RAG Pipeline with LangChain and OpenAI
Python · LangChain · OpenAI · Vector Search · Jupyter
View source →Overview
A hands-on RAG implementation covering the full retrieval-augmented generation loop:
- Chunking — splitting source documents with overlap strategies
- Embedding — vectorizing chunks for semantic search
- Retrieval — similarity search against the vector store
- Generation — grounding LLM responses in retrieved context
Related writing: my RAG evaluation piece (“Text Summarization Evaluation Paradox”) explores how evaluation methods hit the same token-limit constraints as summarization itself.