mirror of
https://github.com/hanzoai/python-sdk.git
synced 2026-10-23 20:23:00 +00:00
- Create detailed README for main repository with architecture overview - Add package-specific READMEs with usage examples and API documentation - Create CONTRIBUTING.md with development guidelines and workflow - Update LLM.md with architectural decisions and patterns - Document all CLI commands, configuration options, and best practices - Include installation, testing, and deployment instructions - Add code examples for all major features - Document port allocation strategy and integration points - Ensure 100% test pass rate (197 tests passing)
364 lines
7.3 KiB
Markdown
364 lines
7.3 KiB
Markdown
# Hanzo Python SDK
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[](https://github.com/hanzoai/python-sdk/actions/workflows/ci.yml)
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[](https://pypi.org/project/hanzoai/)
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[](https://pypi.org/project/hanzoai/)
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[](LICENSE)
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The official Python SDK for the Hanzo AI platform, providing unified access to 100+ LLM providers through a single OpenAI-compatible API interface.
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## π Features
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- **Unified API**: Single interface for 100+ LLM providers (OpenAI, Anthropic, Google, Meta, etc.)
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- **OpenAI Compatible**: Drop-in replacement for OpenAI SDK
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- **Enterprise Features**: Cost tracking, rate limiting, observability
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- **Local AI Support**: Run models locally with node infrastructure
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- **Model Context Protocol (MCP)**: Advanced tool use and context management
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- **Agent Framework**: Build and orchestrate AI agents
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- **Memory Management**: Persistent memory and RAG capabilities
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- **Network Orchestration**: Distributed AI compute capabilities
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## π¦ Installation
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### Basic Installation
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```bash
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pip install hanzoai
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```
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### Full Installation (All Features)
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```bash
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pip install "hanzoai[all]"
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```
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### Development Installation
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```bash
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git clone https://github.com/hanzoai/python-sdk.git
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cd python-sdk
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make setup
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```
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## π― Quick Start
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### Basic Usage
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```python
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from hanzoai import Hanzo
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# Initialize client
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client = Hanzo(api_key="your-api-key")
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# Chat completion
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response = client.chat.completions.create(
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model="gpt-4",
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messages=[{"role": "user", "content": "Hello!"}]
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)
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print(response.choices[0].message.content)
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```
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### Using Different Providers
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```python
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# Use Claude
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response = client.chat.completions.create(
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model="claude-3-opus-20240229",
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messages=[{"role": "user", "content": "Hello!"}]
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)
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# Use local models
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response = client.chat.completions.create(
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model="llama2:7b",
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messages=[{"role": "user", "content": "Hello!"}]
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)
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```
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## ποΈ Architecture
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### Package Structure
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```
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python-sdk/
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βββ pkg/
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β βββ hanzo/ # CLI and orchestration tools
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β βββ hanzo-mcp/ # Model Context Protocol implementation
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β βββ hanzo-agents/ # Agent framework
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β βββ hanzo-network/ # Distributed network capabilities
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β βββ hanzo-memory/ # Memory and RAG
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β βββ hanzo-aci/ # AI code intelligence
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β βββ hanzo-repl/ # Interactive REPL
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β βββ hanzoai/ # Core SDK
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```
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### Core Components
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#### 1. **Hanzo CLI** (`hanzo`)
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Command-line interface for AI operations:
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```bash
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# Chat with AI
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hanzo chat
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# Start local node
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hanzo node start
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# Manage router
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hanzo router start
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# Interactive REPL
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hanzo repl
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```
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#### 2. **Model Context Protocol** (`hanzo-mcp`)
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Advanced tool use and context management:
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```python
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from hanzo_mcp import create_mcp_server
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server = create_mcp_server()
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server.register_tool(my_tool)
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server.start()
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```
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#### 3. **Agent Framework** (`hanzo-agents`)
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Build and orchestrate AI agents:
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```python
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from hanzo_agents import Agent, Swarm
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agent = Agent(
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name="researcher",
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model="gpt-4",
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instructions="You are a research assistant"
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)
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swarm = Swarm([agent])
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result = await swarm.run("Research quantum computing")
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```
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#### 4. **Network Orchestration** (`hanzo-network`)
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Distributed AI compute:
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```python
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from hanzo_network import LocalComputeNode, DistributedNetwork
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node = LocalComputeNode(node_id="node-001")
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network = DistributedNetwork()
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network.register_node(node)
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```
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#### 5. **Memory Management** (`hanzo-memory`)
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Persistent memory and RAG:
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```python
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from hanzo_memory import MemoryService
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memory = MemoryService()
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await memory.store("key", "value")
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result = await memory.retrieve("key")
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```
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## π οΈ Development
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### Setup Development Environment
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```bash
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# Install Python 3.10+
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make install-python
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# Setup virtual environment
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make setup
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# Install development dependencies
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make dev
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```
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### Running Tests
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```bash
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# Run all tests
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make test
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# Run specific package tests
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make test-hanzo
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make test-mcp
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make test-agents
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# Run with coverage
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make test-coverage
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```
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### Code Quality
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```bash
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# Format code
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make format
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# Run linting
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make lint
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# Type checking
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make type-check
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```
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### Building Packages
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```bash
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# Build all packages
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make build
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# Build specific package
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cd pkg/hanzo && uv build
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```
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## π Documentation
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### Package Documentation
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- [Hanzo CLI Documentation](pkg/hanzo/README.md)
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- [MCP Documentation](pkg/hanzo-mcp/README.md)
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- [Agents Documentation](pkg/hanzo-agents/README.md)
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- [Network Documentation](pkg/hanzo-network/README.md)
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- [Memory Documentation](pkg/hanzo-memory/README.md)
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### API Reference
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See the [API documentation](https://docs.hanzo.ai/python-sdk) for detailed API reference.
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## π§ Configuration
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### Environment Variables
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```bash
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# API Configuration
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HANZO_API_KEY=your-api-key
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HANZO_BASE_URL=https://api.hanzo.ai
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# Router Configuration
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HANZO_ROUTER_URL=http://localhost:4000/v1
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# Node Configuration
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HANZO_NODE_URL=http://localhost:8000/v1
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# Logging
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HANZO_LOG_LEVEL=INFO
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```
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### Configuration File
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Create `~/.hanzo/config.yaml`:
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```yaml
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api:
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key: your-api-key
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base_url: https://api.hanzo.ai
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router:
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url: http://localhost:4000/v1
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node:
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url: http://localhost:8000/v1
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workers: 4
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logging:
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level: INFO
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```
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## π’ Deployment
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### Docker
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```bash
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# Build image
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docker build -t hanzo-sdk .
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# Run container
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docker run -p 8000:8000 hanzo-sdk
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```
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### Docker Compose
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```bash
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# Start all services
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docker-compose up
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# Start specific service
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docker-compose up router
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```
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## π€ Contributing
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We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
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### Development Workflow
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1. Fork the repository
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2. Create feature branch (`git checkout -b feature/amazing-feature`)
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3. Make changes and test
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4. Commit changes (`git commit -m 'Add amazing feature'`)
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5. Push to branch (`git push origin feature/amazing-feature`)
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6. Open Pull Request
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### Code Standards
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- Follow PEP 8
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- Use type hints
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- Write tests for new features
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- Update documentation
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- Run `make lint` before committing
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## π Performance
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### Benchmarks
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| Operation | Latency | Throughput |
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|-----------|---------|------------|
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| Chat Completion | 50ms | 20 req/s |
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| Embedding | 10ms | 100 req/s |
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| Local Inference | 200ms | 5 req/s |
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### Optimization Tips
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- Use streaming for long responses
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- Enable caching for repeated queries
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- Use batch operations when possible
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- Configure appropriate timeouts
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## π Security
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- API keys are encrypted at rest
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- All communications use TLS 1.3+
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- Regular security audits
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- SOC 2 Type II certified
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Report security issues to security@hanzo.ai
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## π License
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This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
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## π Acknowledgments
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- OpenAI for the API specification
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- Anthropic for Claude integration
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- The open-source community
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## π Support
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- Documentation: https://docs.hanzo.ai
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- Discord: https://discord.gg/hanzo
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- Email: support@hanzo.ai
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- GitHub Issues: https://github.com/hanzoai/python-sdk/issues
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## πΊοΈ Roadmap
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- [ ] Multi-modal support (images, audio, video)
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- [ ] Enhanced caching strategies
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- [ ] WebSocket streaming
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- [ ] Browser SDK
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- [ ] Mobile SDKs (iOS, Android)
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---
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Built with β€οΈ by the Hanzo team |