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feat: support claude model (#267)
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@ -21,6 +21,7 @@ bilingual_book_maker 是一个 AI 翻译工具,使用 ChatGPT 帮助用户制
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- 本地放了一个 `test_books/animal_farm.epub` 给大家测试
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- 默认用了 [GPT-3.5-turbo](https://openai.com/blog/introducing-chatgpt-and-whisper-apis) 模型,也就是 ChatGPT 正在使用的模型,用 `--model gpt3` 来使用 gpt3 模型
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- 可以使用 DeepL 封装的 api 进行翻译,需要付费,[DeepL Translator](https://rapidapi.com/splintPRO/api/deepl-translator) 来获得 token `--model deepl --deepl_key ${deepl_key}`
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- 可以使用 [Claude](https://console.anthropic.com/docs) 模型进行翻译 `--model claude --claude_key ${claude_key}`
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- 可以使用 google 来翻译 `--model google`
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- 可用使用彩云进行翻译 `--model caiyun --caiyun_key ${caiyun_key}`
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- 使用 `--test` 命令如果大家没付费可以加上这个先看看效果(有 limit 稍微有些慢)
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@ -62,8 +63,10 @@ export OPENAI_API_KEY=${your_api_key}
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python3 make_book.py --book_name test_books/animal_farm.epub --model gpt3 --language ja
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# Use the DeepL model with Japanese
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python3 make_book.py --book_name test_books/animal_farm.epub --model deepl --deepl_token ${deepl_key}--language ja
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python3 make_book.py --book_name test_books/animal_farm.epub --model deepl --deepl_key ${deepl_key} --language ja
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# Use the Claude model with Japanese
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python3 make_book.py --book_name test_books/animal_farm.epub --model claude --claude_key ${claude_key} --language ja
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# Translate contents in <div> and <p>
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python3 make_book.py --book_name test_books/animal_farm.epub --translate-tags div,p
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@ -20,7 +20,8 @@ The bilingual_book_maker is an AI translation tool that uses ChatGPT to assist u
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Or, just set environment variable `BMM_OPENAI_API_KEY` instead.
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- A sample book, `test_books/animal_farm.epub`, is provided for testing purposes.
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- 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 gpt3` to change the underlying model to `GPT3`
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5. support DeepL model [DeepL Translator](https://rapidapi.com/splintPRO/api/deepl-translator) need pay to get the token use `--model deepl --deepl_key ${deepl_key}`
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- Support DeepL model [DeepL Translator](https://rapidapi.com/splintPRO/api/deepl-translator) need pay to get the token use `--model deepl --deepl_key ${deepl_key}`
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- Support [Claude](https://console.anthropic.com/docs) model, use `--model claude --claude_key ${claude_key}`
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- Use `--test` option to preview the result if you haven't paid for the service. Note that there is a limit and it may take some time.
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- Set the target language like `--language "Simplified Chinese"`. Default target language is `"Simplified Chinese"`.
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Read available languages by helper message: `python make_book.py --help`
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@ -70,8 +71,10 @@ export OPENAI_API_KEY=${your_api_key}
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python3 make_book.py --book_name test_books/animal_farm.epub --model gpt3 --language ja
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# Use the DeepL model with Japanese
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python3 make_book.py --book_name test_books/animal_farm.epub --model deepl --deepl_token ${deepl_token}--language ja
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python3 make_book.py --book_name test_books/animal_farm.epub --model deepl --deepl_key ${deepl_key} --language ja
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# Use the Claude model with Japanese
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python3 make_book.py --book_name test_books/animal_farm.epub --model claude --claude_key ${claude_key} --language ja
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# Translate contents in <div> and <p>
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python3 make_book.py --book_name test_books/animal_farm.epub --translate-tags div,p
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@ -92,6 +92,12 @@ def main():
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type=str,
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help="you can apply deepl key from here (https://rapidapi.com/splintPRO/api/deepl-translator",
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)
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parser.add_argument(
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"--claude_key",
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dest="claude_key",
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type=str,
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help="you can find claude key from here (https://console.anthropic.com/account/keys)",
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)
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parser.add_argument(
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"--test",
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@ -273,6 +279,10 @@ So you are close to reaching the limit. You have to choose your own value, there
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API_KEY = options.deepl_key or env.get("BBM_DEEPL_API_KEY")
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if not API_KEY:
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raise Exception("Please provid deepl key")
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elif options.model == "claude":
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API_KEY = options.claude_key or env.get("BBM_CLAUDE_API_KEY")
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if not API_KEY:
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raise Exception("Please provid claude key")
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else:
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API_KEY = ""
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@ -3,6 +3,7 @@ from book_maker.translator.chatgptapi_translator import ChatGPTAPI
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from book_maker.translator.deepl_translator import DeepL
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from book_maker.translator.google_translator import Google
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from book_maker.translator.gpt3_translator import GPT3
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from book_maker.translator.claude_translator import Claude
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MODEL_DICT = {
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"chatgptapi": ChatGPTAPI,
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@ -10,5 +11,6 @@ MODEL_DICT = {
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"google": Google,
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"caiyun": Caiyun,
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"deepl": DeepL,
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"claude": Claude,
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# add more here
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}
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52
book_maker/translator/claude_translator.py
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52
book_maker/translator/claude_translator.py
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@ -0,0 +1,52 @@
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import re
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import requests
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from rich import print
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from .base_translator import Base
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class Claude(Base):
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def __init__(
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self, key, language, api_base=None, prompt_template=None, **kwargs
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) -> None:
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super().__init__(key, language)
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self.api_url = (
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f"{api_base}v1/complete"
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if api_base
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else "https://api.anthropic.com/v1/complete"
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)
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self.headers = {
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"Content-Type": "application/json",
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"x-api-key": key,
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}
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self.data = {
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"prompt": "",
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"model": "claude-v1.3",
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"max_tokens_to_sample": 1024,
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"temperature": 1,
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"stop_sequences": ["\n\nHuman:"],
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}
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self.session = requests.session()
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self.language = language
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self.prompt_template = (
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prompt_template
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or "\n\nHuman: Help me translate the text within triple backticks into {language} and provide only the translated result.\n```{text}```\n\nAssistant: "
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)
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def rotate_key(self):
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pass
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def translate(self, text):
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print(text)
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self.rotate_key()
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self.data["prompt"] = self.prompt_template.format(
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text=text,
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language=self.language,
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)
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r = self.session.post(self.api_url, headers=self.headers, json=self.data)
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if not r.ok:
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return text
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t_text = r.json().get("completion").strip()
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print("[bold green]" + re.sub("\n{3,}", "\n\n", t_text) + "[/bold green]")
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return t_text
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