mlx-omni-server 0.5.2
MLX Omni Server is a server that provides OpenAI-compatible APIs using Apple's MLX framework.
Requires Python: >=3.11
Keywords: agi, ai, aigc, mlx, openai, server, stt, tts

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# MLX Omni Server

*Local AI inference server optimized for Apple Silicon*

[![PyPI version](https://img.shields.io/pypi/v/mlx-omni-server.svg)](https://pypi.python.org/pypi/mlx-omni-server)
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://python.org)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/madroidmaq/mlx-omni-server)

![MLX Omni Server Banner](docs/banner.png)

**MLX Omni Server** provides dual API compatibility with both **OpenAI** and **Anthropic APIs**, enabling seamless local inference on Apple Silicon using the MLX framework.

[Installation](#-installation) • [Quick Start](#-quick-start) • [Documentation](#-documentation) • [Contributing](#-contributing)

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## ✨ Features

- 🚀 **Apple Silicon Optimized** - Built on MLX framework for M1/M2/M3/M4 chips
- 🔌 **Dual API Support** - Compatible with both OpenAI and Anthropic APIs
- 🎯 **Complete AI Suite** - Chat, audio processing, image generation, embeddings
- ⚡ **High Performance** - Local inference with hardware acceleration
- 🔐 **Privacy-First** - All processing happens locally on your machine
- 🛠 **Drop-in Replacement** - Works with existing OpenAI and Anthropic SDKs

## 🚀 Installation

```bash
pip install mlx-omni-server
```

## ⚡ Quick Start

1. **Start the server:**
   ```bash
   mlx-omni-server
   ```

2. **Choose your preferred API:**

   <details>
   <summary><b>OpenAI API</b> (Click to expand)</summary>

   ```python
   from openai import OpenAI

   client = OpenAI(
       base_url="http://localhost:10240/v1",
       api_key="not-needed"
   )

   response = client.chat.completions.create(
       model="mlx-community/gemma-3-1b-it-4bit-DWQ",
       messages=[{"role": "user", "content": "Hello!"}]
   )
   print(response.choices[0].message.content)
   ```
   </details>

   <details>
   <summary><b>Anthropic API</b> (Click to expand)</summary>

   ```python
   import anthropic

   client = anthropic.Anthropic(
       base_url="http://localhost:10240/anthropic",
       api_key="not-needed"
   )

   message = client.messages.create(
       model="mlx-community/gemma-3-1b-it-4bit-DWQ",
       max_tokens=1000,
       messages=[{"role": "user", "content": "Hello!"}]
   )
   print(message.content[0].text)
   ```
   </details>

🎉 **That's it!** You're now running AI locally on your Mac.

## 📋 API Support

### OpenAI Compatible Endpoints (`/v1/*`)

| Endpoint | Feature | Status |
|----------|---------|--------|
| `/v1/chat/completions` | Chat with tools, streaming, structured output | ✅ |
| `/v1/audio/speech` | Text-to-Speech | ✅ |
| `/v1/audio/transcriptions` | Speech-to-Text | ✅ |
| `/v1/images/generations` | Image Generation | ✅ |
| `/v1/embeddings` | Text Embeddings | ✅ |
| `/v1/models` | Model Management | ✅ |

### Anthropic Compatible Endpoints (`/anthropic/v1/*`)

| Endpoint | Feature | Status |
|----------|---------|--------|
| `/anthropic/v1/messages` | Messages with tools, streaming, thinking mode | ✅ |
| `/anthropic/v1/models` | Model listing with pagination | ✅ |


## ⚙️ Configuration

```bash
# Default (port 10240)
mlx-omni-server

# Custom options
mlx-omni-server --port 8000
MLX_OMNI_LOG_LEVEL=debug mlx-omni-server

# View all options
mlx-omni-server --help
```

## 🛠 Development

<details>
<summary><b>Development Setup</b></summary>

```bash
git clone https://github.com/madroidmaq/mlx-omni-server.git
cd mlx-omni-server
uv sync

# Start with hot-reload
uv run uvicorn mlx_omni_server.main:app --reload --host 0.0.0.0 --port 10240
```

**Testing:**
```bash
uv run pytest                    # All tests
uv run pytest tests/chat/openai/ # OpenAI tests
uv run pytest tests/chat/anthropic/ # Anthropic tests
```

**Code Quality:**
```bash
uv run black . && uv run isort . # Format code
uv run pre-commit run --all-files # Run hooks
```
</details>

## 🎯 Key Features

**Model Management**
- Auto-discovery of MLX models in HuggingFace cache
- On-demand loading and intelligent caching
- Automatic model downloading when needed

**Advanced Capabilities**
- Function calling with model-specific parsers
- Real-time streaming for both APIs
- JSON schema validation and structured output
- Extended reasoning (thinking mode) for supported models

## 📚 Documentation

| Resource | Description |
|----------|-------------|
| [OpenAI API Guide](docs/openai-api.md) | Complete OpenAI API reference |
| [Anthropic API Guide](docs/anthropic-api.md) | Complete Anthropic API reference |
| [Examples](examples/) | Practical usage examples |

## 🔍 Troubleshooting

<details>
<summary><b>Common Issues</b></summary>

**Requirements:**
- Python 3.11+
- Apple Silicon Mac (M1/M2/M3/M4)
- MLX framework installed

**Quick fixes:**
```bash
# Check requirements
python --version  # Should be 3.11+
python -c "import mlx; print(mlx.__version__)"

# Pre-download models (if needed)
huggingface-cli download mlx-community/gemma-3-1b-it-4bit-DWQ

# Enable debug logging
MLX_OMNI_LOG_LEVEL=debug mlx-omni-server
```
</details>

## 🤝 Contributing

**Quick contributor setup:**
```bash
git clone https://github.com/madroidmaq/mlx-omni-server.git
cd mlx-omni-server
uv sync && uv run pytest
```

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---

## 🙏 Acknowledgments

Built with [MLX](https://github.com/ml-explore/mlx) by Apple • [FastAPI](https://fastapi.tiangolo.com/) • [MLX-LM](https://github.com/ml-explore/mlx-lm)

## 📄 License

[MIT License](LICENSE) • Not affiliated with OpenAI, Anthropic, or Apple

## 🌟 Star History

[![Star History Chart](https://api.star-history.com/svg?repos=madroidmaq/mlx-omni-server&type=Date)](https://star-history.com/#madroidmaq/mlx-omni-server&Date)

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