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A market prediction app
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FinancePython · JavaScriptGitHub @souravdas090300OnlineOwner unconfirmed
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AI-powered market prediction platform with advanced authentication, role-based access control, and comprehensive market analysis tools.
Market Prediction
• Automatic Mode: Combines technical indicators, candlestick patterns, ML models, and news sentiment
• Material Mode: Analyze your own news, reports, or notes about assets
• Multi-Market Support: Stocks, crypto, forex, and commodities
• Real-time Analysis: Live quotes, charts, and predictions
• Advanced Analytics: Backtesting, risk management, strategy optimizationRead the full README ↗AI-powered market prediction platform with advanced authentication, role-based access control, and comprehensive market analysis tools.
# Clone the repository
git clone https://github.com/souravdas090300/market-predictor.git
cd market-predictor
# Install Python dependencies
pip install -r requirements.txt
# Run development server
python scripts/run_dev.py
cd frontend
# Install dependencies
npm install
# Run development server
npm run dev
Admin User:
adminadmin12345superuserDemo User:
demodemo12345user| Role | Dashboard Access | Admin Access | API Access |
|---|---|---|---|
user | ✅ | ❌ | Public APIs |
admin | ✅ | ✅ | Admin APIs |
superuser | ✅ | ✅ | All APIs |
POST /api/auth/register - User registrationPOST /api/auth/login - User login (returns role)POST /api/auth/refresh - Refresh access tokenGET /api/auth/me - Get current user infoPOST /api/auth/api-key - Create API keyGET /api/auth/api-keys - List API keysDELETE /api/auth/api-key/{key_id} - Revoke API keyGET /api/watchlist - Get watchlistGET /api/signal/{symbol} - Get signal for symbolGET /api/quote/{symbol} - Get live quoteGET /api/quotes - Get multiple quotesGET /api/assets/all - Get all assetsGET /api/predictions/assets - Get assets listGET /api/predictions/assets/{symbol}/predictions - Get predictionsPOST /api/material - Analyze text materialPOST /api/material-from-url - Fetch and analyze URLPOST /api/material-from-file - Upload and analyze filePOST /api/admin/auth/login - Admin loginGET /api/admin/users - List all usersPOST /api/admin/add-admin/{username} - Add admin userDELETE /api/admin/remove-admin/{username} - Remove adminPUT /api/admin/user/{username}/enable - Enable userPUT /api/admin/user/{username}/disable - Disable userGET /api/admin/stats - System statisticsPOST /api/backtest/run - Run backtestPOST /api/sentiment/advanced - Advanced sentiment analysisPOST /api/risk/calculate - Calculate risk metricsPOST /api/strategy/optimize - Optimize strategyPOST /api/portfolio/analyze - Analyze portfolio/ - Landing page/auth/login - Login page/auth/signup - Registration page/dashboard - User dashboard (requires login)/admin - Admin dashboard (requires admin role)Frontend (Vercel):
cd frontend
npm run build
vercel deploy
Backend (Railway):
# Railway auto-deploys from GitHub
# Ensure railway.json is configured
railway up
Frontend (.env.local):
NEXT_PUBLIC_API_URL=https://your-railway-app.up.railway.app
NEXT_PUBLIC_APP_URL=https://your-vercel-app.vercel.app
Backend (.env):
SECRET_KEY=your-secret-key-here
CORS_ORIGINS=https://your-vercel-app.vercel.app,http://localhost:3000
docker build -t market-predictor .
docker run -p 8000:8000 market-predictor
pytest -q
# Test market prediction
python -m scripts.cli AAPL BTC-USD EURUSD=X
# Test signal history
python -m scripts.cli history --symbol AAPL
# Test portfolio metrics
python -m scripts.cli portfolio AAPL,BTC-USD
# Test login
curl -X POST http://localhost:8000/api/auth/login \
-H "Content-Type: application/json" \
-d '{"username":"admin","password":"admin12345"}'
# Test market signal
curl http://localhost:8000/api/signal/AAPL
Out of the box: shares (AAPL, MSFT, NVDA, S&P 500), crypto (BTC, ETH), forex (EUR/USD, GBP/USD) and commodities (gold, silver, WTI oil, natural gas, copper).
Any Yahoo Finance symbol works:
symbol or SYMBOL = share (e.g. TSLA, NVDA, ^GSPC)symbol-USD = crypto (e.g. SOL-USD, ETH-USD)symbol=X = forex pair (e.g. EURUSD=X, GBPUSD=X)symbol=F = commodity futures (e.g. GC=F for gold, CL=F for oil)Edit app/core/config.py to customize:
Combines:
Lets you analyze your own text material:
# Development mode with auto-reload
python scripts/run_dev.py
# Production mode locally
python scripts/run_prod.py
cd frontend
npm run dev
# Run tests
pytest -q
# Linting (if configured)
flake8 app/
This project is licensed under the MIT License.
For issues and questions:
Built with ❤️ using Next.js, FastAPI, and modern ML techniques