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docs: Add comprehensive README for Hanzo Dev AI Coding OS
- Feature documentation - Installation guide - Usage examples - Troubleshooting section - Comparison with competitors
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# Hanzo Dev - AI Coding OS
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**Chat-first REPL with Multi-Orchestrator Support**
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Version 0.3.20 brings revolutionary features to Hanzo Dev, transforming it into a complete AI Coding OS with intelligent fallback, memory persistence, and seamless orchestration.
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## 🚀 Quick Start
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```bash
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# Install
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pip install hanzo>=0.3.20
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# Run with automatic AI selection
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hanzo dev
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# Run with specific orchestrator
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hanzo dev --orchestrator gpt-4
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hanzo dev --orchestrator claude
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hanzo dev --orchestrator local:llama3.2
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```
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## ✨ Key Features
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### 1. **Chat-First Interface**
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Just type naturally! No commands needed.
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```
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> Write a REST API in FastAPI
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> Help me debug this error
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> Refactor this function for better performance
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```
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### 2. **Intelligent Fallback**
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Automatically tries all available AI options:
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- ✅ OpenAI API (GPT-4/GPT-5)
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- ✅ Anthropic API (Claude 3.5)
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- ✅ Google API (Gemini Pro)
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- ✅ OpenAI CLI (no API key needed)
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- ✅ Claude Desktop
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- ✅ Ollama (local models)
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- ✅ Free APIs (Codestral, StarCoder)
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### 3. **Memory Management**
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Persistent context like Claude Desktop:
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```
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#memory show - View current memories
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#memory add <text> - Add important context
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#memory clear - Clear memories
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#memory export - Save memories to file
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#memory context - Show AI context
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```
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### 4. **Multi-Orchestrator Support**
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| Orchestrator | Description | Requirements |
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|-------------|-------------|--------------|
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| `gpt-5` | Ultimate code AI | OPENAI_API_KEY |
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| `gpt-4` | Production OpenAI | OPENAI_API_KEY |
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| `claude` | Claude 3.5 Sonnet | ANTHROPIC_API_KEY |
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| `codex` | OpenAI CLI | OpenAI CLI installed |
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| `local:llama3.2` | Local Llama | Ollama installed |
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| `auto` | Automatic selection | Tries all available |
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### 5. **System 2 Thinking**
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Deep analysis with critic agents:
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- Code review and improvement suggestions
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- Bug detection and security analysis
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- Performance optimization recommendations
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- Best practices enforcement
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### 6. **Cost Optimization**
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90% cost reduction through intelligent routing:
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- Simple tasks → Local models ($0.00)
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- Complex tasks → Premium APIs ($0.03-$0.05)
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- Code review → Specialized models
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- Documentation → Free APIs
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## 📋 Commands
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### Chat Commands (/)
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```
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/help - Show available commands
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/status - System status
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/clear - Clear screen
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/exit - Exit REPL
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```
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### Memory Commands (#)
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```
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#memory [show] - Display memories
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#memory add <text> - Add memory
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#memory remove <id> - Remove memory
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#memory clear - Clear all memories
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#memory save - Save to disk
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#memory export [file] - Export memories
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#memory import <file> - Import memories
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#memory context - Show AI context
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#memory help - Memory help
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```
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## 🔧 Configuration
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### Environment Variables
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```bash
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# API Keys (optional - will use fallbacks)
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export OPENAI_API_KEY="sk-..."
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export ANTHROPIC_API_KEY="sk-ant-..."
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export GOOGLE_API_KEY="..."
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# Preferences
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export HANZO_DEV_MODEL="gpt-4" # Default model
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export HANZO_DEV_MEMORY="/path/to/memories" # Memory location
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```
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### Memory Persistence
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Memories are automatically saved to:
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- Project: `<workspace>/.hanzo/memory/`
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- Global: `~/.hanzo/memory/`
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### Fallback Priority
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1. API keys (fastest, most reliable)
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2. CLI tools (no API key needed)
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3. Local models (free, requires setup)
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4. Free cloud APIs (rate limited)
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## 🎯 Use Cases
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### 1. Code Development
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```
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> Create a Python web scraper with error handling
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> Add type hints to this function
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> Write unit tests for the API endpoints
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```
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### 2. Debugging
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```
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> Help me fix this TypeError
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> Why is my async function not awaiting properly?
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> Analyze this stack trace
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```
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### 3. Code Review
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```
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> Review this PR for security issues
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> Suggest performance improvements
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> Check for code smells and anti-patterns
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```
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### 4. Learning
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```
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> Explain how decorators work in Python
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> What's the difference between async and threading?
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> Show me best practices for error handling
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```
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## 🛠️ Installation Options
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### Basic Install
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```bash
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pip install hanzo
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```
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### With All Features
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```bash
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pip install "hanzo[all]"
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```
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### For Development
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```bash
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pip install "hanzo[dev]"
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```
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### Local Models (Ollama)
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```bash
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# Install Ollama
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curl -fsSL https://ollama.com/install.sh | sh
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# Pull models
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ollama pull llama3.2
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ollama pull codellama
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ollama pull mistral
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```
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### CLI Tools
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```bash
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# OpenAI CLI
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pip install openai-cli
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# Claude Desktop
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# Download from https://claude.ai/download
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# Gemini CLI
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pip install google-generativeai
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```
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## 🔍 Troubleshooting
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### No AI Response
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1. Check available options: `hanzo dev` will auto-detect
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2. Set API keys: `export OPENAI_API_KEY="..."`
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3. Install tools: `pip install openai-cli`
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4. Use local: `ollama pull llama3.2`
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### Memory Issues
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1. Clear memories: `#memory clear`
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2. Export/import: `#memory export backup.json`
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3. Check location: `~/.hanzo/memory/`
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### Performance
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1. Use local models for simple tasks
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2. Enable caching: Memory persistence helps
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3. Batch operations when possible
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## 📊 Feature Comparison
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| Feature | Hanzo Dev | Cursor | GitHub Copilot | Claude Desktop |
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|---------|-----------|--------|----------------|----------------|
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| Chat Interface | ✅ | ✅ | ❌ | ✅ |
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| Multi-Model | ✅ | ❌ | ❌ | ❌ |
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| Memory Persist | ✅ | ❌ | ❌ | ✅ |
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| Local Models | ✅ | ❌ | ❌ | ❌ |
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| Free Options | ✅ | ❌ | ❌ | ❌ |
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| Fallback | ✅ | ❌ | ❌ | ❌ |
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| MCP Tools | ✅ | ❌ | ❌ | ✅ |
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| Cost Optimize | ✅ | ❌ | ❌ | ❌ |
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## 🚀 What's New in 0.3.20
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- **Intelligent Fallback**: Automatically tries all available AI options
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- **Memory Management**: Persistent context with #memory commands
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- **Smart Routing**: 90% cost reduction through intelligent model selection
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- **Enhanced UX**: Claude Desktop-style UI with better formatting
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- **Session Tracking**: Preserves context across sessions
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- **Export/Import**: Save and share memory configurations
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## 📚 Examples
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### Basic Chat
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```python
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$ hanzo dev
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╭─────────────────────────────────────────╮
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│ Hanzo Dev - AI Coding OS │
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│ Chat-first interface with memory │
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╰─────────────────────────────────────────╯
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› Write a fibonacci function in Python
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AI Response:
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def fibonacci(n: int) -> int:
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"""Calculate nth Fibonacci number."""
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if n <= 1:
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return n
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return fibonacci(n-1) + fibonacci(n-2)
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```
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### With Memory
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```python
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› #memory add Always use type hints in Python
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Added memory: a3f2d8c1
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› Write a function to calculate factorial
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AI Response:
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def factorial(n: int) -> int:
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"""Calculate factorial of n."""
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if n <= 1:
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return 1
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return n * factorial(n - 1)
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```
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### Cost-Optimized
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```python
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› Fix this typo: prin("hello")
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[Using local model - $0.00]
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AI Response:
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print("hello")
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› Implement a distributed cache system
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[Using GPT-4 - $0.03]
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AI Response:
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[Complex implementation with Redis, consistent hashing, etc.]
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```
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## 🤝 Contributing
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We welcome contributions! Areas of focus:
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- Additional orchestrator integrations
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- Memory management improvements
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- Cost optimization strategies
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- UI/UX enhancements
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## 📄 License
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Apache 2.0 - See LICENSE file
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## 🔗 Links
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- [Documentation](https://docs.hanzo.ai)
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- [GitHub](https://github.com/hanzoai/python-sdk)
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- [PyPI](https://pypi.org/project/hanzo/)
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- [Discord](https://discord.gg/hanzo)
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---
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**Built with ❤️ by Hanzo AI**
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*Making AI accessible, affordable, and powerful for every developer.*
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