mirror of
https://github.com/gpt-omni/mini-omni
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104 lines
2.9 KiB
Markdown
104 lines
2.9 KiB
Markdown
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# Mini-Omni
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<p align="center"><strong style="font-size: 18px;">
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Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming
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</strong>
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</p>
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<p align="center">
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🤗 <a href="https://huggingface.co/gpt-omni/mini-omni">Hugging Face</a> | 📖 <a href="https://github.com/gpt-omni/mini-omni">Github</a>
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| 📑 <a href="https://arxiv.org/abs/2408.16725">Technical report</a>
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</p>
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Mini-Omni is an open-source multimodal large language model that can **hear, talk while thinking**. Featuring real-time end-to-end speech input and **streaming audio output** conversational capabilities.
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<p align="center">
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<img src="data/figures/frameworkv3.jpg" width="100%"/>
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</p>
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## Features
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✅ **Real-time speech-to-speech** conversational capabilities. No extra ASR or TTS models required.
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✅ **Talking while thinking**, with the ability to generate text and audio at the same time.
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✅ **Streaming audio outupt** capabilities.
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✅ With "Audio-to-Text" and "Audio-to-Audio" **batch inference** to further boost the performance.
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## Demo
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NOTE: need to unmute first.
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https://github.com/user-attachments/assets/03bdde05-9514-4748-b527-003bea57f118
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## Install
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Create a new conda environment and install the required packages:
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```sh
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conda create -n omni python=3.10
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conda activate omni
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git clone https://github.com/gpt-omni/mini-omni.git
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cd mini-omni
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pip install -r requirements.txt
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```
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## Quick start
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**Interactive demo**
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- start server
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```sh
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conda activate omni
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cd mini-omni
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python3 server.py --ip '0.0.0.0' --port 60808
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```
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- run streamlit demo
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NOTE: you need to run streamlit locally with PyAudio installed.
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```sh
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pip install PyAudio==0.2.14
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API_URL=http://0.0.0.0:60808/chat streamlit run webui/omni_streamlit.py
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```
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- run gradio demo
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```sh
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API_URL=http://0.0.0.0:60808/chat python3 webui/omni_gradio.py
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```
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example:
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NOTE: need to unmute first. Gradio seems can not play audio stream instantly, so the latency feels a bit longer.
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https://github.com/user-attachments/assets/29187680-4c42-47ff-b352-f0ea333496d9
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**Local test**
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```sh
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conda activate omni
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cd mini-omni
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# test run the preset audio samples and questions
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python inference.py
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```
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## Acknowledgements
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- [Qwen2](https://github.com/QwenLM/Qwen2/) as the LLM backbone.
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- [litGPT](https://github.com/Lightning-AI/litgpt/) for training and inference.
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- [whisper](https://github.com/openai/whisper/) for audio encoding.
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- [snac](https://github.com/hubertsiuzdak/snac/) for audio decoding.
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- [CosyVoice](https://github.com/FunAudioLLM/CosyVoice) for generating synthetic speech.
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- [OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) and [MOSS](https://github.com/OpenMOSS/MOSS/tree/main) for alignment.
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## Star History
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[](https://star-history.com/#gpt-omni/mini-omni&Date)
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