StockBotWebApp

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StockBotWebApp is a full-stack, voice-enabled trading platform I’ve always wanted to build. It pairs a Next.js frontend with an Express API and a Python FastAPI StockBot for analysis, backtesting, and real-time broker connectivity (Schwab, Alpaca). Features include the Jarvis assistant for voice interaction, secure env management via Infisical

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# Stock Bot Web Application

A comprehensive full-stack platform for automated stock trading with AI-powered assistance. The system combines modern web technologies with sophisticated trading algorithms and real-time market data integration.

## 🏗️ Architecture

The project consists of three interconnected services:

- **Frontend** – Next.js 15 with React 19 interface for users
- **Backend** – Node.js/Express API layer with MongoDB
- **StockBot** – Python FastAPI service for trading logic and AI

For a detailed walkthrough of how these components interact during training, backtesting, and live trading, see the [StockBot Trading Pipeline](docs/StockbotTradingPipeline.md) guide.

## ✨ Key Features

### 🤖 AI Assistant "Jarvis"
- Voice-enabled trading assistant with speech-to-text/text-to-speech
- Multiple AI providers (Ollama local models, HuggingFace)
- Real-time market analysis and trading recommendations
- WebSocket-based voice interaction

### 📊 Broker Integrations
- **Charles Schwab** - Full API integration with OAuth authentication
- **Alpaca Markets** - Paper and live trading support
- Real-time portfolio tracking and transaction history
- Secure credential management

### 💼 Trading Capabilities
- Multiple trading strategies (momentum, custom algorithms)
- Comprehensive backtesting engine
- Risk management with circuit breakers and exposure limits
- Paper trading simulation environment
- Real-time market data ingestion

## 🛠️ Prerequisites

### Required Software
- **Node.js** (v18 or higher) and npm
- **Python 3.8+** with pip
- **MongoDB** (local or cloud instance)
- **Infisical CLI** for secure environment management

### Optional (for AI features)
- **Ollama** for local AI models
- **CUDA-compatible GPU** for enhanced AI performance

## 🚀 Quick Start

> **Note:** Use `.bat` scripts on Windows and `.command` scripts on macOS.

### 1. Clone and Initial Setup
```bash
git clone https://github.com/BilliamsFluster/StockBotWebApp.git
cd StockBotWebApp
```

### 2. Install Infisical CLI
```bash
# Windows (using npm)
npm install -g @infisical/cli

# macOS (using Homebrew)
brew install infisical/get-cli/infisical

# Linux
curl -1sLf 'https://dl.cloudsmith.io/public/infisical/infisical-cli/setup.deb.sh' | sudo -E bash
sudo apt-get update && sudo apt-get install infisical
```

### 3. Automated Setup
```bash
# Windows
start-dev-all.bat

# macOS
./start-dev-all.command
```

### 4. Manual Setup (All Platforms)

#### Backend Setup
```bash
cd backend
npm install
infisical init  # Follow prompts to connect to your Infisical project
npm run dev     # Starts on port 5001
```

#### Frontend Setup
```bash
cd frontend
npm install
infisical init  # Connect to Infisical project
npm run dev     # Starts on https://localhost:3000
```

#### StockBot Python Service
```bash
cd stockbot

# Windows
setup_venv.bat      # One-time setup
run_dev.bat         # Start the service

# macOS
./setup_venv.command  # One-time setup
./run_dev.command     # Start the service

# Linux
python -m venv venv
source venv/bin/activate  # or `venv/bin/activate.fish` for fish shell
pip install --upgrade pip
pip install -r requirements.txt
uvicorn server:app --reload --host 0.0.0.0 --port 5002
```

## 🔧 Configuration

### Environment Variables (Infisical)

The application uses Infisical for secure environment management. You'll need to configure the following variables in Infisical:

#### Backend (.env)
Variables below are stored in Infisical and loaded by modules in [`backend/config`](backend/config).

```bash
# URLs & Ports
BACKEND_URL=https://localhost:5001        # Public URL for logging and callbacks
BACKEND_PORT=5001                         # Port the Express server listens on
STOCKBOT_URL=http://localhost:5002        # Python StockBot service
FRONTEND_URL=https://localhost:3000       # Single allowed CORS origin
FRONTEND_URLS=https://localhost:3000      # Comma-separated list of allowed origins

# Database
MONGO_URI=mongodb://localhost:27017/stockbot  # MongoDB connection string

# Auth & Security
JWT_SECRET=change-me                     # JWT signing secret
REFRESH_SECRET=change-me-too             # Refresh token secret
MASTER_ENCRYPTION_KEY=your-master-key    # Encrypts stored broker tokens
LOG_LEVEL=info                           # pino logger level

# Schwab OAuth
SCHWAB_APP_KEY=your-schwab-app-key       # Schwab developer app key
SCHWAB_APP_SECRET=your-schwab-app-secret # Schwab developer app secret
SCHWAB_REDIRECT_URI=https://127.0.0.1    # OAuth redirect URI

# SSL (required in production)
SSL_CERT=./certs/cert.crt                # Path to SSL certificate
SSL_KEY=./certs/cert.key                 # Path to SSL private key
SSL_CA=./certs/ca.crt                    # Optional CA bundle
```

#### Frontend (.env)
```bash
# API Endpoints
NEXT_PUBLIC_BACKEND_URL=https://localhost:5001
NEXT_PUBLIC_STOCKBOT_URL=http://localhost:5002

# SSL Certificates (for HTTPS development)
SSL_CERT=./certs/cert.crt
SSL_KEY=./certs/cert.key
SSL_CA=./certs/ca.crt

# Frontend Configuration
FRONTEND_PORT=3000
FRONTEND_HOST=0.0.0.0
```

#### StockBot (.env)
```bash
# AI Configuration
OLLAMA_BASE_URL=http://localhost:11434
HUGGINGFACE_API_TOKEN=your-huggingface-token

# Database
DATABASE_URL=sqlite:///./stockbot.db

# External APIs
ALPHA_VANTAGE_API_KEY=your-alpha-vantage-key
```

### SSL Certificates Setup

The frontend runs on HTTPS for secure broker integrations. Generate certificates:

```bash
# Install mkcert (one-time setup)
npm install -g mkcert

# Create certificates
cd frontend/certs
mkcert -install
mkcert localhost 127.0.0.1 ::1

# Rename files
mv localhost+2.pem cert.crt
mv localhost+2-key.pem cert.key

#place files inside frontend/certs and backend/certs
```

### Broker API Setup

#### Charles Schwab
1. Register at [Schwab Developer Portal](https://developer.schwab.com/)
2. Create a new app with redirect URI: `https://localhost:3000/schwab/callback`
3. Add credentials to Infisical

#### Alpaca Markets
1. Sign up at [Alpaca Markets](https://alpaca.markets/)
2. Generate API keys from dashboard
3. Use paper trading URL for testing: `https://paper-api.alpaca.markets`

## 📁 Project Structure

```
StockBotWebApp/
├── backend/                 # Node.js/Express API
│   ├── controllers/         # Route handlers
│   ├── models/             # Database models
│   ├── routes/             # API routes
│   ├── config/             # Configuration files
│   └── middleware/         # Custom middleware
├── frontend/               # Next.js React application
│   ├── src/
│   │   ├── app/           # Next.js 13+ app directory
│   │   ├── components/    # React components
│   │   ├── hooks/         # Custom React hooks
│   │   ├── api/           # API client functions
│   │   └── types/         # TypeScript definitions
│   └── public/            # Static assets
└── stockbot/              # Python trading service
    ├── api/               # FastAPI routes and controllers
    ├── jarvis/            # AI assistant modules
    ├── ingestion/         # Data providers
    ├── strategy/          # Trading strategies
    ├── execution/         # Trade execution
    ├── backtest/          # Backtesting engine
    └── config/            # Configuration files
```

## 🌐 Service Endpoints

- **Frontend**: https://localhost:3000
- **Backend API**: https://localhost:5001
- **StockBot API**: http://localhost:5002
- **API Documentation**: http://localhost:5002/docs (FastAPI auto-generated)

## 🔍 Development Workflow

### Running Individual Services

```bash
# Backend only
cd backend && npm run dev

# Frontend only  
cd frontend && npm run dev

# StockBot only
cd stockbot && run_dev.bat         # Windows
cd stockbot && ./run_dev.command   # macOS
cd stockbot && source venv/bin/activate && uvicorn server:app --reload --host 0.0.0.0 --port 5002  # Linux
```

### Database Setup

```bash
# MongoDB (if running locally)
mongod --dbpath /path/to/your/db

# The application will automatically create collections on first run
```

### AI Model Setup (Optional)

```bash
# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Pull recommended models
ollama pull llama2
ollama pull codellama
```

## 🧪 Testing

```bash
# Backend tests
cd backend && npm test

# Frontend tests
cd frontend && npm test

# Python tests
cd stockbot && python -m pytest
```

## 🚨 Troubleshooting

### Common Issues

**Port Conflicts**
- Backend: Change `BACKEND_PORT` in Infisical
- Frontend: Change `FRONTEND_PORT` in Infisical
- StockBot: Modify port in `run_dev.bat`/`run_dev.command` or startup command

**SSL Certificate Issues**
```bash
# Regenerate certificates
cd frontend/certs
rm *.crt *.key
mkcert localhost 127.0.0.1 ::1
mv localhost+2.pem cert.crt
mv localhost+2-key.pem cert.key
```

**Python Dependencies**
```bash
# Clear and reinstall
cd stockbot
rm -rf venv
setup_venv.bat        # Windows
./setup_venv.command  # macOS
# or manual setup for Linux
```

**Database Connection**
- Ensure MongoDB is running
 - Check `MONGO_URI` in Infisical configuration
- Verify network connectivity

### Logs and Debugging

- **Backend logs**: Console output from `npm run dev`
- **Frontend logs**: Browser console and terminal output
- **StockBot logs**: FastAPI logs in terminal
- **Database logs**: MongoDB logs (if running locally)

## 📚 API Documentation

- **Backend API**: Available at runtime via route inspection
- **StockBot API**: Auto-generated docs at http://localhost:5002/docs
- **Frontend**: Component documentation in source files

## 📈 Walk-forward Probability Evaluation

The `stockbot.prob.walkforward` module provides a small CLI for assessing
the regime-switching model on rolling windows of historical returns. Run
the evaluation with:

```bash
python -m stockbot.prob.walkforward data.json --train 200 --test 50 --states 2
```

The command prints per-fold log-likelihoods and the average log-loss across
all folds. Input data can be supplied as JSON, CSV or plain text files.

## 🔐 Security Considerations

- All sensitive data managed through Infisical
- HTTPS enforced for frontend (required for broker OAuth)
- JWT-based authentication with secure token storage
- API rate limiting and CORS configuration
- Broker credentials encrypted at rest

StockBotWebApp

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