@@ -23,6 +23,7 @@ from pydantic import BaseModel, Field, field_validator
from docutranslate import __version__
from docutranslate . agents . agent import ThinkingMode
from docutranslate . cacher import md_based_convert_cacher
from docutranslate . exporter . md . types import ConvertEngineType
# --- 核心代码 Imports ---
from docutranslate . global_values . conditional_import import DOCLING_EXIST
from docutranslate . workflow . base import Workflow
@@ -70,23 +71,6 @@ def _create_default_task_state() -> Dict[str, Any]:
}
# --- [KEPT FOR TEMP ENDPOINT] 旧的 Workflow 工厂函数 (仅为临时接口保留) ---
def _get_workflow_for_file ( filename : str , logger : logging . Logger ) - > Workflow :
""" 根据文件名后缀选择并返回合适的 Workflow 实例。这是扩展点。 """
suffix = Path ( filename ) . suffix . lower ( )
if suffix == ' .txt ' :
logger . info ( " 检测到 .txt 文件，使用 TXTWorkflow。 " )
# 为临时接口创建虚拟config
return TXTWorkflow ( config = TXTWorkflowConfig ( translator_config = None , html_exporter_config = None , logger = logger ) )
else :
# 默认为基于 Markdown 的流程（处理 .pdf, .docx, .md 等）
logger . info ( f " 检测到 { suffix } 文件，使用 MarkdownBasedWorkflow。 " )
# 为临时接口创建虚拟config
return MarkdownBasedWorkflow ( config = MarkdownBasedWorkflowConfig (
convert_engine = None , converter_config = None , translator_config = None , html_exporter_config = None , logger = logger
) )
# --- 日志处理器 (保持不变) ---
class QueueAndHistoryHandler ( logging . Handler ) :
def __init__ ( self , queue_ref : asyncio . Queue , history_list_ref : List [ str ] , max_history_items : int , task_id : str ) :
@@ -192,6 +176,8 @@ class BaseWorkflowParams(BaseModel):
chunk_size : int = Field ( default = default_params [ " chunk_size " ] , description = " 文本分割的块大小（字符）。 " )
concurrent : int = Field ( default = default_params [ " concurrent " ] , description = " 并发请求数。 " )
temperature : float = Field ( default = default_params [ " temperature " ] , description = " LLM温度参数。 " )
thinking : ThinkingMode = Field ( default_params [ " thinking " ] , description = " 是否启用深度思考 " ,
examples = [ " default " , " enable " , " disable " ] ) ,
custom_prompt : Optional [ str ] = Field ( None , description = " 用户自定义的翻译Prompt。 " , alias = " custom_prompt " )
@@ -200,10 +186,10 @@ class MarkdownWorkflowParams(BaseWorkflowParams):
workflow_type : Literal [ ' markdown_based ' ] = Field ( . . . , description = " 指定使用基于Markdown的翻译工作流。 " )
# --- Markdown-specific Converter Params ---
convert_engine : Optional [ Literal [ " mineru " , " docling " ] ] = Field (
None ,
description = " 文档解析引擎。`mineru`在线服务, `docling`本地引擎。如果输入文件是.md， " ,
examples = [ " mineru " , " docling " ]
convert_engine : ConvertEngineType = Field (
" identity " ,
description = " 文档解析引擎。`identity`处理markdown文件,` mineru`在线服务, `docling`本地引擎。如果输入文件是.md， " ,
examples = [ " identity " , " " , " docling " ]
)
mineru_token : Optional [ str ] = Field ( None , description = " 当 `convert_engine` 为 ' mineru ' 时必填的API令牌。 " )
formula_ocr : bool = Field ( True , description = " 是否对公式进行OCR识别。对 `mineru` 和 `docling` 均有效。 " )
@@ -251,6 +237,7 @@ class TranslateServiceRequest(BaseModel):
" chunk_size " : 3000 ,
" concurrent " : 10 ,
" temperature " : 0.1 ,
" thinking " : " enable " ,
" custom_prompt " : " 将所有技术术语翻译为业界公认的中文对应词汇。 "
}
}
@@ -294,7 +281,7 @@ async def _perform_translation(
translator_config = MDTranslatorConfig (
* * payload . model_dump ( include = {
' base_url ' , ' api_key ' , ' model_id ' , ' to_lang ' , ' custom_prompt ' ,
' temperature ' , ' timeout ' , ' chunk_size ' , ' concurrent '
' temperature ' , ' thinking ' , ' ' , ' chunk_size ' , ' concurrent '
} , exclude_none = True )
)
@@ -328,7 +315,7 @@ async def _perform_translation(
translator_config = TXTTranslatorConfig (
* * payload . model_dump ( include = {
' base_url ' , ' api_key ' , ' model_id ' , ' to_lang ' , ' custom_prompt ' ,
' temperature ' , ' timeout ' , ' chunk_size ' , ' concurrent '
' temperature ' , ' thinking ' , ' ' , ' chunk_size ' , ' concurrent '
} , exclude_none = True )
)
@@ -1076,62 +1063,41 @@ async def temp_translate(
model_id : str = Body ( . . . , description = " 使用的模型ID。 " , examples = [ " gpt-4-turbo " ] ) ,
mineru_token : Optional [ str ] = Body ( None , description = " Mineru引擎的Token。 " ) ,
file_name : str = Body ( . . . ,
description = " 文件名，用以判断文件类型。当后缀为txt时该接口返回普通文本， " ,
description = " 文件名，用以判断文件类型。 " ,
examples = [ " test.txt " , " test.md " , " test.pdf " ] ) ,
file_content : str = Body ( . . . , description = " 文件内容， " ) ,
to_lang : str = Body ( " 中文 " , description = " 目标语言。 " , examples = [ " 中文 " , " 英文 " , " English " ] ) ,
concurrent : int = Body ( default_params [ " concurrent " ] , description = " ai翻译请求并发数 " ) ,
temperature : float = Body ( default_params [ " temperature " ] , description = " ai翻译请求温度 " ) ,
thinking : ThinkingMode = Body ( default_params [ " thinking " ] , description = " 是否启用深度思考 " , examples = [ " default " , " enable " , " disable " ] ) ,
thinking : ThinkingMode = Body ( default_params [ " thinking " ] , description = " 是否启用深度思考 " ,
examples = [ " default " , " enable " , " disable " ] ) ,
chunk_size : int = Body ( default_params [ " chunk_size " ] , description = " 文本分块大小（ ） " ) ,
custom_prompt : Optional [ str ] = Body ( None , description = " 翻译自定义提示词 " ,
examples = [ " 人名保持原文不翻译 " ] ) ,
examples = [ " 人名保持原文不翻译 " ] ) ,
) :
""" 一个用于快速测试的同步翻译接口。 """
file_name = Path ( file_name )
try :
decoded_content = base64 . b64decode ( file_content )
except ( ValueError , binascii . Error ) :
decoded_content = file_content . encode ( ' utf-8 ' )
try :
# [MODIFIED] 使用旧的辅助函数，仅为这个临时接口服务
workflow = _get_workflow_for_file ( file_name , global_logger )
workflow . read_bytes ( decoded_content , Path ( file_name ) . stem , Path ( file_name ) . suffix )
# Manually set up configs for the workflow instance for this temp endpoint
if isinstance ( workflow , MarkdownBasedWorkflow ) :
translator_config = MDTranslatorConfig (
base_url = base_url , api_key = api_key , model_id = model_id , to_lang = to_lang ,
custom_prompt = custom_prompt , temperature = temperature , thinking = thinking ,
chunk_size = chunk_size , concurrent = concurrent , logger = global_logger , timeout = 2000
)
convert _config = ConverterMineruConfig ( mineru_token = mineru_token ,
f ormula_ocr = True ) if mineru_token else None
# Update workflow's internal config for translate() to work
workflow . config . translator_config = translator_config
workflow . config . converter_config = convert_config
workflow . config . convert_engine = ' mineru ' if mineru_token and convert_config else ' identity '
await workflow . translate_async ( )
return { " success " : True , " content " : workflow . export_to_markdown ( ) }
elif isinstance ( workflow , TXTWorkflow ) :
translator_config = TXTTranslatorConfig (
base_url = base_url , api_key = api_key , model_id = model_id , to_lang = to_lang ,
custom_prompt = custom_prompt , temperature = temperature , thinking = thinking ,
chunk_size = chunk_size , concurrent = concurrent , logger = global_logger , timeout = 2000
)
# Update workflow's internal config
workflow . config . translator_config = translator_config
await workflow . translate_async ( )
return { " success " : True , " content " : workflow . export_to_txt ( ) }
else :
raise NotImplementedError ( f " Temp endpoint does not support workflow type { type ( workflow ) . __name__ } " )
workflow_config = MarkdownBasedWorkflowConfig ( convert_engine = " mineru " ,
converter_config = ConverterMineruConfig ( mineru_token = mineru_token ) ,
translator_config = MDTranslatorConfig ( base_url = base_url ,
api_key = api_key ,
model_id = model_id ,
to_lang = to_lang ,
custom_prompt = custom_prompt ,
temperature = temperature ,
thinking = thinking ,
chunk_size = chunk_size ,
concurrent = concurrent ) ,
html_exporter _config = MD2HTMLExporterConfig ( ) )
w orkflow = MarkdownBasedWorkflow ( workflow_config )
workflow . read_bytes ( content = decoded_content , stem = file_name . stem , suffix = file_name . stem )
return { " success " : True , " content " : workflow . export_to_markdown ( ) }
except Exception as e :
global_logger . error ( f " 临时翻译接口出现错误： { e . __repr__ ( ) } " , exc_info = True )
return { " success " : False , " reason " : e . __repr__ ( ) }
@@ -1163,4 +1129,4 @@ def run_app(port: int | None = None):
if __name__ == " __main__ " :
run_app ( )
run_app ( )
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