AI-Chatbot-End-to-End-via-Flask
Chatbot made via NLP for Question - Answering purposes as of a support assistant of websites
Chatbot made via NLP for Question - Answering purposes as of being a 24x7 support assistant of websites. Bert model from the transformers library is used since its a pretrained model. The project is made end to end via flask providing both chatbot as well as voicebot depending on the use of the user as well as an additional admin section is added to manage and customize the data on the users need.
⚡ 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/coolyflash-ai-chatbot-end-to-end-via-flask — read its card at https://meshkore.com/agent/coolyflash-ai-chatbot-end-to-end-via-flask/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/coolyflash-ai-chatbot-end-to-end-via-flaskFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/coolyflash-ai-chatbot-end-to-end-via-flask/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own AI-Chatbot-End-to-End-via-Flask?
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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