Building a Privacy-First RAG Pipeline with LangChain and Local LLMs

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Building a Privacy-First RAG Pipeline with LangChain and Local LLMs

A code-heavy tutorial on building a ‘Chat with your PDF’ app that never touches the internet. Uses widely available open-source tools.

Key Sections:
1. **Architecture:** Ingestion -> Embedding -> Vector Store -> Retrieval -> Generation.
2. **The Stack:** LangChain, Ollama (Llama 3), ChromaDB or pgvector, Nomad/local embeddings.
3. **Code Implementation:** Python implementation steps. Handling document parsing.
4. **Optimization:** Improving retrieval context window usage.
5. **UI Layer:** Quickly adding a Streamlit interface.

**Internal Linking Strategy:** Link to Pillar. Link to ‘Ollama vs vLLM’.

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Building a Privacy-First RAG Pipeline with LangChain and Local LLMs
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