Spaces:
Running
on
CPU Upgrade
Enable Space CI
Browse filesThis PR enables Space CI on your Space. **Gradio Space CI is a tool to create ephemeral Spaces for each PR opened on your Space repo.** The goal is to improve developer experience by making the review process as lean as possible.
### βοΈ How it works:
- Listens to pull requests events:
- If PR is opened => starts an ephemeral Space
- If PR is updated => updates the Space
- If PR is closed => deleted the Space
- Checks PR author:
- If trusted author => ephemeral Space is configured with variables, secrets and hardware.
- If not a trusted author => ephemeral Space is started without configuration.
- Space owners are trusted by default. Additional "trusted authors" can be configuration manually.
### β οΈ Before merging:
1. Check that the configuration is correct. By default the Space is configured to run ephemeral Spaces on a (free) CPU instance without any secrets.
2. You must set `HF_TOKEN` as a secret in your Space settings. Token must have 'write' permission. You can create a new one in your [User settings](https://huggingface.co/settings/token).
---
This is an automated PR created with https://huggingface.co/spaces/Wauplin/gradio-space-ci.
For more details about Space CI, checkout [this page]](https://huggingface.co/spaces/Wauplin/gradio-space-ci/blob/main/README.md).
If you find any issues, please report here: https://huggingface.co/spaces/Wauplin/gradio-space-ci/discussions
Feel free to ignore this PR.
- README.md +10 -6
- app.py +6 -0
- requirements.txt +2 -1
@@ -1,13 +1,17 @@
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---
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title: TTS Arena
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emoji: π
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colorFrom: blue
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colorTo: blue
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sdk: gradio
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app_file: app.py
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-
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tags:
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- leaderboard
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header: mini
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-
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-
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---
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title: TTS Arena
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sdk: gradio
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app_file: app.py
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license: zlib
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tags:
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- leaderboard
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emoji: π
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colorFrom: blue
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colorTo: blue
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pinned: true
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header: mini
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space_ci:
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trusted_authors: []
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secrets: []
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hardware: cpu-basic
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---
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@@ -14,6 +14,12 @@ import os
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import tempfile
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from pydub import AudioSegment
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toxicity = Detoxify('original')
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with open('harvard_sentences.txt') as f:
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sents = f.read().strip().splitlines()
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import tempfile
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from pydub import AudioSegment
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from gradio_space_ci import enable_space_ci
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enable_space_ci()
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toxicity = Detoxify('original')
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with open('harvard_sentences.txt') as f:
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sents = f.read().strip().splitlines()
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@@ -6,4 +6,5 @@ gradio_client
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git+https://github.com/unitaryai/detoxify
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pyloudnorm
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langdetect
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pydub
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git+https://github.com/unitaryai/detoxify
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pyloudnorm
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langdetect
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pydub
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gradio-space-ci @ git+https://huggingface.co/spaces/Wauplin/[email protected]
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