构建更智能的现实世界生成式人工智能系统
Building Smarter Real-World Generative Ai Systems
- 1 - Introduction
- 2 - Generative AI
- 3 - LLM
- 4 - LangChain FrameWork
- 5 - LangChain Dataflow
- 6 - Python Installation
- 7 - LangChain and LangGraph Installation
- 8 - Setting up OpenAI Account
- 9 - Setting up Jupyter notebook
- 10 - Setting API Key in Environment File
- 11 - What is Tools
- 12 - Types of Tools
- 13 - Builtin Tools
- 14 - Components of a Tool
- 15 - Custom Tools
- 16 - Agents
- 17 - ReAct Agent
- 18 - ReAct Agent in detail
- 19 - Building ReAct Agent
- 20 - Disadvantages of Agent
- 21 - What is LangGraph
- 22 - Key Features of LangGraph
- 23 - LangGraph in Action A RealWorld Example
- 24 - Salvation by MultiAgent Approach
- 25 - Smarter Planning with Stateful Systems
- 26 - Optimizing Decisions with Cycles and Persistence
- 27 - Interactive and RealTime Systems
- 28 - LangGraphs Inspiration
- 29 - Introduction to LangGraph World
- 30 - Understanding State in LangGraph
- 31 - State Definition in Python
- 32 - Node Activation and Execution
- 33 - Understanding Edges Connecting the Dots
- 34 - Exploring State Graph Managing Communication and Workflow
- 35 - Enhancing AI Interactions with Message Graph
- 36 - First Graph Preview
- 37 - Building a basic Chatbot
- 38 - Enhancing Chatbot with Tools
- 39 - Introduction to RAG
- 40 - RAG Pipeline
- 41 - Components of RAG
- 42 - Simple RAG App Overview
- 43 - Building a Retriever
- 44 - Agentic RAG App Overview
- 45 - Building Agent Node
- 46 - Buildng Generate Node
- 47 - Constructing Graph
- 48 - Visualize the RAG Graph
- 49 - Experiment the RAG
- 50 - Conclusion