- Enables OpenAI's reasoning models, o1 and o3, for translation.
- Switched to Google's newer genai SDK to enable support for Flash Thinking models
- Extracts reasoning content from the deepseek-reasoner model.
- Adds a new option under the OpenAI provider settings, reasoning effort - options are low, medium and high.
- Adds a max_toxens setting for DeepSeek, enabling generation of the full 8192 output tokens the model supports, rather than the default 4096.
- Changed the default temperature for DeepSeek to 1.3, which is what they recommend for translation (not sure why, seems high to me!)
Since reasoning models are tuned for reasoning they may score lower for "creative" tasks like translation. However, they may perform better with subtitles that contain OCR or transcription errors.
Note that there are additional costs with reasoning models in the form of reasoning tokens that do not form part of the final translations. The number of reasoning tokens generated is extracted from the response when available and can be viewed by double-clicking a translated batch and selecting the "Response" tab.
If the reasoning content is included in the response there will also be a Reasoning tab so you can see how the model thought about translating the subtitles with the provided context. This is currently only available for DeepSeek as the other providers do not expose the model's reasoning in the API.
Line 35: "一向是穿寬鞋賣大布" → "have always walked tall and proud," The idiom here is tricky. "穿寬鞋賣大布" literally is "wear wide shoes and sell big cloth," but idiomatically, it might mean acting confidently or with swagger.
Line 59: "2." – probably a scene number or a typo. Since subtitles don't usually have just numbers, maybe it's a misplaced line or part of a previous sentence. Maybe it's a misread of "二" (two), but in context, perhaps it's a card in a game, like "Two." But the next lines are about gambling ("梭" is "all-in" in poker). So maybe line #59 is "2." referring to a card, so translated as "Two."
Line 66: "今晚可以財色兼收了" – "財色兼收" means to obtain both wealth and beauty. So "Tonight I'll get both wealth and women!" fits the character's boastful tone.
o1 and o3 support a reasoning effort setting (available in the GUI settings when a reasoning model is selected). Higher effort implies higher hidden costs in the form of reasoning tokens.
NOTE: No MacOS release for this version due to PyInstaller issues again. Use version 1.0.4 or install from source.