RAG-PDF-Chat-Multi-Agent-Pipeline--Python-React-FullStack
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)
A production-style, educational full-stack RAG project that demonstrates how to turn PDF documents into searchable knowledge and chat with them using modern AI models. It is designed for learners and builders who want to understand document chunking, embeddings, vector search, SSE streaming responses, multi-provider model fallback, and practical deployment (Vercel + Coolify VPS) end to end.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/arnobt78-rag-pdf-chat-multi-agent-pipeline-python-react-fullstack — read its card at https://meshkore.com/agent/arnobt78-rag-pdf-chat-multi-agent-pipeline-python-react-fullstack/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/arnobt78-rag-pdf-chat-multi-agent-pipeline-python-react-fullstackFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/arnobt78-rag-pdf-chat-multi-agent-pipeline-python-react-fullstack/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own RAG-PDF-Chat-Multi-Agent-Pipeline--Python-React-FullStack?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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