This repo contains the code and projects I'm building while learning LangChain and RAG (Retrieval Augmented Generation) from CampusX.
I'm learning how to build AI applications using LangChain, following CampusX's "Generative AI using LangChain" playlist. Topics covered in this journey:
- LangChain basics, architecture and components
- Models (LLMs, Chat Models, Embedded Models)
- Prompts and Prompt Templates
- Structured Output
- Output Parsers
- Chains
- Runnables
- Document Loaders
- Text Splitters
- Vector Stores (FAISS, Chroma, etc.)
- Retrievers
- Semantic Search
- Retrieval Augmented Generation (RAG)
- Tool Calling
- Building end-to-end AI Agents
I'll be uploading the code and mini-projects I build during the course, organized by topic as I go through the learning journey.
This repo is mainly for my own learning and practice. It's a record of what I've built so I can track my progress and revisit concepts later.
Learning from CampusX's LangChain and RAG course.
Playlist: Generative AI using LangChain