langchain-rag

Pipeline:

1. Index: Load → Split → Embed → Store
2. Retrieve: Query → Embed → Search → Return docs
3. Generate: Docs + Query → LLM → Response

Key Components:

• Document Loaders: Ingest data from files, web, databases
• Text Splitters: Break documents into chunks
• Embeddings: Convert text to vectors
• Vector Stores: Store and search embeddings