Gemini-RAG
Chatbot that uses Gemini-1.0-Pro to answer questions, with memory by using LangChain. Also, it's enriched by RAG and deployed in Dialogflow
This project is part of the GDE's Gemini Sprint. The idea was to develop a chatbot that uses Gemini-1.0-Pro to answer questions, and has memory of past interactions by using LangChain. Also, it has its context enriched by RAG (Retrieval Augmented Generation). This memory obtained through LangChain allows the chatbot to remember past interactions independently of Dialogflow $session.params. RAG document is vectorized with gecko-embeddings, chunked and a FAISS index is created. Later, a TOP-K result of embeddings similarity is retrieved to answer the questions, along with the chat history.
⚡ 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/rubenszimbres-gemini-rag — read its card at https://meshkore.com/agent/rubenszimbres-gemini-rag/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/rubenszimbres-gemini-ragFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/rubenszimbres-gemini-rag/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own Gemini-RAG?
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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