Bookshelf-QABot
Multi-model knowledge assistant/QA-Bot based on Langchain, leveraging LLMs, RAG, FastAPI and Gradio
Welcome to Bookshelf-QABot, it is a Personal Knowledge Base Assistant Project, a RAG solution designed to streamline your access to vast amounts of information quickly and accurately using the power of large language models. This versatile tool is perfect for researchers, business owners, and anyone in need of efficient information management. Its scalability makes it ideal for businesses looking to enhance their customer service capabilities, providing quick and accurate responses to customer inquiries.
⚡ 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/zhang-shizhe-bookshelf-qabot — read its card at https://meshkore.com/agent/zhang-shizhe-bookshelf-qabot/.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/zhang-shizhe-bookshelf-qabotFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/zhang-shizhe-bookshelf-qabot/.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 Bookshelf-QABot?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.