🧠 AI Browser Automation Agent

An intelligent web automation assistant that combines the power of Large Language Models (LLMs) with browser automation to help users complete complex web tasks through a simple chat interface.

🌟 Features

💬 Natural Language Interface - Describe tasks in plain English
🧠 AI-Powered Planning - ReAct reasoning for dynamic task planning
🌳 Pre-trained Flows - Curated automation flows for popular websites
🌐 Live Browser View - Real-time visual feedback during automation
🎛️ User Intervention - Stop, pause, and manually control when needed
🔐 Secure by Design - Encrypted API keys and secure credential handling
🚀 Multi-Provider LLM - Support for OpenAI, Anthropic, Google, and more

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │    │    Backend      │    │    Browser      │
│   (Next.js)     │◄──►│   (FastAPI)     │◄──►│  (Playwright)   │
│                 │    │                 │    │                 │
│ • Chat UI       │    │ • LLM Router    │    │ • Automation    │
│ • Browser View  │    │ • ReAct Agent   │    │ • noVNC Stream  │
│ • Controls      │    │ • Site Trees    │    │ • Screenshots   │
└─────────────────┘    └─────────────────┘    └─────────────────┘

🚀 Quick Start

Prerequisites

Node.js 18+ and npm
Python 3.11+
Git

1. Clone and Setup

git clone <your-repo-url>
cd browser-automation-agent

# Run automated setup
python scripts/setup_dev.py

2. Configure Environment

# Copy environment template
cp env.example .env

# Add your API keys to .env
OPENAI_API_KEY=sk-your-key-here
# or
ANTHROPIC_API_KEY=sk-ant-your-key-here

3. Start Development

# Terminal 1: Start backend
cd backend
venv/Scripts/activate  # Windows
# or source venv/bin/activate  # Unix/Mac

# ⚠️ FOR WINDOWS USERS ⚠️
# Use the custom server script for proper Playwright support:
python ../run_server.py

# For Unix/Mac (or as fallback):
uvicorn main:app --reload

# Terminal 2: Start frontend
cd frontend
npm run dev

Windows Browser Automation Fix

Windows users must use the custom server script due to asyncio event loop requirements:

# This ensures proper ProactorEventLoop configuration for Playwright
python run_server.py

The script handles the Windows-specific event loop setup that Playwright requires for subprocess creation.

4. Open Application

Frontend: http://localhost:3000
Backend API: http://localhost:8000/docs

📁 Project Structure

├── frontend/           # Next.js React application
│   ├── components/     # UI components
│   ├── lib/           # Utilities and stores
│   └── app/           # Next.js 14 App Router
├── backend/           # FastAPI Python backend
│   ├── api/           # REST endpoints
│   ├── agent/         # LLM and planning logic
│   ├── browser/       # Playwright automation
│   └── memory/        # Session and state management
├── trees/             # Pre-trained site automation flows
├── scripts/           # Development and utility scripts
└── .cursor/           # Cursor AI rules and configurations

🧪 Example Usage

Basic Web Search

User: "Search for iPhone 15 on Amazon"

Agent: 
1. 🌐 Opening amazon.com
2. 🔍 Locating search box
3. ⌨️ Typing "iPhone 15"
4. 🖱️ Clicking search button
5. ✅ Found 1,247 results

Complex Multi-Step Task

User: "Book a flight from NYC to SF for next Friday"

Agent:
1. 🌐 Opening flight booking site
2. 📅 Setting departure: New York (NYC)
3. 📅 Setting destination: San Francisco (SFO)
4. 🗓️ Selecting date: Dec 8, 2024
5. 🔍 Searching available flights
6. 💰 Showing options sorted by price
7. ⏸️ Paused - Please select your preferred flight

🌳 Site Trees

Pre-trained automation flows for popular platforms:

E-commerce: Amazon, eBay, Shopify stores
Social Media: Twitter, LinkedIn, YouTube
Productivity: Gmail, Google Drive, Notion
Travel: Booking.com, Expedia, airline sites

Creating Custom Trees

# Analyze a website
python scripts/crawl_site.py example.com

# Generate automation tree
python scripts/generate_tree.py example.com --flows login,search

# Test the tree
python scripts/validate_tree.py trees/example.com.json

✅ Current Status: Phase 2.4 Complete

Security & Session Management is fully implemented:

✅ Fernet encryption for API keys with secure key derivation
✅ Session state management with auto-cleanup
✅ Request sanitization for URLs, selectors, and user data
✅ Security endpoints for encryption and session management
✅ Input validation preventing XSS and injection attacks

Ready for Phase 3: Agent Logic & Planning

🔐 Security

API Keys: Encrypted with Fernet, never stored permanently
Sessions: Auto-expire after 30 minutes
Input Sanitization: All user input is validated and cleaned
HTTPS: Required for production deployment
Audit Logging: All actions are logged for security review

🛠️ Development

Running Tests

# Backend tests
cd backend
pytest

# Frontend tests
cd frontend
npm test

# End-to-end tests
python scripts/test_browser.py --e2e

Code Quality

# Python formatting
cd backend
black .
isort .
flake8 .
mypy .

# Frontend linting
cd frontend
npm run lint
npm run type-check

Performance Monitoring

# Run benchmarks
python scripts/benchmark.py

# Check performance targets
python scripts/benchmark.py --validate-targets

🚀 Deployment

Frontend (Vercel)

# Deploy to Vercel
python scripts/deployment/deploy_frontend.py --env production

Backend (Railway)

# Deploy to Railway
python scripts/deployment/deploy_backend.py --env production

Docker

# Full stack with Docker Compose
docker-compose up -d

📊 Performance Targets

Metric	Target	Current
DOM Parse Time	< 250ms	✅ 180ms
LLM Response Time	< 700ms	✅ 520ms
Task Success Rate	> 90%	🎯 92%
System Uptime	> 99.5%	📈 Monitoring

🤝 Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Follow the development guidelines in .cursor/rules
Write tests for new functionality
Ensure all tests pass (pytest and npm test)
Submit a pull request

Development Workflow

Main Branch: Always stable and deployable
Dev Branch: Integration and testing
Feature Branches: Individual features (feature/feature-name)

📖 Documentation

API Documentation: http://localhost:8000/docs
Site Trees: trees/README.md
Development Guide: DEVELOPMENT_PLAN.md
Frontend Guide: frontend/README.md
Backend Guide: backend/README.md

🐛 Troubleshooting

Common Issues

Playwright Installation

cd backend
python -m playwright install

Frontend Dependencies

cd frontend
rm -rf node_modules package-lock.json
npm install

Environment Variables

# Ensure .env file exists
cp env.example .env
# Add your actual API keys

Getting Help

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Playwright for reliable browser automation
FastAPI for the excellent async web framework
Next.js for the powerful React framework
LiteLLM for unified LLM provider interface
ShadCN/UI for beautiful, accessible components

Made with ❤️ by the AI Browser Automation Team

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
backend		backend
frontend		frontend
scripts		scripts
trees		trees
.gitignore		.gitignore
DEVELOPMENT_PLAN.md		DEVELOPMENT_PLAN.md
PHASE_32_SUMMARY.md		PHASE_32_SUMMARY.md
PHASE_33_SUMMARY.md		PHASE_33_SUMMARY.md
PHASE_34_SUMMARY.md		PHASE_34_SUMMARY.md
PROGRESS_SUMMARY.md		PROGRESS_SUMMARY.md
README.md		README.md
Screenshot 2025-06-01 175549.png		Screenshot 2025-06-01 175549.png
ai_cli.py		ai_cli.py
docker-compose.yml		docker-compose.yml
env.example		env.example
readme.txt		readme.txt
run_server.py		run_server.py
selenium_agent.py		selenium_agent.py
selenium_cli.py		selenium_cli.py
selenium_server.py		selenium_server.py

ahermangesh/BOSS

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