I just published a new tutorial on building a full RAG (Retrieval-Augmented Generation) pipeline using LangChain 0.3+. This guide walks through:
- PDF loading & parsing
- Chunking with RecursiveCharacterTextSplitter
- Embedding generation
- FAISS vector storage
- RAG pipeline construction
- Streamlit chatbot UI
- Source citations
Optional advanced features (re-ranking, document upload, memory, etc.)
If you're looking to build an AI assistant trained on your own documents, this is a complete end-to-end example.
👉 Read the full tutorial:
https://www.djamware.com/post/6927fb6c0260e42c0dc8eb48/train-a-custom-ai-model-on-your-pdf-documents-using-langchain
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