🚀 Chatbot with HTML Structured Formatted (Flask + Bootstrap)

A full-stack, production-grade Question Answering Chatbot built using Gemini API, Python Flask, and Bootstrap. This app mimics the ChatGPT-style UI by rendering structured Markdown responses from Gemini, including code blocks, headers, and lists.

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📸 Demo Preview

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🔧 Tech Stack

Layer	Technology
Frontend	HTML, CSS, Bootstrap 5, Vanilla JS
Backend	Python, Flask
AI/LLM	Google Gemini Pro (via google-generativeai)
API Key Mgmt	python-dotenv
Markdown Rendering	markdown Python library

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⚙️ Features

• ✅ ChatGPT-style Markdown rendering (code blocks, headings, lists)
• ✅ Gemini-powered accurate responses using gemini-pro
• ✅ Clean Bootstrap UI with responsive design
• ✅ JavaScript-powered asynchronous chat (no page reload)
• ✅ Error-handling for broken requests
• ✅ Easily extensible to include login, memory, tools, etc.

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📁 Project Structure

gemini_chatbot/
├── app.py                     # Flask backend
├── .env                       # API keys (not shared)
├── requirements.txt           # Dependencies
├── templates/
│   └── index.html             # Frontend UI
├── static/
│   └── style.css              # Optional custom styles

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🔑 Environment Setup

1. Clone the Repo

git clone https://github.com/<your-username>/gemini-chatbot.git
cd gemini-chatbot

2. Create .env File

GEMINI_API_KEY=your_gemini_api_key_here

🔐 Keep this file private and never share your API key publicly.

3. Install Dependencies

pip install -r requirements.txt

If you don’t have requirements.txt, manually install:

pip install flask google-generativeai markdown python-dotenv

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🚀 Run the Application

python app.py

Then visit: http://127.0.0.1:5000

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💡 Example Prompts

Prompt	Response Style
Give for loop code in Python	Code + explanation
What is a dictionary in Python?	Bullet points + example
Write HTML code for a login form	Rendered code block
Explain AI in 3 bullet points	Structured Markdown

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🛠️ Customization Ideas (Next-Level)

You can easily extend this app into:

• 🔐 User authentication system
• 💬 Persistent chat history (local DB / SQLite)
• 🧠 LangChain or Agentic AI integration
• 🧾 Export conversation to PDF or Markdown
• 🌐 Deploy on Render, Vercel, or Railway
• 📲 Mobile-responsive design

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📦 Deployment Suggestions

Platform	Status
Render.com	✅ Easy Flask deploy
Railway.app	✅ One-click deploy
Heroku (legacy)	⚠️ Deprecated
Docker	✅ Production-ready container

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📄 License

This project is licensed under the MIT License. Feel free to fork, modify, and use in commercial or educational projects. ⭐

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🤝 Contact

🔗 Developed by Md Emon Hasan 📧 Email: iconicemon01@gmail.com 💼 GitHub: Md-Emon-Hasan 📱 WhatsApp: +8801834363533

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