speechless
UV Installation Instructions
To install dependencies and manage the project, we use uv, a fast Python package manager and resolver. Follow the steps below to set up your environment.
Step 1: Install uv
You can install uv via pip:
pip install uv
Or with pipx:
pipx install uv
Verify the installation:
uv --version
Step 2 · Create (and activate) the virtual environment
Use uv to manage your environment:
uv venv source .venv/bin/activate
(If you prefer another tool like venv/virtualenv, activate it before continuing.)
Step 3 · Install dependencies
Install all runtime, dev, and extras in one step:
uv sync --all-extras --dev
This also creates or updates uv.lock automatically.
Step 4 · Run the project or test suite
If not already activated:
source .venv/bin/activate
Then run the tests:
uv run pytest
Step 5 · Run pre-commit hooks
Ensure your code stays clean:
uv run pre-commit run --all-files
Quick commands you might love:
| Task | Command |
|---|---|
| Update dependencies to newest allowed refs | uv sync --upgrade |
| Re-create a fresh lockfile | rm uv.lock && uv sync |
| Add a new development dependency | uv add --dev |
Step 6: Convert the model to ONNX format
To convert the model to ONNX format, run:
python export_to_onnx.py --checkpoint /path/to/checkpoint --onnx_model /path/to/onnx_model
Step 7: Add OPENAI_API_KEY and/or Set Up WHISPER_CPP_MODEL
The whisper_1 model requires an OpenAI subscription. As an alternative, you can use whisper.cpp.
To download a supported model:
# Linux
docker run -it --rm -v ./data/models:/models ghcr.io/ggerganov/whisper.cpp:main "./models/download-ggml-model.sh small /models"
# Windows (PowerShell)
docker run -it --rm -v "$(pwd -W)/models":/models ghcr.io/ggerganov/whisper.cpp:main "./models/download-ggml-model.sh small /models"
Once WHISPER_CPP_MODEL is set, inference is handled locally:
ffmpeg -i data/temp_results/uploaded_audio.mp3 -ar 16000 -ac 1 -c:a pcm_s16le data/audio/output.wav
Run whisper.cpp:
# Linux
docker run -it --rm -v ./data/models:/models -v ./data/audio:/audios ghcr.io/ggerganov/whisper.cpp:main "./build/bin/whisper-cli -m /models/ggml-small.bin -f /audios/output.wav -ml 16 -oj -l en"
# Windows
docker run -it --rm -v "$(pwd -W)/data/models":/models -v "$(pwd -W)/data":/audios ghcr.io/ggerganov/whisper.cpp:main "./build/bin/whisper-cli -m /models/ggml-small.bin -f /audios/output.wav -ml 16 -oj -l en"
Metadata
Release files for o2-speechless 0.0.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| o2_speechless-0.0.9.tar.gz | 24.9 kB | Without provenance | Details for o2_speechless-0.0.9.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| o2_speechless-0.0.9-py3-none-any.whl | Python 3 | none | any | Details for o2_speechless-0.0.9-py3-none-any.whl |
Total release size: 54.3 kB
Release files / o2_speechless-0.0.9.tar.gz
| Download URL | o2_speechless-0.0.9.tar.gz |
|---|---|
| Size | 24.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.7.11
|
Release files / o2_speechless-0.0.9-py3-none-any.whl
| Download URL | o2_speechless-0.0.9-py3-none-any.whl |
|---|---|
| Size | 29.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
b3fc3545cc5978c2c801b029d49d8ba8556b151da10b69d76962544cd04a7b26
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.7.11
|
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