github/bilingual_book_maker
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reformat python script

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Cangming H 2025-03-11 12:32:34 +08:00
parent cf992aef70
commit b83ac10e88
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2 changed files with 44 additions and 19 deletions
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46
book_maker/cli.py
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@ -17,6 +17,7 @@ def parse_prompt_arg(prompt_arg):
if prompt_arg.endswith(".md") and os.path.exists(prompt_arg): if prompt_arg.endswith(".md") and os.path.exists(prompt_arg):
try: try:
from promptdown import StructuredPrompt from promptdown import StructuredPrompt
structured_prompt = StructuredPrompt.from_promptdown_file(prompt_arg) structured_prompt = StructuredPrompt.from_promptdown_file(prompt_arg)
# Initialize our prompt structure # Initialize our prompt structure
@ -24,27 +25,40 @@ def parse_prompt_arg(prompt_arg):
# Handle developer_message or system_message # Handle developer_message or system_message
# Developer message takes precedence if both are present # Developer message takes precedence if both are present
if hasattr(structured_prompt, 'developer_message') and structured_prompt.developer_message: if (
prompt['system'] = structured_prompt.developer_message hasattr(structured_prompt, "developer_message")
elif hasattr(structured_prompt, 'system_message') and structured_prompt.system_message: and structured_prompt.developer_message
prompt['system'] = structured_prompt.system_message ):
prompt["system"] = structured_prompt.developer_message
elif (
hasattr(structured_prompt, "system_message")
and structured_prompt.system_message
):
prompt["system"] = structured_prompt.system_message
# Extract user message from conversation # Extract user message from conversation
if hasattr(structured_prompt, 'conversation') and structured_prompt.conversation: if (
hasattr(structured_prompt, "conversation")
and structured_prompt.conversation
):
for message in structured_prompt.conversation: for message in structured_prompt.conversation:
if message.role.lower() == 'user': if message.role.lower() == "user":
prompt['user'] = message.content prompt["user"] = message.content
break break
# Ensure we found a user message # Ensure we found a user message
if 'user' not in prompt or not prompt['user']: if "user" not in prompt or not prompt["user"]:
raise ValueError("PromptDown file must contain at least one user message") raise ValueError(
"PromptDown file must contain at least one user message"
)
print(f"Successfully loaded PromptDown file: {prompt_arg}") print(f"Successfully loaded PromptDown file: {prompt_arg}")
# Validate required placeholders # Validate required placeholders
if any(c not in prompt["user"] for c in ["{text}"]): if any(c not in prompt["user"] for c in ["{text}"]):
raise ValueError("User message in PromptDown must contain `{text}` placeholder") raise ValueError(
"User message in PromptDown must contain `{text}` placeholder"
)
return prompt return prompt
except Exception as e: except Exception as e:
@ -388,7 +402,17 @@ So you are close to reaching the limit. You have to choose your own value, there
translate_model = MODEL_DICT.get(options.model) translate_model = MODEL_DICT.get(options.model)
assert translate_model is not None, "unsupported model" assert translate_model is not None, "unsupported model"
API_KEY = "" API_KEY = ""
if options.model in ["openai", "chatgptapi", "gpt4", "gpt4omini", "gpt4o", "o1preview", "o1", "o1mini", "o3mini"]: if options.model in [
"openai",
"chatgptapi",
"gpt4",
"gpt4omini",
"gpt4o",
"o1preview",
"o1",
"o1mini",
"o3mini",
]:
if OPENAI_API_KEY := ( if OPENAI_API_KEY := (
options.openai_key options.openai_key
or env.get( or env.get(

1
book_maker/translator/chatgptapi_translator.py
View File

@ -64,6 +64,7 @@ O3MINI_MODEL_LIST = [
"o3-mini", "o3-mini",
] ]
class ChatGPTAPI(Base): class ChatGPTAPI(Base):
DEFAULT_PROMPT = "Please help me to translate,`{text}` to {language}, please return only translated content not include the origin text" DEFAULT_PROMPT = "Please help me to translate,`{text}` to {language}, please return only translated content not include the origin text"