This repository contains the backend code for my personal chatbot, integrated into my portfolio website:
🔗 sayees.vercel.app
The chatbot is built using Flask and Gunicorn, designed to handle chat interactions and API requests from the front-end (Next.js). It is hosted on Render for fast, always-on access and is connected to the portfolio as an embedded chat widget.
🟢 API hosted at:
https://chatbot*****render.com
Used in production on my portfolio site: sayees.vercel.app
| Layer | Tools & Technologies |
|---|---|
| Server | Flask Cors |
| Framework | Gunicorn |
| Deployment | Render |
| API Format | JSON over HTTP |
| Integration | Next.js Frontend (via Fetch API) |
- Lightweight, Express-based server
- Handles POST requests from frontend
- Configured with timeout handling for long responses
- Sends back chatbot replies in real-time
- Secure CORS-enabled for cross-origin access
- Optimized for deployment on Render
- Frontend chat widget (in
sayees.vercel.app) sends a message to this API. - Backend processes the message and generates a response.
- Response is sent back to the client and shown in the UI.
- Optional: Add AI logic or database support to make it smarter.
git clone https://github.com/sayeesx/chatbot.git cd chatbot npm install node index.js
Then visit: http://localhost:5000
📬 Integration Example (Frontend) const response = await fetch("https://chatbot-...(your render link)", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ message: "Hello!" }), }); const data = await response.json(); console.log(data.reply);
🚧 To-Do / Improvements Add NLP or AI logic for smarter replies
Implement a rate limiter to protect the endpoint
Support message history and context
Deploy backup server for redundancy
🤝 Contributing Feel free to fork the repo, explore it, or improve on it. PRs are welcome if you’d like to collaborate.
📄 License MIT License. Free to use and modify.
Made with Node.js and purpose ✨ © 2025 Sayees. All rights reserved.