁 es
__init__.py
__init__.py
📁 clients
embedding_client_manager.py [1.3 KB]
__init__.py
qdrant_client_manager.py [2.1 KB]
mysql_client_manager.py [2.0 KB]
es_client_manager.py [4.2 KB]
📁 __pycache__
__init__.cpython-311.pyc [167.0 B]
📁 conf
📁 __pycache__
app_config.cpython-311.pyc [3.7 KB]
__init__.cpython-311.pyc [172.0 B]
text_config.cpython-311.pyc [1.2 KB]
text_config.py [844.0 B]
app_config.py [1.2 KB]
__init__.py
__init__.py
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
📁 dataSources
📁 0deae914-40e2-4145-9ff2-eeba6054ba72
📁 storage_v2
📁 _src_
📁 schema
performance_schema.kIw0nw.meta [76.0 B]
information_schema.FNRwLQ.meta [76.0 B]
0deae914-40e2-4145-9ff2-eeba6054ba72.xml [46.3 KB]
sqldialects.xml [296.0 B]
workspace.xml [12.0 KB]
data_agent.iml [404.0 B]
misc.xml [300.0 B]
dataSources.xml [530.0 B]
dataSources.local.xml [1.1 KB]
.gitignore [238.0 B]
modules.xml [279.0 B]
pyproject.toml [545.0 B]
main.py [544.0 B]
uv.lock [766.1 KB]
📁 day07
📁 2.资料
Git-2.43.0-64-bit.exe [58.0 MB]
a.txt
📁 4.视频
12_总结.mp4 [37.5 MB]
05_多分支操作_解决合并冲突.mp4 [71.6 MB]
04_git基本命令2.mp4 [93.4 MB]
07_远程操作_pull与push.mp4 [15.6 MB]
git_笔记.md [3.7 KB]
01_了解版本控制.mp4 [66.8 MB]
09_PyCharm集成git进行版本控制.mp4 [72.1 MB]
11_PyCharm集成Gitee并使用.mp4 [52.4 MB]
02_安装Git.mp4 [35.4 MB]
03_git的基本命令1.mp4 [151.9 MB]
06_gitee远程仓库基本使用.mp4 [40.4 MB]
08_远程操作_多人协作开发.mp4 [36.4 MB]
10_解决忽略的问题.mp4 [38.3 MB]
📁 1.笔记
尚硅谷大模型技术之Git1.1.docx [11.8 MB]
git_笔记.md [3.7 KB]
📁 3.代码
📁 git_pycharm
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
Project_Default.xml [720.0 B]
modules.xml [281.0 B]
workspace.xml [7.3 KB]
vcs.xml [185.0 B]
claudeCodeTabState.xml [607.0 B]
git_pycharm.iml [291.0 B]
.gitignore [238.0 B]
main.txt [89.0 B]
.gitignore [106.0 B]
📁 git_test
main.txt [82.0 B]
README.md [25.0 B]
📁 阶段07：LangGraph（2026年5月开始）
📁 2.代码
📁 3.视频
📁 day03
📁 课堂笔记
📁 images
节点的订阅和写入.png [38.1 KB]
人工审核节点.png [81.4 KB]
可控循环.png [28.2 KB]
输入输出数据隔离.png [769.8 KB]
节点执行流程.png [59.6 KB]
pregel底层原理.drawio.png [99.8 KB]
故障节点断点续传.png [957.2 KB]
工作流逻辑图.drawio.png [45.3 KB]
多次调用保持上下文.png [897.0 KB]
LangGraph.png [78.7 KB]
LangGraph-day02.md [100.5 KB]
📁 代码
langgraph_demo.zip [15.0 MB]
02-尚硅谷-LangGraph-节点的人工审核核中断机制的流程梳理.mp4 [268.7 MB]
06-尚硅谷-LangGraph-节点的人工审核与中断机制的拒绝测试.mp4 [4.4 MB]
11-尚硅谷-LangGraph-边-Pregel的超步执行流程的补充.mp4 [16.3 MB]
05-尚硅谷-LangGraph-节点的人工审核与中断机制的代码编写.mp4 [219.3 MB]
01-尚硅谷-LangGraph-day02总结和今日内容.mp4 [87.7 MB]
10-尚硅谷-LangGraph-边-条件边的路由返回值.mp4 [28.1 MB]
03-尚硅谷-LangGraph-节点的人工审核与中断机制的文字流程图的解读.mp4 [15.1 MB]
09-尚硅谷-LangGraph-边-演示可控循环.mp4 [104.7 MB]
07-尚硅谷-LangGraph-边-条件边.mp4 [146.6 MB]
08-尚硅谷-LangGraph-边-什么是可控循环.mp4 [25.3 MB]
04-尚硅谷-LangGraph-节点的人工审核与中断机制的伪代码编写.mp4 [27.4 MB]
📁 day01
📁 代码
langgraph_demo.zip [15.0 MB]
📁 课堂笔记
📁 images
pregel底层原理.drawio.png [99.8 KB]
故障节点断点续传.png [957.2 KB]
LangGraph.png [78.7 KB]
节点执行流程.png [59.6 KB]
节点的订阅和写入.png [38.1 KB]
输入输出数据隔离.png [769.8 KB]
多次调用保持上下文.png [897.0 KB]
工作流逻辑图.drawio.png [45.3 KB]
LangGraph-day01.md [58.4 KB]
25-尚硅谷-langGraph-状态存储的业务场景.mp4 [19.5 MB]
08-尚硅谷-langGraph-上节课总结和本节内容.mp4 [12.7 MB]
13-尚硅谷-langGraph-State-Pydantic.mp4 [49.8 MB]
28-尚硅谷-langGraph-上节课总结.mp4 [32.2 MB]
.mp4 [9.4 MB]
02-尚硅谷-langGraph-介绍.mp4 [50.4 MB]
24-尚硅谷-langGraph-Reducer-并行执行与状态合并.mp4 [27.4 MB]
17-尚硅谷-langGraph-State-节点数据隔离.mp4 [34.6 MB]
01-尚硅谷-langGraph-课程介绍.mp4 [7.9 MB]
23-尚硅谷-langGraph-Reducer-自定义函数.mp4 [85.2 MB]
15-尚硅谷-langGraph-State-输入数据隔离.mp4 [60.7 MB]
09-尚硅谷-langGraph-State-定义的三种方式-dict.mp4 [22.5 MB]
31-尚硅谷-langGraph-持久化记忆和sqlite.mp4 [47.5 MB]
16-尚硅谷-langGraph-State-输出数据隔离.mp4 [55.2 MB]
05-尚硅谷-langGraph-定义图状态.mp4 [18.9 MB]
10-尚硅谷-langGraph-State-定义的三种方式-TypedDict.mp4 [6.6 MB]
06-尚硅谷-langGraph-定义节点.mp4 [51.2 MB]
30-尚硅谷-langGraph-基于内存的状态记忆.mp4 [42.3 MB]
29-尚硅谷-langGraph-LangGraph状态记忆机制.mp4 [6.8 MB]
22-尚硅谷-langGraph-Reducer-上节课总结.mp4 [16.6 MB]
26-尚硅谷-langGraph-会话存储的使用场景和技术实现.mp4 [31.4 MB]
27-尚硅谷-langGraph-回顾LangChain中的Checkpointer.mp4 [54.9 MB]
04-尚硅谷-langGraph-实现一个入门工作流的步骤分析.mp4 [12.1 MB]
32-尚硅谷-langGraph-实现持久化记忆.mp4 [40.7 MB]
07-尚硅谷-langGraph-定义完整的工作流.mp4 [50.3 MB]
33-尚硅谷-langGraph-崩溃恢复.mp4 [27.6 MB]
18-尚硅谷-langGraph-上午总结和下午内容.mp4 [35.2 MB]
21-尚硅谷-langGraph-Reducer-追加.mp4 [20.2 MB]
12-尚硅谷-langGraph-State-TypeDict的可选字段.mp4 [28.9 MB]
20-尚硅谷-langGraph-Reducer-默认行为-覆盖.mp4 [121.4 MB]
03-尚硅谷-langGraph-环境安装.mp4 [23.2 MB]
11-尚硅谷-langGraph-State-定义的三种方式-TypedDict和dict的区别的总结.mp4 [24.7 MB]
19-尚硅谷-langGraph-Reducer函数三种行为介绍.mp4 [21.6 MB]
📁 day02
📁 代码
langgraph_demo.zip [15.0 MB]
📁 课堂笔记
📁 images
故障节点断点续传.png [957.2 KB]
pregel底层原理.drawio.png [99.8 KB]
人工审核节点.png [81.4 KB]
节点的订阅和写入.png [38.1 KB]
多次调用保持上下文.png [897.0 KB]
节点执行流程.png [59.6 KB]
可控循环.png [28.2 KB]
工作流逻辑图.drawio.png [45.3 KB]
输入输出数据隔离.png [769.8 KB]
LangGraph.png [78.7 KB]
LangGraph-day02.md [98.9 KB]
14-尚硅谷-LangGraph-节点-sys.intern.mp4 [39.5 MB]
25-尚硅谷-LangGraph-节点-流式输出-mode是混合模式.mp4 [12.9 MB]
13-尚硅谷-LangGraph-节点-特殊节点-START和END.mp4 [11.1 MB]
16-尚硅谷-LangGraph-节点-缓存的实现.mp4 [39.7 MB]
19-尚硅谷-LangGraph-节点-流式输出说明和案例的初步编写.mp4 [142.2 MB]
03-尚硅谷-LangGraph-pregel-什么是Actors、Channel、SuperStep.mp4 [73.2 MB]
23-尚硅谷-LangGraph-节点-流式输出-mode是messages.mp4 [18.1 MB]
15-尚硅谷-LangGraph-节点-缓存的实现步骤说明.mp4 [11.2 MB]
01-尚硅谷-LangGraph-day01回顾和今日内容.mp4 [90.4 MB]
06-尚硅谷-LangGraph-pregel-查看节点的历史状态.mp4 [78.1 MB]
12-尚硅谷-LangGraph-上午总结.mp4 [29.3 MB]
07-尚硅谷-LangGraph-节点-常见的三个输入参数.mp4 [23.5 MB]
17-尚硅谷-LangGraph-节点-重试机制的说明.mp4 [21.7 MB]
20-尚硅谷-LangGraph-节点-流式输出-mode是values.mp4 [24.3 MB]
10-尚硅谷-LangGraph-节点-三个输入参数案例实现3-runtime.mp4 [52.8 MB]
21-尚硅谷-LangGraph-节点-流式输出-mode是updates.mp4 [16.6 MB]
18-尚硅谷-LangGraph-节点-重试的实现.mp4 [65.5 MB]
08-尚硅谷-LangGraph-节点-三个输入参数案例实现1-state.mp4 [54.5 MB]
02-尚硅谷-LangGraph-pregel-一个案例.mp4 [41.4 MB]
24-尚硅谷-LangGraph-节点-流式输出-mode是debug.mp4 [24.2 MB]
05-尚硅谷-LangGraph-pregel-SuperStep的进一步解释.mp4 [42.9 MB]
11-尚硅谷-LangGraph-节点-输出.mp4 [38.1 MB]
22-尚硅谷-LangGraph-节点-流式输出-mode是custom.mp4 [23.2 MB]
09-尚硅谷-LangGraph-节点-三个输入参数案例实现2-config.mp4 [24.8 MB]
04-尚硅谷-LangGraph-pregel-执行流程图解.mp4 [35.7 MB]
📁 1.笔记
尚硅谷大模型技术之LangGraphV1.1.0.docx [1.8 MB]
阶段07：LangGraph（2026年5月开始）资料.png [493.5 KB]
📁 阶段04：AI Agent大模型基础
📁 2.资料
Cherry-Studio-1.7.13-x64-setup.exe [114.8 MB]
提示词相关知识点.txt [1.6 KB]
飞书文档链接.txt [82.0 B]
📁 4.视频
20_提示词模版.mp4 [30.5 MB]
03_大模型出现的原因.mp4 [54.1 MB]
15_工程实现概述.mp4 [33.7 MB]
09_大模型的训练范式.mp4 [25.9 MB]
27_总结.mp4 [64.8 MB]
23_微调相关知识.mp4 [13.7 MB]
06_AIGC&AGI以及大模型开源的概念.mp4 [24.3 MB]
13_CUDA的作用.mp4 [10.8 MB]
21_提示词工程的能力边界.mp4 [25.1 MB]
16_在线调用模型API.mp4 [38.3 MB]
24_续训相关知识.mp4 [6.4 MB]
26_MCP工具的调用.mp4 [120.4 MB]
19_多轮对话消息结构设计.mp4 [52.8 MB]
10_硬件基础设施.mp4 [40.5 MB]
05_大模型的分类.mp4 [39.6 MB]
08_为什么大模型都采用单解码器架构.mp4 [36.9 MB]
22_RAG相关知识.mp4 [38.4 MB]
04_大模型计量单位.mp4 [35.0 MB]
12_推理阶段的硬件瓶颈.mp4 [34.8 MB]
25_智能体相关知识.mp4 [52.4 MB]
17_提示词五要素的编写.mp4 [108.9 MB]
11_训练阶段的硬件瓶颈.mp4 [47.0 MB]
18_提示词五要素的编写(下).mp4 [30.2 MB]
28_Harness相关知识分享.mp4 [86.6 MB]
02_大模型的定义.mp4 [26.9 MB]
07_大模型架构演进以及transformer的优点.mp4 [49.4 MB]
01-大模型概述.mp4 [6.9 MB]
14_总结.mp4 [85.0 MB]
📁 3.代码
📁 1.笔记
尚硅谷大模型技术之大模型概述v1.1.8.docx [14.1 MB]
📁 阶段05：智能体 Coze、Dify
📁 1-课件
📁 04-大模型项目之商户运营管家
📁 04-06-Dify案例：商品评论分析
📁 images
image-20251118111335934.png [398.1 KB]
image-20251118111016157.png [354.4 KB]
image-20251118111613972.png [1.1 MB]
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image-20251117174459641.png [287.9 KB]
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image-20251118111421852.png [573.7 KB]
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image-20251118102652013.png [145.3 KB]
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image-20251118104915776.png [244.8 KB]
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image-20251118102559500.png [139.5 KB]
image-20251118110014344.png [264.4 KB]
image-20251118111203292.png [372.9 KB]
image-20251118111003806.png [288.4 KB]
尚硅谷-商品评论分析-Dify.md [203.5 KB]
商品评论数据.csv [30.2 KB]
尚硅谷-商品评论分析.yml [16.5 KB]
📁 04-02-Coze案例：一键生成商品宣传视频
📁 数据
商品信息.txt [1.1 KB]
大纲生成提示词.txt [2.1 KB]
洗地机.png [268.0 KB]
📁 输出示例
📁 分镜视频
10-11.mp4 [4.2 MB]
5-6.mp4 [4.2 MB]
3-4.mp4 [4.1 MB]
14-15.mp4 [4.2 MB]
11-12.mp4 [4.2 MB]
12-13.mp4 [4.2 MB]
9-10.mp4 [4.1 MB]
2-3.mp4 [9.1 MB]
1-2.mp4 [4.2 MB]
7-8.mp4 [4.2 MB]
15-16.mp4 [3.9 MB]
8-9.mp4 [4.2 MB]
4-5.mp4 [9.1 MB]
6-7.mp4 [14.0 MB]
13-14.mp4 [4.2 MB]
📁 分镜图片
镜头9.png [2.6 MB]
镜头10.png [2.0 MB]
镜头11.png [2.2 MB]
镜头8.png [1.5 MB]
镜头5.png [2.0 MB]
镜头7.png [1.7 MB]
镜头4.png [1.3 MB]
镜头12.png [2.4 MB]
镜头1.png [2.9 MB]
镜头13.png [1.3 MB]
镜头3.png [1.2 MB]
镜头6.png [2.3 MB]
镜头16.png [348.8 KB]
镜头15.png [1.8 MB]
镜头2.png [1.9 MB]
镜头14.png [2.2 MB]
大纲、分镜脚本和旁白.txt [6.2 KB]
📁 工作流和UI配置文件
gen_pic_2.txt [5.3 KB]
gen_pic_1.txt [5.3 KB]
set_product_info-chat_flow.txt [22.9 KB]
UI.txt [27.5 KB]
app_var_test.txt [6.6 KB]
gen_pic_3.txt [5.3 KB]
generate_outline.txt [10.8 KB]
user_var_test.txt [6.6 KB]
generate_pictures.txt [16.6 KB]
📁 images
image-20251211191828413.png [201.3 KB]
image-20251211173959394.png [242.0 KB]
image-20251212105633374.png [581.3 KB]
image-20251211170327815.png [241.8 KB]
image-20251211185606003.png [335.7 KB]
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尚硅谷-一键生成商品宣传视频.md [150.9 KB]
📁 04-07-Coze案例：商品营销卖点提炼
📁 数据及背景图
📁 logo 2张
尚硅谷logo2.png [45.3 KB]
尚硅谷logo1.png [32.3 KB]
5.尚硅谷-高质量营销文案技巧.xlsx [11.6 KB]
开场海报.png [634.8 KB]
4.尚硅谷-短视频脚本技巧_结尾.xlsx [9.5 KB]
3.尚硅谷-短视频脚本技巧_开头.xlsx [10.5 KB]
1.尚硅谷-抖音热点.xlsx [9.1 KB]
product_list数据表结构.jpg [192.1 KB]
2.尚硅谷-微博热点.xlsx [5.2 KB]
用户变量.jpg [278.2 KB]
📁 images
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1.全流程调用链.svg [761.8 KB]
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📁 架构图
0.尚硅谷-商品营销卖点提炼-调用链.drawio [52.9 KB]
4.单独生成买点调用链.svg [247.8 KB]
3.单独生成卖点调用链.svg [196.9 KB]
2.单独设置产品信息调用链.svg [203.2 KB]
1.全流程调用链.svg [761.8 KB]
5.生成文案或脚本调用链.svg [249.2 KB]
04-单独生成买点调用链.txt [106.7 KB]
05-生成文案或脚本调用链.txt [50.1 KB]
02-单独设置产品信息调用链.txt [33.8 KB]
01-全流程调用链.txt [17.8 KB]
尚硅谷-商品营销卖点提炼-Coze.md [141.8 KB]
03-单独生成卖点调用链.txt [125.1 KB]
📁 04-05-Coze案例：客服对话记录分析
📁 images
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尚硅谷-客服对话记录分析-Coze.md [96.7 KB]
应用界面.txt
尚硅谷-客服对话记录分析-message_process.txt [23.0 KB]
尚硅谷-客服对话记录分析-excel_process.txt [6.9 KB]
客服对话记录.xlsx [11.6 KB]
📁 04-05-Dify案例：客服对话记录分析
📁 images
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尚硅谷-客服对话记录分析-whole-workflow.jpeg [650.5 KB]
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尚硅谷-客服对话记录分析-Dify.md [73.8 KB]
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客服对话数据.xlsx [11.6 KB]
📁 04-01-Coze案例：产品营销海报生成
尚硅谷-产品营销海报生成-应用界面1.txt [116.4 KB]
尚硅谷-产品营销海报生成-工作流.txt [59.5 KB]
尚硅谷-产品营销海报生成-应用界面2.txt [29.9 KB]
03-03-Coze案例：产品营销海报生成.md [5.9 KB]
📁 04-06-Coze案例：商品评论分析
📁 images
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📁 04-03-Dify案例：客户投诉分类助手-钉钉
03-04-Dify案例：客户投诉分类助手-钉钉.md [3.6 KB]
客户投诉分类助手-钉钉.yml [29.7 KB]
📁 images
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📁 04-04-Dify案例：一键生成行业(或产品)调研报告
03-05-Dify案例：一键生成行业(或产品)调研报告.md [234.1 KB]
一键生成行业(或产品)调研报告.yml [35.5 KB]
📁 images
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📁 03-低代码平台介绍
📁 images
意图识别节点.png [152.9 KB]
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输出节点-退款结果.png [66.1 KB]
通用回复节点.png [68.9 KB]
文本处理节点.png [108.6 KB]
输出节点-欢迎语.png [68.0 KB]
终止循环节点.png [49.1 KB]
循环节点-商品名称校验.png [95.4 KB]
大模型节点-陪聊.png [229.2 KB]
选择器节点.png [92.2 KB]
workflow.svg [48.5 MB]
输出节点-重新输入提示.png [65.2 KB]
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输出节点-咨询回复.png [72.1 KB]
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电商客服初级.txt [37.6 KB]
商家客服初级.md [17.7 KB]
05-Python调用Dify平台工作流.md [62.8 KB]
09-企业级大模型的部署.md [34.4 KB]
02-基于Coze&Dify平台的智能体开发.md [39.8 KB]
07-Coze的Windows平台部署.md [21.4 KB]
06-Python调用Coze平台工作流.md [7.2 KB]
01-RAG-搭建企业私有&个人知识库.md [16.3 KB]
08-Dify的Windows平台部署.md [3.3 KB]
📁 2-资料
📁 抖音文案-康师傅
已经从事软件开发，要不要转投鸿蒙？.docx [16.5 KB]
网络&信息安全：想说爱你不容易.docx [14.5 KB]
什么人适合学习Go.docx [14.5 KB]
云计算运维：这其实算是俩方向 - 副本.docx [14.5 KB]
剖析Java死不透的底层逻辑.docx [14.7 KB]
听说Java入行要学很多技术栈，零基础，非科班，如何规划学习？.docx [21.8 KB]
C语言到底要不要学？.docx [14.2 KB]
人工智能：看看2025年高薪机遇.docx [14.5 KB]
Java转GO，是越走越窄，还是柳暗花明？.docx [16.5 KB]
想入行软件开发，不知道选啥语言？.docx [17.0 KB]
Python：非专业开发的首选语言？.docx [14.5 KB]
哪些人适合入手C++.docx [14.5 KB]
AI的火爆，会不会让程序员大量失业.docx [17.0 KB]
计科相关专业的哪些课程比较重要呢.docx [19.2 KB]
云计算运维：这其实算是俩方向.docx [14.5 KB]
成为Java工程师，要掌握全栈、分布式、嵌入式和C++吗？.docx [53.6 KB]
📁 学生使用共享镜像
📁 images
image-20250811182609146.png [26.1 KB]
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设置腾讯云实例的镜像.md [391.0 B]
使用讲师共享的镜像的操作步骤.txt [515.0 B]
📁 images
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image-20250227213455972.png [8.6 KB]
image-20250209221847478.png [12.2 KB]
微信图片_20250207102910-1739761241988.jpg [38.2 KB]
image-20250209221553039.png [25.2 KB]
image-20250206230224080-1739761241989.png [85.2 KB]
image-20250206181403088-1739761241989.png [184.6 KB]
image-20250209221812441.png [6.9 KB]
image-20250209220136729.png [22.8 KB]
AutoDL使用文档.pdf [2.3 MB]
多智能体的交互.mp4 [12.9 MB]
对比：宇树科技G1功夫小子V6.0.mp4 [32.8 MB]
对比：TESLA特斯拉人形机器人.mp4 [22.1 MB]
logo.jpg [412.8 KB]
刑法.txt [114.6 KB]
代码中转义字符操作的理解.jpg [117.6 KB]
部署架构.drawio [179.3 KB]
二维码.jpg [48.1 KB]
gSpTfQL9G1Bd5NvY.pptx [2.9 MB]
本地大模型的安装部署.md [7.8 KB]
📁 3-软件
OllamaSetup.exe [1.1 GB]
ima.copilot-win-x64-10000075-2.1.0(3484).exe [191.9 MB]
Docker Desktop Installer.exe [561.1 MB]
9_学习必备_Typora.zip [88.5 MB]
Postman-win64-9.15.2-Setup.exe [153.4 MB]
coze-loop-main.zip [7.6 MB]
dify-0.15.5.tar.gz [22.7 MB]
go1.25.4.windows-amd64.msi [53.5 MB]
📁 5-视频
📁 day03
requirements.txt [400.0 B]
13_算力云平台部署XInference.mp4 [122.7 MB]
11_腾讯云部署docker并安装dify.mp4 [222.2 MB]
05_生成用户买点工作流.mp4 [80.6 MB]
14_XInference安装模型并配置Dify.mp4 [55.8 MB]
15_实例释放的说明.mp4 [12.8 MB]
10_企业部署大模型的介绍.mp4 [60.8 MB]
09_python调用dify工作流.mp4 [36.4 MB]
04_生成营销卖点工作流.mp4 [147.7 MB]
06_生成营销文案工作流.mp4 [87.7 MB]
12_算力云平台创建实例.mp4 [194.1 MB]
02_商品营销卖点提炼说明及演示.mp4 [103.7 MB]
01_今天的三个任务.mp4 [13.3 MB]
03_生成产品描述工作流.mp4 [102.4 MB]
08_python调用coze工作流.mp4 [81.5 MB]
07_项目案例的挑选.mp4 [14.9 MB]
📁 day02
3_coze案例1_关于两个变量的介绍.mp4 [39.4 MB]
9_dify案例2_一键生成行业调研报告.mp4 [176.9 MB]
1_案例介绍.mp4 [172.0 MB]
13_coze案例3_商品评论分析.mp4 [155.4 MB]
7_dify案例1_客服投诉分类助手.mp4 [97.0 MB]
4_coze案例1_一键生成宣传视频对话流介绍.mp4 [74.1 MB]
5_coze案例1_生成大纲工作流介绍.mp4 [33.1 MB]
11_dify案例3_客服对话记录分析.mp4 [72.6 MB]
2_coze案例1_一键生成商品宣传视频.mp4 [85.3 MB]
14_dify案例4_商品评论分析.mp4 [45.9 MB]
6_coze案例1_生成图片工作流介绍mp4.mp4 [160.4 MB]
12_dify插件配置说明.mp4 [4.2 MB]
10_coze案例2_客服对话记录分析.mp4 [216.3 MB]
8_dIfy案例2_插件的配置.mp4 [69.3 MB]
📁 day01
01_总结回顾.mp4 [75.0 MB]
13_家庭记账助手智能体.mp4 [56.3 MB]
20_产品营销海报用户界面功能说明.mp4 [292.9 MB]
10_深夜情感主持智能体.mp4 [77.6 MB]
17_商户运营工作流实战下.mp4 [97.8 MB]
07_本地部署模型.mp4 [26.6 MB]
05_ima构建RAG知识库.mp4 [29.1 MB]
04_cherrystduio构建RAG.mp4 [81.3 MB]
14_Dify旅游规划助手.mp4 [66.8 MB]
02_RAG介绍.mp4 [82.1 MB]
06_dify构建RAG知识库.mp4 [66.8 MB]
18_问题说明.mp4 [12.1 MB]
03_产品选型介绍.mp4 [18.9 MB]
09_coze平台功能介绍.mp4 [48.8 MB]
19_第四章案例说明.mp4 [20.1 MB]
21_产品营销海报工作流说明.mp4 [69.2 MB]
08_三个level智能体的介绍.mp4 [124.0 MB]
16_商户运营工作流实战上.mp4 [46.5 MB]
12_大学百事通智能体.mp4 [132.3 MB]
15_Coze节点的简单介绍.mp4 [68.6 MB]
11_前情回顾.mp4 [26.0 MB]
📁 4-代码
📁 阶段08：RAG项目
📁 4.视频
📁 day12
📁 课堂笔记
📁 images
向量化节点流程图.png [949.0 KB]
保存milvus节点流程图.png [955.1 KB]
879160d3-2358-43ec-9551-e8ab9fa42af6-17732210276796.jpg [127.5 KB]
13.节点基类执行流程.jpg [468.0 KB]
rff融合排序流程.png [885.6 KB]
文档切片流程图.png [1000.7 KB]
image-20260310183103711.png [53.9 KB]
image-20260315191452504.png [46.6 KB]
重排序流程图.png [963.7 KB]
产品确认节点流程图.png [962.3 KB]
image-20260202160422170.png [137.8 KB]
向量搜索流程图.png [910.0 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
image-20260312235630471.png [114.6 KB]
文档切片流程图3.png [1005.3 KB]
假设性文档生成流程图.png [991.2 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
image-20260429013135647.png [48.2 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
PDF转MD流程图.png [956.4 KB]
主体识别节点流程图.png [1020.9 KB]
文档切片流程图2.png [956.5 KB]
image-20260318025329233.png [53.8 KB]
1.整体架构图.jpg [569.9 KB]
向量.jpeg [99.5 KB]
image-20260326223039801.png [5.7 KB]
MCP节点流程.png [925.4 KB]
wps1-17699496797303-17732210276785.jpg [62.4 KB]
入口节点流程图.png [6.7 MB]
image-20260202145456329.png [21.2 KB]
MD图片处理流程.png [1.0 MB]
image-20260310183135191.png [56.5 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
16【掌柜智库】【检索】结果融合重排.md [12.0 KB]
15【掌柜智库】【检索】网络搜索.md [9.9 KB]
01【掌柜智库】项目简介.md [8.0 KB]
14【掌柜智库】【检索】假设性文档向量搜索.md [13.8 KB]
02【掌柜智库】环境准备.md [17.6 KB]
13【掌柜智库】【检索】搜索向量库.md [7.4 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
17【掌柜智库】【检索】Rerank重排序.md [19.2 KB]
12【掌柜智库】【检索】产品确认.md [58.2 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
14-尚硅谷-掌柜智库-Renrank重排序-配置千问的rerank模型.mp4 [63.7 MB]
knowledge_base.zip [471.1 KB]
05-尚硅谷-掌柜智库-RRF融合排序-单元测试以及为什么RRF中只有两路搜索.mp4 [26.0 MB]
17-尚硅谷-掌柜智库-Renrank重排序-断崖戒断.mp4 [155.5 MB]
09-尚硅谷-掌柜智库-上午总结和下午内容.mp4 [50.0 MB]
16-尚硅谷-掌柜智库-Renrank重排序-获取相关性排序后的结果列表.mp4 [90.2 MB]
07-尚硅谷-掌柜智库-RRF融合排序上节课总结以及接下来要做的事情.mp4 [57.2 MB]
03-尚硅谷-掌柜智库-RRF融合排序-为什么需要RRF.mp4 [38.0 MB]
04-尚硅谷-掌柜智库-RRF融合排序-k值的大小以及RRF的总结.mp4 [20.5 MB]
01-尚硅谷-掌柜智库-day11总结和今日内容.mp4 [12.1 MB]
10-尚硅谷-掌柜智库-什么是rerank重排.mp4 [15.9 MB]
08-尚硅谷-掌柜智库-RRF融合排序-数据的融合和测试.mp4 [84.9 MB]
11-尚硅谷-掌柜智库-交叉编码和两阶段检索策略.mp4 [84.8 MB]
15-尚硅谷-掌柜智库-Renrank重排序-调用千问的rerank模型.mp4 [219.9 MB]
06-尚硅谷-掌柜智库-RRF融合排序-使用倒数排名进行融合排序.mp4 [369.1 MB]
02-尚硅谷-掌柜智库-RRF融合排序-什么是RRF融合以及公式.mp4 [126.5 MB]
12-尚硅谷-掌柜智库-Renrank重排序-断崖检测.mp4 [79.2 MB]
13-尚硅谷-掌柜智库-Renrank重排序-业务流程-第一步组装rrf和mcp结果数据.mp4 [146.6 MB]
📁 day11
📁 课堂笔记
📁 images
主体识别节点流程图.png [1020.9 KB]
假设性文档生成流程图.png [991.2 KB]
image-20260326223039801.png [5.7 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
image-20260315191452504.png [46.6 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
文档切片流程图.png [1000.7 KB]
879160d3-2358-43ec-9551-e8ab9fa42af6-17732210276796.jpg [127.5 KB]
image-20260310183103711.png [53.9 KB]
产品确认节点流程图.png [962.3 KB]
image-20260312235630471.png [114.6 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
向量搜索流程图.png [910.0 KB]
image-20260318025329233.png [53.8 KB]
image-20260202145456329.png [21.2 KB]
入口节点流程图.png [6.7 MB]
13.节点基类执行流程.jpg [468.0 KB]
image-20260429013135647.png [48.2 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
wps1-17699496797303-17732210276785.jpg [62.4 KB]
向量.jpeg [99.5 KB]
1.整体架构图.jpg [569.9 KB]
保存milvus节点流程图.png [955.1 KB]
MD图片处理流程.png [1.0 MB]
image-20260310183135191.png [56.5 KB]
文档切片流程图2.png [956.5 KB]
文档切片流程图3.png [1005.3 KB]
MCP节点流程.png [925.4 KB]
image-20260202160422170.png [137.8 KB]
向量化节点流程图.png [949.0 KB]
PDF转MD流程图.png [956.4 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
13【掌柜智库】【检索】搜索向量库.md [7.4 KB]
14【掌柜智库】【检索】假设性文档向量搜索.md [13.8 KB]
12【掌柜智库】【检索】产品确认.md [58.2 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
02【掌柜智库】环境准备.md [17.6 KB]
15【掌柜智库】【检索】网络搜索.md [9.9 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
01【掌柜智库】项目简介.md [8.0 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
12-尚硅谷-掌柜智库-根据假设性文档进行向量查询.mp4 [89.2 MB]
08-尚硅谷-掌柜智库-什么是假设性文档生成以及单元测试.mp4 [56.2 MB]
03-尚硅谷-掌柜智库-向量搜索节点-节点功能的实现.mp4 [207.2 MB]
06-尚硅谷-掌柜智库-意图确认和向量搜索节点目前的问题的解决.mp4 [178.0 MB]
17-尚硅谷-掌柜智库-MCP搜索-调用MCP方法.mp4 [85.3 MB]
09-尚硅谷-掌柜智库-假设性搜索流程分析.mp4 [18.8 MB]
11-尚硅谷-掌柜智库-上午总结以及llm工具类分析和假设性文档生成测试.mp4 [173.4 MB]
knowledge_base.zip [463.5 KB]
10-尚硅谷-掌柜智库-生成搜假设性文档.mp4 [152.3 MB]
16-尚硅谷-掌柜智库-MCP搜索-定义MCP方法.mp4 [93.3 MB]
13-尚硅谷-掌柜智库-假设性文档向量搜索-测试.mp4 [22.3 MB]
05-尚硅谷-掌柜智库-意图确认和向量搜索节点目前的问题.mp4 [70.2 MB]
01-尚硅谷-掌柜智库-day10回顾和今日内容.mp4 [94.2 MB]
04-尚硅谷-掌柜智库-向量搜索节点-功能测试.mp4 [76.0 MB]
14-尚硅谷-掌柜智库-aliyun百炼的MCP.mp4 [117.9 MB]
02-尚硅谷-掌柜智库-向量搜索节点-节点功能和单元测试.mp4 [21.6 MB]
07-尚硅谷-掌柜智库-导入流程的全流程测试.mp4 [65.0 MB]
15-尚硅谷-掌柜智库-MCP搜索-一些准备工作.mp4 [33.6 MB]
📁 day02
📁 课堂笔记
📁 images
image-20260429013135647.png [48.2 KB]
image-20260310183135191.png [56.5 KB]
image-20260312235630471.png [114.6 KB]
image-20260310183103711.png [53.9 KB]
image-20260202160422170.png [137.8 KB]
image-20260202145456329.png [21.2 KB]
image-20260315191452504.png [46.6 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
13.节点基类执行流程.jpg [468.0 KB]
1.整体架构图.jpg [569.9 KB]
15.整体流程概述.jpg [495.4 KB]
01【掌柜智库】项目简介.md [8.0 KB]
04【掌柜智库】【导入】入口节点.md [5.7 KB]
uv.toml [185.0 B]
项目描述参考模板.txt [389.0 B]
02【掌柜智库】环境准备.md [21.9 KB]
03【掌柜智库】【导入】骨架代码.md [41.4 KB]
📁 代码
knowledge_base.zip [29.0 MB]
06-尚硅谷-掌柜智库-安装部分项目依赖以及uv sync.mp4 [10.1 MB]
16-尚硅谷-掌柜智库-自定义BaseNode的梳理.mp4 [145.2 MB]
02-尚硅谷-掌柜智库-安装和激活项目的虚拟环境.mp4 [73.4 MB]
03-尚硅谷-掌柜智库-创建.env文件.mp4 [16.5 MB]
12-尚硅谷-掌柜智库-uv python install无法下载的问题.mp4 [11.9 MB]
.mp4 [41.0 MB]
22-尚硅谷-掌柜智库-优化工作流的获取流程.mp4 [91.5 MB]
15-尚硅谷-掌柜智库-上午总结.mp4 [15.0 MB]
18-尚硅谷-掌柜智库-BaseNode设计的梳理2.mp4 [84.9 MB]
.mp4 [22.4 MB]
05-尚硅谷-掌柜智库-测试环境变量的优先级.mp4 [14.8 MB]
04-尚硅谷-掌柜智库-uv add和uv pip install的区别.mp4 [20.9 MB]
17-尚硅谷-掌柜智库-BaseNode设计的梳理.mp4 [34.0 MB]
09-尚硅谷-掌柜智库-全局配置的设计思想.mp4 [80.3 MB]
13-尚硅谷-掌柜智库-自定义异常.mp4 [93.2 MB]
19-尚硅谷-掌柜智库-BaseNode的梳理.mp4 [82.3 MB]
07-尚硅谷-掌柜智库-上节课总结.mp4 [12.2 MB]
20-尚硅谷-掌柜智库-所有导入流程相关节点的创建.mp4 [27.1 MB]
14-尚硅谷-掌柜智库-state的设计思想.mp4 [24.3 MB]
01-尚硅谷-掌柜智库-day01总结今日内容以及面试中如何进行项目描述.mp4 [62.1 MB]
08-尚硅谷-掌柜智库-骨架代码介绍.mp4 [63.5 MB]
21-尚硅谷-掌柜智库-创建图结构.mp4 [147.8 MB]
📁 day08
📁 课堂笔记
📁 images
13.节点基类执行流程.jpg [468.0 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
文档切片流程图3.png [1005.3 KB]
image-20260202145456329.png [21.2 KB]
image-20260429013135647.png [48.2 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
image-20260310183135191.png [56.5 KB]
向量.jpeg [99.5 KB]
文档切片流程图2.png [956.5 KB]
文档切片流程图.png [1000.7 KB]
image-20260315191452504.png [46.6 KB]
1.整体架构图.jpg [569.9 KB]
image-20260312235630471.png [114.6 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
MD图片处理流程.png [1.0 MB]
image-20260326223039801.png [5.7 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
image-20260310183103711.png [53.9 KB]
PDF转MD流程图.png [956.4 KB]
image-20260202160422170.png [137.8 KB]
image-20260318025329233.png [53.8 KB]
向量化节点流程图.png [949.0 KB]
主体识别节点流程图.png [1020.9 KB]
保存milvus节点流程图.png [955.1 KB]
入口节点流程图.png [6.7 MB]
02【掌柜智库】环境准备.md [17.6 KB]
09【掌柜智库】【导入】向量化.md [7.0 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
03【掌柜智库】【导入】骨架代码.md [41.6 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.2 KB]
08【掌柜智库】【导入】主体识别.md [43.3 KB]
01【掌柜智库】项目简介.md [8.0 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
10【掌柜智库】【导入】存入 Milvus.md [15.5 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
01-尚硅谷-掌柜智库-day07总结和今日内容.mp4 [84.7 MB]
08-尚硅谷-掌柜智库-商品名识别-主体识别节点的总结.mp4 [75.6 MB]
16-尚硅谷-掌柜智库-商品名识别-chuns数据存储节点-步骤1&2总结.mp4 [22.1 MB]
13-尚硅谷-掌柜智库-商品名识别-chunks数据的组装2.mp4 [138.2 MB]
11-尚硅谷-掌柜智库-商品名识别-chunks向量化节点的单元测试.mp4 [36.0 MB]
10-尚硅谷-掌柜智库-商品名识别-chunks向量化节点的需求说明.mp4 [14.4 MB]
03-尚硅谷-掌柜智库-商品名识别-数据回填.mp4 [35.4 MB]
02-尚硅谷-掌柜智库-商品名识别-llm识别.mp4 [212.7 MB]
knowledge_base.zip [340.1 KB]
09-尚硅谷-掌柜智库-商品名识别-幂等删除的优化.mp4 [14.9 MB]
04-尚硅谷-掌柜智库-商品名识别-向量生成.mp4 [67.9 MB]
18-尚硅谷-掌柜智库-商品名识别-chuns数据存储节点-步骤4.mp4 [121.4 MB]
12-尚硅谷-掌柜智库-商品名识别-chunks数据的组装.mp4 [114.0 MB]
07-尚硅谷-掌柜智库-商品名识别-特殊支付的处理.mp4 [66.1 MB]
06-尚硅谷-掌柜智库-商品名识别-数据的保存.mp4 [103.6 MB]
14-尚硅谷-掌柜智库-商品名识别-chuns数据存储节点-流程说明和步骤1的实现.mp4 [68.5 MB]
17-尚硅谷-掌柜智库-商品名识别-chuns数据存储节点-步骤3.mp4 [128.0 MB]
05-尚硅谷-掌柜智库-商品名识别-集合的创建.mp4 [392.5 MB]
15-尚硅谷-掌柜智库-商品名识别-chuns数据存储节点-步骤2-集合的创建.mp4 [160.7 MB]
📁 day07
📁 课堂笔记
📁 images
文档切片流程图.png [1000.7 KB]
13.节点基类执行流程.jpg [468.0 KB]
image-20260318025329233.png [53.8 KB]
文档切片流程图2.png [956.5 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
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image-20260429013135647.png [48.2 KB]
文档切片流程图3.png [1005.3 KB]
image-20260202145456329.png [21.2 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
image-20260315191452504.png [46.6 KB]
image-20260310183135191.png [56.5 KB]
向量.jpeg [99.5 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
1.整体架构图.jpg [569.9 KB]
PDF转MD流程图.png [956.4 KB]
image-20260202160422170.png [137.8 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
image-20260312235630471.png [114.6 KB]
入口节点流程图.png [6.7 MB]
image-20260310183103711.png [53.9 KB]
MD图片处理流程.png [1.0 MB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
03【掌柜智库】【导入】骨架代码.md [41.6 KB]
01【掌柜智库】项目简介.md [8.0 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.2 KB]
02【掌柜智库】环境准备.md [17.6 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.6 KB]
08【掌柜智库】【导入】主体识别.md [43.6 KB]
22-尚硅谷-掌柜智库-向量模型工具类-稀疏向量的获取2.mp4 [13.6 MB]
19-尚硅谷-掌柜智库-向量模型工具类-稠密向量的获取.mp4 [10.4 MB]
21-尚硅谷-掌柜智库-向量模型工具类-稀疏向量的获取.mp4 [112.9 MB]
稀疏向量-压缩矩阵稀疏行的数据结构.drawio [6.4 KB]
23-尚硅谷-掌柜智库-向量模型工具类-L2归一化.mp4 [40.7 MB]
13-尚硅谷-掌柜智库-BGE-M3模型的配置.mp4 [41.4 MB]
03-尚硅谷-掌柜智库-向量-基本概念.mp4 [31.5 MB]
02-尚硅谷-掌柜智库-主体识别节点的作用.mp4 [127.9 MB]
07-尚硅谷-掌柜智库-向量-稠密向量和稀疏向量的作用.mp4 [36.6 MB]
10-尚硅谷-掌柜智库-pytorch安装的注意事项总结.mp4 [18.3 MB]
24-尚硅谷-掌柜智库-节点业务流程梳理.mp4 [93.9 MB]
25-尚硅谷-掌柜智库-步骤1&步骤2的实现.mp4 [212.2 MB]
11-尚硅谷-掌柜智库-向量数据库的基本配置.mp4 [17.5 MB]
06-尚硅谷-掌柜智库-向量-稠密向量和稀疏向量.mp4 [23.7 MB]
16-尚硅谷-掌柜智库-向量转换的测试.mp4 [33.5 MB]
08-尚硅谷-掌柜智库-pytorch的安装和注意事项.mp4 [102.3 MB]
14-尚硅谷-掌柜智库-关于torch版本的说明.mp4 [5.4 MB]
05-尚硅谷-掌柜智库-向量-相似度计算.mp4 [26.1 MB]
20-尚硅谷-掌柜智库-稀疏向量的底层存储-压缩稀疏行矩阵行.mp4 [121.2 MB]
18-尚硅谷-掌柜智库-上午总结.mp4 [97.1 MB]
knowledge_base.zip [328.3 KB]
09-尚硅谷-掌柜智库-其他向量转换和存储相关依赖的安装和注意事项.mp4 [124.2 MB]
12-尚硅谷-掌柜智库-BGE-M3模型的下载.mp4 [25.2 MB]
01-尚硅谷-掌柜智库-day06总结.mp4 [18.8 MB]
04-尚硅谷-掌柜智库-向量-使用维度信息进行语义表达.mp4 [32.0 MB]
17-尚硅谷-掌柜智库-稠密向量获取的测试.mp4 [47.4 MB]
15-尚硅谷-掌柜智库-定义获取BGE-M3模型全局单例对象的工具类.mp4 [33.7 MB]
📁 day13
📁 课堂笔记
📁 images
文档切片流程图2.png [956.5 KB]
image-20260429013135647.png [48.2 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
image-20260310183135191.png [56.5 KB]
image-20260312235630471.png [114.6 KB]
13.节点基类执行流程.jpg [468.0 KB]
向量化节点流程图.png [949.0 KB]
PDF转MD流程图.png [956.4 KB]
wps1-17699496797303-17732210276785.jpg [62.4 KB]
入口节点流程图.png [6.7 MB]
image-20260318025329233.png [53.8 KB]
image-20260326223039801.png [5.7 KB]
MD图片处理流程.png [1.0 MB]
文档切片流程图3.png [1005.3 KB]
879160d3-2358-43ec-9551-e8ab9fa42af6-17732210276796.jpg [127.5 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
1.整体架构图.jpg [569.9 KB]
主体识别节点流程图.png [1020.9 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
保存milvus节点流程图.png [955.1 KB]
产品确认节点流程图.png [962.3 KB]
image-20260202145456329.png [21.2 KB]
假设性文档生成流程图.png [991.2 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
image-20260519055337137.png [47.8 KB]
rff融合排序流程.png [885.6 KB]
文档切片流程图.png [1000.7 KB]
image-20260310183103711.png [53.9 KB]
重排序流程图.png [963.7 KB]
向量搜索流程图.png [910.0 KB]
image-20260202160422170.png [137.8 KB]
image-20260315191452504.png [46.6 KB]
向量.jpeg [99.5 KB]
MCP节点流程.png [925.4 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
14【掌柜智库】【检索】假设性文档向量搜索.md [13.8 KB]
13【掌柜智库】【检索】搜索向量库.md [7.4 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
12【掌柜智库】【检索】产品确认.md [58.2 KB]
01【掌柜智库】项目简介.md [8.0 KB]
15【掌柜智库】【检索】网络搜索.md [9.9 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
18【掌柜智库】【Web服务】.md [55.2 KB]
17【掌柜智库】【检索】Rerank重排序.md [19.2 KB]
02【掌柜智库】环境准备.md [17.6 KB]
16【掌柜智库】【检索】结果融合重排.md [12.0 KB]
07-尚硅谷-掌柜智库-html-引入css样式的三种方式.mp4 [93.7 MB]
10-尚硅谷-掌柜智库-html-布局.mp4 [59.2 MB]
24-尚硅谷-掌柜智库-JavaScript-事件字符串运算符语句等.mp4 [169.6 MB]
01-尚硅谷-掌柜智库-day12总结和今日内容.mp4 [58.7 MB]
08-尚硅谷-掌柜智库-html-表格和表单.mp4 [131.0 MB]
23-尚硅谷-掌柜智库-JavaScript-作用域.mp4 [31.8 MB]
18-尚硅谷-掌柜智库-JavaScript-字面量.mp4 [19.9 MB]
17-尚硅谷-掌柜智库-JavaScript-入门程序-一个交互操作.mp4 [40.7 MB]
06-尚硅谷-掌柜智库-html-一些标签.mp4 [124.0 MB]
12-尚硅谷-掌柜智库-html-样式定义的关键知识点.mp4 [76.3 MB]
05-尚硅谷-掌柜智库-html-一些常识.mp4 [32.1 MB]
11-尚硅谷-掌柜智库-html-什么是CSS.mp4 [46.2 MB]
16-尚硅谷-掌柜智库-JavaScript-入门程序-一个DOM操作.mp4 [61.7 MB]
22-尚硅谷-掌柜智库-JavaScript-函数.mp4 [30.8 MB]
04-尚硅谷-掌柜智库-html-常见标签和一些特性.mp4 [173.7 MB]
03-尚硅谷-掌柜智库-html-标准.mp4 [69.0 MB]
19-尚硅谷-掌柜智库-JavaScript-变量.mp4 [118.9 MB]
20-尚硅谷-掌柜智库-JavaScript-数据类型.mp4 [65.0 MB]
14-尚硅谷-掌柜智库-css-常见样式1.mp4 [213.5 MB]
13-尚硅谷-掌柜智库-上午总结.mp4 [43.9 MB]
09-尚硅谷-掌柜智库-html-列表.mp4 [24.7 MB]
02-尚硅谷-掌柜智库-html-入门.mp4 [64.1 MB]
15-尚硅谷-掌柜智库-css-常见样式2.mp4 [223.6 MB]
21-尚硅谷-掌柜智库-JavaScript-对象的定义.mp4 [50.1 MB]
knowledge_base.zip [517.4 KB]
📁 day06
📁 课堂笔记
📁 images
image-20260429013135647.png [48.2 KB]
image-20260315191452504.png [46.6 KB]
文档切片流程图2.png [956.5 KB]
文档切片流程图3.png [1005.3 KB]
13.节点基类执行流程.jpg [468.0 KB]
image-20260312235630471.png [114.6 KB]
image-20260202160422170.png [137.8 KB]
image-20260318025329233.png [53.8 KB]
入口节点流程图.png [6.7 MB]
PDF转MD流程图.png [956.4 KB]
文档切片流程图.png [1000.7 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
image-20260310183103711.png [53.9 KB]
image-20260310183135191.png [56.5 KB]
MD图片处理流程.png [1.0 MB]
1.整体架构图.jpg [569.9 KB]
image-20260202145456329.png [21.2 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.2 KB]
07【掌柜智库】【导入】文档切片.md [31.2 KB]
03【掌柜智库】【导入】骨架代码.md [41.6 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
02【掌柜智库】环境准备.md [17.6 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.6 KB]
01【掌柜智库】项目简介.md [8.0 KB]
11-尚硅谷-掌柜智库-文档切片-短段落合并-合并的测试2.mp4 [180.9 MB]
15-尚硅谷-掌柜智库-文档切片-补充-长切短合后的父标题兜底.mp4 [19.2 MB]
13-尚硅谷-掌柜智库-文档切片-日志打印和json备份.mp4 [96.6 MB]
12-尚硅谷-掌柜智库-文档切片-关于切片策略的选择.mp4 [19.4 MB]
05-尚硅谷-掌柜智库-文档切片-无标题兜底.mp4 [46.7 MB]
03-尚硅谷-掌柜智库-文档切片-按标题切分每个段落.mp4 [474.7 MB]
01-尚硅谷-掌柜智库-day05总结和今日内容.mp4 [39.0 MB]
09-尚硅谷-掌柜智库-文档切片-短段落合并-判断合并的条件.mp4 [157.0 MB]
06-尚硅谷-掌柜智库-文档切片-精细化切分的基本步骤梳理.mp4 [68.8 MB]
04-尚硅谷-掌柜智库-文档切片-特殊代码块标记的情况.mp4 [128.1 MB]
02-尚硅谷-掌柜智库-文档切片步骤梳理以及第一步的实现.mp4 [106.8 MB]
08-尚硅谷-掌柜智库-文档切片-长段落分割-切分content.mp4 [365.3 MB]
14-尚硅谷-掌柜智库-文档切片-生图模型介绍.mp4 [49.8 MB]
07-尚硅谷-掌柜智库-文档切片-长段落分割-判断段落标题.mp4 [214.4 MB]
knowledge_base.zip [175.5 KB]
10-尚硅谷-掌柜智库-文档切片-短段落合并-合并的测试1.mp4 [229.2 MB]
📁 day05
📁 课堂笔记
📁 images
image-20260312235630471.png [114.6 KB]
MD图片处理流程.png [1.0 MB]
image-20260310183135191.png [56.5 KB]
image-20260310183103711.png [53.9 KB]
image-20260202145456329.png [21.2 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
image-20260318025329233.png [53.8 KB]
1.整体架构图.jpg [569.9 KB]
image-20260315191452504.png [46.6 KB]
image-20260202160422170.png [137.8 KB]
image-20260429013135647.png [48.2 KB]
13.节点基类执行流程.jpg [468.0 KB]
入口节点流程图.png [6.7 MB]
PDF转MD流程图.png [956.4 KB]
03【掌柜智库】【导入】骨架代码.md [41.6 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
02【掌柜智库】环境准备.md [17.6 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.6 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.4 KB]
01【掌柜智库】项目简介.md [8.0 KB]
07【掌柜智库】【导入】文档切片.md [27.9 KB]
📁 扩展知识
MinerU手册.md [9.2 KB]
cuda_12.8.0_571.96_windows.exe [3.2 GB]
01-尚硅谷-掌柜智库-day04总结和今日内容.mp4 [199.2 MB]
09-尚硅谷-掌柜智库-minio-复制新的文件并设置state的值.mp4 [35.7 MB]
12-尚硅谷-掌柜智库-文本分片节点逻辑分析.mp4 [73.0 MB]
10-尚硅谷-掌柜智库-MinerU-下载和使用本地模型.mp4 [344.4 MB]
03-尚硅谷-掌柜智库-minio客户端对象的创建.mp4 [119.5 MB]
08-尚硅谷-掌柜智库-minio-md_content中内容的替换.mp4 [133.9 MB]
knowledge_base.zip [166.7 KB]
07-尚硅谷-掌柜智库-minio-图片迭代的梳理以及删除图片问题的分析.mp4 [133.2 MB]
02-尚硅谷-掌柜智库-minio服务的参数获取和配置.mp4 [120.7 MB]
06-尚硅谷-掌柜智库-minio-文件清理和上传的逻辑梳理以及测试.mp4 [147.4 MB]
04-尚硅谷-掌柜智库-minio客户端设置为http访问方式.mp4 [32.2 MB]
05-尚硅谷-掌柜智库-minio-文件清理和上传.mp4 [308.6 MB]
11-尚硅谷-掌柜智库-MinerU-关于CUDA.mp4 [174.4 MB]
20260508_165206.mp4 [73.0 MB]
📁 day16
📁 课堂笔记
📁 images
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
image-20260326223039801.png [5.7 KB]
PDF转MD流程图.png [956.4 KB]
主体识别节点流程图.png [1020.9 KB]
向量化节点流程图.png [949.0 KB]
重排序流程图.png [963.7 KB]
image-20260429013135647.png [48.2 KB]
image-20260310183135191.png [56.5 KB]
image-20260202160422170.png [137.8 KB]
image-20260202145456329.png [21.2 KB]
MCP节点流程.png [925.4 KB]
MD图片处理流程.png [1.0 MB]
13.节点基类执行流程.jpg [468.0 KB]
文档切片流程图2.png [956.5 KB]
向量.jpeg [99.5 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
image-20260312123628867.png [314.7 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
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文档切片流程图.png [1000.7 KB]
wps1-17699496797303-17732210276785.jpg [62.4 KB]
image-20260310183103711.png [53.9 KB]
879160d3-2358-43ec-9551-e8ab9fa42af6-17732210276796.jpg [127.5 KB]
保存milvus节点流程图.png [955.1 KB]
image-20260315191452504.png [46.6 KB]
1.整体架构图.jpg [569.9 KB]
image-20260312235630471.png [114.6 KB]
假设性文档生成流程图.png [991.2 KB]
产品确认节点流程图.png [962.3 KB]
image-20260401042410241.png [23.8 KB]
入口节点流程图.png [6.7 MB]
image-20260318025329233.png [53.8 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
image-20260519055337137.png [47.8 KB]
向量搜索流程图.png [910.0 KB]
文档切片流程图3.png [1005.3 KB]
rff融合排序流程.png [885.6 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
18【掌柜智库】【Web服务】.md [59.5 KB]
14【掌柜智库】【检索】假设性文档向量搜索.md [13.8 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
02【掌柜智库】环境准备.md [17.6 KB]
20【掌柜智库】【检索】答案输出.md [25.5 KB]
12【掌柜智库】【检索】产品确认.md [58.2 KB]
01【掌柜智库】项目简介.md [8.0 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
19【掌柜智库】【API接口和前端页面】.md [24.0 KB]
17【掌柜智库】【检索】Rerank重排序.md [19.2 KB]
16【掌柜智库】【检索】结果融合重排.md [12.0 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
13【掌柜智库】【检索】搜索向量库.md [7.4 KB]
15【掌柜智库】【检索】网络搜索.md [9.9 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
01-尚硅谷-掌柜智库-任务追踪的一些细节.mp4 [130.8 MB]
06-尚硅谷-掌柜智库-检索-答案节点3.mp4 [143.2 MB]
03-尚硅谷-掌柜智库-单元测试的task_id.mp4 [9.6 MB]
尚硅谷大模型项目实战之掌柜智库实战.zip [163.8 MB]
08-尚硅谷-掌柜智库-检索-答案节点的流程梳理.mp4 [360.7 MB]
04-尚硅谷-掌柜智库-检索-答案节点1.mp4 [297.9 MB]
05-尚硅谷-掌柜智库-检索-答案节点2.mp4 [109.8 MB]
07-尚硅谷-掌柜智库-检索-答案节点4.mp4 [363.5 MB]
10-尚硅谷-掌柜智库-检索-答案节点的工作流测试.mp4 [104.5 MB]
答案节点流程梳理.md [4.9 KB]
knowledge_base.zip [704.9 KB]
02-尚硅谷-掌柜智库-查询api的流程梳理.mp4 [178.9 MB]
09-尚硅谷-掌柜智库-检索-答案节点的单元测试.mp4 [36.5 MB]
11-尚硅谷-掌柜智库-检索-前后端测试.mp4 [240.7 MB]
📁 day01
📁 课堂笔记
📁 images
1.整体架构图.jpg [569.9 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
13.节点基类执行流程.jpg [468.0 KB]
image-20260202160422170.png [137.8 KB]
image-20260429013135647.png [48.2 KB]
image-20260310183103711.png [53.9 KB]
image-20260202145456329.png [21.2 KB]
image-20260312235630471.png [114.6 KB]
image-20260310183135191.png [56.5 KB]
image-20260315191452504.png [46.6 KB]
01【掌柜智库】项目简介.md [8.0 KB]
02【掌柜智库】环境准备.md [21.4 KB]
03【掌柜智库】【导入】骨架代码.md [30.2 KB]
02-尚硅谷-掌柜智库-项目定位目标和核心功能.mp4 [109.2 MB]
08-尚硅谷-掌柜智库-安装docker.mp4 [84.3 MB]
05-尚硅谷-掌柜智库-Centos7的安装.mp4 [141.5 MB]
06-尚硅谷-掌柜智库-ip地址问题的修复.mp4 [50.1 MB]
01-尚硅谷-掌柜智库-项目介绍.mp4 [159.8 MB]
09-尚硅谷-掌柜智库-配置docker反向隧道.mp4 [190.0 MB]
04-尚硅谷-掌柜智库-第三方中间件与技术栈.mp4 [38.5 MB]
13-尚硅谷-掌柜智库-容器-mongo的安装.mp4 [31.9 MB]
03-尚硅谷-掌柜智库-项目架构介绍.mp4 [91.0 MB]
10-尚硅谷-掌柜智库-docker反向隧道的底层原理.mp4 [24.8 MB]
07-尚硅谷-掌柜智库-配置yum源.mp4 [124.8 MB]
11-尚硅谷-掌柜智库-容器-minio的安装.mp4 [82.3 MB]
12-尚硅谷-掌柜智库-容器-milvus的安装.mp4 [216.2 MB]
📁 day04
📁 课堂笔记
📁 images
image-20260310183135191.png [56.5 KB]
PDF转MD流程图.png [956.4 KB]
image-20260202145456329.png [21.2 KB]
1.整体架构图.jpg [569.9 KB]
MD图片处理流程.png [1.0 MB]
入口节点流程图.png [6.7 MB]
image-20260429013135647.png [48.2 KB]
image-20260202160422170.png [137.8 KB]
image-20260310183103711.png [53.9 KB]
image-20260315191452504.png [46.6 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
13.节点基类执行流程.jpg [468.0 KB]
image-20260312235630471.png [114.6 KB]
image-20260318025329233.png [53.8 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
03【掌柜智库】【导入】骨架代码.md [41.6 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.6 KB]
01【掌柜智库】项目简介.md [8.0 KB]
02【掌柜智库】环境准备.md [17.6 KB]
03-尚硅谷-掌柜智库-pdf转md节点-zip解压和重命名.mp4 [69.4 MB]
02-尚硅谷-掌柜智库-pdf转md节点-zip下载.mp4 [46.8 MB]
14-尚硅谷-掌柜智库-md图片处理-步骤3-使用双端队列进行限速.mp4 [33.7 MB]
01-尚硅谷-掌柜智库-day03总结和知识的梳理.mp4 [131.9 MB]
07-尚硅谷-掌柜智库-md图片处理节点-.mp4 [14.0 MB]
04-尚硅谷-掌柜智库-md图片处理节点的介绍以及MinIO的基本使用.mp4 [137.4 MB]
06-尚硅谷-掌柜智库-md图片处理节点-流程梳理.mp4 [85.5 MB]
05-尚硅谷-掌柜智库-md图片处理节点的-实现思路和步骤分解.mp4 [57.1 MB]
09-尚硅谷-掌柜智库-md图片处理-步骤1-获取文件和文件路径.mp4 [59.4 MB]
12-尚硅谷-掌柜智库-md图片处理-步骤3-流程介绍.mp4 [82.2 MB]
knowledge_base.zip [31.2 MB]
13-尚硅谷-掌柜智库-md图片处理-步骤3-维护双端队列作为滑动窗口实现速率控制.mp4 [83.0 MB]
08-尚硅谷-掌柜智库-上午总结及主流程的实现.mp4 [38.9 MB]
10-尚硅谷-掌柜智库-md图片处理-步骤2-分析图片列表并在md中截取上文和下文.mp4 [281.7 MB]
11-尚硅谷-掌柜智库-md图片处理-步骤2-总结和完善.mp4 [44.3 MB]
15-尚硅谷-掌柜智库-md图片处理-步骤3-调用VL模型获取图片摘要.mp4 [93.5 MB]
📁 day09
📁 课堂笔记
📁 images
image-20260202160422170.png [137.8 KB]
image-20260315191452504.png [46.6 KB]
image-20260310183135191.png [56.5 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
PDF转MD流程图.png [956.4 KB]
文档切片流程图2.png [956.5 KB]
image-20260312235630471.png [114.6 KB]
向量.jpeg [99.5 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
MD图片处理流程.png [1.0 MB]
image-20260429013135647.png [48.2 KB]
image-20260318025329233.png [53.8 KB]
image-20260310183103711.png [53.9 KB]
文档切片流程图.png [1000.7 KB]
image-20260202145456329.png [21.2 KB]
向量化节点流程图.png [949.0 KB]
1.整体架构图.jpg [569.9 KB]
13.节点基类执行流程.jpg [468.0 KB]
入口节点流程图.png [6.7 MB]
文档切片流程图3.png [1005.3 KB]
保存milvus节点流程图.png [955.1 KB]
主体识别节点流程图.png [1020.9 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
image-20260326223039801.png [5.7 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.1 KB]
01【掌柜智库】项目简介.md [8.0 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.2 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
08【掌柜智库】【导入】主体识别.md [43.3 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
12【掌柜智库】【检索】产品确认.md [57.8 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
02【掌柜智库】环境准备.md [17.6 KB]
14-尚硅谷-掌柜智库-主体识别节点-业务流程.mp4 [44.4 MB]
09-尚硅谷-掌柜智库-骨架代码-异常处理的说明2.mp4 [33.2 MB]
10-尚硅谷-掌柜智库-骨架代码-其他节点的创建.mp4 [26.4 MB]
03-尚硅谷-掌柜智库-骨架代码-state定义的说明.mp4 [99.3 MB]
16-尚硅谷-掌柜智库-mongo的数据组织的特点.mp4 [51.2 MB]
17-尚硅谷-掌柜智库-python操作mongo.mp4 [116.3 MB]
04-尚硅谷-掌柜智库-骨架代码-base定义的说明.mp4 [13.4 MB]
11-尚硅谷-掌柜智库-骨架代码-图结构说明.mp4 [27.3 MB]
knowledge_base.zip [377.5 KB]
08-尚硅谷-掌柜智库-骨架代码-异常处理的说明.mp4 [46.7 MB]
07-尚硅谷-掌柜智库-骨架代码-日志功能的全局定义.mp4 [91.4 MB]
19-尚硅谷-掌柜智库-业务流程-参数校验.mp4 [43.4 MB]
05-尚硅谷-掌柜智库-骨架代码-NodeItemNameConfirm节点的定义.mp4 [36.0 MB]
12-尚硅谷-掌柜智库-骨架代码-图结构V2.mp4 [217.3 MB]
13-尚硅谷-掌柜智库-上午总结.mp4 [32.5 MB]
02-尚硅谷-掌柜智库-骨架代码的说明.mp4 [28.0 MB]
15-尚硅谷-掌柜智库-mongo的使用.mp4 [186.1 MB]
01-尚硅谷-掌柜智库-导入流程总结.mp4 [23.4 MB]
21-尚硅谷-掌柜智库-业务流程-保存历史会话记录.mp4 [120.7 MB]
06-尚硅谷-掌柜智库-骨架代码-__call__方法的定义.mp4 [54.8 MB]
20-尚硅谷-掌柜智库-业务流程-获取历史会话记录.mp4 [43.0 MB]
18-尚硅谷-掌柜智库-历史记录管理工具的代码梳理.mp4 [349.6 MB]
22-尚硅谷-掌柜智库-业务流程-将当前问题存入历史记录.mp4 [73.2 MB]
📁 day14
📁 课堂笔记
📁 images
13.节点基类执行流程.jpg [468.0 KB]
image-20260312235630471.png [114.6 KB]
image-20260401042410241.png [23.8 KB]
image-20260310183135191.png [56.5 KB]
文档切片流程图.png [1000.7 KB]
image-20260326223039801.png [5.7 KB]
image-20260315191452504.png [46.6 KB]
重排序流程图.png [963.7 KB]
image-20260202160422170.png [137.8 KB]
向量化节点流程图.png [949.0 KB]
向量.jpeg [99.5 KB]
rff融合排序流程.png [885.6 KB]
wps1-17699496797303-17732210276785.jpg [62.4 KB]
文档切片流程图3.png [1005.3 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
产品确认节点流程图.png [962.3 KB]
入口节点流程图.png [6.7 MB]
保存milvus节点流程图.png [955.1 KB]
image-20260202145456329.png [21.2 KB]
假设性文档生成流程图.png [991.2 KB]
879160d3-2358-43ec-9551-e8ab9fa42af6-17732210276796.jpg [127.5 KB]
image-20260310183103711.png [53.9 KB]
image-20260429013135647.png [48.2 KB]
向量搜索流程图.png [910.0 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
v2-b88f750dc797da4f9cc45da0fdd482dc_1440w.jpg [29.4 KB]
image-20260519055337137.png [47.8 KB]
v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
image-20260318025329233.png [53.8 KB]
image-20260401042318014.png [19.8 KB]
1.整体架构图.jpg [569.9 KB]
主体识别节点流程图.png [1020.9 KB]
MCP节点流程.png [925.4 KB]
MD图片处理流程.png [1.0 MB]
文档切片流程图2.png [956.5 KB]
PDF转MD流程图.png [956.4 KB]
16【掌柜智库】【检索】结果融合重排.md [12.0 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
12【掌柜智库】【检索】产品确认.md [58.2 KB]
14【掌柜智库】【检索】假设性文档向量搜索.md [13.8 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
01【掌柜智库】项目简介.md [8.0 KB]
18【掌柜智库】【Web服务】.md [59.4 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
17【掌柜智库】【检索】Rerank重排序.md [19.2 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
15【掌柜智库】【检索】网络搜索.md [9.9 KB]
13【掌柜智库】【检索】搜索向量库.md [7.4 KB]
02【掌柜智库】环境准备.md [17.6 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
📁 Cookie跨域的例子
cookie_test.html [7.5 KB]
cookie_test.py [3.7 KB]
📁 图
FastAPI.drawio [64.7 KB]
30-尚硅谷-掌柜智库-SSE-案例3-实现.mp4 [205.3 MB]
07-尚硅谷-掌柜智库-FastAPI-常见响应-json和文件.mp4 [57.0 MB]
21-尚硅谷-掌柜智库-FastAPI-文件上传流程说明.mp4 [38.9 MB]
08-尚硅谷-掌柜智库-FastAPI-常见响应-html和纯文本.mp4 [28.3 MB]
19-尚硅谷-掌柜智库-FastAPI-上节课梳理以及总结.mp4 [11.7 MB]
23-尚硅谷-掌柜智库-FastAPI-文件上传接口的定义2和测试.mp4 [131.8 MB]
03-尚硅谷-掌柜智库-FastAPI的参数传递.mp4 [34.0 MB]
26-尚硅谷-掌柜智库-SSE-案例1-后端.mp4 [40.6 MB]
04-尚硅谷-掌柜智库-FastAPI-pydantic数据校验以及post的请求和响应.mp4 [114.1 MB]
17-尚硅谷-掌柜智库-FastAPI-同步和异步1.mp4 [11.4 MB]
20-尚硅谷-掌柜智库-FastAPI-异步任务.mp4 [113.9 MB]
05-尚硅谷-掌柜智库-FastAPI-get的请求和响应.mp4 [17.1 MB]
29-尚硅谷-掌柜智库-SSE-案例3-需求分析.mp4 [30.5 MB]
24-尚硅谷-掌柜智库-SSE-什么是SSE.mp4 [47.1 MB]
16-尚硅谷-掌柜智库-FastAPI-跨域的使用场景.mp4 [5.1 MB]
06-尚硅谷-掌柜智库-FastAPI-常见响应.mp4 [49.1 MB]
06-尚硅谷-掌柜智库-FastAPI-pydantic.mp4 [74.6 MB]
knowledge_base.zip [646.7 KB]
12-尚硅谷-掌柜智库-FastAPI-静态资源托管.mp4 [52.2 MB]
28-尚硅谷-掌柜智库-SSE-案例2-前后端.mp4 [91.4 MB]
25-尚硅谷-掌柜智库-SSE-yield的使用.mp4 [20.9 MB]
18-尚硅谷-掌柜智库-FastAPI-同步和异步2.mp4 [20.0 MB]
09-尚硅谷-掌柜智库-FastAPI-常见响应-流式响应.mp4 [48.4 MB]
15-尚硅谷-掌柜智库-FastAPI-跨域演示-后端开发.mp4 [179.2 MB]
01-尚硅谷-掌柜智库-今日内容.mp4 [4.8 MB]
14-尚硅谷-掌柜智库-FastAPI-跨域演示-前端的开发.mp4 [117.8 MB]
27-尚硅谷-掌柜智库-SSE-案例1-前端.mp4 [51.7 MB]
22-尚硅谷-掌柜智库-FastAPI-文件上传接口的定义.mp4 [145.7 MB]
13-尚硅谷-掌柜智库-上午总结.mp4 [57.5 MB]
02-尚硅谷-掌柜智库-FastAPI的断点调试和热更新.mp4 [96.8 MB]
11-尚硅谷-掌柜智库-FastAPI-项目的架构.mp4 [78.6 MB]
10-尚硅谷-掌柜智库-FastAPI-常见响应-基础响应.mp4 [31.6 MB]
📁 day03
📁 课堂笔记
📁 images
image-20260315191452504.png [46.6 KB]
image-20260202160422170.png [137.8 KB]
13.节点基类执行流程.jpg [468.0 KB]
PDF转MD流程图.png [956.4 KB]
1.整体架构图.jpg [569.9 KB]
image-20260310183103711.png [53.9 KB]
入口节点流程图.png [6.7 MB]
image-20260310183135191.png [56.5 KB]
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b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
01【掌柜智库】项目简介.md [8.0 KB]
05【掌柜智库】【导入】PDF转Markdown.md [16.9 KB]
04【掌柜智库】【导入】入口节点.md [5.8 KB]
02【掌柜智库】环境准备.md [17.6 KB]
03【掌柜智库】【导入】骨架代码.md [41.6 KB]
04-尚硅谷-掌柜智库-入口节点-单元测试.mp4 [63.4 MB]
07-尚硅谷-掌柜智库-入口节点-实现完整的业务逻辑.mp4 [106.7 MB]
06-尚硅谷-掌柜智库-入口节点-判断输入参数的合法性以及异常抛出流程的分析.mp4 [320.5 MB]
16-尚硅谷-掌柜智库-PDF转MD的流程-步骤2-校验配置信息.mp4 [39.5 MB]
02-尚硅谷-掌柜智库-主图流程的梳理和完善.mp4 [169.1 MB]
10-尚硅谷-掌柜智库-MinerU的开发参数配置.mp4 [81.8 MB]
11-尚硅谷-掌柜智库-MinerU的开发参数配置-方式2.mp4 [46.0 MB]
08-尚硅谷-掌柜智库-上午总结.mp4 [20.0 MB]
15-尚硅谷-掌柜智库-PDF转MD的流程-步骤1-校验参数.mp4 [74.6 MB]
17-尚硅谷-掌柜智库-PDF转MD的流程-步骤2-文件上传链接的申请.mp4 [193.2 MB]
05-尚硅谷-掌柜智库-入口节点-流程分析.mp4 [20.1 MB]
03-尚硅谷-掌柜智库-入口节点-需求说明.mp4 [77.0 MB]
13-尚硅谷-掌柜智库-PDF转MD的流程梳理.mp4 [40.9 MB]
knowledge_base.zip [29.0 MB]
19-尚硅谷-掌柜智库-PDF转MD的流程-步骤4-轮询获取解析结果.mp4 [281.6 MB]
18-尚硅谷-掌柜智库-PDF转MD的流程-步骤3-文件上传.mp4 [42.0 MB]
01-尚硅谷-掌柜智库-课程回顾和骨架代码梳理以及知识点补充.mp4 [254.2 MB]
12-尚硅谷-掌柜智库-PDFToMD节点-单元测试.mp4 [15.6 MB]
09-尚硅谷-掌柜智库-MinerU的使用方式.mp4 [98.2 MB]
14-尚硅谷-掌柜智库-PDF转MD的流程-主流程实现.mp4 [60.5 MB]
📁 day15
📁 课堂笔记
📁 images
主体识别节点流程图.png [1020.9 KB]
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向量.jpeg [99.5 KB]
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重排序流程图.png [963.7 KB]
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PDF转MD流程图.png [956.4 KB]
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1.整体架构图.jpg [569.9 KB]
b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
MD图片处理流程.png [1.0 MB]
rff融合排序流程.png [885.6 KB]
wps1-17699496797303-17732210276785.jpg [62.4 KB]
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13.节点基类执行流程.jpg [468.0 KB]
入口节点流程图.png [6.7 MB]
image-20260312235630471.png [114.6 KB]
向量化节点流程图.png [949.0 KB]
image-20260519055337137.png [47.8 KB]
15【掌柜智库】【检索】网络搜索.md [9.9 KB]
02【掌柜智库】环境准备.md [17.6 KB]
19【掌柜智库】【API接口和前端页面】.md [24.0 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
13【掌柜智库】【检索】搜索向量库.md [7.4 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
01【掌柜智库】项目简介.md [8.0 KB]
06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
14【掌柜智库】【检索】假设性文档向量搜索.md [13.8 KB]
18【掌柜智库】【Web服务】.md [59.5 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
16【掌柜智库】【检索】结果融合重排.md [12.0 KB]
20【掌柜智库】【检索】答案输出.md [24.4 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
12【掌柜智库】【检索】产品确认.md [58.2 KB]
17【掌柜智库】【检索】Rerank重排序.md [19.2 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
📁 图
web前后端的流式输出.drawio [5.2 KB]
📁 代码
📁 page
import.html [11.6 KB]
chat.html [29.6 KB]
📁 utils
task_utils.py [5.5 KB]
sse_utils.py [2.7 KB]
04-尚硅谷-掌柜智库-上午总结.mp4 [73.7 MB]
08-尚硅谷-掌柜智库-import_service-异步任务方法解读.mp4 [34.2 MB]
11-尚硅谷-掌柜智库-query_service-代码解析.mp4 [208.7 MB]
10-尚硅谷-掌柜智库-import_service-状态轮询.mp4 [315.9 MB]
09-尚硅谷-掌柜智库-import_service-文件上传.mp4 [123.2 MB]
掌柜智库-高频面试题.docx [4.0 MB]
01-尚硅谷-掌柜智库-SSE-案例4.mp4 [154.0 MB]
knowledge_base.zip [694.0 KB]
05-尚硅谷-掌柜智库-sse_util解读-管理异步队列.mp4 [102.4 MB]
07-尚硅谷-掌柜智库-总结task和sse的util.mp4 [7.9 MB]
03-尚硅谷-掌柜智库-导入流程-import_service.mp4 [247.7 MB]
笔记.txt [1.0 KB]
06-尚硅谷-掌柜智库-task_util解读-管理任务列表.mp4 [187.1 MB]
02-尚硅谷-掌柜智库-SSE-案例5.mp4 [92.7 MB]
📁 day10
📁 课堂笔记
📁 images
PDF转MD流程图.png [956.4 KB]
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入口节点流程图.png [6.7 MB]
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b52b9253-436a-474d-885a-f229a1896600.jpg [69.6 KB]
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MD图片处理流程.png [1.0 MB]
向量.jpeg [99.5 KB]
保存milvus节点流程图.png [955.1 KB]
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13.节点基类执行流程.jpg [468.0 KB]
1.整体架构图.jpg [569.9 KB]
v2-55c2f61aceb86313711d50a5e6e9f8fd_1440w.jpg [21.8 KB]
文档切片流程图.png [1000.7 KB]
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v2-db52b20a89a5dc3bde66da11691a7438_1440w-1773557457203-6.jpg [21.7 KB]
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06【掌柜智库】【导入】MD图片处理节点.md [28.3 KB]
09【掌柜智库】【导入】向量化.md [7.1 KB]
03【掌柜智库】【导入】骨架代码.md [41.7 KB]
02【掌柜智库】环境准备.md [17.6 KB]
12【掌柜智库】【检索】产品确认.md [58.1 KB]
11【掌柜智库】【检索】骨架代码.md [30.0 KB]
10【掌柜智库】【导入】存入 Milvus.md [16.2 KB]
04【掌柜智库】【导入】入口节点.md [5.5 KB]
01【掌柜智库】项目简介.md [8.0 KB]
08【掌柜智库】【导入】主体识别.md [43.0 KB]
05【掌柜智库】【导入】PDF转Markdown节点.md [16.3 KB]
07【掌柜智库】【导入】文档切片.md [29.4 KB]
03-尚硅谷-尚硅谷-关于提示词的优化.mp4 [107.7 MB]
11-尚硅谷-尚硅谷-产品确认-检查确认状态.mp4 [110.5 MB]
02-尚硅谷-尚硅谷-JSON的序列化.mp4 [199.8 MB]
12-尚硅谷-尚硅谷-产品确认-保存历史记录并测试.mp4 [224.1 MB]
01-尚硅谷-尚硅谷-day09总结.mp4 [59.9 MB]
04-尚硅谷-尚硅谷-通过AI识别用户问题的主体以及对用户问题进行改写的测试.mp4 [82.5 MB]
knowledge_base.zip [391.4 KB]
08-尚硅谷-尚硅谷-混合向量检索的最终结果数据组装和测试.mp4 [123.8 MB]
10-尚硅谷-尚硅谷-产品确认-关于step6的进一步测试的说明.mp4 [11.9 MB]
06-尚硅谷-尚硅谷-混合向量搜索.mp4 [88.2 MB]
05-尚硅谷-尚硅谷-混合搜索的工具方法.mp4 [369.2 MB]
03-尚硅谷-尚硅谷-创建提示词以及调用模型进行主体信息的获取.mp4 [242.0 MB]
07-尚硅谷-尚硅谷-混合向量搜索测试.mp4 [37.8 MB]
09-尚硅谷-尚硅谷-产品确认-评分对齐.mp4 [218.8 MB]
📁 1.笔记
📁 images
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为什么需要rrf融合.jpg [607.3 KB]
a2e311f60bc9dfa46cf6474eaf2f8278.png [30.2 KB]
11【掌柜智库】【导入】【Web服务集成】.md [43.3 KB]
06【掌柜智库】【导入】【节点3】图片处理.md [35.1 KB]
19【掌柜智库】【检索】【节点6】Rerank重排序.md [11.8 KB]
16【掌柜智库】【检索】【节点3】假设性文档向量搜索.md [12.2 KB]
04【掌柜智库】【导入】【节点1】入口节点.md [4.7 KB]
08【掌柜智库】【导入】【节点5】主体识别.md [43.8 KB]
12【掌柜智库】【检索】【数据图与状态定义】.md [37.8 KB]
14【掌柜智库】【检索】【节点1】产品确认.md [36.8 KB]
02【掌柜智库】环境准备.md [21.4 KB]
07【掌柜智库】【导入】【节点4】文档切分.md [27.1 KB]
13【掌柜智库】【检索】【Web服务端搭建】.md [47.1 KB]
09【掌柜智库】【导入】【节点6】向量化.md [8.9 KB]
01【掌柜智库】项目简介.md [8.0 KB]
15【掌柜智库】【检索】【节点2】搜索向量库.md [6.3 KB]
03【掌柜智库】【导入】【骨架代码】.md [31.3 KB]
10【掌柜智库】【导入】【节点7】存入 Milvus.md [19.2 KB]
18【掌柜智库】【检索】【节点5】结果融合重排.md [10.6 KB]
20【掌柜智库】【检索】【节点7】答案输出.md [23.0 KB]
05【掌柜智库】【导入】【节点2】PDF 转 Markdown.md [15.5 KB]
17【掌柜智库】【检索】【节点4】网络搜索.md [8.3 KB]
📁 3.代码
📁 2.资料
📁 03-工具
mongodb-compass-1.49.4-win32-x64.exe [160.3 MB]
📁 01-CentOS
CentOS-Base.repo [2.5 KB]
CentOS-7-x86_64-Minimal-2009.iso [973.0 MB]
📁 05-初始代码
state.py [2.3 KB]
exceptions.py [2.7 KB]
base.py [3.2 KB]
config.py [3.4 KB]
📁 02-镜像
02-镜像.exe [822.5 MB]
📁 04-设备手册汇总
📁 doc
HUAWEI MateBook B7-410 用户手册-(02,zh-cn,MachDZ).pdf [5.5 MB]
华为擎云W515X 用户指南-(PGUX,KOS&UOS_02,zh-cn).pdf [1.4 MB]
华为擎云 M272Q 用户指南-(XSN-27QBZ,02,zh-cn).pdf [1.1 MB]
华为擎云W585X 用户指南-(PGUX,KOS&UOS_02,zh-cn).pdf [1.4 MB]
华为擎云B530 用户指南-(PUCZ,Windows11_03,zh-cn).pdf [670.3 KB]
H3C MSR WiNet系列云简路由器 用户手册-R0821-6W100-整本手册.pdf [4.5 MB]
H3C MSR系列开放多业务路由器 Web配置指导(V7)-R6728-6W102-整本手册.pdf [6.0 MB]
Z26 MIC机型打印机用户手册（联想）ver02.30-20251029.pdf [5.7 MB]
华为平板 C3 用户指南-(BZD-AL00&AL10&W00,EMUI10.1_01,ZH-CN).pdf [2.2 MB]
HUAWEI Matestation B520 用户手册-(PanguBZ,Windows11_02,zh-cn).pdf [1.8 MB]
华为擎云 HM740 用户指南-(HM740-001&031,HarmonyOS 6.0_01,zh-cn).pdf [10.3 MB]
华为擎云 P5 激光多功能一体机 CV81Z-LDM 用户指南-(CV81Z-LDM,06,zh-cn).pdf [5.7 MB]
华为显示器 B3-211H 用户指南-(NSN-21BZ,02,zh-cn).pdf [724.6 KB]
华为平板 C5 平板用户指南-(BZT3-W59&W69,EMUI10.1_01,ZH-CN).pdf [2.6 MB]
华为显示器 B7-281U 用户指南-(HSN-CAA,04,zh-cn).pdf [2.1 MB]
华为平板 C7 用户指南-(DBY-W09,HarmonyOS 2_01,ZH-CN).pdf [3.0 MB]
HUAWEI MateBook B3-430 用户指南-(NFZ,Windows11_02,zh-cn).pdf [2.3 MB]
华为擎云 S520 Gen2 用户指南-(YZ,Windows11_03,zh-cn).pdf [1.2 MB]
华为擎云 L420x 用户指南-(华为擎云 L420x-Axxx,UOS&KOS_01,zh-cn).pdf [1.2 MB]
华为擎云L410 用户手册-(KelvinU,01,zh-cn).pdf [1.2 MB]
华为擎云 C5 (第4代) 用户指南-(BYD5-W10&AL10,HarmonyOS 4.3_01,zh-cn).pdf [9.5 MB]
华为擎云 L540x 用户指南-(华为擎云 L540x-Axxx,UOS_01,zh-cn).pdf [1.5 MB]
HUAWEI PixLab B5 用户指南-(CV81Z,06,zh-cn).pdf [9.1 MB]
CS2610DNW_Manuals_ALL_20240423095554.pdf [3.2 MB]
迅饶网关与小米产品通讯配置说明.pdf [1.3 MB]
华为显示器 B3-242H 用户指南-(SSN-24BZ,VGA,04,zh-cn).pdf [1.8 MB]
HUAWEI MateBook B5-330 用户指南-(WRTDZ-WFH9&WFE9,Windows11_01,zh-cn).pdf [3.8 MB]
华为显示器 B3-271Q 用户指南-(XWU-CBA,02,zh-cn).pdf [3.2 MB]
华为擎云 W525 用户指南-(PGUW-WBX0,KOS&UOS_02,zh-cn).pdf [920.3 KB]
Z26通用机型打印机用户手册（至像）ver02.30-20251029.pdf [6.1 MB]
华为擎云 W585y 用户指南-(PGUY,KOS&UOS_01,zh-cn).pdf [1.3 MB]
M3070系列用户手册.pdf [11.5 MB]
H3C LA2608室内无线网关 用户手册-6W100-整本手册.pdf [171.0 KB]
HUAWEI MateBook B7-420 用户指南-(MRGFZ,Windows11_02,zh-cn).pdf [1.1 MB]
华为平板 C5e 用户指南-(BZI-W00&AL00,EMUI10.1_01,zh-cn).pdf [2.2 MB]
Z35打印机用户手册（联想）V01.30-20251030.pdf [10.7 MB]
hl3070使用说明书.pdf [14.7 MB]
H3C NR-1200W企业级无线宽带路由器 用户手册-5W100-整本手册.pdf [7.2 MB]
HUAWEI MateBook B5-430 用户手册-(03,zh-cn,KelvinDZ).pdf [5.5 MB]
华为擎云 S540 用户指南-(YTFZ,Windows11_03,zh-cn).pdf [1.2 MB]
M3系列&T3&M3470系列用户手册.pdf [8.6 MB]
H3C MSR-XS系列路由器 用户手册-R0821-6W100-整本手册.pdf [4.5 MB]
hak180产品安全手册.pdf [627.8 KB]
HUAWEI MateStation S 12代酷睿版 用户指南-(PUC,Windows11_02,zh-cn).pdf [1.0 MB]
联想至像大象系列打印机用户手册V1.02-20250217.pdf [8.4 MB]
Aolynk CC系列室内型Cable网络集中器 用户手册-6W202-整本手册.pdf [2.1 MB]
Z2_Manuals_Win_20241011153854.pdf [5.8 MB]
联想鲸鱼系列用户手册.pdf [17.9 MB]
华为擎云B730 用户指南-(PUCZ,Windows11_03,zh-cn).pdf [670.3 KB]
LJ2268系列用户手册.pdf [14.4 MB]
华为擎云 L540 用户指南-(KLVV,UOS&KOS_01,zh-cn).pdf [1.2 MB]
H3C UG系列路由器 用户手册-R0130-6W102-整本手册.pdf [6.9 MB]
Aolynk CB304n Cable网桥 用户手册-5W100-整本手册.pdf [776.3 KB]
PantumP3000userguideGDIzh_CNV1.9_1644314230264.pdf [11.5 MB]
HUAWEI MateBook B3-410&B3-510 用户手册-(03,zh-cn,Boh&Nbl,HUAWEI).pdf [6.2 MB]
华为擎云W585 用户指南-(PGUV,KOS&UOS_01,zh-cn).pdf [895.3 KB]
H3C NER214W路由器 用户手册-6W101-整本手册.pdf [5.5 MB]
HUAWEI MateBook B5-440 用户指南-(KLVFZ,Windows11_02,zh-cn).pdf [1.2 MB]
华为擎云 G540 用户指南-(YTFZ,Windows11_03,zh-cn).pdf [1.2 MB]
LJ2680DN用户手册.pdf [5.0 MB]
M7268系列用户手册.pdf [13.7 MB]
万用表RS-12的使用.pdf [1.4 MB]
hl3040网络说明书.pdf [3.4 MB]
PantumP3500用户手册zh_CNV1.2_1644316283788.pdf [24.0 MB]
H3C ER2100企业级路由器 用户手册-6W104-整本手册.pdf [2.7 MB]
华为擎云 C5e (第2代) 用户指南-(BZF5-W00,HarmonyOS3.0_01,zh-cn).pdf [6.9 MB]
华为显示器 B3-241H 用户指南-(SSN-24BZ,VGA,04,zh-cn).pdf [1.8 MB]
华为擎云W515 用户指南-(PanguV,KOS_05,zh-cn).pdf [1.5 MB]
H3C MER系列路由器 用户手册-R0821-6W105-整本手册.pdf [4.7 MB]
hak180使用说明书.pdf [1.2 MB]
华为显示器 B5-341W 用户指南-(ZQE-CBA,04,zh-cn).pdf [2.2 MB]
Pantum P3030 User Guide zh_CN V1_2.pdf [6.8 MB]
HUAWEI MateBook B5-420 用户手册-(05,zh-cn,KLV&KLVC&KLCZ).pdf [5.4 MB]
HUAWEI MateBook B3-520 用户手册-(03,zh-cn,BohrDZ).pdf [4.3 MB]
HUAWEI MateStation B515 用户手册-(PanguL,Windows11_02,zh-cn).pdf [1.3 MB]
华为擎云 W515y 用户指南-(PGUY,KOS&UOS_01,zh-cn).pdf [1.3 MB]
华为擎云L420 用户手册-(KelvinV,01,zh-cn).pdf [1.2 MB]
联想海豚用户手册.pdf [23.4 MB]
manual_cs_250-1187-E_GC251DNS_V0100.pdf [4.5 MB]
华为擎云 G740 用户指南-(KLVG-16Z,Windows11_02,zh-cn).pdf [1.1 MB]
HUAWEI MateBook B3-420 用户指南-(NDZ,Windows11_01,zh-cn).pdf [3.3 MB]
华为擎云 HM940 用户指南-(HAD-W72-001&W72-006,HarmonyOS 5.0_02,ch-zn).pdf [5.8 MB]
M7208W_Pro用户手册.pdf [13.6 MB]
Panda Pro系列打印机用户手册V1.04-20251029.pdf [5.9 MB]
华为显示器 B3-243H 用户指南-(SSNB-24BZ,01,zh-cn).pdf [1.3 MB]
📁 阶段01：Python语法基础（3月开班）
📁 3.视频
📁 day08
📁 study
class_three_test.py [3.9 KB]
test.txt
class_one_test.py [1.3 KB]
exception_one_test.py [3.6 KB]
class_four_test.py [963.0 B]
class_five_test.py [581.0 B]
class_two_test.py [1.1 KB]
bird_test.py [2.0 KB]
📁 homework
two.py [843.0 B]
one.py [235.0 B]
three.py [743.0 B]
13-捕获异常.mp4 [37.8 MB]
10-多态.mp4 [52.1 MB]
14-try...except.mp4 [49.4 MB]
每日一考.md [812.0 B]
15-try...except...else.mp4 [32.1 MB]
07-MRO方法解析顺序.mp4 [105.6 MB]
08-方法的重写.mp4 [16.9 MB]
16-else和finally.mp4 [47.3 MB]
每日一考_答案.md [2.8 KB]
09-抽象类.mp4 [44.6 MB]
12-错误和异常.mp4 [49.6 MB]
03-继承概述.mp4 [16.9 MB]
05-多继承.mp4 [46.9 MB]
11-综合案例：愤怒的小鸟.mp4 [69.4 MB]
02-回顾.mp4 [57.2 MB]
06-使用super()复用父类方法.mp4 [41.4 MB]
01-晨测.mp4 [39.8 MB]
04-单继承.mp4 [42.1 MB]
📁 day12
📁 study
📁 __pycache__
customer_info.cpython-312.pyc [2.2 KB]
regex_test.py [2.3 KB]
客户管理系统思路.txt [2.0 KB]
customer_manage.py [9.9 KB]
customer_info.py [1.2 KB]
16-客户管理系统之功能测试.mp4 [89.3 MB]
05-测试正则表达式.mp4 [54.3 MB]
每日一考_答案.md [3.3 KB]
02-正则表达式概述.mp4 [40.1 MB]
12-客户管理系统之添加功能（3）.mp4 [64.6 MB]
15-客户管理系统之查询功能.mp4 [36.9 MB]
13-客户管理系统之删除功能.mp4 [33.4 MB]
01-晨测和回顾.mp4 [92.7 MB]
07-客户管理系统之客户管理类.mp4 [33.8 MB]
08-客户管理系统之增删改查功能分析.mp4 [56.9 MB]
03-re模块常用方法.mp4 [54.2 MB]
14-客户管理系统之修改功能.mp4 [30.8 MB]
每日一考.md [726.0 B]
09-客户管理系统之编写客户信息类.mp4 [40.5 MB]
11-客户管理系统之添加功能（2）.mp4 [42.7 MB]
06-客户管理系统之客户类设计.mp4 [44.1 MB]
10-客户管理系统之添加功能（1）.mp4 [57.2 MB]
04-正则表达式的语法.mp4 [68.7 MB]
📁 day06
📁 study
lambda_test.py [1.9 KB]
fun_test.py [744.0 B]
file_one_test.py [818.0 B]
file_copy_test.py [294.0 B]
test.txt [24.0 B]
class_one_test.py [3.1 KB]
var_scope_test.py [1.4 KB]
03-闭包和嵌套作用域.mp4 [23.4 MB]
08-函数的注释.mp4 [9.9 MB]
05-递归.mp4 [62.5 MB]
12-文件拷贝.mp4 [54.2 MB]
07-匿名函数的使用.mp4 [45.9 MB]
04-全局变量和局部变量.mp4 [29.1 MB]
13-面向对象概述.mp4 [63.9 MB]
06-匿名函数.mp4 [42.5 MB]
02-变量作用域.mp4 [13.3 MB]
10-文件的读写.mp4 [54.8 MB]
11-递归遍历目录.mp4 [29.3 MB]
15-类的操作之成员访问.mp4 [46.2 MB]
每日一考.md [980.0 B]
14-类的定义.mp4 [29.9 MB]
01-晨测和回顾.mp4 [69.4 MB]
16-类的操作之实例化.mp4 [34.3 MB]
每日一考_答案.md [2.8 KB]
09-文件操作概述.mp4 [39.5 MB]
17-类的__init__().mp4 [78.8 MB]
📁 day04
📁 study
list_three_test.py [1.9 KB]
str_two_test.py [4.0 KB]
list_one_test.py [487.0 B]
str_one_test.py [822.0 B]
tuple_test.py [1.4 KB]
for_test.py [1.2 KB]
list_two_test.py [2.5 KB]
08-列表中数据的修改.mp4 [18.2 MB]
每日一考.md [679.0 B]
16-字符串其他函数.mp4 [37.9 MB]
12-列表常用函数.mp4 [80.3 MB]
03-break和pass.mp4 [28.6 MB]
15-字符串常用函数.mp4 [104.2 MB]
05-列表的创建.mp4 [19.7 MB]
01-晨测和回顾.mp4 [34.2 MB]
07-列表中添加数据、相加和相乘.mp4 [26.9 MB]
09-列表获取最大值、最小值、求和.mp4 [22.1 MB]
11-列表推导式.mp4 [31.0 MB]
06-列表获取数据和切片操作.mp4 [30.4 MB]
13-列表删除数据的问题.mp4 [48.6 MB]
04-列表List概述.mp4 [28.5 MB]
14-字符串常用功能.mp4 [23.2 MB]
10-列表的遍历.mp4 [44.0 MB]
17-元组.mp4 [61.8 MB]
02-for...else和continue.mp4 [36.8 MB]
📁 day03
📁 study
match_case_test.py [933.0 B]
if_one_test.py [674.0 B]
print_test.py [1.6 KB]
if_inner_test.py [982.0 B]
input_test.py [487.0 B]
operator_test.py [1.9 KB]
if_else_test.py [593.0 B]
if_more_test.py [1.4 KB]
while_test.py [1.4 KB]
logic_test.py [35.0 B]
for_test.py [1.2 KB]
11-成员运算符和身份运算符.mp4 [43.7 MB]
21-for循环案例.mp4 [25.0 MB]
20-for循环.mp4 [50.2 MB]
14-双分支.mp4 [17.9 MB]
06-格式化输出之format处理浮点.mp4 [24.1 MB]
19-while...else.mp4 [56.4 MB]
18-while循环案例1.mp4 [61.6 MB]
02-输入函数input().mp4 [28.2 MB]
05-格式化输出之format.mp4 [21.9 MB]
每日一考_答案.md [857.0 B]
07-格式化输出之f字符串.mp4 [15.8 MB]
01-晨测和回顾.mp4 [50.7 MB]
16-嵌套分支.mp4 [33.2 MB]
15-多分支.mp4 [46.0 MB]
04-格式化输出之占位符.mp4 [33.4 MB]
17-match...case和三目运算符.mp4 [48.8 MB]
13-单分支.mp4 [45.4 MB]
08-算术运算符和赋值运算符.mp4 [31.6 MB]
10-逻辑运算符.mp4 [31.0 MB]
12-Python的编码规范.mp4 [56.6 MB]
09-比较运算符.mp4 [27.4 MB]
每日一考.md [338.0 B]
03-输出函数print().mp4 [15.9 MB]
📁 day02
📁 代码
encoding_test.py [704.0 B]
keyword_test.py [94.0 B]
type_test.py [1.1 KB]
int_test.py [1.4 KB]
string_test.py [741.0 B]
bin_test.py [615.0 B]
var_test.py [1.3 KB]
type_cast_test.py [1.4 KB]
bool_test.py [280.0 B]
float_test.py [403.0 B]
14-浮点类型.mp4 [25.0 MB]
05-标识符的命名方法.mp4 [19.7 MB]
08-Python中操作进制.mp4 [23.3 MB]
18-自动类型转换.mp4 [48.1 MB]
17-字符串中的转义字符.mp4 [42.0 MB]
每日一考.md [511.0 B]
06-变量值互换和常量.mp4 [26.0 MB]
15-布尔类型.mp4 [22.7 MB]
13-小整数池.mp4 [47.4 MB]
每日一考_答案.md [1.7 KB]
12-type()和isinstance().mp4 [31.7 MB]
11-整型和布尔的关系.mp4 [40.7 MB]
01-日考题讲解和回顾.mp4 [55.5 MB]
03-变量的创建和赋值.mp4 [39.2 MB]
10-数据类型.mp4 [34.4 MB]
09-进制的转换.mp4 [25.0 MB]
04-标识符的命名规则.mp4 [22.8 MB]
07-进制.mp4 [25.8 MB]
16-字符串类型.mp4 [24.2 MB]
20-编码和解码.mp4 [87.8 MB]
02-PyCharm中创建项目的方式.mp4 [8.8 MB]
19-强制类型转换.mp4 [70.8 MB]
📁 day11
📁 homework
three.py [618.0 B]
two.py [423.0 B]
📁 study
th_two_test.py [589.0 B]
th_four_test.py [565.0 B]
ps_two_test.py [462.0 B]
decorator_one_test.py [352.0 B]
ps_five_test.py [783.0 B]
ps_three_test.py [469.0 B]
th_one_test.py [764.0 B]
th_three_test.py [856.0 B]
decorator_two_test.py [486.0 B]
ps_one_test.py [1.1 KB]
test.txt [273.0 B]
ps_four_test.py [487.0 B]
15-线程概述.mp4 [25.2 MB]
21-进程和线程的区别以及使用场景.mp4 [37.0 MB]
01-晨测.mp4 [38.1 MB]
每日一考_答案.md [2.9 KB]
16-使用threading.Thread创建线程.mp4 [22.6 MB]
14-使用队列在进程间实现数据共享.mp4 [29.6 MB]
12-测试进程间的通信.mp4 [29.5 MB]
17-使用Thread的子类创建线程.mp4 [27.3 MB]
10-进程池介绍.mp4 [53.2 MB]
13-队列概述.mp4 [23.2 MB]
20-互斥锁的使用和GIL.mp4 [37.5 MB]
11-使用进程池创建进程.mp4 [31.4 MB]
09-使用进程子类创建进程.mp4 [20.4 MB]
05-并发、并行和同步异步.mp4 [35.6 MB]
02-回顾.mp4 [51.1 MB]
08-使用multiprocessing.Process创建进程.mp4 [61.5 MB]
每日一考.md [629.0 B]
03-带参数的装饰器.mp4 [24.0 MB]
18-使用线程池创建线程.mp4 [47.4 MB]
07-multiprocessing.Process的参数、属性以及方法.mp4 [34.2 MB]
19-测试线程安全问题.mp4 [36.6 MB]
06-进程概述.mp4 [31.1 MB]
04-类装饰器.mp4 [35.2 MB]
📁 day07
📁 study
class_one_test.py [2.2 KB]
class_four_test.py [1.6 KB]
class_five_test.py [1.6 KB]
homework_test.py [609.0 B]
class_six_test.py [2.8 KB]
class_three_test.py [1.7 KB]
class_two_test.py [349.0 B]
.mp4 [85.0 MB]
13-封装概述.mp4 [28.9 MB]
11-动态添加类属性、实例属性、实例方法.mp4 [40.6 MB]
07-类方法和静态方法.mp4 [41.8 MB]
12-动态删除属性和方法.mp4 [42.8 MB]
09-魔法方法（1）.mp4 [38.6 MB]
06-实例方法.mp4 [17.6 MB]
03-类和对象的内存结构.mp4 [66.8 MB]
10-魔法方法（2）.mp4 [37.1 MB]
每日一考.md [738.0 B]
14-私有化.mp4 [55.8 MB]
05-类和对象中存在同名成员的情况.mp4 [75.8 MB]
类和对象内存图.bmpr [74.0 KB]
01-晨测和回顾.mp4 [80.3 MB]
08-将类外的方法设置实例方法.mp4 [16.5 MB]
02-回顾类和对象.mp4 [48.9 MB]
每日一考_答案.md [2.0 KB]
04-类属性.mp4 [48.8 MB]
📁 day09
📁 study_exception
exception_four_test.py [1.6 KB]
exception_one_test.py [885.0 B]
test.txt
exception_three_test.py [761.0 B]
exception_two_test.py [312.0 B]
📁 module_test
📁 graphic.egg-info
SOURCES.txt [191.0 B]
top_level.txt [8.0 B]
dependency_links.txt [1.0 B]
PKG-INFO [52.0 B]
📁 dist
graphic-1.0.tar.gz [1.1 KB]
📁 graphic_test
📁 __pycache__
circle.cpython-312.pyc [527.0 B]
__init__.cpython-312.pyc [209.0 B]
circle.py [158.0 B]
__init__.py [93.0 B]
rectangle.py [186.0 B]
📁 build
📁 lib
📁 graphic
__init__.py [93.0 B]
circle.py [158.0 B]
rectangle.py [186.0 B]
setup.py [217.0 B]
main.py [1.6 KB]
📁 study_import
📁 __pycache__
test_multi.cpython-312.pyc [358.0 B]
test_add.cpython-312.pyc [545.0 B]
test_add.py [229.0 B]
main.py [2.8 KB]
test_multi.py [92.0 B]
📁 homework
four_test.py [402.0 B]
three_test.py [947.0 B]
error.log [60.0 B]
one_test.py [71.0 B]
22-打包并安装自己的包.mp4 [50.8 MB]
10-全局导入.mp4 [16.5 MB]
每日一考.md [1.0 KB]
01-晨测.mp4 [46.1 MB]
17-包概述.mp4 [34.7 MB]
12-局部导入（2）.mp4 [13.8 MB]
06-异常的传递.mp4 [36.7 MB]
11-局部导入（1）.mp4 [23.9 MB]
每日一考_答案.md [3.1 KB]
05-自定义异常.mp4 [24.1 MB]
20-pip命令的使用.mp4 [97.7 MB]
19-包的局部导入.mp4 [81.1 MB]
02-回顾.mp4 [32.3 MB]
16-dir().mp4 [36.4 MB]
03-使用raise抛异常.mp4 [25.3 MB]
07-with关键字概述.mp4 [35.0 MB]
04-断言.mp4 [33.4 MB]
08-使用with操作文件读写.mp4 [63.7 MB]
14-特殊变量__all__.mp4 [29.8 MB]
09-模块和包.mp4 [40.7 MB]
13-模块搜索顺序.mp4 [25.1 MB]
21-在PyCharm中下载第三方库.mp4 [26.8 MB]
15-内置变量__name__.mp4 [24.2 MB]
18-创建包并使用全局导入.mp4 [26.3 MB]
📁 day05
📁 study
dict_two_test.py [1.5 KB]
set_two_test.py [2.1 KB]
set_one_test.py [1.1 KB]
fun_two_test.py [2.4 KB]
dict_one_test.py [2.2 KB]
fun_three_test.py [791.0 B]
fun_one_test.py [1.9 KB]
05-字典概述.mp4 [33.7 MB]
08-函数概述.mp4 [21.3 MB]
03-集合常用操作.mp4 [28.5 MB]
17-函数的返回值.mp4 [35.3 MB]
11-函数内存结构.mp4 [59.2 MB]
12-函数的参数传递.mp4 [24.8 MB]
10-函数的参数.mp4 [23.6 MB]
01-晨测和回顾.mp4 [22.6 MB]
16-浅拷贝和深拷贝.mp4 [39.5 MB]
函数内存结构图.bmpr [36.0 KB]
13-函数的参数传输可变对象和不可变对象.mp4 [43.2 MB]
每日一考_答案.md [3.6 KB]
14-函数的参数形式（1）.mp4 [24.6 MB]
15-函数的参数形式（2）.mp4 [62.8 MB]
balsamiqmockupspro.rar [21.0 MB]
18-函数的嵌套调用.mp4 [18.2 MB]
04-集合常用函数.mp4 [64.8 MB]
每日一考.md [961.0 B]
02-集合概述.mp4 [22.8 MB]
06-字典常用操作.mp4 [53.5 MB]
09-函数的抽取和调用.mp4 [45.1 MB]
07-字典常用函数.mp4 [41.6 MB]
📁 day10
📁 study
copy_test.py [1.6 KB]
decorator_three_test.py [811.0 B]
test.txt [25.0 B]
iter_three_test.py [536.0 B]
generator_one_test.py [2.8 KB]
iter_one_test.py [2.0 KB]
iter_two_test.py [1.5 KB]
decorator_two_test.py [1.5 KB]
decorator_one_test.py [800.0 B]
09-生成器概述.mp4 [26.5 MB]
08-创建迭代器倒序获取列表中的数据.mp4 [34.5 MB]
14-闭包.mp4 [42.3 MB]
17-多层装饰器.mp4 [46.4 MB]
01-回顾.mp4 [50.4 MB]
16-装饰器的使用.mp4 [46.3 MB]
15-装饰器概述.mp4 [42.2 MB]
12-命名空间.mp4 [28.5 MB]
13-作用域.mp4 [23.0 MB]
03-测试浅拷贝.mp4 [33.9 MB]
02-浅拷贝和深拷贝概述.mp4 [23.8 MB]
07-创建迭代器获取列表中的数据.mp4 [47.3 MB]
04-测试深拷贝.mp4 [34.9 MB]
06-迭代器.mp4 [49.9 MB]
11-使用send()操作生成器.mp4 [66.5 MB]
每日一考.md [402.0 B]
05-可迭代对象.mp4 [49.0 MB]
10-使用生成器获取斐波那契数列.mp4 [48.5 MB]
📁 day01
📁 代码
📁 day01_python
📁 .venv
📁 Lib
📁 site-packages
📁 pip-23.2.1.dist-info
LICENSE.txt [1.1 KB]
top_level.txt [4.0 B]
entry_points.txt [125.0 B]
RECORD [70.7 KB]
METADATA [4.1 KB]
AUTHORS.txt [9.8 KB]
INSTALLER [5.0 B]
WHEEL [92.0 B]
📁 pip
📁 _vendor
📁 distlib
…（层级过深，已停止）
📁 chardet
…（层级过深，已停止）
📁 msgpack
…（层级过深，已停止）
📁 pyproject_hooks
…（层级过深，已停止）
📁 pkg_resources
…（层级过深，已停止）
📁 distro
…（层级过深，已停止）
📁 pygments
…（层级过深，已停止）
📁 webencodings
…（层级过深，已停止）
📁 packaging
…（层级过深，已停止）
📁 resolvelib
…（层级过深，已停止）
📁 platformdirs
…（层级过深，已停止）
📁 tenacity
…（层级过深，已停止）
📁 colorama
…（层级过深，已停止）
📁 urllib3
…（层级过深，已停止）
📁 pyparsing
…（层级过深，已停止）
📁 tomli
…（层级过深，已停止）
📁 certifi
…（层级过深，已停止）
📁 idna
…（层级过深，已停止）
📁 requests
…（层级过深，已停止）
📁 rich
…（层级过深，已停止）
📁 cachecontrol
…（层级过深，已停止）
vendor.txt [475.0 B]
six.py [33.7 KB]
__init__.py [4.8 KB]
typing_extensions.py [108.5 KB]
📁 _internal
📁 distributions
…（层级过深，已停止）
📁 network
…（层级过深，已停止）
📁 index
…（层级过深，已停止）
📁 utils
…（层级过深，已停止）
📁 vcs
…（层级过深，已停止）
📁 commands
…（层级过深，已停止）
📁 resolution
…（层级过深，已停止）
📁 metadata
…（层级过深，已停止）
📁 locations
…（层级过深，已停止）
📁 cli
…（层级过深，已停止）
📁 models
…（层级过深，已停止）
📁 operations
…（层级过深，已停止）
📁 req
…（层级过深，已停止）
pyproject.py [7.0 KB]
cache.py [10.2 KB]
wheel_builder.py [11.6 KB]
__init__.py [573.0 B]
build_env.py [10.0 KB]
exceptions.py [23.2 KB]
configuration.py [13.5 KB]
main.py [340.0 B]
self_outdated_check.py [8.0 KB]
__pip-runner__.py [1.4 KB]
__main__.py [854.0 B]
__init__.py [357.0 B]
py.typed [286.0 B]
📁 __pycache__
_virtualenv.cpython-312.pyc [4.1 KB]
_virtualenv.py [4.3 KB]
pip-23.2.1.virtualenv
_virtualenv.pth [18.0 B]
📁 Scripts
pip-3.12.exe [105.9 KB]
pip3.12.exe [105.9 KB]
pythonw.exe [257.4 KB]
activate.bat [1.0 KB]
pip.exe [105.9 KB]
activate [2.2 KB]
activate.ps1 [1.6 KB]
pydoc.bat [24.0 B]
activate.nu [2.7 KB]
activate_this.py [1.3 KB]
pip3.exe [105.9 KB]
activate.fish [3.0 KB]
deactivate.bat [537.0 B]
python.exe [268.0 KB]
pyvenv.cfg [266.0 B]
.gitignore [42.0 B]
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
misc.xml [183.0 B]
.gitignore [184.0 B]
day01_python.iml [411.0 B]
workspace.xml [9.1 KB]
modules.xml [283.0 B]
📁 study
hello.py [20.0 B]
comment.py [325.0 B]
var.py [428.0 B]
test.py [40.0 B]
09-Python版本和解释器.mp4 [46.7 MB]
05-计算机语言的执行过程.mp4 [49.3 MB]
06-Python程序执行过程.mp4 [19.8 MB]
07-Python概述.mp4 [49.5 MB]
15-变量.mp4 [38.5 MB]
10-安装Python.mp4 [79.4 MB]
03-计算机软件.mp4 [12.4 MB]
jetbrains.rar [2.3 MB]
01-课程介绍.mp4 [15.9 MB]
04-程序和计算机语言.mp4 [39.6 MB]
13-第一个Python程序.mp4 [51.1 MB]
11-安装PyCharm.mp4 [101.7 MB]
12-配置PyCharm.mp4 [31.3 MB]
00-课程必备软件.mp4 [77.5 MB]
02-计算机硬件.mp4 [21.7 MB]
08-Python的应用场景、优缺点.mp4 [67.4 MB]
14-注释.mp4 [21.4 MB]
尚硅谷大模型技术之Python课后练习题以及答案.docx [312.7 KB]
📁 2.资料
📁 课堂必备软件
📁 Typora
📁 Typora主题
📁 themes
📁 night
.png [407.0 B]
credit.html [295.0 B]
mermaid.dark.css [4.2 KB]
codeblock.dark.css [1.5 KB]
sourcemode.dark.css [714.0 B]
cursor.png [372.0 B]
📁 github
700i.woff [63.5 KB]
400.woff [65.9 KB]
600i.woff [64.3 KB]
700.woff [68.5 KB]
400i.woff [63.7 KB]
📁 cobalt
📁 nunito
NunitoSans-ExtraBold.woff [52.4 KB]
NunitoSans-Regular.woff [51.9 KB]
NunitoSans-Italic.woff [53.7 KB]
NunitoSans-ExtraBoldItalic.woff [54.2 KB]
📁 hack
hack-regular.woff [137.8 KB]
splash.png [242.1 KB]
aurum.psd [2.8 MB]
📁 vue
fonts.css [9.2 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwlBduz8A.woff2 [8.1 KB]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qNq7lqDY.woff2 [14.7 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwlxdu.woff2 [15.4 KB]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qPK7lqDY.woff2 [9.5 KB]
L0x5DF4xlVMF-BfR8bXMIjhGq3-cXbKDO1w.woff2 [11.1 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwlxdu.woff2 [15.4 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwkxduz8A.woff2 [9.3 KB]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qN67lqDY.woff2 [5.3 KB]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qO67lqDY.woff2 [8.3 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwmRduz8A.woff2 [14.8 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwmRduz8A.woff2 [14.4 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwmBduz8A.woff2 [5.3 KB]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qOK7l.woff2 [15.5 KB]
L0x5DF4xlVMF-BfR8bXMIjhIq3-cXbKDO1w.woff2 [5.0 KB]
L0x5DF4xlVMF-BfR8bXMIjhLq3-cXbKD.woff2 [10.4 KB]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qNK7lqDY.woff2 [7.2 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwmBduz8A.woff2 [5.2 KB]
L0x5DF4xlVMF-BfR8bXMIjhHq3-cXbKDO1w.woff2 [812.0 B]
6xK3dSBYKcSV-LCoeQqfX1RYOo3qNa7lqDY.woff2 [6.7 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwmhduz8A.woff2 [6.7 KB]
L0x5DF4xlVMF-BfR8bXMIjhEq3-cXbKDO1w.woff2 [3.6 KB]
L0x5DF4xlVMF-BfR8bXMIjhFq3-cXbKDO1w.woff2 [7.7 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwmhduz8A.woff2 [6.6 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwmxduz8A.woff2 [7.3 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwkxduz8A.woff2 [9.3 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3i54rwmxduz8A.woff2 [7.1 KB]
6xKydSBYKcSV-LCoeQqfX1RYOo3ik4zwlBduz8A.woff2 [8.2 KB]
L0x5DF4xlVMF-BfR8bXMIjhPq3-cXbKDO1w.woff2 [6.4 KB]
📁 newsprint
pt-serif-v9-latin-italic.woff [39.9 KB]
pt-serif-v9-latin-700.woff [34.0 KB]
pt-serif-v9-latin-regular.woff [38.1 KB]
pt-serif-v9-latin-700italic.woff [32.9 KB]
📁 pixyll
lato-v14-latin-900.woff [26.6 KB]
merriweather-v19-latin-300italic.woff [22.3 KB]
merriweather-v19-latin-700.woff [22.2 KB]
lato-v14-latin-300.woff [29.2 KB]
merriweather-v19-latin-700italic.woff [22.5 KB]
merriweather-v19-latin-300.woff [22.3 KB]
lato-v14-latin-900italic.woff [28.0 KB]
lato-v14-latin-300italic.woff [21.8 KB]
📁 old-themes
github.css [5.9 KB]
newsprint.css [9.0 KB]
whitey.css [4.3 KB]
github.css [5.9 KB]
cobalt.css [25.1 KB]
Readme.md [256.0 B]
night.css [15.5 KB]
vue.css [6.8 KB]
pixyll.css [8.7 KB]
vue-dark.css [12.7 KB]
使用说明.txt [168.0 B]
Typora安装包+破解教程.7z [67.8 MB]
notepad-plus-8.4.6（文本编辑器）.exe [4.1 MB]
README.txt [677.0 B]
金山打字通.exe [20.2 MB]
PixPin_1.8.22.0.exe [32.7 MB]
haozip_v5.3.1（解压缩软件）.exe [9.4 MB]
geek（强制卸载软件工具）.exe [6.3 MB]
xmind-9-windows（脑图笔记软件）.exe [157.4 MB]
EVCapture_v5.1.6.exe [32.4 MB]
python-3.12.9-amd64.exe [25.7 MB]
jetbrains.rar [2.3 MB]
python-3.12.8-amd64.exe [25.8 MB]
pycharm-professional-2024.3.1.1.exe [818.1 MB]
📁 1.笔记
尚硅谷大模型技术之Python2.0.docx [10.4 MB]
📁 阶段13：Loop Engineering
📁 视频
01_什么是Loop Engineering.mp4 [63.5 MB]
06_重要模块指引.mp4 [46.5 MB]
02_项目背景&核心概念.mp4 [86.5 MB]
05_核心模块指引.mp4 [72.4 MB]
04_运行演示.mp4 [94.9 MB]
00_概述.mp4 [104.5 MB]
随堂笔记.txt [608.0 B]
03_项目架构说明.mp4 [54.1 MB]
工程调研助手(Loop Engineering)_0706.zip [1.3 MB]
📁 阶段14：Agent框架之Hermes
📁 视频
09_Hermes_案例：深度研究.mp4 [279.8 MB]
02_Hermes_会话.mp4 [88.5 MB]
01_Hermes_基础.mp4 [105.5 MB]
06_Hermes_Gateway_2.mp4 [37.1 MB]
04_Hermes_Hooks&Plugins.mp4 [85.0 MB]
05_Hermes_Gateway_1.mp4 [87.4 MB]
03_Hermes_Toolsets&MCP&Skills.mp4 [137.4 MB]
08_Hermes_Kanban.mp4 [121.0 MB]
07_Hermes_Profile&Cron&Delegation.mp4 [111.6 MB]
📁 资料
📁 hermes
📁 deepresearch
📁 skills
📁 deepresearch-orchestrator
SKILL.md [18.3 KB]
📁 deepresearch-searcher
SKILL.md [7.7 KB]
📁 deepresearch-synthesizer
SKILL.md [7.1 KB]
📁 deepresearch-reviewer
SKILL.md [6.7 KB]
📁 deepresearch-renderer
SKILL.md [6.1 KB]
📁 deepresearch-writer
SKILL.md [5.9 KB]
📁 docker
docker-compose.yaml [600.0 B]
📁 scripts
📁 hooks
mac-toast.swift [5.1 KB]
agent-notify.py [14.4 KB]
README.md [134.7 KB]
📁 阶段06：LangChain
📁 01版本（推荐看）
📁 day03_LangChain的Retrieval
📁 4_other
📁 MinerU解析在线PDF后的产物
📁 images
02048b50b7bcaf48dca018041414db664717ce723075a148e393d0873acc00aa.jpg [2.8 KB]
9771ce49be30d62dded021d1fd406125a6b5470b9238c0b5d20add7f88391a1a.jpg [71.9 KB]
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f066daf5-ee11-42b1-98b7-dc5af1ebce9a_origin.pdf [315.0 KB]
full.md [50.4 KB]
f066daf5-ee11-42b1-98b7-dc5af1ebce9a_model.json [81.2 KB]
content_list_v2.json [138.4 KB]
layout.json [896.3 KB]
f066daf5-ee11-42b1-98b7-dc5af1ebce9a_content_list.json [77.3 KB]
📁 MinerU解析本地PDF后的产物
📁 images
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content_list_v2.json [1.4 MB]
2b2496f2-7ad1-4e7d-88f3-0b68f0dd41b9_content_list.json [764.5 KB]
2b2496f2-7ad1-4e7d-88f3-0b68f0dd41b9_origin.pdf [15.3 MB]
full.md [278.4 KB]
2b2496f2-7ad1-4e7d-88f3-0b68f0dd41b9_model.json [1.1 MB]
layout.json [4.4 MB]
📁 高级进阶
📁 Milvus检索全家桶
📁 images
9、权重调优建议.jpg [601.5 KB]
17、各检索方式速查表.jpg [625.1 KB]
12、二者区分.jpg [678.7 KB]
6、范围搜索核心原理.jpg [543.3 KB]
8、 混合搜索核心原理.jpg [502.6 KB]
10、 Analyzer 工作流程.png [83.8 KB]
4、 相似度度量方式.jpg [541.4 KB]
2、Milvus 检索体系全景图.jpg [386.6 KB]
13、 与手动稀疏向量（BGE-M3）的对比.jpg [585.3 KB]
3、 基本 ANN 搜索原理图.jpg [502.7 KB]
16、决策流程.jpg [570.6 KB]
5、 过滤搜索核心原理.jpg [475.4 KB]
14、组合方式.jpg [664.0 KB]
15、向量索引类型选择.jpg [486.1 KB]
7、 分组搜索核心原理.jpg [579.5 KB]
掌柜智库项目_Milvus检索体系全解.md [35.7 KB]
📁 高级RAG优化技术
📁 images
16.自我反思.png [84.2 KB]
11.元数据过滤检索.png [95.6 KB]
5.查询增强策略决策树.png [1.1 MB]
6.合并块.png [136.5 KB]
20.RAG五维增强体系.png [1.2 MB]
18.查询路由1.png [81.1 KB]
19.管道增强策略决策树.png [1.3 MB]
3.子问题拆解.png [84.8 KB]
13.压缩提示词.png [130.5 KB]
2.假设文档嵌入.png [69.1 KB]
10.句子窗口检索.png [113.5 KB]
12.检索器增强策略决策树.png [1.2 MB]
4.回溯原理图.png [105.0 KB]
8.混合检索和重排序.png [77.3 KB]
1.假设问题原理图.png [91.2 KB]
14.块顺序调整.png [115.6 KB]
7.分层索引.png [73.9 KB]
17.查询路由.png [76.4 KB]
检索器增强.jpg [731.7 KB]
9.索引增强策略决策树.png [1.1 MB]
15.生成器增强策略决策树.png [1.1 MB]
高级RAG增强技术.pdf [22.7 MB]
高级RAG增强技术.md [74.9 KB]
尚硅谷大模型技术之LangChainV1.1.0.docx [5.0 MB]
01_文档加载器.ipynb [13.4 KB]
bge-m3混合向量的结果结构.json [967.0 B]
03_文档嵌入.ipynb [1.0 KB]
02_文档切分器.ipynb [589.0 B]
📁 1_vcr
16、AI_RAG_文档嵌入阶段（Bge-m3嵌入模型混合向量生成的使用）.mp4 [180.1 MB]
2、AI_RAG的两大核心阶段（索引、检索）.mp4 [64.9 MB]
14、AI_RAG_文档嵌入阶段（HuggingFace平台的bge嵌入模型使用）.mp4 [49.8 MB]
5、AI_RAG_文档加载阶段（加载Word格式的文档）.mp4 [80.0 MB]
18、AI_RAG_文档嵌入阶段（Milvus的部署）.mp4 [77.8 MB]
8、AI_RAG_文档加载阶段（API方式接入MinerU解析本地PDF）.mp4 [173.2 MB]
17、AI_RAG_文档嵌入阶段（Milvus向量数据库架构设计）.mp4 [128.0 MB]
4、AI_RAG_文档加载阶段（加载MarkDown格式的文档）.mp4 [131.3 MB]
15、AI_RAG_文档嵌入阶段（OpenAI平台的嵌入模型使用）.mp4 [35.0 MB]
6、AI_RAG_文档加载阶段（加载pdf的说明MinerU说明）.mp4 [119.6 MB]
9、AI_RAG_文档加切分阶段（为什么进行切分）.mp4 [48.3 MB]
12、AI_RAG_文档加切分阶段（递归切分器的使用演示）.mp4 [113.6 MB]
11、AI_RAG_文档加切分阶段（递归切分器的流程）.mp4 [77.5 MB]
7、AI_RAG_文档加载阶段（API方式接入MinerU解析在线PDF）.mp4 [180.7 MB]
3、AI_RAG_文档加载阶段（文档加载的原因分析）.mp4 [73.5 MB]
1、AI_RAG的概述.mp4 [86.3 MB]
13、AI_RAG_文档嵌入阶段（为什么要嵌入）.mp4 [58.8 MB]
19、AI_RAG_文档嵌入阶段（Milvus核心概念）.mp4 [270.6 MB]
10、AI_RAG_文档加切分阶段（递归切分策略的选择）.mp4 [79.9 MB]
📁 3_code
📁 day03_retrieval
📁 assets
sample.pdf [828.1 KB]
尚硅谷大模型技术之NLP1.0.2.pdf [16.0 MB]
sample.txt [313.0 B]
sample.docx [153.1 KB]
sample.md [6.3 KB]
01_文档加载器.ipynb [13.8 KB]
02_文档切分器_bak.ipynb [589.0 B]
02_文档切分器.ipynb [11.2 KB]
demo.py [1.4 KB]
03_文档嵌入.ipynb [5.2 KB]
📁 2_resource
📁 images
11、数据插入流程 (Insert).png [978.4 KB]
8、 为什么要嵌入.png [4.2 MB]
5、MinerU两阶段策略.png [1.1 MB]
23、数据流向.png [1.0 MB]
9、稠密向量vs稀疏向量.png [1.1 MB]
4、文档加载器概览.png [1.0 MB]
6、工作原理.png [4.5 MB]
14、数据类型.png [1.2 MB]
17、三种对比.png [1.2 MB]
18、Milvus基本流程.png [1000.0 KB]
10、关系性数据库和向量数据库.png [1.3 MB]
12、向量检索流程 (Search).png [1011.0 KB]
19、RRF重排序.png [1.1 MB]
17、度量类型.jpg [565.7 KB]
16、倒排索引.png [1.1 MB]
3、RAG完整数据流程.png [1.1 MB]
1、RAG 架构流程.png [1.1 MB]
13、Milvus核心概念.png [1.0 MB]
22、RAG完整技术栈.png [1.1 MB]
20、RAG流程.png [1.0 MB]
21、架构图.png [152.8 KB]
7、OverLap示意图.png [4.2 MB]
2、RAG的应用场景.png [1.1 MB]
15、HNSW.png [1.0 MB]
课件04_Retrieval_RAG检索增强生成.md [76.6 KB]
day03_LangChain的Retrieval.torrent [62.8 KB]
📁 day02_LangChain核心组件（Prompts、OutPutParser、Chains）
📁 1_vcr
6、AI_FewShotPromptTemplate的使用.mp4 [124.1 MB]
11、AI_LangChain其它输出解析器（字符串输出解析器、Pydantic输出解析器）).mp4 [294.3 MB]
9、AI_输出解析器_JsonOutParser深入理解.mp4 [130.5 MB]
16、AI_LangChain中的Runnable组合器（RunnableParallel ）使用.mp4 [137.7 MB]
18、AI_LangChain中的Runnable组合器（为链添加历史对话 ）使用.mp4 [150.6 MB]
10、AI_LangChain集成了统一结构化输出的API(with_structured_output).mp4 [161.3 MB]
17、AI_LangChain中的Runnable组合器（RunnablePassthrough、RunnableLambda ）使用.mp4 [101.9 MB]
4、AI_ChatPromptTemplate的使用以及注意细节.mp4 [58.9 MB]
15、AI_LangChain中的Runnable组合器（RunnableSequence）使用.mp4 [79.3 MB]
8、AI_输出解析器_Pydantic的说明.mp4 [62.3 MB]
1、AI_提示词模版的介绍与原理分析.mp4 [104.1 MB]
3、AI_PromptTemplate的部分变量使用.mp4 [43.2 MB]
13、AI_LangChain自定义输出解析器.mp4 [26.9 MB]
5、AI_MessagePlaceHolder的使用.mp4 [81.6 MB]
7、AI_输出解析器_JsonOutPutParser的基础使用.mp4 [100.0 MB]
2、AI_PromptTemplate的基础使用.mp4 [153.8 MB]
12、AI_LangChain其它输出解析器（额外的补充).mp4 [40.5 MB]
14、AI_LangChain中的Runnable、LCEL、Chain的概念.mp4 [73.4 MB]
📁 2_resource
📁 images
1.提示词模板类型概览.png [1.2 MB]
课件03_LangChain核心组件(提示词模板、输出解析、Chains.md [39.3 KB]
📁 4_other
📁 day02_core_components
01_提示词模版.ipynb [1.8 KB]
02_输出解析器.ipynb [1.3 KB]
03_链&可运行对象.ipynb [1.3 KB]
课堂笔记.excalidraw [76.9 KB]
📁 3_code
📁 day02_core_components
02_输出解析器.ipynb [8.7 KB]
demo.ipynb [21.4 KB]
03_链&可运行对象.ipynb [16.9 KB]
01_提示词模版.ipynb [25.8 KB]
day02_LangChain核心组件（Prompts、OutPutParser、Chains）.torrent [21.7 KB]
📁 day04_LangChain的Agent（智能体）
📁 2_resource
📁 images
1、Agent的核心组件.png [861.3 KB]
5、MCP架构.png [816.9 KB]
7、执行流程图示.png [1.0 MB]
3、技术栈定位.png [795.7 KB]
4、 MCP是什么.png [631.3 KB]
2、Agent的工作循环.png [1.0 MB]
6、 中间件概念.png [805.7 KB]
8、LangChain完整知识体系.png [776.7 KB]
课件05_Agents_智能代理.md [57.8 KB]
📁 1_vcr
15、AI_LangChain的mcp的接入（streamable）以及为Agent接入mcp工具.mp4 [169.6 MB]
5、AI_LangChain的混合向量检索的RRF重排序器的原理.mp4 [65.0 MB]
12、AI_LangChain的Agent的使用.mp4 [216.7 MB]
10、AI_LangChain的底层Funcation_Call的背后逻辑.mp4 [266.4 MB]
9、AI_LangChain的Agent概念（核心理解）.mp4 [155.0 MB]
7、AI_LangChain的混合向量检索混合搜索结合重排序器的使用.mp4 [114.9 MB]
16、AI_LangChain的Agent集成记忆机制.mp4 [46.9 MB]
2、AI_LangChain向量数据库Milvus的完整入库操作.mp4 [156.8 MB]
8、AI_LangChain的检索生成完整案例（RAG流程）.mp4 [135.4 MB]
4、AI_LangChain的混合向量检索的加权排序器的原理.mp4 [95.9 MB]
11、AI_LangChain的工具封装和使用mp4.mp4 [57.7 MB]
13、AI_LangChain的mcp介绍.mp4 [81.2 MB]
3、AI_LangChain向量数据库Milvus的(稠密、稀疏向量)检索.mp4 [213.1 MB]
14、AI_LangChain的mcp的接入（stdio）.mp4 [135.0 MB]
17、AI_LangChain的Agent集成中间件.mp4 [173.8 MB]
1、AI_LangChain向量数据库Milvus的操作.mp4 [105.2 MB]
6、AI_LangChain的混合向量检索混合搜索请求的使用步骤.mp4 [52.0 MB]
📁 4_other
课堂笔记.excalidraw [178.7 KB]
📁 3_code
WH0316_LangChain.zip [16.3 MB]
day04_LangChain的Agent（智能体）.torrent [13.8 KB]
📁 day01_LangChain概述&环境准备&模型调用
📁 3_code
WH0316_LangChain.zip [260.4 KB]
📁 2_resource
📁 images
1、架构分层图.png [1.5 MB]
2、Python工具对比.png [1.3 MB]
3、 MOdelIO 的三个环节.png [1.2 MB]
课件02_Model_IO_模型调用.md [48.8 KB]
课件01_LangChain概述与环境准备.md [26.4 KB]
📁 1_vcr
13、AI_模型调用方式（3组6个api）操作.mp4 [221.7 MB]
2、AI_LangChain的背景介绍.mp4 [96.4 MB]
7、AI_常用大模型服务平台（国内API_Key申请方式）.mp4 [95.4 MB]
5、AI_Pytharm创建环境管理（uv方式）.mp4 [80.3 MB]
9、AI_使用LangChain调用模型.mp4 [156.3 MB]
3、AI_LangChain三层架构全局概览.mp4 [95.4 MB]
10、AI_使用LangChain调用模型温度参数.mp4 [120.8 MB]
4、AI_conda、uv、pip、venv之间的关系.mp4 [78.6 MB]
11、AI_使用LangChain调用init_chat_model的使用.mp4 [119.7 MB]
1、AI_LangChain大模型语言框架..mp4 [128.8 MB]
17、AI_模型调用高级主题（限速、token统计）.mp4 [122.3 MB]
12、AI_模型调用的消息类型以及传入方式.mp4 [137.5 MB]
6、AI_常用大模型服务平台.mp4 [82.4 MB]
16、AI_模型调用高级主题（多模态使用）.mp4 [119.7 MB]
8、AI_使用原生SDK方式调用和模型通信.mp4 [190.5 MB]
15、AI_模型调用方式（运行本地模型）.mp4 [47.4 MB]
14、AI_模型调用方式（运行时配置）操作.mp4 [117.0 MB]
📁 4_other
📁 day01_intro_and_models
03_多模型切换与对比.ipynb [1.4 KB]
image.jpg [91.1 KB]
02_模型调用方式.ipynb [2.7 KB]
01_和大语言模型交互.ipynb [2.2 KB]
04_高级主题.ipynb [1.0 KB]
day01_LangChain概述&环境准备&模型调用.torrent [22.4 KB]
📁 02版本
📁 2.资料
📁 assets
📁 sample
📁 word
📁 theme
theme1.xml [6.9 KB]
📁 _rels
document.xml.rels [1.2 KB]
document.xml [1.5 MB]
settings.xml [4.8 KB]
fontTable.xml [4.6 KB]
footer2.xml [2.8 KB]
footer1.xml [2.8 KB]
styles.xml [22.4 KB]
📁 docProps
core.xml [633.0 B]
custom.xml [383.0 B]
app.xml [627.0 B]
📁 customXml
📁 _rels
item2.xml.rels [296.0 B]
item1.xml.rels [296.0 B]
item1.xml [258.0 B]
itemProps1.xml [327.0 B]
itemProps2.xml [236.0 B]
item2.xml [289.0 B]
📁 _rels
.rels [737.0 B]
[Content_Types].xml [1.8 KB]
📁 models
📁 bge-m3
📁 imgs
mkqa.jpg [593.8 KB]
long.jpg [474.1 KB]
nqa.jpg [154.6 KB]
bm25.jpg [128.8 KB]
miracl.jpg [563.0 KB]
others.webp [20.5 KB]
📁 1_Pooling
config.json [191.0 B]
README.md [15.5 KB]
colbert_linear.pt [2.0 MB]
pytorch_model.bin [2.1 GB]
sentence_bert_config.json [54.0 B]
modules.json [349.0 B]
config.json [687.0 B]
sparse_linear.pt [3.4 KB]
tokenizer.json [16.3 MB]
long.jpg [123.9 KB]
sentencepiece.bpe.model [4.8 MB]
tokenizer_config.json [444.0 B]
special_tokens_map.json [964.0 B]
.gitattributes [1.6 KB]
config_sentence_transformers.json [123.0 B]
📁 bge-base-zh-v1.5
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
config.json.metadata [103.0 B]
tokenizer_config.json.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
.gitattributes.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
modules.json.metadata [104.0 B]
README.md.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
special_tokens_map.json.metadata [104.0 B]
config.json.metadata [104.0 B]
config_sentence_transformers.json.metadata [103.0 B]
pytorch_model.bin.metadata [128.0 B]
.gitignore [1.0 B]
📁 1_Pooling
config.json [190.0 B]
tokenizer.json [428.8 KB]
tokenizer_config.json [366.0 B]
.gitattributes [1.5 KB]
pytorch_model.bin [390.2 MB]
config_sentence_transformers.json [124.0 B]
sentence_bert_config.json [52.0 B]
modules.json [349.0 B]
README.md [27.1 KB]
vocab.txt [107.0 KB]
special_tokens_map.json [125.0 B]
config.json [998.0 B]
📁 bge-base-en-v1.5
📁 1_Pooling
config.json [190.0 B]
📁 onnx
📁 .cache
📁 huggingface
📁 download
📁 1_Pooling
config.json.metadata [104.0 B]
📁 onnx
ihhw_uFzBe-Y54_HOJQmXx4GS8A=.9bc579acdba21c253c62a9bf866891355a63ffa3442b52c8a37d75b2ccb91848.incomplete
README.md.metadata [104.0 B]
vocab.txt.metadata [104.0 B]
config_sentence_transformers.json.metadata [101.0 B]
tokenizer_config.json.metadata [104.0 B]
sentence_bert_config.json.metadata [104.0 B]
tokenizer.json.metadata [104.0 B]
config.json.metadata [104.0 B]
model.safetensors.metadata [128.0 B]
special_tokens_map.json.metadata [104.0 B]
pytorch_model.bin.metadata [128.0 B]
.gitattributes.metadata [104.0 B]
modules.json.metadata [104.0 B]
.gitignore [1.0 B]
.gitattributes [1.5 KB]
tokenizer_config.json [366.0 B]
model.safetensors [417.7 MB]
config.json [777.0 B]
tokenizer.json [694.7 KB]
README.md [92.3 KB]
config_sentence_transformers.json [124.0 B]
special_tokens_map.json [125.0 B]
modules.json [349.0 B]
sentence_bert_config.json [52.0 B]
vocab.txt [226.1 KB]
pytorch_model.bin [417.7 MB]
📁 mineru_output
📁 images
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content_list_v2.json [1.4 MB]
2b2496f2-7ad1-4e7d-88f3-0b68f0dd41b9_origin.pdf [15.3 MB]
2b2496f2-7ad1-4e7d-88f3-0b68f0dd41b9_model.json [1.1 MB]
layout.json [4.4 MB]
full.md [278.4 KB]
2b2496f2-7ad1-4e7d-88f3-0b68f0dd41b9_content_list.json [764.5 KB]
sample.pdf [828.1 KB]
sample.json [1016.0 B]
sample.md [6.3 KB]
尚硅谷大模型技术之NLP1.0.2.pdf [16.0 MB]
sample.txt [313.0 B]
sample.csv [359.0 B]
sample.docx [153.1 KB]
📁 models
📁 blobs
sha256-cff3f395ef3756ab63e58b0ad1b32bb6f802905cae1472e6a12034e4246fbbdb [120.0 B]
sha256-05a61d37b08453e59290add468e3bb2f688e23a01e967fecb0e2fa41218cea76 [487.0 B]
sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f [4.9 GB]
sha256-ae370d884f108d16e7cc8fd5259ebc5773a0afa6e078b11f4ed7e39a27e0dfc4 [1.7 KB]
sha256-d18a5cc71b84bc4af394a31116bd3932b42241de70c77d2b76d69a314ec8aa12 [11.1 KB]
📁 manifests
📁 registry.ollama.ai
📁 library
📁 qwen3
latest [859.0 B]
8b [859.0 B]
Anaconda3-2024.10-1-Windows-x86_64.exe [950.5 MB]
Docker Desktop Installer.exe [586.3 MB]
attu.Setup.2.6.4.exe [86.6 MB]
standalone.bat [4.3 KB]
Anaconda3-2024.10-1-Linux-x86_64.sh [1.0 GB]
milvus_image.tar [2.4 GB]
standalone_embed.sh [5.1 KB]
requirements.txt [6.4 KB]
bge-m3.exe [995.0 MB]
📁 4.视频
01_问题说明.mp4 [30.5 MB]
09_环境的补充说明.mp4 [31.5 MB]
17_异步调用大模型.mp4 [29.4 MB]
13_init_chat_model调用模型.mp4 [99.5 MB]
06_Anaconda的介绍.mp4 [76.1 MB]
11_openai_responses_api.mp4 [63.9 MB]
05_LangChain的包以及模块划分.mp4 [44.5 MB]
19_批次传入消息列表.mp4 [11.6 MB]
07_虚拟环境的创建以及依赖导入.mp4 [50.0 MB]
12_google_sdk.mp4 [21.0 MB]
08_环境变量的导入.mp4 [71.0 MB]
20_调用ollama本地模型.mp4 [24.9 MB]
10_openai_completion.mp4 [87.8 MB]
21_pycharm的bug说明.mp4 [3.6 MB]
15_构造消息列表传入数据.mp4 [36.3 MB]
18_流式输出实现打字机效果 .mp4 [25.5 MB]
04_从两个问题的角度介绍为什么需要LangChain.mp4 [40.9 MB]
03_LangChain概述.mp4 [52.0 MB]
16_传入元组和字典.mp4 [28.1 MB]
14_langchain_openai的调用.mp4 [25.1 MB]
02_课程教材说明.mp4 [11.0 MB]
📁 3.代码
LangChainDemo.rar [7.9 KB]
📁 1.笔记
📁 conda使用指南
📁 images
image-20250620165046595.png [11.0 KB]
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编辑系统环境变量.png [234.7 KB]
环境变量.png [114.1 KB]
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尚硅谷-conda使用指南.md [17.5 KB]
Anaconda安装说明.docx [4.9 MB]
尚硅谷大模型技术之LangChainV1.1.0.docx [5.0 MB]
📁 阶段10：智能体项目：Agent多智能体项目
📁 1.课件
📁 RAGFlow.assets
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image-20250619112847346.png [1.1 MB]
image-20250619134716042.png [563.9 KB]
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📁 assets
image-20260222125636193.png [29.8 KB]
image-20260222190235512.png [38.2 KB]
image-20260312162445613.png [23.6 KB]
image-20260214225424700.png [430.2 KB]
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image-20260218202038937.png [25.4 KB]
image-20260221204200574.png [25.2 KB]
image-20260605230424307.png [11.3 KB]
deepagents_笔记.md [3.9 KB]
1.deepAgents.md [89.4 KB]
4.api文档.md [5.6 KB]
2.深度搜索项目.md [108.0 KB]
3.RAGFlow.md [13.3 KB]
📁 4.视频
📁 day04
03_配置ragflow_聊天提交交流.mp4 [63.9 MB]
07_MainAgent的3个工具.mp4 [128.1 MB]
02_流程图.mp4 [19.9 MB]
08_MainAgent的主体实现1.mp4 [169.6 MB]
deep-search_0316.zip [69.0 MB]
05_查询聊天助手列表.mp4 [82.4 MB]
06_实现ragflow的子智能体.mp4 [28.0 MB]
10_测试项目功能.mp4 [29.1 MB]
01_复习.mp4 [125.7 MB]
09_MainAgent的主体实现2.mp4 [99.2 MB]
04_分析Gagflow助手.mp4 [66.2 MB]
📁 day03
11_定义生成连接配置的函数.mp4 [93.9 MB]
12_得到所有表的工具函数.mp4 [45.0 MB]
15_搭建RAGFlow服务器_最后有点问题_后面补上.mp4 [184.5 MB]
10_数据库子智能分析.mp4 [62.4 MB]
02_项目流程分析.mp4 [38.4 MB]
14_定义数据库查询的子agent并测试.mp4 [56.5 MB]
03_演示项目功能.mp4 [68.7 MB]
06_准备基础代码.mp4 [34.0 MB]
04_项目依赖库说明.mp4 [13.8 MB]
16_重新测试没有问题_应该是网络问题.mp4 [10.4 MB]
deep-search_0316.zip [65.0 MB]
07_初始化模型.mp4 [12.4 MB]
08_加载项目的yaml配置.mp4 [45.8 MB]
09_创建搜索的子智能并测试.mp4 [259.7 MB]
13_查询指定表数据和执行指定的sql.mp4 [101.5 MB]
05_创建项目和文件目录结构.mp4 [42.5 MB]
01_测试题.mp4 [40.6 MB]
📁 day01
07_智能体流式调用并读取数据.mp4 [87.9 MB]
Git测试题（带答案）.md [2.3 KB]
12_字典形式的子智能体.mp4 [212.1 MB]
deepagents_test_0316.zip [24.4 MB]
04_deepagents的核心能力.mp4 [24.2 MB]
14_CompiledSubagent子智能体_包装langgraph.mp4 [25.7 MB]
08_上午总结.mp4 [20.6 MB]
11_子智能体理解.mp4 [52.3 MB]
05_第一次使用deepagents.mp4 [146.5 MB]
deepagents笔记.md [3.9 KB]
17_下午_总结.mp4 [14.5 MB]
02_引入.mp4 [39.2 MB]
06_使用langsmith记录调用过程.mp4 [48.9 MB]
13_ComiledSubagent子智能体_包装langChain.mp4 [32.7 MB]
16_子智能体嵌套.mp4 [56.9 MB]
03_相关框架比较.mp4 [96.8 MB]
01_问测试题.mp4 [17.0 MB]
09_异步执行.mp4 [88.3 MB]
10_使用git管理项目.mp4 [9.9 MB]
15_子智能体格式化输出.mp4 [28.7 MB]
📁 day02
deepagents_笔记.md [6.5 KB]
09_Backends存储_混合存储.mp4 [53.8 MB]
03_人工审批1_同意与拒绝.mp4 [174.3 MB]
04_人工审批2_编辑.mp4 [29.2 MB]
08_Backends存储_内存存储.mp4 [68.2 MB]
deepagents_test_0316.zip [24.5 MB]
01_测试题.mp4 [57.3 MB]
12_总结.mp4 [41.1 MB]
课件_资料（替换掉第一天的）.zip [1.3 GB]
02_人工审批的理解.mp4 [32.5 MB]
可以添加这个输入来显示使用的skill.jpg [66.3 KB]
10_文件权限控制.mp4 [97.4 MB]
05_人工审批3_相关问题.mp4 [30.3 MB]
06_Backends存储_理解.mp4 [44.9 MB]
11_加载skill并使用.mp4 [156.7 MB]
07_Backends存储_本地文件存储.mp4 [68.4 MB]
📁 2.资料
📁 ragflow使用
📁 知识库文件
📁 文学作品知识库
瓦尔登湖.txt [579.7 KB]
百年孤独.txt [253.4 KB]
《罗马帝国衰亡史》下册 .txt [902.8 KB]
《罗马帝国衰亡史》上册 .txt [830.6 KB]
📁 空调安装知识库
窗式空调安装说明书.pdf [2.9 MB]
风管式空调机组安装规范.pdf [5.5 MB]
📁 游戏知识库
泰拉瑞亚生物图鉴.xlsx [80.1 KB]
📁 企业管理知识库
企业内部控制管理手册.pdf [3.6 MB]
📁 刑法知识库
中华人民共和国刑法.docx [85.6 KB]
沃华医药：2025年年度报告.pdf [1.2 MB]
镜像资料.exe [887.0 MB]
📁 测试文件
📁 test_session_123
📁 sub_dir
测试文件.docx [13.2 KB]
测试文件.pdf [96.8 KB]
测试文件.xlsx [11.3 KB]
测试文件.md [51.0 B]
ui.zip [22.4 MB]
📁 3.代码
📁 阶段16：就业面试指导
📁 last-面试01
1 面试小问题.mp4 [61.9 MB]
6 中间件、依赖注入、生命周期.mp4 [62.3 MB]
4 关于异步协程.mp4 [121.7 MB]
5 conda和uv.mp4 [30.7 MB]
2 python 基础.mp4 [85.3 MB]
3 内存、迭代器、生成器.mp4 [56.9 MB]
📁 面试题-问数
4 关于优化多处llm的问题.mp4 [86.3 MB]
3 问数流程.mp4 [218.9 MB]
2 背景.mp4 [99.5 MB]
1 线程和协程的误区.mp4 [55.8 MB]
5 问数面试题.mp4 [224.2 MB]
📁 last-面试02
2 、agent上.mp4 [154.4 MB]
1 、langchain langgraph.mp4 [95.0 MB]
3 agent中.mp4 [132.2 MB]
4 agent 下.mp4 [189.2 MB]
📁 电商小二
📁 视频
02-电商小二-用户消息处理主流程.mp4 [74.8 MB]
03-电商小二-TaskHandler.mp4 [136.4 MB]
04-电商小二-KnowledgeHandler.mp4 [48.7 MB]
06-电商小二-常见面试问题.mp4 [281.7 MB]
01-电商小二-应用初始化加载.mp4 [231.8 MB]
05-电商小二-项目介绍串讲.mp4 [91.0 MB]
07-电商小二-数字人流程回顾.mp4 [37.6 MB]
在线流程图.txt [60.0 B]
📁 掌柜智库
📁 视频
03-掌柜智库-项目串讲.mp4 [175.6 MB]
10-掌柜智库-检索召回与排序生成.mp4 [92.2 MB]
07-掌柜智库-数据来源与知识整理相关.mp4 [47.5 MB]
04-掌柜智库-文档切分表格处理补充.mp4 [18.3 MB]
02-掌柜智库-查询流程.mp4 [80.1 MB]
05-掌柜智库-指标数据.mp4 [149.7 MB]
08-掌柜智库-文档解析与内容处理.mp4 [86.6 MB]
06-掌柜智库-项目背景与使用情况相关.mp4 [109.6 MB]
09-掌柜智库-文档切片与上下文完整性.mp4 [102.5 MB]
11-掌柜智库-模型、指标与评测-前后端交互-性能与部署.mp4 [99.0 MB]
01-掌柜智库-导入流程.mp4 [150.5 MB]
📁 文档
尚硅谷AI全能开发技术之高频面试题-V1.9.0.docx [37.5 MB]
切分与合并参数简单评估方式.md [10.6 KB]
MarkDown表格处理方案.md [17.9 KB]
扩展技术概念.md [17.6 KB]
📁 课件
课堂随笔.pptx [125.4 KB]
尚硅谷AI全能开发技术之高频面试题-V1.12.0.docx [37.5 MB]
last面试-课堂随笔.pptx [110.9 KB]
📁 阶段02：MySQL、Linux、Docker
📁 01 Linux及Shell
📁 2.资料
VMware-workstation-full-17.5.1-23298084.exe [594.3 MB]
Xshell-8.0.0069p.exe [44.5 MB]
Xftp-8.0.0068p.exe [35.9 MB]
ubuntu-22.04.4-desktop-amd64.iso [4.7 GB]
VMware 17的许可密钥.txt [29.0 B]
📁 1.笔记
尚硅谷大模型技术之Linux（Ubuntu）1.0.docx [13.5 MB]
尚硅谷大模型技术之Shell1.0.docx [980.4 KB]
📁 4.视频
📁 day01
test.txt [2.9 MB]
20-Ubuntu中的root用户.mp4 [37.4 MB]
02-Linux和Windows的对比.mp4 [35.8 MB]
09-Linux的目录结构.mp4 [64.5 MB]
07-Linux的网络设置.mp4 [63.7 MB]
18-VI和VIM的编辑模式.mp4 [17.6 MB]
03-安装VMware.mp4 [54.0 MB]
01-Linux概述.mp4 [47.5 MB]
19-VI和VIM的命令模式.mp4 [44.9 MB]
05-安装Ubuntu.mp4 [41.5 MB]
08-远程访问工具.mp4 [68.4 MB]
16-Linux常用命令之ln和history.mp4 [39.1 MB]
12-Linux常用命令之ls.mp4 [35.7 MB]
10-APT软件包管理器.mp4 [39.1 MB]
13-Linux常用命令之cd、mkdir、touch.mp4 [34.5 MB]
21-Linux常用命令之用户操作.mp4 [43.9 MB]
04-配置虚拟机.mp4 [51.6 MB]
06-VMware的三种网络模式.mp4 [90.5 MB]
11-Linux常用命令之帮助手册.mp4 [63.6 MB]
15-Linux常用命令之tail、head、echo、输出重定向.mp4 [36.9 MB]
17-VI和VIM的一般模式.mp4 [91.8 MB]
14-Linux常用命令之cp、rm、mv、cat.mp4 [53.0 MB]
📁 day02
04-Linux常用命令之权限管理命令.mp4 [30.9 MB]
14-Shell的条件判断.mp4 [37.9 MB]
03-Linux常用命令之权限介绍.mp4 [56.1 MB]
18-Shell的while循环和read命令.mp4 [31.5 MB]
02-Linux常用命令之用户组管理命令.mp4 [48.9 MB]
05-Linux常用命令之文件查找类命令.mp4 [65.3 MB]
06-Linux磁盘类命令和压缩解压类命令.mp4 [42.3 MB]
13-Shell的变量（2）.mp4 [22.7 MB]
15-Shell的分支语句之if.mp4 [35.0 MB]
07-Linux常用命令之网络类命令.mp4 [31.9 MB]
17-Shell的循环语句之for.mp4 [33.8 MB]
11-Shell概述和入门案例.mp4 [39.8 MB]
12-Shell的变量（1）.mp4 [54.0 MB]
09-Linux定时任务（1）.mp4 [63.2 MB]
shell.tar.gz [1.3 KB]
16-Shell的分支语句之case.mp4 [23.4 MB]
01-Linux常用命令之用户管理命令.mp4 [41.7 MB]
10-Linux定时任务（2）.mp4 [28.8 MB]
08-Linux常用命令之进程管理类命令.mp4 [87.5 MB]
📁 3.代码
📁 02 MySQL
📁 1.笔记
尚硅谷大模型技术之Python连接MySQL.docx [1.4 MB]
尚硅谷大模型技术之MySQL2.0.docx [8.5 MB]
📁 4.视频
📁 day01
📁 sql
DML.sql [2.0 KB]
DDL.sql [1.3 KB]
运算符.sql [605.0 B]
06-MySQL概述.mp4 [56.9 MB]
16-DML之修改语句.mp4 [18.7 MB]
14-DML之添加语句.mp4 [38.9 MB]
02-Shell的函数.mp4 [30.3 MB]
13-DDL之表相关语句.mp4 [54.3 MB]
17-DML之查询语句.mp4 [63.0 MB]
03-Shell工具之cut命令.mp4 [36.4 MB]
每日一考.md [695.0 B]
09-设置MySQL的环境变量.mp4 [43.2 MB]
15-DML之删除语句.mp4 [33.2 MB]
11-SQL的分类、语法规范和注释.mp4 [45.6 MB]
05-数据库概述.mp4 [47.3 MB]
08-MySQL安装.mp4 [65.3 MB]
每日一考（答案）.md [4.5 KB]
18-算术运算符.mp4 [64.5 MB]
01-晨测和回顾.mp4 [56.8 MB]
12-DDL之库相关语句.mp4 [37.9 MB]
04-Shell工具之awk命令.mp4 [72.9 MB]
10-MySQL的各种客户端.mp4 [88.0 MB]
07-MySQL卸载.mp4 [51.1 MB]
📁 day02
📁 sql
运算符.sql [3.7 KB]
MySQL数据类型.sql [2.0 KB]
MySQL函数.sql [6.7 KB]
05-关于null值的判断.mp4 [51.9 MB]
06-MySQL数据类型之整数类型.mp4 [66.8 MB]
13-MySQL的日期时间函数.mp4 [99.8 MB]
02-区间或集合范围比较运算符.mp4 [70.0 MB]
14-MySQL的加密函数和系统信息函数.mp4 [35.7 MB]
10-MySQL数据类型之日期时间类型.mp4 [47.6 MB]
12-MySQL的字符串函数.mp4 [82.9 MB]
08-MySQL数据类型之字符串类型.mp4 [58.8 MB]
07-MySQL数据类型之浮点类型.mp4 [28.4 MB]
15-MySQL的条件判断函数.mp4 [74.2 MB]
16-MySQL的分组函数.mp4 [27.5 MB]
01-比较运算符.mp4 [22.0 MB]
11-MySQL的数学函数.mp4 [26.4 MB]
17-表关系.mp4 [98.5 MB]
03-模糊匹配比较运算符.mp4 [36.2 MB]
09-MySQL数据类型之枚举和集合.mp4 [21.7 MB]
04-逻辑运算符.mp4 [29.1 MB]
📁 day03
📁 sql
关联查询.sql [2.6 KB]
MySQL函数.sql [8.2 KB]
select的七大子句.sql [2.6 KB]
事务.sql [1.1 KB]
子查询.sql [5.0 KB]
21-用户和权限.mp4 [39.7 MB]
11-where型和having型子查询.mp4 [42.5 MB]
06-SELECT的七大子句之from、on、where.mp4 [50.4 MB]
16-CTE通用表达式.mp4 [67.5 MB]
04-关联查询的其他结果.mp4 [57.3 MB]
17-事务概述以及ACID.mp4 [25.7 MB]
18-开启事务的方式1.mp4 [60.0 MB]
14-update语句使用子查询.mp4 [46.9 MB]
03-外连接.mp4 [39.3 MB]
20-事务的隔离级别.mp4 [79.9 MB]
07-SELECT的七大子句之group by.mp4 [31.6 MB]
02-内连接.mp4 [63.3 MB]
05-自连接.mp4 [17.4 MB]
01-表关系回顾.mp4 [40.6 MB]
09-SELECT的七大子句之order by和limit.mp4 [65.6 MB]
08-SELECT的七大子句之having.mp4 [33.1 MB]
13-from型子查询.mp4 [25.1 MB]
15-delete语句使用子查询.mp4 [34.1 MB]
10-SELECT型子查询.mp4 [56.4 MB]
22-窗口函数.mp4 [103.7 MB]
19-开启事务的方式2.mp4 [19.9 MB]
12-exists型子查询.mp4 [59.5 MB]
📁 2.资料
📁 客户端
📁 SQLyog客户端专业版
密钥.txt [107.0 B]
SQLyog-12.0.8-0.x64.exe [7.0 MB]
SQLyog-12.0.8-0.x86.exe [6.4 MB]
Navicatls_17.rar [149.1 MB]
演示数据.sql [8.2 KB]
mysql-apt-config_0.8.36-1_all.deb [17.7 KB]
练习数据.sql [15.4 KB]
MySQL的卸载与安装.docx [1.5 MB]
mysql-installer-community-8.0.26.0.msi [450.7 MB]
📁 3.代码
📁 03 Docker
📁 1.笔记
尚硅谷大模型技术之Docker1.0.docx [1.2 MB]
📁 4.视频
12-Docker案例之测试docker compose功能.mp4 [143.4 MB]
07-Docker概述.mp4 [69.8 MB]
08-Docker架构和核心概念.mp4 [85.6 MB]
03-Python连接MySQL之获取连接.mp4 [47.7 MB]
13-Ubuntu安装Docker.mp4 [62.8 MB]
06-Ubuntu安装MySQL.mp4 [99.4 MB]
01-回顾.mp4 [102.5 MB]
05-Python连接MySQL之增删改功能.mp4 [34.5 MB]
04-Python连接MySQL之查询功能.mp4 [47.7 MB]
11-Docker案例之编写Dockerfile和docler compose文件.mp4 [93.6 MB]
14-Ubuntu测试Python连接MySQL.mp4 [99.4 MB]
02-Python连接MySQL之下载依赖包.mp4 [17.9 MB]
10-Docker基础案例之测试MySQL.mp4 [86.3 MB]
09-Docker安装和配置.mp4 [73.9 MB]
📁 3.代码
📁 docker-python-mysql
Dockerfile [552.0 B]
docker-compose(linux).yml [3.3 KB]
test_mysql.py [733.0 B]
test_mysql1.py [2.4 KB]
docker-compose(windows).yml [3.2 KB]
mysql-8.0.45.tar [235.9 MB]
python-app.tar [405.0 MB]
📁 2.资料
镜像源.txt [350.0 B]
wsl.2.6.3.0.x64.msi [235.7 MB]
Docker Desktop Installer.exe [598.5 MB]适合人群
- 后端开发新手
- Web API开发者
- FastAPI框架爱好者
学习收获
掌握FastAPI框架
熟练使用SQLAlchemy
构建高性能Web API
祝您学习愉快！
学有所成，前程似锦！