AI Chat Assistant

A modern, web-based chatbot interface powered by OpenAI's GPT-3.5-turbo model.

Features

• 🎨 Modern UI: Clean, responsive design with TailwindCSS
• 💬 Real-time Chat: Instant messaging with AI assistant
• 📚 Document Knowledge Base: Upload and process PDFs, DOCX, and TXT files
• 🔍 Smart Document Search: AI-powered document retrieval and context
• 🔄 Chat History: Maintains conversation context
• 🧹 Clear Chat: Reset conversation history
• ♿ Accessible: Built with accessibility features
• 📱 Mobile Responsive: Works on all device sizes
• ⚡ Fast: Optimized for performance with vector database

Setup Instructions

1. Install Dependencies

pip install -r requirements.txt

2. Configure OpenAI API Key

Set your OpenAI API key as an environment variable:

export OPENAI_API_KEY="your-api-key-here"

Or create a .env file in the project root:

OPENAI_API_KEY=your-api-key-here

3. Run the Application

python main.py

The application will be available at http://localhost:5000

Usage

1. Upload Documents: Click "📄 Upload Docs" to add PDFs, DOCX, or TXT files to your knowledge base
2. Start a Conversation: Type your message in the text area and press Enter or click Send
3. Ask About Documents: The AI will automatically search your documents and provide relevant answers
4. Keyboard Shortcuts: Use Ctrl+Enter to send messages quickly
5. Clear Chat: Click the "Clear Chat" button to reset the conversation
6. Document Management: View your knowledge base summary in the document upload section

API Endpoints

• GET / - Main chat interface
• POST /api/chat - Send message to AI assistant
• POST /api/clear - Clear conversation history
• POST /api/documents/upload - Upload and process documents
• POST /api/documents/process - Process all documents in directory
• GET /api/documents/summary - Get document knowledge base summary

Technical Details

• Backend: Flask (Python)
• Frontend: HTML, TailwindCSS, Alpine.js
• AI Model: OpenAI GPT-3.5-turbo
• Document Processing: PyPDF2, python-docx, sentence-transformers
• Vector Database: ChromaDB for semantic search
• Styling: TailwindCSS utility classes
• Accessibility: ARIA labels, keyboard navigation, focus management

File Structure

agentchatbot/
├── main.py                 # Flask application
├── document_processor.py   # Document processing and vector search
├── requirements.txt        # Python dependencies
├── README.md              # This file
├── documents/             # Upload your PDFs, DOCX, TXT files here
├── processed/             # Processed document data and vector database
└── templates/
    └── chat.html          # Chat interface template

Security Notes

• Never commit your API key to version control
• Use environment variables for sensitive configuration
• Consider rate limiting for production use

Troubleshooting

• API Key Error: Ensure your OpenAI API key is set correctly
• Port Already in Use: Change the port in main.py or kill the existing process
• Module Not Found: Run pip install -r requirements.txt

License

This project is open source and available under the MIT License. # agentchatbot