Batch capacity optimization
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Description
首先，非常感谢制作如此优秀的软件。最喜欢批量操作了！
1、批量生成字幕中，如果导入很多视频，譬如我导入300多个运行时就会白屏，但是实际还是运行的。
2、批量生成字幕中，如果视频很多软件界面操作就会很卡，这是否与内存占用过高有关系？
3、批量生成字幕中，在选择中希望除了全选以外可以增加反选的功能，300多个视频在卡顿的情况下选择其中几个再运行耗费很久时间去点击。
4、模型使用过程中添加提示词隐藏的太深，除了第一次显眼，再找到有点费劲
5、目前语音识别是本地模型，如果生成语音模型也是本地的话，只有翻译需要调用API了。这样除了API的费用就是软件费用了，在没有别的功能的情况下，目前非优惠的定价是否有些高了？
感谢你们的努力！
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points and combines batch processing, interface responsiveness, selection controls, prompt discoverability, local models, and pricing. Start by separating these requests and locating the batch subtitle workflow; done would require an agreed scope and acceptance criteria for the selected improvement.
Written by the indexing model from the issue text.
Assessment
- Domain
- ai, frontend, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100