intent_based_chatbot
An intent-based chatbot in python with tflearn and TensorFlow. It can be trained for a specific purpose and works well within that specific scope.
An intent-based chatbot in python with tflearn and tensorflow. It can be trained for a specific purpose and works well within that specific scope. The file can be updated based on purpose and even if statement pattern given from the user varies from the patterns on which model is trained, the model still will give accurate results. The model gives probabilities for different tags based on the input and then appropriate response corresponding to that tag is returned. That response is also piped out with pyttx3 which is a text-to-speech conversion library.
⚡ 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/adiprogrammer7-intentbasedchatbot — read its card at https://meshkore.com/agent/adiprogrammer7-intentbasedchatbot/.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/adiprogrammer7-intentbasedchatbotFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/adiprogrammer7-intentbasedchatbot/.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 intent_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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