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This commit is contained in:
xunbu
2025-08-01 13:05:35 +08:00
parent fe2c199ee7
commit 89b1963b97
5 changed files with 147 additions and 99 deletions
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1
docutranslate/agents/markdown_agent.py
View File

@@ -47,6 +47,7 @@ code、latex和HTML保持结构
class MDTranslateAgent(Agent): class MDTranslateAgent(Agent):
def __init__(self, custom_prompt=None, to_lang="中文", **kwargs: Unpack[AgentArgs]): def __init__(self, custom_prompt=None, to_lang="中文", **kwargs: Unpack[AgentArgs]):
print(f"custom_prompt:{custom_prompt}")
super().__init__(**kwargs) super().__init__(**kwargs)
self.system_prompt = f""" self.system_prompt = f"""
# 角色 # 角色

1
docutranslate/agents/txt_agent.py
View File

@@ -10,6 +10,7 @@ class TXTTranslateAgentArgs(AgentArgs, total=True):
class TXTTranslateAgent(Agent): class TXTTranslateAgent(Agent):
def __init__(self, custom_prompt=None, to_lang="中文", **kwargs: Unpack[AgentArgs]): def __init__(self, custom_prompt=None, to_lang="中文", **kwargs: Unpack[AgentArgs]):
print(f"custom_prompt:{custom_prompt}")
super().__init__(**kwargs) super().__init__(**kwargs)
self.system_prompt = f""" self.system_prompt = f"""
# 角色 # 角色

238
docutranslate/app.py
View File

@@ -9,7 +9,7 @@ import time
import uuid import uuid
from contextlib import asynccontextmanager, closing from contextlib import asynccontextmanager, closing
from pathlib import Path from pathlib import Path
from typing import List, Dict, Any, Optional, Literal, Union, Annotated, TYPE_CHECKING from typing import List, Dict, Any, Optional, Literal, Union, Annotated, TYPE_CHECKING, Type
from urllib.parse import quote from urllib.parse import quote
import httpx import httpx
@@ -18,31 +18,31 @@ from fastapi import FastAPI, HTTPException, APIRouter, Body, Path as FastApiPath
from fastapi.openapi.docs import get_swagger_ui_html, get_swagger_ui_oauth2_redirect_html, get_redoc_html from fastapi.openapi.docs import get_swagger_ui_html, get_swagger_ui_oauth2_redirect_html, get_redoc_html
from fastapi.responses import HTMLResponse, JSONResponse, StreamingResponse, FileResponse from fastapi.responses import HTMLResponse, JSONResponse, StreamingResponse, FileResponse
from fastapi.staticfiles import StaticFiles from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, Field from pydantic import BaseModel, Field, field_validator
from docutranslate import __version__
from docutranslate.cacher import md_based_convert_cacher
# --- 核心代码 Imports ---
from docutranslate.global_values.conditional_import import DOCLING_EXIST from docutranslate.global_values.conditional_import import DOCLING_EXIST
# --- 核心代码重构后的新 Imports ---
from docutranslate.workflow.base import Workflow from docutranslate.workflow.base import Workflow
from docutranslate.workflow.interfaces import HTMLExportable, MDFormatsExportable, TXTExportable from docutranslate.workflow.interfaces import HTMLExportable, MDFormatsExportable, TXTExportable
from docutranslate.workflow.md_based_workflow import MarkdownBasedWorkflow from docutranslate.workflow.md_based_workflow import MarkdownBasedWorkflow, MarkdownBasedWorkflowConfig
from docutranslate.workflow.txt_workflow import TXTWorkflow from docutranslate.workflow.txt_workflow import TXTWorkflow, TXTWorkflowConfig
if DOCLING_EXIST or TYPE_CHECKING: if DOCLING_EXIST or TYPE_CHECKING:
from docutranslate.converter.x2md.converter_docling import ConverterDoclingConfig from docutranslate.converter.x2md.converter_docling import ConverterDoclingConfig
from docutranslate.converter.x2md.converter_mineru import ConverterMineruConfig from docutranslate.converter.x2md.converter_mineru import ConverterMineruConfig
from docutranslate.exporter.md.md2html_exporter import MD2HTMLExporterConfig from docutranslate.exporter.md.md2html_exporter import MD2HTMLExporterConfig
from docutranslate.exporter.txt.txt2html_exporter import TXT2HTMLExporterConfig from docutranslate.exporter.txt.txt2html_exporter import TXT2HTMLExporterConfig
from docutranslate.translator.base import AiTranslateConfig
from docutranslate.translator.ai_translator.md_translator import MDTranslatorConfig from docutranslate.translator.ai_translator.md_translator import MDTranslatorConfig
from docutranslate.translator.ai_translator.txt_translator import TXTTranslatorConfig from docutranslate.translator.ai_translator.txt_translator import TXTTranslatorConfig
# ------------------------------------ # ------------------------------------
from docutranslate import __version__
from docutranslate.logger import global_logger from docutranslate.logger import global_logger
from docutranslate.translator import default_params from docutranslate.translator import default_params
from docutranslate.utils.resource_utils import resource_path from docutranslate.utils.resource_utils import resource_path
# --- 全局配置 (MODIFIED) --- # --- 全局配置 ---
tasks_state: Dict[str, Dict[str, Any]] = {} tasks_state: Dict[str, Dict[str, Any]] = {}
tasks_log_queues: Dict[str, asyncio.Queue] = {} tasks_log_queues: Dict[str, asyncio.Queue] = {}
tasks_log_histories: Dict[str, List[str]] = {} tasks_log_histories: Dict[str, List[str]] = {}
@@ -50,13 +50,13 @@ MAX_LOG_HISTORY = 200
httpx_client: httpx.AsyncClient httpx_client: httpx.AsyncClient
# --- [NEW] Workflow字典 --- # --- [NEW] Workflow字典 ---
WORKFLOW_DICT: Dict[str, type[Workflow]] = { WORKFLOW_DICT: Dict[str, Type[Workflow]] = {
"markdown_based": MarkdownBasedWorkflow, "markdown_based": MarkdownBasedWorkflow,
"txt": TXTWorkflow, "txt": TXTWorkflow,
} }
# --- 辅助函数 (MODIFIED) --- # --- 辅助函数 ---
def _create_default_task_state() -> Dict[str, Any]: def _create_default_task_state() -> Dict[str, Any]:
"""创建新的默认任务状态，存储 workflow 实例而不是具体内容""" """创建新的默认任务状态，存储 workflow 实例而不是具体内容"""
return { return {
@@ -69,17 +69,21 @@ def _create_default_task_state() -> Dict[str, Any]:
} }
# --- [KEPT FOR TEMP ENDPOINT] Workflow 工厂函数 (旧逻辑，仅为临时接口保留) --- # --- [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: 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。""" """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() suffix = Path(filename).suffix.lower()
if suffix == '.txt': if suffix == '.txt':
logger.info("检测到 .txt 文件，使用 Workflow。") logger.info("检测到 .txt 文件，使用 TXTWorkflow。")
return TXTWorkflow(logger=logger) # 为临时接口创建虚拟config
return TXTWorkflow(config=TXTWorkflowConfig(translator_config=None, html_exporter_config=None, logger=logger))
else: else:
# 默认为基于 Markdown 的流程（处理 .pdf, .docx, .md 等） # 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。") logger.info(f"检测到 {suffix} 文件，使用 MarkdownBasedWorkflow。")
return MarkdownBasedWorkflow(logger=logger) # 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) --- # --- 日志处理器 (保持不变) ---
@@ -181,13 +185,13 @@ app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
# 1. 定义所有工作流共享的基础参数 # 1. 定义所有工作流共享的基础参数
class BaseWorkflowParams(BaseModel): class BaseWorkflowParams(BaseModel):
base_url: str = Field(..., description="LLM API的基础URL。", examples=["https://api.openai.com/v1"]) 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"]) api_key: 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"]) 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"]) to_lang: str = Field(default="中文", description="目标翻译语言。", examples=["简体中文", "English"])
chunk_size: int = Field(default_params["chunk_size"], description="文本分割的块大小（字符）。") chunk_size: int = Field(default=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。") concurrent: int = Field(default=default_params["concurrent"], description="并发请求数。")
temperature: float = Field(default_params["temperature"], description="LLM温度参数。") temperature: float = Field(default=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。") custom_prompt: Optional[str] = Field(None, description="用户自定义的翻译Prompt。", alias="custom_prompt")
# 2. 为每个工作流创建独立的参数模型 # 2. 为每个工作流创建独立的参数模型
@@ -195,19 +199,24 @@ class MarkdownWorkflowParams(BaseWorkflowParams):
workflow_type: Literal['markdown_based'] = Field(..., description="指定使用基于Markdown的翻译工作流。") workflow_type: Literal['markdown_based'] = Field(..., description="指定使用基于Markdown的翻译工作流。")
# --- Markdown-specific Converter Params --- # --- Markdown-specific Converter Params ---
convert_engin: Optional[Literal["mineru", "docling"]] = Field( convert_engine: Optional[Literal["mineru", "docling"]] = Field(
None, 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，此项可为`null`或不传。", 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，此项可为`null`或不传。",
examples=["mineru", "docling"] examples=["mineru", "docling"]
) )
mineru_token: Optional[str] = Field(None, description="当 `convert_engin` 为 'mineru' 时必填的API令牌。") 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。") 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。") code_ocr: bool = Field(True, description="是否对代码块进行OCR识别。仅 `docling` 引擎有效。")
@field_validator('mineru_token')
def check_mineru_token(cls, v, values):
if values.data.get('convert_engine') == 'mineru' and not v:
raise ValueError("当 `convert_engine` 为 'mineru' 时，`mineru_token` 字段是必须的。")
return v
class TextWorkflowParams(BaseWorkflowParams): class TextWorkflowParams(BaseWorkflowParams):
workflow_type: Literal['txt'] = Field(..., description="指定使用纯文本的翻译工作流。") workflow_type: Literal['txt'] = Field(..., description="指定使用纯文本的翻译工作流。")
# TXT 工作流没有额外的参数
# 3. 使用可辨识联合类型（Discriminated Union）将它们组合起来 # 3. 使用可辨识联合类型（Discriminated Union）将它们组合起来
@@ -231,17 +240,17 @@ class TranslateServiceRequest(BaseModel):
"payload": { "payload": {
"workflow_type": "markdown_based", "workflow_type": "markdown_based",
"base_url": "https://api.openai.com/v1", "base_url": "https://api.openai.com/v1",
"apikey": "sk-your-api-key-here", "api_key": "sk-your-api-key-here",
"model_id": "gpt-4o", "model_id": "gpt-4o",
"to_lang": "简体中文", "to_lang": "简体中文",
"convert_engin": "mineru", "convert_engine": "mineru",
"mineru_token": "your-mineru-token-if-any", "mineru_token": "your-mineru-token-if-any",
"formula_ocr": True, "formula_ocr": True,
"code_ocr": True, "code_ocr": True,
"chunk_size": 3000, "chunk_size": 3000,
"concurrent": 10, "concurrent": 10,
"temperature": 0.1, "temperature": 0.1,
"custom_prompt_translate": "将所有技术术语翻译为业界公认的中文对应词汇。" "custom_prompt": "将所有技术术语翻译为业界公认的中文对应词汇。"
} }
} }
} }
@@ -271,66 +280,80 @@ async def _perform_translation(
task_state["status_message"] = f"正在处理 '{original_filename}'..." task_state["status_message"] = f"正在处理 '{original_filename}'..."
try: try:
# 1. 根据工作流类型选择合适的 Workflow # 1. 根据工作流类型选择合适的 Workflow Class
workflow_class = WORKFLOW_DICT.get(payload.workflow_type) workflow_class = WORKFLOW_DICT.get(payload.workflow_type)
if not workflow_class: if not workflow_class:
raise ValueError(f"不支持的工作流类型: '{payload.workflow_type}'") raise ValueError(f"不支持的工作流类型: '{payload.workflow_type}'")
workflow = workflow_class(logger=task_logger)
# 2. 从 payload 构建通用的 AiTranslateConfig workflow: Workflow
ai_config = AiTranslateConfig(
base_url=payload.base_url, # 2. 根据 payload 的具体类型构建配置并实例化 workflow (类型安全!)
api_key=payload.apikey, if isinstance(payload, MarkdownWorkflowParams):
model_id=payload.model_id, task_logger.info("构建 MarkdownBasedWorkflow 配置。")
to_lang=payload.to_lang, translator_config = MDTranslatorConfig(
custom_prompt=payload.custom_prompt_translate, **payload.model_dump(include={
temperature=payload.temperature, 'base_url', 'api_key', 'model_id', 'to_lang', 'custom_prompt',
timeout=2000, 'temperature', 'timeout', 'chunk_size', 'concurrent'
chunk_size=payload.chunk_size, }, exclude_none=True)
concurrent=payload.concurrent,
logger=task_logger
) )
# 3. 读取文件内容 converter_config = None
file_stem = Path(original_filename).stem if payload.convert_engine == 'mineru':
file_suffix = Path(original_filename).suffix converter_config = ConverterMineruConfig(
workflow.read_bytes(content=file_contents, stem=file_stem, suffix=file_suffix)
# 4. 根据 payload 的具体类型执行不同的翻译流程 (类型安全!)
if isinstance(payload, MarkdownWorkflowParams) and isinstance(workflow, MarkdownBasedWorkflow):
task_logger.info("执行 MarkdownBased 翻译流程。")
translate_config = MDTranslatorConfig(**ai_config.__dict__)
convert_config = None
if payload.convert_engin == 'mineru':
if not payload.mineru_token:
raise ValueError("使用 'mineru' 引擎需要提供 'mineru_token'。")
convert_config = ConverterMineruConfig(
mineru_token=payload.mineru_token, mineru_token=payload.mineru_token,
formula_ocr=payload.formula_ocr formula_ocr=payload.formula_ocr
) )
elif payload.convert_engin == 'docling': elif payload.convert_engine == 'docling' and DOCLING_EXIST:
convert_config = ConverterDoclingConfig( converter_config = ConverterDoclingConfig(
code_ocr=payload.code_ocr, code_ocr=payload.code_ocr,
formula_ocr=payload.formula_ocr formula_ocr=payload.formula_ocr
) )
await workflow.translate_async( # HTML导出器配置
convert_engin=payload.convert_engin, html_exporter_config = MD2HTMLExporterConfig(cdn=True)
convert_config=convert_config,
translate_config=translate_config # 创建完整的工作流配置
workflow_config = MarkdownBasedWorkflowConfig(
convert_engine=payload.convert_engine,
converter_config=converter_config,
translator_config=translator_config,
html_exporter_config=html_exporter_config,
logger=task_logger
)
workflow = MarkdownBasedWorkflow(config=workflow_config)
elif isinstance(payload, TextWorkflowParams):
task_logger.info("构建 TXTWorkflow 配置。")
translator_config = TXTTranslatorConfig(
**payload.model_dump(include={
'base_url', 'api_key', 'model_id', 'to_lang', 'custom_prompt',
'temperature', 'timeout', 'chunk_size', 'concurrent'
}, exclude_none=True)
) )
elif isinstance(payload, TextWorkflowParams) and isinstance(workflow, TXTWorkflow): # HTML导出器配置
task_logger.info("执行 TXT 翻译流程。") html_exporter_config = TXT2HTMLExporterConfig(cdn=True)
translate_config = TXTTranslatorConfig(**ai_config.__dict__)
await workflow.translate_async(translate_config=translate_config) # 创建完整的工作流配置
workflow_config = TXTWorkflowConfig(
translator_config=translator_config,
html_exporter_config=html_exporter_config,
logger=task_logger
)
workflow = TXTWorkflow(config=workflow_config)
else: else:
raise TypeError( raise TypeError(
f"工作流类型 '{payload.workflow_type}'与Workflow类型 '{type(workflow).__name__}' 不匹配或未实现。") f"工作流类型 '{payload.workflow_type}' 的处理逻辑未实现。")
# 5. 任务成功，存储 workflow 实例并更新状态 # 3. 读取文件内容并执行翻译
file_stem = Path(original_filename).stem
file_suffix = Path(original_filename).suffix
workflow.read_bytes(content=file_contents, stem=file_stem, suffix=file_suffix)
await workflow.translate_async() # Config is already set in __init__
# 4. 任务成功，存储 workflow 实例并更新状态
end_time = time.time() end_time = time.time()
duration = end_time - task_state["task_start_time"] duration = end_time - task_state["task_start_time"]
task_state.update({ task_state.update({
@@ -372,6 +395,8 @@ async def _perform_translation(
task_state["current_task_ref"] = None task_state["current_task_ref"] = None
task_logger.info(f"后台翻译任务 '{original_filename}' 处理结束。") task_logger.info(f"后台翻译任务 '{original_filename}' 处理结束。")
task_logger.removeHandler(task_handler) task_logger.removeHandler(task_handler)
# 清理缓存，防止内存泄漏
md_based_convert_cacher.clear()
# --- [MODIFIED] 核心任务启动逻辑 --- # --- [MODIFIED] 核心任务启动逻辑 ---
@@ -444,7 +469,7 @@ def _cancel_translation_logic(task_id: str):
# =================================================================== # ===================================================================
# --- Service Endpoints (/service) (部分已重构) --- # --- Service Endpoints (/service) (已重构) ---
# =================================================================== # ===================================================================
@service_router.post( @service_router.post(
@@ -709,8 +734,8 @@ async def service_get_status(
"content": {"application/json": { "content": {"application/json": {
"example": { "example": {
"logs": [ "logs": [
"2023-10-27 10:30:05 - INFO - 后台翻译任务开始: 文件 'annual_report_2023.pdf', 工作流: 'markdown'", "2023-10-27 10:30:05 - INFO - 后台翻译任务开始: 文件 'annual_report_2023.pdf', 工作流: 'markdown_based'",
"2023-10-27 10:30:05 - INFO - 执行 MarkdownBased 翻译流程。", "2023-10-27 10:30:05 - INFO - 构建 MarkdownBasedWorkflow 配置。",
"2023-10-27 10:30:15 - INFO - 正在转化为markdown", "2023-10-27 10:30:15 - INFO - 正在转化为markdown",
"2023-10-27 10:30:25 - INFO - markdown分为50块", "2023-10-27 10:30:25 - INFO - markdown分为50块",
"2023-10-27 10:30:30 - INFO - 正在翻译markdown" "2023-10-27 10:30:30 - INFO - 正在翻译markdown"
@@ -758,18 +783,25 @@ async def _get_content_from_workflow(task_id: str, file_type: FileType) -> tuple
media_type: str media_type: str
filename: str filename: str
if file_type == 'html' and isinstance(workflow, HTMLExportable): # 对于HTML导出，我们需要检查CDN的可用性
config = MD2HTMLExporterConfig(cdn=True) if isinstance(workflow, html_config = None
MarkdownBasedWorkflow) else TXT2HTMLExporterConfig( if file_type == 'html':
cdn=True) is_cdn_available = True
try: try:
# 检查一个常用的CDN资源
await httpx_client.head("https://s4.zstatic.net/ajax/libs/KaTeX/0.16.9/contrib/auto-render.min.js", await httpx_client.head("https://s4.zstatic.net/ajax/libs/KaTeX/0.16.9/contrib/auto-render.min.js",
timeout=3) timeout=3)
except (httpx.TimeoutException, httpx.RequestError): except (httpx.TimeoutException, httpx.RequestError):
workflow.logger.warning("CDN连接失败，使用本地JS进行渲染。") is_cdn_available = False
if hasattr(config, 'cdn'): workflow.config.logger.warning("CDN连接失败，将使用本地JS进行渲染。")
config.cdn = False
content_str = workflow.export_to_html(config) if isinstance(workflow, MarkdownBasedWorkflow):
html_config = MD2HTMLExporterConfig(cdn=is_cdn_available)
elif isinstance(workflow, TXTWorkflow):
html_config = TXT2HTMLExporterConfig(cdn=is_cdn_available)
if file_type == 'html' and isinstance(workflow, HTMLExportable):
content_str = workflow.export_to_html(html_config)
content_bytes, media_type, filename = content_str.encode( content_bytes, media_type, filename = content_str.encode(
'utf-8'), "text/html; charset=utf-8", f"{filename_stem}_translated.html" 'utf-8'), "text/html; charset=utf-8", f"{filename_stem}_translated.html"
@@ -792,7 +824,7 @@ async def _get_content_from_workflow(task_id: str, file_type: FileType) -> tuple
return content_bytes, media_type, filename return content_bytes, media_type, filename
except Exception as e: except Exception as e:
workflow.logger.error(f"导出 {file_type} 时出错: {e}", exc_info=True) workflow.config.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=500, detail=f"导出 {file_type} 时发生内部错误: {e}")
@@ -1016,9 +1048,8 @@ async def redoc_html():
### ###
@app.post("/temp/translate", @app.post("/temp/translate",
summary="[临时]同步翻译接口 (已重构)", summary="[临时]同步翻译接口",
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。**", 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"], tags=["Temp"],
responses={ responses={
@@ -1051,7 +1082,7 @@ async def temp_translate(
concurrent: int = Body(default_params["concurrent"], description="ai翻译请求并发数"), 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"), 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（bytes）"), chunk_size: int = Body(default_params["chunk_size"], description="文本分块大小（bytes）"),
custom_prompt_translate: Optional[str] = Body(None, description="翻译自定义提示词", 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。""" """一个用于快速测试的同步翻译接口。"""
@@ -1063,29 +1094,44 @@ async def temp_translate(
try: try:
# [MODIFIED] 使用旧的辅助函数，仅为这个临时接口服务 # [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 = _get_workflow_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
)
workflow.read_bytes(decoded_content, Path(file_name).stem, Path(file_name).suffix) 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): if isinstance(workflow, MarkdownBasedWorkflow):
translate_config = MDTranslatorConfig(**ai_config.__dict__) translator_config = MDTranslatorConfig(
convert_config = ConverterMineruConfig(mineru_token=mineru_token) if mineru_token else None base_url=base_url, api_key=api_key, model_id=model_id, to_lang=to_lang,
convert_engin = 'mineru' if mineru_token else None custom_prompt=custom_prompt, temperature=temperature,
await workflow.translate_async(convert_engin, convert_config, translate_config) chunk_size=chunk_size, concurrent=concurrent, logger=global_logger, timeout=2000
)
convert_config = ConverterMineruConfig(mineru_token=mineru_token,
formula_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()} return {"success": True, "content": workflow.export_to_markdown()}
elif isinstance(workflow, TXTWorkflow): elif isinstance(workflow, TXTWorkflow):
translate_config = TXTTranslatorConfig(**ai_config.__dict__) translator_config = TXTTranslatorConfig(
await workflow.translate_async(translate_config) base_url=base_url, api_key=api_key, model_id=model_id, to_lang=to_lang,
custom_prompt=custom_prompt, temperature=temperature,
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()} return {"success": True, "content": workflow.export_to_txt()}
else:
raise NotImplementedError(f"Temp endpoint does not support workflow type {type(workflow).__name__}")
except Exception as e: except Exception as e:
print(f"临时翻译接口出现错误：{e.__repr__()}") 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__()} return {"success": False, "reason": e.__repr__()}
@@ -1109,7 +1155,7 @@ def run_app(port: int | None = None):
print(f"正在启动 DocuTranslate WebUI 版本号：{__version__}\n") 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"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") 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: except Exception as e:
print(f"启动失败: {e}") print(f"启动失败: {e}")

2
docutranslate/static/index.html
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2
docutranslate/workflow/interfaces.py
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@@ -36,7 +36,7 @@ class MDZIPExportable(Protocol[T_ExporterConfig]):
@runtime_checkable @runtime_checkable
class MDFormatsExportable(MDZIPExportable[T_ExporterConfig], MDExportable[T_ExporterConfig]): class MDFormatsExportable(MDZIPExportable[T_ExporterConfig], MDExportable[T_ExporterConfig],Protocol):
... ...