> "uv add"

One life-changing thing I've been using `uv` for:

System python version is 3.12:

    $ python3 --version
    Python 3.12.3

    $ cat test.py
    #!/usr/bin/env python3

    import sys
    from rich import print

    if sys.version_info < (3, 13):
        print("This script will not work on Python 3.12")
    else:
        print(f"Hello world, this is python {sys.version}")

    $ python3 test.py
    Traceback (most recent call last):
    File "/tmp/tmp/test.py", line 10, in <module>
        from rich import print
    ModuleNotFoundError: No module named 'rich'

    $ uv add --script=test.py --python '3.13' rich
    Updated `test.py`

    $ cat test.py
    #!/usr/bin/env python3
    # /// script
    # requires-python = ">=3.13"
    # dependencies = [
    #     "rich",
    # ]
    # ///

    import sys
    from rich import print

    if sys.version_info < (3, 13):
        print("This script will not work on Python 3.12")
    else:
        print(f"Hello world, this is python {sys.version}")

    $ uv run test.py
    Downloading cpython-3.13.5-linux-x86_64-gnu (download) (33.8MiB)
    Downloading cpython-3.13.5-linux-x86_64-gnu (download)
    Installed 4 packages in 7ms
    Hello world, this is python 3.13.5 (main, Jun 12 2025, 12:40:22) [Clang 20.1.4 ]

    $ uv run --python 3.12 test.py
    warning: The requested interpreter resolved to Python 3.12.3, which is incompatible with the script's Python requirement: `>=3.13`
    Installed 4 packages in 7ms
    This script will not work on Python 3.12

    $ uv python list
    cpython-3.14.0b2-linux-x86_64-gnu                 <download available>
    cpython-3.14.0b2+freethreaded-linux-x86_64-gnu    <download available>
    cpython-3.13.5-linux-x86_64-gnu                   /home/dan/.local/share/uv/python/cpython-3.13.5-linux-x86_64-gnu/bin/python3.13
    cpython-3.13.5+freethreaded-linux-x86_64-gnu      <download available>
    cpython-3.12.11-linux-x86_64-gnu                  <download available>
    cpython-3.12.3-linux-x86_64-gnu                   /usr/bin/python3.12
    cpython-3.12.3-linux-x86_64-gnu                   /usr/bin/python3 -> python3.12
    cpython-3.11.13-linux-x86_64-gnu                  /home/dan/.local/share/uv/python/cpython-3.11.13-linux-x86_64-gnu/bin/python3.11
    cpython-3.10.18-linux-x86_64-gnu                  /home/dan/.local/share/uv/python/cpython-3.10.18-linux-x86_64-gnu/bin/python3.10
    cpython-3.9.23-linux-x86_64-gnu                   <download available>
    cpython-3.8.20-linux-x86_64-gnu                   <download available>
    pypy-3.11.11-linux-x86_64-gnu                     <download available>
    pypy-3.10.16-linux-x86_64-gnu                     <download available>
    pypy-3.9.19-linux-x86_64-gnu                      <download available>
    pypy-3.8.16-linux-x86_64-gnu                      <download available>
    graalpy-3.11.0-linux-x86_64-gnu                   <download available>
    graalpy-3.10.0-linux-x86_64-gnu                   <download available>
    graalpy-3.8.5-linux-x86_64-gnu                    <download available>

They’ve definitely saved me many hours of wasted time between uv and ruff.

Agreed, making the virtual environment management and so much else disappear lets so much more focus go to python itself.

This, but I want a summary about the 3 hour video first before getting spending the time on it.

Download -> generate subtitles -> feed to AI for summary works pretty well

You'll probably like Whisper Live and it's browser extensions: https://github.com/collabora/WhisperLive?tab=readme-ov-file#...

Start playing a YouTube video in the browser, select "start capture" in the extension, and it starts writing subtitles in white text on a black background below the video. When you stop capturing you can download the subtitles as a standard .srt file.

IF the dialog is badly recorded or unintelligible speech, how would a transcription process get it correct?

I did this as recently as today, for that reason, using ffmpeg and whisper.cpp. But not on the fly. I ran it on a few videos to generate VTT files.

> input.mp3

Thanks but I'm looking for live diarization.

I used diarization in https://github.com/jhj0517/Whisper-WebUI last night and once it downloads the model from HuggingFace it runs offline (it claims).

Or at least more details. Very cool!

You only need the ASR bits -- this is where I got to when I previously looked into running Parakeet:

    # NeMo does not run on 3.13+
    python3.12 -m venv .venv
    source .venv/bin/activate

    git clone https://github.com/NVIDIA/NeMo.git nemo
    cd nemo

    pip install torch torchaudio torchvision --index-url https://download.pytorch.org/whl/cu128
    pip install .[asr]

    deactivate

    import os
    import sys
    import nemo.collections.asr as nemo_asr

    model_path = sys.argv[1]
    audio_path = sys.argv[2]

    # Load from a local path...
    asr_model = nemo_asr.models.EncDecRNNTBPEModel.restore_from(restore_path=model_path)

    # Or download from huggingface ('org/model')...
    asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained(model_name=model_path)

    output = asr_moel.transcribe([audio_path])
    print(output[0])

You'll need to modify the python script to process the response and output it in a format you can use.