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<p align="center"><img src=".github/hero.svg" alt="python-sdk" width="880"></p>
<p align="center"><img src=".github/hero.svg" alt="Hanzo Python SDK" width="880"></p>
# Hanzo Python SDK
**The flagship Python SDK for the Open AI Cloud — models, agents, tools, memory, and MCP in one install.**
[![CI](https://github.com/hanzoai/python-sdk/actions/workflows/ci.yml/badge.svg)](https://github.com/hanzoai/python-sdk/actions/workflows/ci.yml)
[![PyPI](https://img.shields.io/pypi/v/hanzoai.svg)](https://pypi.org/project/hanzoai/)
[![Python Version](https://img.shields.io/pypi/pyversions/hanzoai.svg)](https://pypi.org/project/hanzoai/)
[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
The official Python SDK for the Hanzo AI platform, providing unified access to 100+ LLM providers through a single OpenAI-compatible API interface.
This is the most complete Hanzo SDK — a `uv` workspace of 60+ composable packages
covering the full AI surface: the typed cloud client, an agent framework, the
Model Context Protocol server and tools, persistent memory + RAG, distributed
compute, and a batteries-included CLI. If you build AI in Python, start here.
## 🚀 Features
- **Unified API**: Single interface for 100+ LLM providers (OpenAI, Anthropic, Google, Meta, etc.)
- **OpenAI Compatible**: Drop-in replacement for OpenAI SDK
- **Enterprise Features**: Cost tracking, rate limiting, observability
- **Local AI Support**: Run models locally with node infrastructure
- **Model Context Protocol (MCP)**: Advanced tool use and context management
- **Agent Framework**: Build and orchestrate AI agents
- **Memory Management**: Persistent memory and RAG capabilities
- **Network Orchestration**: Distributed AI compute capabilities
## 📦 Installation
### Basic Installation
## Install
```bash
pip install hanzoai
pip install hanzo # flagship: CLI + agents + MCP + client
```
### Full Installation (All Features)
Or install exactly what you need:
```bash
pip install "hanzoai[all]"
pip install hanzoai # just the typed cloud API client
pip install "hanzo[all]" # everything, including optional extras
```
### Development Installation
```bash
git clone https://github.com/hanzoai/python-sdk.git
cd python-sdk
make setup
```
## 🎯 Quick Start
### Basic Usage
## Quickstart
```python
from hanzoai import Hanzo
from hanzoai import ApiClient, Configuration, AiOpenAICompatibleApi
from hanzoai import AiChatCompletionRequest, AiChatMessage
# Initialize client
client = Hanzo(api_key="your-api-key")
config = Configuration(host="https://api.hanzo.ai", access_token="sk-...")
# Chat completion
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
with ApiClient(config) as client:
ai = AiOpenAICompatibleApi(client)
resp = ai.ai_create_chat_completion(
AiChatCompletionRequest(
model="zen-coder",
messages=[AiChatMessage(role="user", content="Ship it.")],
)
)
print(resp.choices[0].message.content)
```
### Using Different Providers
Every route is `https://api.hanzo.ai/v1/<service>/*`. Models come from the **Zen**
family (our own models) plus any provider you connect — one typed client, no proxy
in the middle.
```python
# Use Claude
response = client.chat.completions.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello!"}]
)
## Packages
# Use local models
response = client.chat.completions.create(
model="llama2:7b",
messages=[{"role": "user", "content": "Hello!"}]
)
```
The workspace splits cleanly by concern. The headline packages:
## 🏗️ Architecture
### Package Structure
| Package | Purpose |
|---------|---------|
| `hanzoai` | Typed cloud API client (generated from the Hanzo OpenAPI surface). |
| `hanzo` | The `hanzo` CLI + runtime that ties everything together. |
| `hanzo-mcp` | Model Context Protocol server — discovers tools via entry points. |
| `hanzo-agents` / `hanzo-agent` | Agent framework — build and orchestrate agents and swarms. |
| `hanzo-network` | Distributed AI compute and node orchestration. |
| `hanzo-memory` | Persistent memory + RAG (SQLite, optional vector backends). |
| `hanzo-tools-*` | 60+ single-concern tool packages (`shell`, `browser`, `fs`, `code`, `vector`, `iam`, …), each exposing a `TOOLS` list. |
```
python-sdk/
├── pkg/
│ ├── hanzo/ # CLI and orchestration tools
│ ├── hanzo-mcp/ # Model Context Protocol implementation
│ ├── hanzo-agents/ # Agent framework
│ ├── hanzo-network/ # Distributed network capabilities
│ ├── hanzo-memory/ # Memory and RAG
│ ├── hanzo-aci/ # AI code intelligence
│ ├── hanzo-repl/ # Interactive REPL
│ └── hanzoai/ # Core SDK
└── pkg/
├── hanzoai/ # typed cloud client (OpenAPI-generated)
├── hanzo/ # CLI + runtime meta package
├── hanzo-mcp/ # MCP server (entry-point tool discovery)
├── hanzo-agents/ # agent framework
├── hanzo-network/ # distributed compute
├── hanzo-memory/ # memory + RAG
└── hanzo-tools-*/ # composable tool packages
```
### Core Components
## CLI
#### 1. **Hanzo CLI** (`hanzo`)
Command-line interface for AI operations:
`pip install hanzo` gives you the `hanzo` command:
```bash
# Chat with AI
hanzo chat
# Start local node
hanzo node start
# Manage router
hanzo router start
# Interactive REPL
hanzo repl
hanzo chat # chat with the Zen models
hanzo node # start / manage a local compute node
hanzo mcp # run the MCP server for your editor or agent
hanzo agent # build and run agents
hanzo run # run a workflow
hanzo cloud # manage cloud resources
hanzo search # AI-powered search
```
#### 2. **Model Context Protocol** (`hanzo-mcp`)
Advanced tool use and context management:
Run `hanzo --help` for the full command tree.
## Model Context Protocol (`hanzo-mcp`)
`hanzo-mcp` hosts the MCP server and discovers tools through
`[project.entry-points."hanzo.tools"]`, so any installed `hanzo-tools-*` package
lights up automatically.
```python
from hanzo_mcp import create_mcp_server
@@ -123,24 +106,22 @@ server.register_tool(my_tool)
server.start()
```
#### 3. **Agent Framework** (`hanzo-agents`)
Build and orchestrate AI agents:
## Agents (`hanzo-agents`)
```python
from hanzo_agents import Agent, Swarm
agent = Agent(
name="researcher",
model="gpt-4",
instructions="You are a research assistant"
model="zen-coder",
instructions="You are a research assistant.",
)
swarm = Swarm([agent])
result = await swarm.run("Research quantum computing")
result = await swarm.run("Research quantum computing.")
```
#### 4. **Network Orchestration** (`hanzo-network`)
Distributed AI compute:
## Network (`hanzo-network`)
```python
from hanzo_network import LocalComputeNode, DistributedNetwork
@@ -150,8 +131,11 @@ network = DistributedNetwork()
network.register_node(node)
```
#### 5. **Memory Management** (`hanzo-memory`)
Persistent memory and RAG:
## Memory (`hanzo-memory`)
Persistent memory and RAG backed by SQLite, with optional vector search
(`sqlite-vec`, `lancedb`, `kuzu`). Global state lives in `~/.hanzo/`; per-project
state in `.hanzo/`.
```python
from hanzo_memory import MemoryService
@@ -161,206 +145,70 @@ await memory.store("key", "value")
result = await memory.retrieve("key")
```
## 🛠️ Development
## Development
### Setup Development Environment
This is a `uv` workspace.
```bash
# Install Python 3.10+
make install-python
git clone https://github.com/hanzoai/python-sdk.git
cd python-sdk
uv sync --all-packages # install the whole workspace
# Setup virtual environment
make setup
# Install development dependencies
make dev
uv run pytest tests/ -v # run tests
make lint # ruff lint
make format # ruff format
make type-check # mypy / pyright
```
### Running Tests
Per-package work:
```bash
# Run all tests
make test
# Run specific package tests
make test-hanzo
make test-mcp
make test-agents
# Run with coverage
make test-coverage
```
### Code Quality
```bash
# Format code
make format
# Run linting
make lint
# Type checking
make type-check
```
### Building Packages
```bash
# Build all packages
make build
# Build specific package
uv run pytest pkg/hanzo-mcp -v
cd pkg/hanzo && uv build
```
## 📚 Documentation
### Package Documentation
- [Hanzo CLI Documentation](pkg/hanzo/README.md)
- [MCP Documentation](pkg/hanzo-mcp/README.md)
- [Agents Documentation](pkg/hanzo-agents/README.md)
- [Network Documentation](pkg/hanzo-network/README.md)
- [Memory Documentation](pkg/hanzo-memory/README.md)
### API Reference
See the [API documentation](https://docs.hanzo.ai/python-sdk) for detailed API reference.
## 🔧 Configuration
### Environment Variables
## Configuration
```bash
# API Configuration
HANZO_API_KEY=your-api-key
HANZO_BASE_URL=https://api.hanzo.ai
# Router Configuration
HANZO_ROUTER_URL=http://localhost:4000/v1
# Node Configuration
HANZO_NODE_URL=http://localhost:8000/v1
# Logging
HANZO_LOG_LEVEL=INFO
```
### Configuration File
Create `~/.hanzo/config.yaml`:
Or `~/.hanzo/config.yaml`:
```yaml
api:
key: your-api-key
base_url: https://api.hanzo.ai
router:
url: http://localhost:4000/v1
node:
url: http://localhost:8000/v1
workers: 4
logging:
level: INFO
```
## 🚢 Deployment
## Security
### Docker
- Transport is TLS 1.3+. Secrets belong in a KMS, never in source or plaintext.
- SOC 2 audit in progress; HIPAA BAA available.
```bash
# Build image
docker build -t hanzo-sdk .
Report vulnerabilities to **[email protected]**. See [SECURITY.md](SECURITY.md).
# Run container
docker run -p 8000:8000 hanzo-sdk
```
## Contributing
### Docker Compose
Contributions welcome — see [CONTRIBUTING.md](CONTRIBUTING.md). Use type hints,
add tests for new behavior, and run `make lint` before opening a PR.
```bash
# Start all services
docker-compose up
## License
# Start specific service
docker-compose up router
```
Apache License 2.0 — see [LICENSE](LICENSE).
## 🤝 Contributing
## Support
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
### Development Workflow
1. Fork the repository
2. Create feature branch (`git checkout -b feature/amazing-feature`)
3. Make changes and test
4. Commit changes (`git commit -m 'Add amazing feature'`)
5. Push to branch (`git push origin feature/amazing-feature`)
6. Open Pull Request
### Code Standards
- Follow PEP 8
- Use type hints
- Write tests for new features
- Update documentation
- Run `make lint` before committing
## 📊 Performance
### Benchmarks
| Operation | Latency | Throughput |
|-----------|---------|------------|
| Chat Completion | 50ms | 20 req/s |
| Embedding | 10ms | 100 req/s |
| Local Inference | 200ms | 5 req/s |
### Optimization Tips
- Use streaming for long responses
- Enable caching for repeated queries
- Use batch operations when possible
- Configure appropriate timeouts
## 🔒 Security
- API keys are encrypted at rest
- All communications use TLS 1.3+
- Regular security audits
- SOC 2 Type II certified
Report security issues to security@hanzo.ai
## 📄 License
This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- OpenAI for the API specification
- Anthropic for Claude integration
- The open-source community
## 📞 Support
- Documentation: https://docs.hanzo.ai
- Discord: https://discord.gg/hanzo
- Docs: [docs.hanzo.ai](https://docs.hanzo.ai)
- Issues: [github.com/hanzoai/python-sdk/issues](https://github.com/hanzoai/python-sdk/issues)
- Email: support@hanzo.ai
- GitHub Issues: https://github.com/hanzoai/python-sdk/issues
## 🗺️ Roadmap
## Hanzo — the Open AI Cloud
- [ ] Multi-modal support (images, audio, video)
- [ ] Enhanced caching strategies
- [ ] WebSocket streaming
- [ ] Browser SDK
- [ ] Mobile SDKs (iOS, Android)
Open source · every language · on-chain settlement. [hanzo.ai](https://hanzo.ai) · [docs.hanzo.ai](https://docs.hanzo.ai)
---
Built with ❤️ by the Hanzo team
**SDKs in every language** — [Python](https://github.com/hanzoai/python-sdk) (flagship) · [TypeScript](https://github.com/hanzo-js/sdk) · [Go](https://github.com/hanzo-go/sdk) · [Rust](https://github.com/hanzo-rs/sdk) · [C++](https://github.com/hanzo-cpp/sdk) · [Swift](https://github.com/hanzo-swift/sdk) · [Kotlin](https://github.com/hanzo-kt/sdk) · [umbrella](https://github.com/hanzoai/sdk)