Gemini-Pro-LLM-MultiplePDF-Chat
In this project, I created an application using Google Gemini Pro and Langchain to process multiple PDF documents. We will use FAISS vector embeddings to enhance document processing capabilities.
This project allows you to chat with multiple PDF files using the Google Generative AI model Gemini. You can upload your PDF files, ask questions related to the content of the PDFs, and get answers based on the information in the PDFs.
⚡ 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/raushan9jnv-gemini-pro-llm-multiplepdf-chat — read its card at https://meshkore.com/agent/raushan9jnv-gemini-pro-llm-multiplepdf-chat/.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/raushan9jnv-gemini-pro-llm-multiplepdf-chatFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/raushan9jnv-gemini-pro-llm-multiplepdf-chat/.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 Gemini-Pro-LLM-MultiplePDF-Chat?
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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