TradeXAI - AI Financial Copilot

A complete end-to-end web application that combines Generative AI and Agentic AI to help users analyze stocks, manage investments, and make intelligent financial decisions.

🎯 Interactive Feature Pages

1. AI Assistant (/ai-assistant)

• Full conversational AI chatbot with natural language understanding
• Multi-agent system for comprehensive financial analysis
• Real-time responses with explainable AI reasoning
• Quick action buttons for common queries
• Chat history with timestamps

2. Stock Analysis (/stock-analysis)

• User input: Stock symbol + time period
• Real-time price data and historical charts
• Technical indicators (SMA 20, SMA 50, P/E ratio)
• 52-week high/low, volume, market cap
• Trend analysis (bullish/bearish)

3. Price Prediction (/price-prediction)

• User input: Stock symbol
• 7-day ML-powered predictions with confidence scores
• Historical vs predicted price charts
• Model accuracy metrics
• Detailed prediction table

4. News Sentiment (/news-sentiment)

• User input: Stock symbol
• Latest financial news articles
• AI-powered sentiment analysis (positive/negative/neutral)
• Sentiment score visualization
• Article summaries with sources

5. Portfolio Creator (/portfolio-creator)

• User input: Budget + risk level (low/medium/high)
• AI-optimized portfolio allocation
• Interactive pie charts
• Stock breakdown with shares and amounts
• Expected returns and risk analysis
• Personalized recommendations

6. Dashboard (/)

• Overview of all features in one place
• Live market data
• Quick access to all tools

Features

🤖 Multi-Agent Architecture

• Data Agent: Fetches real-time and historical stock data from Yahoo Finance
• News Agent: Analyzes news sentiment (positive/negative/neutral)
• Prediction Agent: ML-powered price forecasting using LSTM/regression
• Decision Agent: Aggregates all data to generate final recommendations

💬 Conversational AI Chatbot

• Natural language queries: "Which stocks should I buy?", "Why is TCS falling?"
• LLM-powered intent detection and task decomposition
• Explainable AI with reasoning for every recommendation

📊 Premium Dark Mode Dashboard

• Real-time stock market data with interactive charts
• Price prediction visualization (predicted vs actual)
• News sentiment analysis with visual indicators
• Portfolio management with allocation charts
• Autonomous alerts and notifications

📈 Advanced Visualizations

• Interactive line charts (stock trends)
• Area charts with gradients
• Pie charts (portfolio allocation)
• Candlestick charts support
• Real-time updates

Tech Stack

Backend

• Framework: FastAPI
• AI/ML: LangChain, OpenAI API, scikit-learn
• Data: Yahoo Finance API, NewsAPI
• Sentiment Analysis: TextBlob

Frontend

• Framework: React 18 with Vite
• Styling: Tailwind CSS
• Charts: Recharts
• Animations: Framer Motion
• Icons: Lucide React
• Notifications: React Hot Toast

Installation

Prerequisites

• Python 3.9+
• Node.js 18+
• npm or yarn

Backend Setup

1. Navigate to backend directory:

cd backend

2. Create virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Create .env file:

cp .env.example .env

5. Add your API keys to .env:

OPENAI_API_KEY=your-openai-api-key
NEWS_API_KEY=your-news-api-key

6. Run the backend:

python app.py

Backend will run on http://localhost:8000

Frontend Setup

1. Navigate to frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Run the development server:

npm run dev

Frontend will run on http://localhost:3000

Usage

1. Open your browser and navigate to http://localhost:3000
2. The dashboard will load with demo data
3. Use the chat panel to ask questions:
   • "Which stocks should I buy?"
   • "Predict AAPL price for next week"
   • "Create a portfolio with ₹50,000 budget"
   • "Why is TCS falling?"
4. Click on stock symbols to view detailed analysis
5. Explore portfolio allocation and performance charts
6. Check alerts for buy/sell opportunities

API Endpoints

Chat

• POST /api/chat - Send message to AI assistant

Stocks

• GET /api/stocks/{symbol} - Get stock data
• GET /api/stocks/{symbol}/prediction - Get price predictions

News

• GET /api/news/{symbol} - Get news with sentiment analysis

Portfolio

• POST /api/portfolio/create - Create optimized portfolio
• GET /api/portfolio/{user_id} - Get user portfolio

Alerts

• GET /api/alerts/{user_id} - Get user alerts

Market

• GET /api/market/overview - Get market overview

Project Structure

ai-financial-copilot/
├── backend/
│   ├── agents/
│   │   ├── data_agent.py          # Stock data fetching
│   │   ├── news_agent.py          # News sentiment analysis
│   │   ├── prediction_agent.py    # Price prediction ML
│   │   ├── decision_agent.py      # Final recommendations
│   │   └── orchestrator.py        # Multi-agent coordination
│   ├── services/
│   │   ├── stock_service.py
│   │   ├── news_service.py
│   │   ├── prediction_service.py
│   │   └── portfolio_service.py
│   ├── database/
│   │   └── db.py                  # Simple file-based DB
│   ├── app.py                     # FastAPI application
│   ├── requirements.txt
│   └── .env.example
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── Header.jsx
│   │   │   ├── ChatPanel.jsx
│   │   │   ├── StockDashboard.jsx
│   │   │   ├── PredictionPanel.jsx
│   │   │   ├── NewsPanel.jsx
│   │   │   ├── PortfolioPanel.jsx
│   │   │   └── AlertsPanel.jsx
│   │   ├── services/
│   │   │   └── api.js
│   │   ├── App.jsx
│   │   ├── main.jsx
│   │   └── index.css
│   ├── package.json
│   ├── vite.config.js
│   ├── tailwind.config.js
│   └── index.html
└── README.md

Features in Detail

Explainable AI

Every recommendation includes:

• Technical analysis signals
• Sentiment analysis results
• Prediction model insights
• Risk assessment
• Confidence levels

User Memory

• Stores user preferences (risk level, budget)
• Personalizes responses based on history
• Remembers favorite stocks

Autonomous Alerts

• Price change notifications
• Buy/sell opportunity detection
• News-based alerts
• Portfolio performance updates

Demo Data

The application includes fallback demo data for:

• Stock prices and historical data
• News articles with sentiment
• Price predictions
• Portfolio allocations

This ensures the app works even without API keys for demonstration purposes.

API Keys

OpenAI API

Get your key from: https://platform.openai.com/api-keys

NewsAPI

Get your key from: https://newsapi.org/register

Note: The app works with demo data if API keys are not provided.

Development

Backend Development

cd backend
uvicorn app:app --reload --host 0.0.0.0 --port 8000

Frontend Development

cd frontend
npm run dev

Build for Production

cd frontend
npm run build

Troubleshooting

Backend Issues

• Ensure Python 3.9+ is installed
• Check if all dependencies are installed: pip list
• Verify API keys in .env file
• Check if port 8000 is available

Frontend Issues

• Clear node_modules and reinstall: rm -rf node_modules && npm install
• Check if port 3000 is available
• Verify backend is running on port 8000

CORS Issues

• Backend includes CORS middleware for localhost:3000
• If using different port, update CORS settings in backend/app.py

Future Enhancements

• Real-time WebSocket updates
• Advanced ML models (LSTM, Transformer)
• Social trading features
• Mobile app (React Native)
• Advanced portfolio optimization
• Backtesting capabilities
• Multi-currency support
• Integration with trading platforms

License

MIT License - feel free to use this project for learning and development.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and questions, please open an issue on GitHub.