LLM-QnA-CHAT-BOT
This is a Generative AI powered Question and Answering app that responds to questions about your uploaded file. Here we utilize HuggingFaceEmbeddings and OpenAI gpt-3.5-turbo
The LLM Question-Answering Application offers a user-friendly interface for seamlessly extracting insights from documents. Users kickstart the process by providing their OpenAI API keys. Following this, they can upload documents in PDF, DOCX, or TXT formats. The application then begins processing, chunking, and embedding the content employing the all-MiniLM-L6-v2 model from HuggingFace. This innovative approach ensures users incur no charges for generating embeddings, with processing times averaging between 1 to 2 minutes, contingent on file size and computational resources.
⚡ 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/jacobj215-llm-qna-chat-bot — read its card at https://meshkore.com/agent/jacobj215-llm-qna-chat-bot/.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/jacobj215-llm-qna-chat-botFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/jacobj215-llm-qna-chat-bot/.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 LLM-QnA-CHAT-BOT?
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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