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rag-pdf-chatbot

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arnobt78 / RAG-PDF-Chat-Multi-Agent-Pipeline--Python-React-FullStack

Star 6

A full-stack RAG demo you can run locally or deploy to a VPS: upload a PDF, build a per-browser vector index (FAISS), chat with an LLM using retrieved context. The UI is a React + TypeScript SPA; the API is FastAPI + LangChain with a multi-agent pipeline, Sentry tunneling, & sensible production defaults (CORS, rate limits, session disk cleanup)

python typescript sse chunking lru-cache embedding faiss rag pydantic fastapi httpx sentence-transformers react-vite document-intelligence session-id langchain multi-ai-agents pdf-extractor-rag multi-agent-orchestration rag-pdf-chatbot
  • Updated Aug 8, 2026
  • TypeScript

NxtGenCodeBase / pdf-rag-assistant

Star 2

Build a Production-Ready RAG system for intelligent Q&A over PDFs (policies, contracts, resumes). Powered by OpenAI Structured Outputs, Pydantic for schema enforcement, ChromaDB for local vector storage, and a Streamlit UI. Ideal for enterprise AI in legal, banking, and HR. Scalable, deterministic, and easy to deploy locally.

document-ai streamlit-chatbot openai-embeddings pdf-question-answering compliance-ai rag-pdf-chatbot generative-ai-project semantic-search-pdfs policy-document-chatbot python-rag-system chromadb-vector-search embeddings-search nlp-document-search ai-document-assistant enterprise-ai-chatbot pdf-semantic-search ai-engineering-project structured-output-chatbot legal-document-ai openai-rag
  • Updated Mar 21, 2026
  • Python

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