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记住上传文件的名字

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xunbu
2025-07-14 18:32:34 +08:00
parent 9a7f8d61d4
commit c08851d570
2 changed files with 43 additions and 19 deletions
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40
docutranslate/app.py
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@@ -38,6 +38,7 @@ def _create_default_task_state() -> Dict[str, Any]:
"download_ready": False, "markdown_content": None, "markdown_zip_content": None,
"html_content": None, "original_filename_stem": None, "task_start_time": 0,
"task_end_time": 0, "current_task_ref": None,
"original_filename": None,
}
@@ -180,6 +181,7 @@ async def _start_translation_task(
"status_message": "任务初始化中...", "error_flag": False, "download_ready": False,
"markdown_content": None, "md_zip_content": None, "html_content": None,
"original_filename_stem": Path(original_filename).stem,
"original_filename": original_filename,
"task_start_time": time.time(), "task_end_time": 0, "current_task_ref": None,
})
@@ -275,9 +277,10 @@ class TranslateServiceRequest(BaseModel):
examples=["task-12345"]
)
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。注意：请勿在不安全的环境中暴露此密钥。", examples=["sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx"])
apikey: str = Field(..., description="LLM API的密钥。注意：请勿在不安全的环境中暴露此密钥。",
examples=["sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx"])
model_id: str = Field(..., description="使用的模型ID。", examples=["gpt-4-turbo"])
to_lang: str = Field("中文", description="目标翻译语言。", examples=["中文","英文","English"])
to_lang: str = Field("中文", description="目标翻译语言。", examples=["中文", "英文", "English"])
formula_ocr: bool = Field(False, description="是否对公式进行OCR识别。")
code_ocr: bool = Field(False, description="是否对代码块进行OCR识别。")
refine_markdown: bool = Field(False, description="是否使用ai对解析后的文档进行一遍优化（现不推荐使用）")
@@ -286,9 +289,11 @@ class TranslateServiceRequest(BaseModel):
chunk_size: int = Field(..., description="文本分块的大小。", examples=[2048])
concurrent: int = Field(..., description="并发请求的数量。", examples=[5])
temperature: float = Field(..., description="LLM的温度参数，控制生成文本的随机性。", examples=[0.7])
custom_prompt_translate: Optional[str] = Field(None, description="用户自定义的翻译Prompt。", examples=["人名保持原文不翻译。"])
custom_prompt_translate: Optional[str] = Field(None, description="用户自定义的翻译Prompt。",
examples=["人名保持原文不翻译。"])
file_name: str = Field(..., description="上传的原始文件名，包含扩展名。", examples=["my_document.pdf"])
file_content: str = Field(..., description="Base64编码的文件内容。", examples=["JVBERi0xLjQKJeLjz9MKMSAwIG9iago8PAovVHlwZS..."])
file_content: str = Field(..., description="Base64编码的文件内容。",
examples=["JVBERi0xLjQKJeLjz9MKMSAwIG9iago8PAovVHlwZS..."])
class Config:
json_schema_extra = {
@@ -357,7 +362,8 @@ async def service_translate(request: TranslateServiceRequest = Body(..., descrip
summary="取消翻译任务",
description="根据任务ID取消一个正在进行的翻译任务。这是一个异步操作，发送取消请求后，任务不会立即停止，需要通过状态接口确认最终状态。"
)
async def service_cancel_translate(task_id: str = FastApiPath(..., description="要取消的任务的ID", example="task-12345")):
async def service_cancel_translate(
task_id: str = FastApiPath(..., description="要取消的任务的ID", example="task-12345")):
"""根据任务ID取消一个正在进行的翻译任务。"""
try:
response_data = _cancel_translation_logic(task_id)
@@ -392,6 +398,7 @@ async def service_get_status(task_id: str = FastApiPath(..., description="要查
"error_flag": task_state["error_flag"],
"download_ready": task_state["download_ready"],
"original_filename_stem": task_state["original_filename_stem"],
"original_filename": task_state.get("original_filename"), # <--- MODIFIED
"task_start_time": task_state["task_start_time"],
"task_end_time": task_state["task_end_time"],
"downloads": {
@@ -423,6 +430,8 @@ async def service_get_logs(task_id: str = FastApiPath(..., description="要获
FileType = Literal["markdown", "markdown_zip", "html"]
@service_router.get(
"/download/{task_id}/{file_type}",
summary="下载翻译结果文件",
@@ -506,14 +515,16 @@ async def main_page_admin():
summary="[内部] 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。**",
tags=["Internal / UI"])
async def temp_translate(base_url: str = Body(..., description="LLM API的基础URL。", example="https://api.openai.com/v1"),
api_key: str = Body(..., description="LLM API的密钥。", example="sk-xxxxxxxxxx"),
model_id: str = Body(..., description="使用的模型ID。", example="gpt-4-turbo"),
mineru_token: str = Body(..., description="Mineru引擎的Token。"),
file_name: str = Body(..., description="原始文件名。", example="test.txt"),
file_content: str = Body(..., description="文件内容，可以是纯文本或Base64编码的字符串。"),
to_lang: str = Body("中文", description="目标语言。")
):
async def temp_translate(
base_url: str = Body(..., description="LLM API的基础URL。", example="https://api.openai.com/v1"),
api_key: str = Body(..., description="LLM API的密钥。", example="sk-xxxxxxxxxx"),
model_id: str = Body(..., description="使用的模型ID。", example="gpt-4-turbo"),
mineru_token: str = Body(..., description="Mineru引擎的Token。"),
file_name: str = Body(..., description="原始文件名。", example="test.txt"),
file_content: str = Body(..., description="文件内容，可以是纯文本或Base64编码的字符串。"),
to_lang: str = Body("中文", description="目标语言。"),
concurrent: int = Body(30, description="ai翻译并发数")
):
def is_base64(s):
try:
base64.b64decode(s)
@@ -525,6 +536,7 @@ async def temp_translate(base_url: str = Body(..., description="LLM API的基础
key=api_key,
model_id=model_id,
mineru_token=mineru_token,
concurrent=concurrent
)
try:
@@ -564,4 +576,4 @@ def run_app(port: int | None = None):
if __name__ == "__main__":
run_app()
run_app()