@@ -23,13 +23,27 @@ from fastapi.responses import HTMLResponse, JSONResponse, StreamingResponse, Fil
from fastapi . staticfiles import StaticFiles
from pydantic import BaseModel , Field
from docutranslate import FileTranslater , __version__
# --- 核心代码重构后的新 Imports ---
from docutranslate . manager . base_manager import BaseManager
from docutranslate . manager . md_based_manager import MarkdownBasedManager
from docutranslate . manager . txt_manager import TXTManager
from docutranslate . manager . interfaces import HTMLExportable , MDFormatsExportable , TXTExportable
from docutranslate . converter . x2md . converter_docling import ConverterDoclingConfig
from docutranslate . converter . x2md . converter_mineru import ConverterMineruConfig
from docutranslate . exporter . md2x . md2html_exporter import MD2HTMLExportConfig
from docutranslate . exporter . txt2x . txt2html_exporter import TXT2HTMLExportConfig
from docutranslate . translater . base import AiTranslateConfig
from docutranslate . translater . md_translator import MDTranslateConfig
from docutranslate . translater . txt_translator import TXTTranslateConfig
# ------------------------------------
from docutranslate import __version__
from docutranslate . global_values import available_packages
from docutranslate . logger import global_logger
from docutranslate . translater import default_params
from docutranslate . utils . resource_utils import resource_path
# --- 全局配置 ---
# --- 全局配置 (MODIFIED) ---
tasks_state : Dict [ str , Dict [ str , Any ] ] = { }
tasks_log_queues : Dict [ str , asyncio . Queue ] = { }
tasks_log_histories : Dict [ str , List [ str ] ] = { }
@@ -37,18 +51,33 @@ MAX_LOG_HISTORY = 200
httpx_client : httpx . AsyncClient
# --- 辅助函数 ---
# --- 辅助函数 (MODIFIED) ---
def _create_default_task_state ( ) - > Dict [ str , Any ] :
""" 创建新的默认任务状态，存储 manager 实例而不是具体内容 """
return {
" is_processing " : False , " status_message " : " 空闲 " , " error_flag " : False ,
" download_ready " : False , " markdown_content " : None , " markdown_zip_content " : None ,
" html_content " : None , " original_filename_stem " : None , " task_start_time " : 0 ,
" download_ready " : False ,
" manager_instance " : None , # <--- 核心改动：存储翻译后的 Manager 实例
" original_filename_stem " : None , " task_start_time " : 0 ,
" task_end_time " : 0 , " current_task_ref " : None ,
" original_filename " : None ,
}
# --- 日志处理器 (修改： ) ---
# --- Manager 工厂函数 (NEW ) ---
def _get_manager_for_file ( filename : str , logger : logging . Logger ) - > BaseManager :
""" 根据文件名后缀选择并返回合适的 Manager 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 TXTManager。 " )
return TXTManager ( 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 MarkdownBasedManager。 " )
return MarkdownBasedManager ( 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 ) :
super ( ) . __init__ ( )
@@ -59,18 +88,12 @@ class QueueAndHistoryHandler(logging.Handler):
def emit ( self , record : logging . LogRecord ) :
log_entry = self . format ( record )
# 打印到控制台，
print ( f " [ { self . task_id } ] { log_entry } " )
# 添加到历史记录
self . history_list . append ( log_entry )
if len ( self . history_list ) > self . max_history :
del self . history_list [ : len ( self . history_list ) - self . max_history ]
# 放入异步队列供API拉取
if self . queue is not None :
try :
# 使用事件循环来安全地从线程（ ）
main_loop = getattr ( app . state , " main_event_loop " , None )
if main_loop and main_loop . is_running ( ) :
main_loop . call_soon_threadsafe ( self . queue . put_nowait , log_entry )
@@ -82,7 +105,7 @@ class QueueAndHistoryHandler(logging.Handler):
print ( f " [ { self . task_id } ] Error putting log to queue: { e } . Log: { log_entry } " )
# --- 应用生命周期事件 ---
# --- 应用生命周期事件 (保持不变) ---
@asynccontextmanager
async def lifespan ( app : FastAPI ) :
global httpx_client
@@ -91,75 +114,97 @@ async def lifespan(app: FastAPI):
tasks_state . clear ( )
tasks_log_queues . clear ( )
tasks_log_histories . clear ( )
# 全局日志器配置（如果需要）
global_logger . propagate = False
global_logger . setLevel ( logging . INFO )
print ( " 应用启动完成，多任务状态已初始化。 " )
yield
await httpx_client . aclose ( )
print ( " 应用关闭，资源已清理。 " )
# --- Background Task Logic (核心业务逻辑, 已修改 ) ---
# --- Background Task Logic (核心业务逻辑, 已重构 ) ---
async def _perform_translation ( task_id : str , params : Dict [ str , Any ] , file_contents : bytes , original_filename : str ) :
task_state = tasks_state [ task_id ]
log_queue = tasks_log_queues [ task_id ]
log_history = tasks_log_histories [ task_id ]
# 1. 为此任务创建一个独立的 logger
task_logger = logging . getLogger ( f " task. { task_id } " )
task_logger . setLevel ( logging . INFO )
task_logger . propagate = False # 关键：防止日志冒泡到 root logger，
# 如果 logger 已有 handlers (例如任务重试), 先清空
task_logger . propagate = False
if task_logger . hasHandlers ( ) :
task_logger . handlers . clear ( )
# 2. 创建一个 handler， （
task_handler = QueueAndHistoryHandler ( log_queue , log_history , MAX_LOG_HISTORY , task_id = task_id )
task_handler . setFormatter ( logging . Formatter ( ' %(asctime)s - %(levelname)s - %(message)s ' ) )
# 3. 将 handler 添加到独立的 task_logger
task_logger . addHandler ( task_handler )
task_logger . info ( f " 后台翻译任务开始: 文件 ' { original_filename } ' " )
task_state [ " status_message " ] = f " 正在处理 ' { original_filename } ' ... "
try :
task_logger . info ( f " 使用 Base URL: { params [ ' base_url ' ] } , Model: { params [ ' model_id ' ] } " )
# 4. 将独立的 task_logger 传递给 FileTranslater
ft = FileTranslater (
base_url = params [ ' base_url ' ] , key = params [ ' apikey ' ] , model_id = params [ ' model_id ' ] ,
chunk_size = params [ ' chunk_size ' ] , concurrent = params [ ' concurrent ' ] ,
temperature = params [ ' temperature ' ] , convert_engin = params [ ' convert_engin ' ] ,
try :
# 1. 选择合适的 Manager
manager = _get_manager_for_file ( original_filename , task_logger )
# 2. 从扁平化的 params 构建结构化的 Config 对象
ai_config = AiTranslateConfig (
base_url = params [ ' base_url ' ] ,
api_key = params [ ' apikey ' ] ,
model_id = params [ ' model_id ' ] ,
to_lang = params [ ' to_lang ' ] ,
custom_prompt = params [ ' custom_prompt_translate ' ] ,
temperature = params [ ' temperature ' ] ,
timeout = 2000 , # 保持默认或从params获取
chunk_size = params [ ' chunk_size ' ] ,
concurrent = params [ ' concurrent ' ] ,
logger = task_logger
)
# 3. 读取文件内容
file_stem = Path ( original_filename ) . stem
file_suffix = Path ( original_filename ) . suffix
manager . read_bytes ( content = file_contents , stem = file_stem , suffix = file_suffix )
# 4. 根据 Manager 类型执行不同的翻译流程
if isinstance ( manager , MarkdownBasedManager ) :
task_logger . info ( " 使用 Markdown 翻译流程。 " )
translate_config = MDTranslateConfig ( * * ai_config . __dict__ )
convert_engin = params [ ' convert_engin ' ]
convert_config = None
if convert_engin == ' mineru ' :
if not params . get ( ' mineru_token ' ) :
raise ValueError ( " 使用 ' mineru ' 引擎需要提供 ' mineru_token ' 。 " )
convert_config = ConverterMineruConfig (
mineru_token = params [ ' mineru_token ' ] ,
logger = task_logger # <--- 核心修改
formula = params [ ' formula_ocr ' ]
)
elif convert_engin == ' docling ' :
convert_config = ConverterDoclingConfig (
code = params [ ' code_ocr ' ] ,
formula = params [ ' formula_ocr ' ]
)
await ft . translate_bytes_ async (
name = original_filename , file = file_contents , to_lang = params [ ' to_lang ' ] ,
formula = params [ ' formula_ocr ' ] , code = params [ ' code_ocr ' ] ,
custom_prompt_translate = params [ ' custom_prompt_translate ' ] ,
refine = params [ ' refine_markdown ' ] , save = False
await manager . translate_async (
convert_engin = convert_engin ,
convert_config = convert_config ,
translate_config = translate_config
)
md_content = ft . export_to_markdown ( )
md_zip_content = await ft . export_to_unembed_markdown_async ( )
try :
await httpx_client . head ( " https://s4.zstatic.net/ajax/libs/KaTeX/0.16.9/contrib/auto-render.min.js " ,
timeout = 3 )
html_content = await ft . export_to_html_async ( title = task_state [ " original_filename_stem " ] , cdn = True )
except ( httpx . TimeoutException , httpx . RequestError ) :
task_logger . info ( " CDN连接失败， " )
html_content = await ft . export_to_html_async ( title = task_state [ " original_filename_stem " ] , cdn = False )
elif isinstance ( manager , TXTManager ) :
task_logger . info ( " 使用 TXT 翻译流程。 " )
translate_config = TXTTranslateConfig ( * * ai_config . __dict__ )
await manager . translate_async ( translate_config = translate_config )
else :
raise TypeError ( f " 不支持的 Manager 类型: { type ( manager ) . __name__ } " )
# 5. 任务成功，存储 manager 实例并更新状态
end_time = time . time ( )
duration = end_time - task_state [ " task_start_time " ]
task_state . update ( {
" markdown_content " : md_content , " markdown_zip_content " : md_zip_content ,
" html_content " : html_content , " " : f " 翻译成功！用时 { duration : .2f } 秒。 " ,
" download_ready " : True , " error_flag " : False , " task_end_time " : end_time ,
" manager_instance " : manager , # <--- 存储实例
" status_message " : f " 翻译成功！用时 { duration : .2f } 秒。 " ,
" download_ready " : True ,
" error_flag " : False ,
" task_end_time " : end_time ,
} )
task_logger . info ( f " 翻译成功完成，用时 { duration : .2f } 秒。 " )
@@ -168,9 +213,11 @@ async def _perform_translation(task_id: str, params: Dict[str, Any], file_conten
duration = end_time - task_state [ " task_start_time " ]
task_logger . info ( f " 翻译任务 ' { original_filename } ' 已被取消 (用时 { duration : .2f } 秒). " )
task_state . update ( {
" status_message " : f " 翻译任务已取消 (用时 { duration : .2f } 秒). " , " error_flag " : False ,
" download_ready " : False , " markdown_content " : None , " md_zip_content " : Non e,
" html_content " : None , " task_end_time " : end_tim e,
" status_message " : f " 翻译任务已取消 (用时 { duration : .2f } 秒). " ,
" error_flag " : Fals e,
" download_ready " : Fals e,
" manager_instance " : None ,
" task_end_time " : end_time ,
} )
except Exception as e :
@@ -180,19 +227,20 @@ async def _perform_translation(task_id: str, params: Dict[str, Any], file_conten
task_logger . error ( error_message , exc_info = True )
task_state . update ( {
" status_message " : f " 翻译过程中发生错误 (用时 { duration : .2f } 秒): { e } " ,
" error_flag " : True , " download_ready " : False , " markdown_content " : None ,
" md_zip_content " : None , " html_content " : None , " task_end_time " : end_tim e,
" error_flag " : True ,
" download_ready " : Fals e,
" manager_instance " : None ,
" task_end_time " : end_time ,
} )
finally :
task_state [ " is_processing " ] = False
task_state [ " current_task_ref " ] = None
task_logger . info ( f " 后台翻译任务 ' { original_filename } ' 处理结束。 " )
# 清理 handler，
task_logger . removeHandler ( task_handler )
# --- 核心任务启动与取消逻辑 (无修改 ) ---
# --- 核心任务启动与取消逻辑 (保持不变 ) ---
async def _start_translation_task (
task_id : str ,
params : Dict [ str , Any ] ,
@@ -211,7 +259,7 @@ async def _start_translation_task(
task_state [ " is_processing " ] = True
task_state . update ( {
" status_message " : " 任务初始化中... " , " error_flag " : False , " download_ready " : False ,
" markdown_content " : None , " md_zip_content " : None , " html_content " : None ,
" manager_instance " : None , # 重置
" original_filename_stem " : Path ( original_filename ) . stem ,
" original_filename " : original_filename ,
" task_start_time " : time . time ( ) , " task_end_time " : 0 , " current_task_ref " : None ,
@@ -227,7 +275,7 @@ async def _start_translation_task(
break
initial_log_msg = f " 收到新的翻译请求: { original_filename } "
print ( f " [ { task_id } ] { initial_log_msg } " ) # 初始消息直接打印
print ( f " [ { task_id } ] { initial_log_msg } " )
log_history . append ( initial_log_msg )
await log_queue . put ( initial_log_msg )
@@ -261,7 +309,7 @@ def _cancel_translation_logic(task_id: str):
return { " cancelled " : True , " message " : " 取消请求已发送。请等待状态更新。 " }
# --- FastAPI 应用和路由设置 ---
# --- FastAPI 应用和路由设置 (保持不变) ---
tags_metadata = [
{
" name " : " Service API " ,
@@ -304,7 +352,6 @@ DocuTranslate 后端服务 API，
)
service_router = APIRouter ( prefix = " /service " , tags = [ " Service API " ] )
STATIC_DIR = resource_path ( " static " )
app . mount ( " /static " , StaticFiles ( directory = STATIC_DIR ) , name = " static " )
@@ -313,78 +360,32 @@ app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
# --- Pydantic Models for Service API (MODIFIED) ---
# ===================================================================
class TranslateServiceRequest ( BaseModel ) :
base_url : str = Field (
. . . ,
description = " LLM API的基础URL， " ,
examples = [ " https://api.openai.com/v1 " ]
)
apikey : str = Field (
. . . ,
description = " LLM API的密钥。 " ,
examples = [ " sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx " ]
)
model_id : str = Field (
. . . ,
description = " 要使用的LLM模型ID。 " ,
examples = [ " gpt-4o " , " gpt-4-turbo " , " llama3-70b-8192 " ]
)
to_lang : str = Field (
default = " 中文 " ,
description = " 目标翻译语言。 " ,
examples = [ " 简体中文 " , " English " , " 英语 " ]
)
formula_ocr : bool = Field (
default = True ,
description = " 是否对文档中的公式进行OCR识别和渲染。 "
)
code_ocr : bool = Field (
default = True ,
description = " 是否对文档中的代码块进行OCR识别。仅在使用 `docling` 引擎时有效。 "
)
refine_markdown : bool = Field (
default = False ,
description = " 是否在翻译前， ， "
)
convert_engin : str = Field (
" mineru " ,
description = " 文档解析和转换引擎。`mineru` 是默认的在线服务，`docling` 是可选的本地引擎（如果已安装）。 " ,
examples = [ " mineru " , " docling " ]
)
mineru_token : Optional [ str ] = Field (
default = None ,
description = " 当 `convert_engin` 设置为 ' mineru ' 时， " ,
examples = [ " your-secret-mineru-token " ]
)
chunk_size : int = Field (
default_params [ " chunk_size " ] ,
description = " 将文本分割的块大小（以字符为单位）。 " ,
examples = [ 3000 ]
)
concurrent : int = Field (
default_params [ " concurrent " ] ,
description = " 同时向LLM API发送的并发请求数量。增加此值可以加快翻译速度， " ,
examples = [ 10 ]
)
temperature : float = Field (
default_params [ " temperature " ] ,
description = " LLM的温度参数， （ ） ， （ " ,
examples = [ 0.1 ]
)
custom_prompt_translate : Optional [ str ] = Field (
default = None ,
description = " 用户自定义的翻译Prompt。可以提供额外的指令， " ,
examples = [ " 请将“DocuTranslate”保持原文， " ]
)
file_name : str = Field (
. . . ,
description = " 上传的原始文件名，包含扩展名。用于确定文件类型和生成输出文件名。 " ,
examples = [ " my_research_paper.pdf " ]
)
file_content : str = Field (
. . . ,
description = " Base64编码的文件内容。 " ,
examples = [ " JVBERi0xLjQKJeLjz9MKMSAwIG9iago8PAovVHlwZXMvUGFnZXM... " ]
base_url : str = Field ( . . . , description = " LLM API的基础URL。 " , examples = [ " https://api.openai.com/v1 " ] )
apikey : str = Field ( . . . , description = " LLM API的密钥。 " , examples = [ " sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx " ] )
model_id : str = Field ( . . . , description = " 要使用的LLM模型ID。 " , examples = [ " gpt-4o " ] )
to_lang : str = Field ( default = " 中文 " , description = " 目标翻译语言。 " , examples = [ " 简体中文 " , " English " ] )
# --- Converter Params ---
convert_engin : Literal [ " mineru " , " docling " , " auto " ] = Field (
" auto " ,
description = " 文档解析引擎。`mineru`在线服务, `docling`本地引擎, `auto`自动选择(优先mineru)。 " ,
examples = [ " mineru " , " docling " , " auto " ]
)
mineru_token : Optional [ str ] = Field ( None , description = " 当 `convert_engin` 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。 " )
code_ocr : bool = Field ( True , description = " 是否对代码块进行OCR识别。仅 `docling` 引擎有效。 " )
# --- Translator Params ---
chunk_size : int = Field ( default_params [ " chunk_size " ] , description = " 文本分割的块大小（字符）。 " )
concurrent : int = Field ( default_params [ " concurrent " ] , description = " 并发请求数。 " )
temperature : float = Field ( default_params [ " temperature " ] , description = " LLM温度参数。 " )
custom_prompt_translate : Optional [ str ] = Field ( None , description = " 用户自定义的翻译Prompt。 " )
# --- File Info ---
file_name : str = Field ( . . . , description = " 上传的原始文件名，含扩展名。 " , examples = [ " my_paper.pdf " ] )
file_content : str = Field ( . . . , description = " Base64编码的文件内容。 " , examples = [ " JVBERi0xLjQK... " ] )
# refine_markdown: bool = Field(False, description="[已废弃] 此功能在新版中已移除。")
class Config :
json_schema_extra = {
@@ -393,11 +394,10 @@ class TranslateServiceRequest(BaseModel):
" apikey " : " sk-your-api-key-here " ,
" model_id " : " gpt-4o " ,
" to_lang " : " 简体中文 " ,
" formula_ocr " : True ,
" code_ocr " : True ,
" refine_markdown " : False ,
" convert_engin " : " mineru " ,
" mineru_token " : " your-mineru-token-if-any " ,
" formula_ocr " : True ,
" code_ocr " : True ,
" chunk_size " : 3000 ,
" concurrent " : 10 ,
" temperature " : 0.1 ,
@@ -409,7 +409,7 @@ class TranslateServiceRequest(BaseModel):
# ===================================================================
# --- Service Endpoints (/service) (MODIFIED ) ---
# --- Service Endpoints (/service) (部分已重构 ) ---
# ===================================================================
@service_router.post (
@@ -453,6 +453,12 @@ async def service_translate(request: TranslateServiceRequest = Body(..., descrip
raise HTTPException ( status_code = 400 , detail = f " 无效的Base64文件内容: { e } " )
params = request . model_dump ( exclude = { ' file_name ' , ' file_content ' } )
# 自动选择引擎逻辑
if params [ ' convert_engin ' ] == ' auto ' :
params [ ' convert_engin ' ] = ' mineru ' if params . get ( ' mineru_token ' ) else ' docling '
print ( f " [ { task_id } ] 自动选择解析引擎: { params [ ' convert_engin ' ] } " )
try :
response_data = await _start_translation_task (
task_id = task_id ,
@@ -462,7 +468,6 @@ async def service_translate(request: TranslateServiceRequest = Body(..., descrip
)
return JSONResponse ( content = response_data )
except HTTPException as e :
# 重新包装为JSONResponse以匹配文档中的响应模型
if e . status_code == 429 :
return JSONResponse ( status_code = e . status_code , content = { " task_started " : False , " message " : e . detail } )
if e . status_code == 500 :
@@ -538,18 +543,15 @@ async def service_release_task(
task_state = tasks_state . get ( task_id )
message_parts = [ ]
# 如果任务正在运行，先取消它
if task_state and task_state . get ( " is_processing " ) and task_state . get ( " current_task_ref " ) :
try :
print ( f " [ { task_id } ] 任务正在进行中，将在释放前尝试取消。 " )
_cancel_translation_logic ( task_id )
message_parts . append ( " 任务已被取消。 " )
except HTTPException as e :
# 忽略取消失败的异常（例如任务已完成），因为我们的最终目标是释放资源
print ( f " [ { task_id } ] 取消任务时出现预期中的情况（可能已完成）: { e . detail } " )
message_parts . append ( f " 任务取消步骤已跳过（可能已完成或取消）。 " )
# 释放所有相关资源
tasks_state . pop ( task_id , None )
tasks_log_queues . pop ( task_id , None )
tasks_log_histories . pop ( task_id , None )
@@ -588,11 +590,7 @@ async def service_release_task(
" original_filename " : " annual_report_2023.pdf " ,
" task_start_time " : 1678886400.123 ,
" task_end_time " : 0 ,
" downloads " : {
" markdown " : None ,
" markdown_zip " : None ,
" html " : None
}
" downloads " : { }
}
} ,
" completed " : {
@@ -626,11 +624,7 @@ async def service_release_task(
" original_filename " : " annual_report_2023.pdf " ,
" task_start_time " : 1678886400.123 ,
" task_end_time " : 1678886445.793 ,
" downloads " : {
" markdown " : None ,
" markdown_zip " : None ,
" html " : None
}
" downloads " : { }
}
}
}
@@ -650,8 +644,17 @@ async def service_get_status(
if not task_state :
raise HTTPException ( status_code = 404 , detail = f " 找不到任务ID ' { task_id } ' 。 " )
def generate_service_url ( file_type ) :
return f " /service/download/ { task_id } / { file_type } " if task_state [ " download_ready " ] else None
# (MODIFIED) 动态生成可用的下载链接
downloads = { }
if task_state . get ( " download_ready " ) and task_state . get ( " manager_instance " ) :
manager = task_state [ " manager_instance " ]
if isinstance ( manager , HTMLExportable ) :
downloads [ " html " ] = f " /service/download/ { task_id } /html "
if isinstance ( manager , MDFormatsExportable ) :
downloads [ " markdown " ] = f " /service/download/ { task_id } /markdown "
downloads [ " markdown_zip " ] = f " /service/download/ { task_id } /markdown_zip "
if isinstance ( manager , TXTExportable ) :
downloads [ " txt " ] = f " /service/download/ { task_id } /txt "
return JSONResponse ( content = {
" task_id " : task_id ,
@@ -663,11 +666,7 @@ async def service_get_status(
" original_filename " : task_state . get ( " original_filename " ) ,
" task_start_time " : task_state [ " task_start_time " ] ,
" task_end_time " : task_state [ " task_end_time " ] ,
" downloads " : {
" markdown " : generate_service_url ( " markdown " ) ,
" markdown_zip " : generate_service_url ( " markdown_zip " ) ,
" html " : generate_service_url ( " html " ) ,
}
" downloads " : downloads
} )
@@ -711,7 +710,50 @@ async def service_get_logs(
return JSONResponse ( content = { " logs " : new_logs } )
FileType = Literal [ " markdown " , " markdown_zip " , " html " ]
FileType = Literal [ " markdown " , " markdown_zip " , " html " , " txt "
async def _get_content_from_manager ( task_id : str , file_type : FileType ) - > tuple [ bytes | str , str , str ] :
""" 辅助函数，从 manager 获取内容、媒体类型和文件名 """
task_state = tasks_state . get ( task_id )
if not task_state :
raise HTTPException ( status_code = 404 , detail = f " 找不到任务ID ' { task_id } ' 。 " )
if not task_state . get ( " download_ready " ) or not task_state . get ( " manager_instance " ) :
raise HTTPException ( status_code = 404 , detail = " 内容尚未准备好。 " )
manager : BaseManager = task_state [ " manager_instance " ]
filename_stem = task_state [ ' original_filename_stem ' ]
try :
if file_type == ' html ' and isinstance ( manager , HTMLExportable ) :
# 自动判断使用哪种 HTML Export Config
config = MD2HTMLExportConfig ( cdn = True ) if isinstance ( manager , MarkdownBasedManager ) else TXT2HTMLExportConfig ( cdn = True )
try :
# 尝试连接CDN，
await httpx_client . head ( " https://s4.zstatic.net/ajax/libs/KaTeX/0.16.9/contrib/auto-render.min.js " , timeout = 3 )
except ( httpx . TimeoutException , httpx . RequestError ) :
manager . logger . info ( " CDN连接失败， " )
if hasattr ( config , ' cdn ' ) :
config . cdn = False
content = manager . export_to_html ( config )
return content . encode ( ' utf-8 ' ) , " text/html; charset=utf-8 " , f " { filename_stem } _translated.html "
if file_type == ' markdown ' and isinstance ( manager , MDFormatsExportable ) :
md_content = manager . export_to_markdown ( )
return md_content . encode ( ' utf-8 ' ) , " text/markdown; charset=utf-8 " , f " { filename_stem } _translated.md "
if file_type == ' markdown_zip ' and isinstance ( manager , MDFormatsExportable ) :
return manager . export_to_markdown_zip ( ) , " application/zip " , f " { filename_stem } _translated.zip "
if file_type == ' txt ' and isinstance ( manager , TXTExportable ) :
txt_content = manager . export_to_txt ( )
return txt_content . encode ( ' utf-8 ' ) , " text/plain; charset=utf-8 " , f " { filename_stem } _translated.txt "
except Exception as e :
manager . logger . error ( f " 导出 { file_type } 时出错: { e } " , exc_info = True )
raise HTTPException ( status_code = 500 , detail = f " 导出 { file_type } 时发生内部错误: { e } " )
raise HTTPException ( status_code = 404 , detail = f " 此任务不支持导出 ' { file_type } ' 类型的文件。 " )
@service_router.get (
@@ -724,7 +766,8 @@ FileType = Literal["markdown", "markdown_zip", "html"]
" content " : {
" text/markdown " : { " schema " : { " type " : " string " , " format " : " binary " } } ,
" application/zip " : { " schema " : { " type " : " string " , " format " : " binary " } } ,
" text/html " : { " schema " : { " type " : " string " , " format " : " binary " } }
" text/html " : { " schema " : { " type " : " string " , " format " : " binary " } } ,
" text/plain " : { " schema " : { " type " : " string " , " format " : " binary " } } ,
}
} ,
404 : {
@@ -738,24 +781,9 @@ async def service_download_file(
file_type : FileType = FastApiPath ( . . . , description = " 要下载的文件类型。 " , examples = [ " html " ] )
) :
""" 根据任务ID和文件类型下载翻译结果。 """
task_state = tasks_state . get ( task_id )
if not task_state : raise HTTPException ( status_code = 404 , detail = f " 找不到任务ID ' { task_id } ' 。 " )
if not task_state [ " download_ready " ] : raise HTTPException ( status_code = 404 , detail = " 内容尚未准备好。 " )
content_map = {
" markdown " : ( task_state [ " markdown_content " ] , " text/markdown " ,
f " { task_state [ ' original_filename_stem ' ] } _translated.md " ) ,
" markdown_zip " : ( task_state [ " markdown_zip_content " ] , " application/zip " ,
f " { task_state [ ' original_filename_stem ' ] } _translated.zip " ) ,
" html " : ( task_state [ " html_content " ] , " text/html " , f " { task_state [ ' original_filename_stem ' ] } _translated.html " ) ,
}
if file_type not in content_map : raise HTTPException ( status_code = 404 , detail = " 无效的文件类型。 " )
content , media_type , filename = content_map [ file_type ]
if content is None : raise HTTPException ( status_code = 404 , detail = f " { file_type . capitalize ( ) } 内容不可用。 " )
content , media_type , filename = await _get_content_from_manager ( task_id , file_type )
headers = { " Content-Disposition " : f " attachment; filename*=UTF-8 ' ' { quote ( filename , safe = ' ' , encoding = ' utf-8 ' ) } " }
if isinstance ( content , str ) : return StreamingResponse ( io . StringIO ( content ) , media_type = media_type , headers = headers )
return StreamingResponse ( io . BytesIO ( content ) , media_type = media_type , headers = headers )
@@ -767,7 +795,7 @@ async def service_download_file(
- **返回结构**: JSON对象包含 `file_type`, `filename`, 和 `content` 三个字段。
- **内容编码**:
- 对于 `html` 和 `markdown` 类型, `content` 字段包含原始的文本内容。
- 对于 `html`, `markdown`, `txt` 类型, `content` 字段包含原始的文本内容。
- 对于 `markdown_zip` 类型, `content` 字段包含Base64编码后的字符串。
- **使用场景**: 适用于需要以编程方式处理文件内容及其元数据（如建议的文件名）的客户端。
- **下载就绪**: 调用前请通过状态接口确认 `download_ready` 为 `true`。
@@ -778,19 +806,11 @@ async def service_download_file(
" content " : {
" application/json " : {
" examples " : {
" markdown " : {
" summary " : " Markdown 内容 " ,
" value " : {
" file_type " : " markdown " ,
" original_filename " : " my_doc.pdf " ,
" content " : " # 标题 \n \n 这是翻译后的Markdown内容... "
}
} ,
" html " : {
" summary " : " HTML 内容 " ,
" value " : {
" file_type " : " html " ,
" original_filename " : " my_doc.pdf " ,
" original_filename " : " my_doc_translated.html " ,
" content " : " <h1>标题</h1><p>这是翻译后的HTML内容...</p> "
}
} ,
@@ -798,7 +818,7 @@ async def service_download_file(
" summary " : " ZIP 内容 (Base64) " ,
" value " : {
" file_type " : " markdown_zip " ,
" filename " : " my_doc.pdf " ,
" filename " : " my_doc_translated.zip " ,
" content " : " UEsDBBQAAAAIA... (base64-encoded string) "
}
}
@@ -807,7 +827,7 @@ async def service_download_file(
}
} ,
404 : {
" description " : " 资源未找到。可能的原因包括： " ,
" description " : " 资源未找到。 " ,
" content " : { " application/json " : { " example " : { " detail " : " 内容尚未准备好。 " } } }
} ,
}
@@ -817,30 +837,22 @@ async def service_content(
file_type : FileType = FastApiPath ( . . . , description = " 要获取内容的文件类型。 " , examples = [ " html " ] )
) :
""" 根据任务ID和文件类型， """
task_state = tasks_state . get ( task_id )
if not task_state :
raise HTTPException ( status_code = 404 , detail = f " 找不到任务ID ' { task_id } ' 。 " )
content , _ , filename = await _get_content_from_manager ( task_id , file_type )
if not task_ stat e[ " download_ready " ] :
raise HTTPException ( status_code = 404 , detail = " 内容尚未准备好。 " )
if isin stanc e( content , bytes ) :
try :
# For text-based formats, decode to string
final_content = content . decode ( ' utf-8 ' )
except UnicodeDecodeError :
# For binary formats (like zip), encode to Base64
final_content = base64 . b64encode ( content ) . decode ( ' utf-8 ' )
else : # Should not happen with current _get_content_from_manager, but for safety
final_content = content
content_map = {
" markdown " : ( task_state . get ( " markdown_content " ) , task_state [ ' original_filename ' ] ) ,
" markdown_zip " : ( task_state . get ( " markdown_zip_content " ) , task_state [ ' original_filename ' ] ) ,
" html " : ( task_state . get ( " html_content " ) , task_state [ ' original_filename ' ] ) ,
}
raw_content , filename = content_map . get ( file_type , ( None , None ) )
if raw_content is None :
raise HTTPException ( status_code = 404 , detail = f " ' { file_type } ' 类型的内容不可用或生成失败。 " )
# 如果内容是字节串 (zip)， ；
final_content = base64 . b64encode ( raw_content ) . decode ( ' utf-8 ' ) if isinstance ( raw_content , bytes ) else raw_content
return JSONResponse ( content = {
" file_type " : file_type ,
" original_ filename" : filename ,
" filename " : filename ,
" content " : final_content
} )
@@ -854,14 +866,15 @@ async def service_content(
responses = {
200 : {
" description " : " 成功返回可用引擎列表。 " ,
" content " : { " application/json " : { " example " : [ " mineru " , " docling " ] } }
" content " : { " application/json " : { " example " : [ " auto " , " " , " docling " ] } }
}
}
)
async def service_get_engin_list ( ) :
""" 返回可用的文档解析引擎列表。 """
engin_list = [ " mineru " ]
if available_packages . get ( " docling " ) : engin_list . append ( " docling " )
engin_list = [ " auto " , " " ]
if available_packages . get ( " docling " ) :
engin_list . append ( " docling " )
return JSONResponse ( content = engin_list )
@@ -952,10 +965,12 @@ async def custom_swagger_ui_html():
swagger_css_url = " /static/swagger/swagger.css " ,
)
@app.get ( app . swagger_ui_oauth2_redirect_url , include_in_schema = False )
async def swagger_ui_redirect ( ) :
return get_swagger_ui_oauth2_redirect_html ( )
@app.get ( " /redoc " , include_in_schema = False )
async def redoc_html ( ) :
return get_redoc_html (
@@ -963,10 +978,12 @@ async def redoc_html():
title = app . title + " - ReDoc " ,
redoc_js_url = " /static/redoc/redoc.js " ,
)
###
@app.post ( " /temp/translate " ,
summary = " [临时]同步翻译接口 " ,
summary = " [临时]同步翻译接口 (已重构) " ,
description = " 一个简单的、同步的翻译接口，用于快速测试。不涉及后台任务、状态管理或多格式输出。**不建议在生产环境中使用。** " ,
tags = [ " Temp " ] ,
responses = {
@@ -990,43 +1007,49 @@ async def temp_translate(
base_url : str = Body ( . . . , description = " LLM API的基础URL。 " , examples = [ " https://api.openai.com/v1 " ] ) ,
api_key : str = Body ( . . . , description = " LLM API的密钥。 " , examples = [ " sk-xxxxxxxxxx " ] ) ,
model_id : str = Body ( . . . , description = " 使用的模型ID。 " , examples = [ " gpt-4-turbo " ] ) ,
mineru_token : str = Body ( . . . , description = " Mineru引擎的Token。 " ) ,
mineru_token : Optional [ str ] = Body ( None , description = " Mineru引擎的Token。 " ) ,
file_name : str = Body ( . . . ,
description = " 文件名， ， " ,
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 | None Body ( default_params [ " temperature " ] , description = " ai翻译请求温度 " ) ,
temperature : float = Body ( default_params [ " temperature " ] , description = " ai翻译请求温度 " ) ,
chunk_size : int = Body ( default_params [ " chunk_size " ] , description = " 文本分块大小（ ） " ) ,
custom_prompt_translate : str | None = Body ( None , description = " 翻译自定义提示词 " ,
custom_prompt_translate : Optional [ str ] = Body ( None , description = " 翻译自定义提示词 " ,
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。 """
def is_base64 ( s ) :
try :
base64 . b64decode ( s , validate = True )
return True
decoded_content = base64 . b64decode ( file_content )
except ( ValueError , binascii . Error ) :
return False
decoded_content = file_content . encode ( ' utf-8 ' )
ft = FileTranslater ( base_url = base_url ,
key = api_key ,
model_id = model_id ,
mineru_token = mineru_token ,
concurrent = concurrent ,
temperature = temperature ,
chunk_size = chunk_size ,
try :
manager = _get_manager_for_file ( file_name , global_logger )
ai_config = AiTranslateConfig (
base_url = base_url , api_key = api_key , model_id = model_id , to_lang = to_lang ,
custom_prompt = custom_prompt_translate , temperature = temperature ,
chunk_size = chunk_size , concurrent = concurrent , logger = global_logger , timeout = 2000
)
try :
decoded_content = base64 . b64decode ( file_content ) if is_base64 ( file_content ) else file_content . encode ( ' utf-8 ' )
await ft . translate_bytes_asy nc( name = file_name , file = decoded_content , to_lang = to_lang , save = False ,
custom_prompt_translate = custom_prompt_translate )
return { " success " : True , " content " : ft . export_to_markdown ( ) }
manager . read_bytes ( decoded_content , Path ( file_name ) . stem , Path ( file_name ) . suffix )
if isinsta nce ( manager , MarkdownBasedManager ) :
translate_config = MDTranslateConfig ( * * ai_config . __dict__ )
convert_config = ConverterMineruConfig ( mineru_token = mineru_token ) if mineru_token else None
convert_engin = ' mineru ' if mineru_token else None
await manager . translate_async ( convert_engin , convert_config , translate_config )
return { " success " : True , " content " : manager . document_translated . get_text ( ) }
elif isinstance ( manager , TXTManager ) :
translate_config = TXTTranslateConfig ( * * ai_config . __dict__ )
await manager . translate_async ( translate_config )
return { " success " : True , " content " : manager . export_to_txt ( ) }
except Exception as e :
print ( f " 翻译 出现错误：{ e . __repr__ ( ) } " )
print ( f " 临时翻译接口 出现错误：{ e . __repr__ ( ) } " )
return { " success " : False , " reason " : e . __repr__ ( ) }
@@ -1050,7 +1073,7 @@ def run_app(port: int | None = None):
print ( f " 正在启动 DocuTranslate WebUI 版本号： { __version__ } \n " )
print ( f " 服务接口文档: http://127.0.0.1: { port_to_use } /docs \n " )
print ( f " 请用浏览器访问 http://127.0.0.1: { port_to_use } \n " )
uvicorn . run ( app , host = None , port = port_to_use , workers = 1 )
uvicorn . run ( app , host = " 0.0.0.0 " , port = port_to_use , workers = 1 )
except Exception as e :
print ( f " 启动失败: { e } " )
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