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Releases: timerring/bilive

v0.2.8

27 Dec 07:00
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What's Changed

This version fixes some known issues.

Full Changelog: v0.2.7...v0.2.8

v0.2.7

13 Dec 13:52
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What's Changed

This version deploys the bilive documentation, optimizes the rendering effect and refactors the configurations.
🎉 Now the formal version has been released!

Full Changelog: v0.2.6...v0.2.7

v0.2.6

10 Dec 13:43
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What's Changed

🎉 Now the production version is released!
This version mainly fixes some known issues, and completed the pipeline mode, which makes full use of the computing resources and can increase performance by around 20%!

Full Changelog: v0.2.5...v0.2.6

v0.2.5

07 Dec 13:04
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What's Changed

This version has completed the refactoring of the project in Python, modularized every part and rewritten some process logic. Additionally, some new features have been added, such as querying hot search suggestions from Bilibili's API and generating upload templates from video metadata, thus avoiding complex configurations.

🎉 Now the production version is released!
Full Changelog: v0.2.4...v0.2.5

v0.2.4

03 Dec 04:57
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🎉 This release version generally completes the Automatic Speech Recognition via OpenAI Whisper model, and refactors the whole process as well as optimizing the workflow.

Full Changelog: v0.2.3...v0.2.4

v0.2.3

27 Nov 13:18
29ea0e0
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What's Changed

If you have never used bilive, I'd recommend you start with this version.
The refactoring work along with merging dev and production version is extremely massive, which makes the project more accessible.
🎉 Now, I am glad to say, the production version is ready.
Full Changelog: v0.2.2...v0.2.3

v0.2.2

21 Nov 11:32
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This version mainly refactors the project to make it more user-friendly.

Full Changelog: v0.2.1...v0.2.2

v0.2.1

17 Nov 15:12
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Full Changelog: v0.2.0...v0.2.1

v0.2.0

08 Nov 09:10
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🎉 This is an archive of new version v0.2.0. We release this new version as the formal production version.
Compared to the last production version, we have:

  • Basically realized the L4 automation via completing the danmaku burning process and uploading queue process.
    • In the danmaku burning process, we mainly check if there are the video segments in the same date and hour. If there are, they will be burned with danmaku and merged together.
    • In the uploading queue process, we use a queue to arrange the order of uploading. Since the bandwidth is limited, I think split or parallel uploading is of no use. The aim is to upload the video as soon as possible.
  • Besides, there are other rules considering bug fixing, I won’t elaborate further here. These make this project more fault-tolerance.

v0.1.7

08 Nov 08:24
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What's Changed

This is the last version of v0.1.x. And a new Major Version is coming!🚀

Full Changelog: v0.1.6...v0.1.7