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@ -24,10 +24,10 @@ Find more info here for using liteLLM: https://github.com/BerriAI/litellm/blob/m
- Use `--openai_key` option to specify OpenAI API key. If you have multiple keys, separate them by commas (xxx,xxx,xxx) to reduce errors caused by API call limits. - Use `--openai_key` option to specify OpenAI API key. If you have multiple keys, separate them by commas (xxx,xxx,xxx) to reduce errors caused by API call limits.
Or, just set environment variable `BBM_OPENAI_API_KEY` instead. Or, just set environment variable `BBM_OPENAI_API_KEY` instead.
- A sample book, `test_books/animal_farm.epub`, is provided for testing purposes. - A sample book, `test_books/animal_farm.epub`, is provided for testing purposes.
- The default underlying model is [GPT-3.5-turbo](https://openai.com/blog/introducing-chatgpt-and-whisper-apis), which is used by ChatGPT currently. Use `--model gpt4` to change the underlying model to `GPT4`. - The default underlying model is [GPT-3.5-turbo](https://openai.com/blog/introducing-chatgpt-and-whisper-apis), which is used by ChatGPT currently. Use `--model gpt4` to change the underlying model to `GPT4`. You can also use `GPT4omini`.
- Important to note that `gpt-4` is significantly more expensive than `gpt-4-turbo`, but to avoid bumping into rate limits, we automatically balance queries across `gpt-4-1106-preview`, `gpt-4`, `gpt-4-32k`, `gpt-4-0613`,`gpt-4-32k-0613`. - Important to note that `gpt-4` is significantly more expensive than `gpt-4-turbo`, but to avoid bumping into rate limits, we automatically balance queries across `gpt-4-1106-preview`, `gpt-4`, `gpt-4-32k`, `gpt-4-0613`,`gpt-4-32k-0613`.
- If you want to use a specific model alias with OpenAI (eg `gpt-4-1106-preview` or `gpt-3.5-turbo-0125`), you can use `--model openai --model_list gpt-4-1106-preview,gpt-3.5-turbo-0125`. `--model_list` takes a comma-separated list of model aliases. - If you want to use a specific model alias with OpenAI (eg `gpt-4-1106-preview` or `gpt-3.5-turbo-0125`), you can use `--model openai --model_list gpt-4-1106-preview,gpt-3.5-turbo-0125`. `--model_list` takes a comma-separated list of model aliases.
- If using `GPT4`, you can add `--use_context` to add a context paragraph to each passage sent to the model for translation (see below). - If using chatgptapi, you can add `--use_context` to add a context paragraph to each passage sent to the model for translation (see below).
- Support DeepL model [DeepL Translator](https://rapidapi.com/splintPRO/api/dpl-translator) need pay to get the token use `--model deepl --deepl_key ${deepl_key}` - Support DeepL model [DeepL Translator](https://rapidapi.com/splintPRO/api/dpl-translator) need pay to get the token use `--model deepl --deepl_key ${deepl_key}`
- Support DeepL free model `--model deeplfree` - Support DeepL free model `--model deeplfree`
- Support Google [Gemini](https://makersuite.google.com/app/apikey) model `--model gemini --gemini_key ${gemini_key}` - Support Google [Gemini](https://makersuite.google.com/app/apikey) model `--model gemini --gemini_key ${gemini_key}`
@ -57,7 +57,11 @@ Find more info here for using liteLLM: https://github.com/BerriAI/litellm/blob/m
- `--accumulated_num` Wait for how many tokens have been accumulated before starting the translation. gpt3.5 limits the total_token to 4090. For example, if you use --accumulated_num 1600, maybe openai will - `--accumulated_num` Wait for how many tokens have been accumulated before starting the translation. gpt3.5 limits the total_token to 4090. For example, if you use --accumulated_num 1600, maybe openai will
output 2200 tokens and maybe 200 tokens for other messages in the system messages user messages, 1600+2200+200=4000, So you are close to reaching the limit. You have to choose your own output 2200 tokens and maybe 200 tokens for other messages in the system messages user messages, 1600+2200+200=4000, So you are close to reaching the limit. You have to choose your own
value, there is no way to know if the limit is reached before sending value, there is no way to know if the limit is reached before sending
- `--use_context` prompts the GPT4 model to create a one-paragraph summary. If it's the beginning of the translation, it will summarize the entire passage sent (the size depending on `--accumulated_num`), but if it's any proceeding passage, it will amend the summary to include details from the most recent passage, creating a running one-paragraph context payload of the important details of the entire translated work, which improves consistency of flow and tone of each translation. - `--use_context` prompts the model to create a three-paragraph summary. If it's the beginning of the translation, it will summarize the entire passage sent (the size depending on `--accumulated_num`). For subsequent passages, it will amend the summary to include details from the most recent passage, creating a running one-paragraph context payload of the important details of the entire translated work. This improves consistency of flow and tone throughout the translation. This option is available for all ChatGPT-compatible models.
- Use `--context_paragraph_limit` to set a limit on the number of context paragraphs when using the `--use_context` option.
- Use `--temperature` to set the temperature parameter for `chatgptapi`/`gpt4`/`claude` models. For example: `--temperature 0.7`.
- Use `--block_size` to merge multiple paragraphs into one block. This may increase accuracy and speed up the process but can disturb the original format. Must be used with `--single_translate`. For example: `--block_size 5`.
- Use `--single_translate` to output only the translated book without creating a bilingual version.
- `--translation_style` example: `--translation_style "color: #808080; font-style: italic;"` - `--translation_style` example: `--translation_style "color: #808080; font-style: italic;"`
- `--retranslate` `--retranslate "$translated_filepath" "file_name_in_epub" "start_str" "end_str"(optional)`<br> - `--retranslate` `--retranslate "$translated_filepath" "file_name_in_epub" "start_str" "end_str"(optional)`<br>
Retranslate from start_str to end_str's tag: Retranslate from start_str to end_str's tag: