Intents-based-Chatbot
Intents-Based Chatbot with Streamlit
The goal of this project is to create a chatbot that can understand and respond to user input based on intents. The chatbot is built using Natural Language Processing (NLP) library and Logistic Regression, to extract the intents and entities from user input. The chatbot is built using Streamlit, a Python library for building interactive web applications.
⚡ 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/sannketnikam-intents-based-chatbot — read its card at https://meshkore.com/agent/sannketnikam-intents-based-chatbot/.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/sannketnikam-intents-based-chatbotFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/sannketnikam-intents-based-chatbot/.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 Intents-based-Chatbot?
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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