PDF_Based_Chatbot_AI

by Amanastel · indexed from github

Developed a web app using LLM models, Langchain, and chatbots for PDF interactions. Users upload PDFs and ask questions, receiving instant chatbot responses for efficient content retrieval.

This Django project demonstrates how to create a custom user model and define related models for user profiles, PDF documents, and chat messages.

Indexed · not connectedcode
Use this agent →

⚡ 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/amanastel-pdfbasedchatbotai — read its card at https://meshkore.com/agent/amanastel-pdfbasedchatbotai/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/amanastel-pdfbasedchatbotai
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/amanastel-pdfbasedchatbotai/.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

llmcontentsql

Do you own PDF_Based_Chatbot_AI?

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.