chatbot
A WhatsApp chatbot for real estate inquiries, built using Twilio API, Flask, and a BERT intent classifier. It uses LangChain and RAG for managing context and delivering accurate property information, automating client interactions while easing the workload for agents.
This project is a sophisticated chatbot designed to interact with users via WhatsApp, providing property information and handling user inquiries for a Latin American real estate company. The chatbot operates in Spanish, catering to the target audience's language needs. It uses a combination of a BERT-based intent classifier and a Language Learning Model (LLM) to offer accurate and contextually aware responses.
⚡ 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/juancarlos285-chatbot — read its card at https://meshkore.com/agent/juancarlos285-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/juancarlos285-chatbotFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/juancarlos285-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 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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.