Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

add speech-to-text to weekly dependency updates #65

Open
Tracked by #1
, #7
...
jmartin-sul opened this issue Dec 10, 2024 · 0 comments · May be fixed by sul-dlss/access-update-scripts#293
Open
Tracked by #1
, #7
...

add speech-to-text to weekly dependency updates #65

jmartin-sul opened this issue Dec 10, 2024 · 0 comments · May be fixed by sul-dlss/access-update-scripts#293
Assignees
@edsu
Labels
prod-blocker

Comments

@jmartin-sul
Copy link
Member

Here's an example from another Python project: https://github.com/sul-dlss/was-pywb/blob/main/.autoupdate/preupdate

That project uses Poetry, but rialto-airflow uses uv to manage dependencies, and we may want to consider adapting that example to uv. The author of this ticket is unsure of the pros/cons offhand, so part of the work for someone who isn't already familiar with both would be to ask for input from people who worked on rialto-airflow what they'd recommend, since that's the more recent of the two projects.
This was referenced Dec 10, 2024
Open
Open
@edsu edsu self-assigned this Jan 30, 2025
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
ccf7bca 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other Python
projects it probably makes sense to add here so that speech-to-text can
be tracked by infra-team's weekly dependency update process.

Closes #80
Refs #65
@edsu edsu mentioned this issue Jan 31, 2025
Merged
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
d722c6f 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other Python
projects it probably makes sense to add here so that speech-to-text can
be tracked by infra-team's weekly dependency update process.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
6946ed7 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other Python
projects it probably makes sense to add here so that speech-to-text can
be tracked by infra-team's weekly dependency update process.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
e2553aa 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other Python
projects it probably makes sense to add here so that speech-to-text can
be tracked by infra-team's weekly dependency update process.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
f9c5c0e 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
54c4858 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
a35f410 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
65506a9 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
ff2a40a 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
ad81408 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
847c186 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
0871c45 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
644e39e 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
43e9853 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
d7de070 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
d21e6fa 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
13e72ae 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
5b0e19e 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Jan 31, 2025
@edsu
Install dependencies with uv
49950f8 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Feb 3, 2025
@edsu
Install dependencies with uv
90f926f 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
edsu added a commit that referenced this issue Feb 3, 2025
@edsu
Install dependencies with uv
a6f2c1c 
We've been installing Python dependencies with Pip, and not tracking
their versions. Since we've started using uv in some other
infrastructure team Python projects it makes sense to add here so that
speech-to-text can be tracked by infra-team's weekly dependency update
process.

Unlike pip, uv always installs system specific Python wheels. There
wasn't a wheel available for triton (an openai-whisper's dependency)
under Python3.8 so the installation of dependencies failed.

So, in addition to adding uv this PR also upgrades our base Docker image
from `nvidia/cuda:12.1.0-devel-ubuntu20.04` to
`nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04` which allows us to install
python3.10 when we `apt install python3`.

Since this significantly change Whisper's behavior I wanted to be able to
compare the VTT transcript output before and after the Docker image
change. I added the start of a benchmarking system that will allow us to
compare the output of a set of 22 SDR items, with a previous benchmark.
Ideally this benchmark would be human vetted, and actually represent a
ground truth for what we believe the transcript should be. But for the
time being it is simply a snapshot in time of what the transcript looked
like today. See the benchmark/README.md file for details.

Closes #80
Refs #65
jmartin-sul added a commit to sul-dlss/access-update-scripts that referenced this issue Feb 7, 2025
@jmartin-sul
add speech-to-text service to weekly dependency updates
d0548cd 
it's a python project, but the update hook was already added in sul-dlss/speech-to-text#81

closes sul-dlss/speech-to-text#65
@jmartin-sul jmartin-sul linked a pull request Feb 7, 2025 that will close this issue
Draft
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees

@edsu edsu

Labels
prod-blocker
Projects
None yet
Milestone
No milestone
2 participants
@edsu @jmartin-sul