Merge pull request #114 from needabetterusername/implement-69-clean

(Re-) Implement #69 (Dockerfile)
This commit is contained in:
Quentin Fuxa
2025-04-09 10:10:08 +02:00
committed by GitHub
2 changed files with 111 additions and 0 deletions

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Dockerfile Normal file
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FROM nvidia/cuda:12.8.1-cudnn-runtime-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1
WORKDIR /app
ARG EXTRAS
ARG HF_PRECACHE_DIR
ARG HF_TKN_FILE
# Install system dependencies
#RUN apt-get update && \
# apt-get install -y ffmpeg git && \
# apt-get clean && \
# rm -rf /var/lib/apt/lists/*
# 2) Install system dependencies + Python + pip
RUN apt-get update && \
apt-get install -y --no-install-recommends \
python3 \
python3-pip \
ffmpeg \
git && \
rm -rf /var/lib/apt/lists/*
RUN pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
COPY . .
# Install WhisperLiveKit directly, allowing for optional dependencies
# Note: For gates modedls, need to add your HF toke. See README.md
# for more details.
RUN if [ -n "$EXTRAS" ]; then \
echo "Installing with extras: [$EXTRAS]"; \
pip install --no-cache-dir .[$EXTRAS]; \
else \
echo "Installing base package only"; \
pip install --no-cache-dir .; \
fi
# Enable in-container caching for Hugging Face models by:
# Note: If running multiple containers, better to map a shared
# bucket.
#
# A) Make the cache directory persistent via an anonymous volume.
# Note: This only persists for a single, named container. This is
# only for convenience at de/test stage.
# For prod, it is better to use a named volume via host mount/k8s.
VOLUME ["/root/.cache/huggingface/hub"]
# or
# B) Conditionally copy a local pre-cache from the build context to the
# container's cache via the HF_PRECACHE_DIR build-arg.
# WARNING: This will copy ALL files in the pre-cache location.
# Conditionally copy a cache directory if provided
RUN if [ -n "$HF_PRECACHE_DIR" ]; then \
echo "Copying Hugging Face cache from $HF_PRECACHE_DIR"; \
mkdir -p /root/.cache/huggingface/hub && \
cp -r $HF_PRECACHE_DIR/* /root/.cache/huggingface/hub; \
else \
echo "No local Hugging Face cache specified, skipping copy"; \
fi
# Conditionally copy a Hugging Face token if provided
RUN if [ -n "$HF_TKN_FILE" ]; then \
echo "Copying Hugging Face token from $HF_TKN_FILE"; \
mkdir -p /root/.cache/huggingface && \
cp $HF_TKN_FILE /root/.cache/huggingface/token; \
else \
echo "No Hugging Face token file specified, skipping token setup"; \
fi
# Expose port for the transcription server
EXPOSE 8000
ENTRYPOINT ["whisperlivekit-server", "--host", "0.0.0.0"]
# Default args
CMD ["--model", "tiny.en"]

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@@ -250,6 +250,35 @@ To deploy WhisperLiveKit in production:
4. **HTTPS Support**: For secure deployments, use "wss://" instead of "ws://" in WebSocket URL
### 🐋 Docker
A basic Dockerfile is provided which allows re-use of python package installation options. See below useage examples:
***NOTE:** For **larger** models, ensure that your **docker runtime** has enough **memory** available.*
#### All defaults
- Create a reuseable image with only the basics and then run as a named container.
```bash
docker build -t whisperlivekit-defaults .
docker create --gpus all --name whisperlivekit -p 8000:8000 whisperlivekit-defaults
docker start -i whisperlivekit
```
> **Note**: If you're running on a system without NVIDIA GPU support (such as Mac with Apple Silicon or any system without CUDA capabilities), you need to **remove the `--gpus all` flag** from the `docker create` command. Without GPU acceleration, transcription will use CPU only, which may be significantly slower. Consider using small models for better performance on CPU-only systems.
#### Customization
- Customise the container options.
```bash
docker build -t whisperlivekit-defaults .
docker create --gpus all --name whisperlivekit-base -p 8000:8000 whisperlivekit-defaults --model base
docker start -i whisperlivekit-base
```
- `--build-arg` Options
- `EXTRAS="whisper-timestamped"` - Add extras to the image's installation (no spaces). Remember to set necessary container options!
- `HF_PRECACHE_DIR=./.cache/` - Pre-load a model cache for faster first-time start
- `HF_TOKEN=./token` - Add your Hugging Face Hub access token to download gated models
## 🔮 Use Cases
- **Meeting Transcription**: Capture discussions in real-time