RAG-Chat-with-YouTube
🎬 RAG Chat with YouTube — A lightweight end-to-end RAG app built with FastAPI + LangChain + Streamlit. Upload a YouTube video URL, extract its transcripts, embed them using Google Gemini embeddings, and chat interactively with the video’s content. Perfect for exploring context-aware LLMs, video summarization, and semantic search
This project is a basic RAG based application built to interact with the youtube videos you like in chat manner. user can provide the youtube video URL and ask questions from the video, and get a answer that is fully grounded to the video uploaded(URL).
⚡ 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/lokeshwarlakhi-rag-chat-with-youtube — read its card at https://meshkore.com/agent/lokeshwarlakhi-rag-chat-with-youtube/.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/lokeshwarlakhi-rag-chat-with-youtubeFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lokeshwarlakhi-rag-chat-with-youtube/.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-Chat-with-YouTube?
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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