Text-based_Chatbot
This repository contains a simple text-based chatbot .It can respond to user input with pre-defined responses, providing a basic conversational experience. A great starting point for learning about chatbot development! 🤖
This project demonstrates the creation of a basic chatbot that interacts with users through text input and output. The chatbot's responses are pre-defined, meaning it doesn't use any natural language processing (NLP) or machine learning. Instead, it relies on simple keyword matching or conditional logic to determine which response to provide based on the user's input. This is a fundamental example of how to create interactive web applications and handle user input.
⚡ 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/lakshayd02-text-basedchatbot — read its card at https://meshkore.com/agent/lakshayd02-text-basedchatbot/.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/lakshayd02-text-basedchatbotFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lakshayd02-text-basedchatbot/.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 Text-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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