""" # 方式1:直接运行 python api/translator_app.py # 方式2:使用 uvicorn uvicorn api.translator_app:app --host 0.0.0.0 --port 6006 --reload 使用说明: Translation HTTP Service This service provides a RESTful API for text translation using Qwen (default) or DeepL API. The service runs on port 6006 and provides a simple translation endpoint. API Endpoint: POST /translate Request Body (JSON): { "text": "要翻译的文本", "target_lang": "en", # Required: target language code (zh, en, ru, etc.) "source_lang": "zh", # Optional: source language code (auto-detect if not provided) "model": "qwen" # Optional: translation model ("qwen" or "deepl", default: "qwen") } Response (JSON): { "text": "要翻译的文本", "target_lang": "en", "source_lang": "zh", "translated_text": "Text to translate", "status": "success" } Usage Examples: 1. Translate Chinese to English: curl -X POST http://localhost:6006/translate \ -H "Content-Type: application/json" \ -d '{ "text": "商品名称", "target_lang": "en", "source_lang": "zh" }' 2. Translate with auto-detection: curl -X POST http://localhost:6006/translate \ -H "Content-Type: application/json" \ -d '{ "text": "Product name", "target_lang": "zh" }' 3. Translate using DeepL model: curl -X POST http://localhost:6006/translate \ -H "Content-Type: application/json" \ -d '{ "text": "商品名称", "target_lang": "en", "source_lang": "zh", "model": "deepl" }' 4. Translate Russian to English: curl -X POST http://localhost:6006/translate \ -H "Content-Type: application/json" \ -d '{ "text": "Название товара", "target_lang": "en", "source_lang": "ru" }' Health Check: GET /health curl http://localhost:6006/health Start the service: python api/translator_app.py # or uvicorn api.translator_app:app --host 0.0.0.0 --port 6006 --reload """ import logging import argparse import uvicorn from typing import Dict, List, Optional, Union from fastapi import FastAPI, HTTPException from fastapi.responses import JSONResponse from fastapi.middleware.cors import CORSMiddleware from pydantic import BaseModel, Field from config.services_config import get_translation_config from translation.service import TranslationService # Configure logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' ) logger = logging.getLogger(__name__) _translation_service: Optional[TranslationService] = None def get_translation_service() -> TranslationService: global _translation_service if _translation_service is None: _translation_service = TranslationService(get_translation_config()) return _translation_service # Request/Response models class TranslationRequest(BaseModel): """Translation request model.""" text: Union[str, List[str]] = Field(..., description="Text to translate (string or list of strings)") target_lang: str = Field(..., description="Target language code (zh, en, ru, etc.)") source_lang: Optional[str] = Field(None, description="Source language code (optional, auto-detect if not provided)") model: Optional[str] = Field(None, description="Translation model: qwen-mt | deepl | llm") scene: Optional[str] = Field(None, description="Translation scene, paired with model routing") context: Optional[str] = Field(None, description="Deprecated alias of scene") prompt: Optional[str] = Field(None, description="Optional prompt override") class Config: json_schema_extra = { "example": { "text": "商品名称", "target_lang": "en", "source_lang": "zh", "model": "llm", "scene": "sku_name" } } class TranslationResponse(BaseModel): """Translation response model.""" text: Union[str, List[str]] = Field(..., description="Original text (string or list)") target_lang: str = Field(..., description="Target language code") source_lang: Optional[str] = Field(None, description="Source language code (detected or provided)") translated_text: Union[str, List[Optional[str]]] = Field( ..., description="Translated text (string or list; list elements may be null on failure)", ) status: str = Field(..., description="Translation status") model: str = Field(..., description="Translation model used") scene: str = Field(..., description="Translation scene used") # Create FastAPI app app = FastAPI( title="Translation Service API", description="RESTful API for text translation using Qwen (default) or DeepL", version="1.0.0", docs_url="/docs", redoc_url="/redoc" ) # Add CORS middleware app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) @app.on_event("startup") async def startup_event(): """Initialize translator on startup.""" logger.info("Starting Translation Service API on port 6006") try: service = get_translation_service() logger.info( "Translation service ready | default_model=%s available_models=%s", service.config.default_model, service.available_models, ) except Exception as e: logger.error(f"Failed to initialize translator: {e}", exc_info=True) raise @app.get("/health") async def health_check(): """Health check endpoint.""" try: service = get_translation_service() return { "status": "healthy", "service": "translation", "default_model": service.config.default_model, "default_scene": service.config.default_scene, "available_models": service.available_models, "enabled_capabilities": service.config.enabled_models, } except Exception as e: logger.error(f"Health check failed: {e}") return JSONResponse( status_code=503, content={ "status": "unhealthy", "error": str(e) } ) @app.post("/translate", response_model=TranslationResponse) async def translate(request: TranslationRequest): """ Translate text to target language. Uses a fixed prompt optimized for product SKU name translation. The translation is cached in Redis for performance. Supports both Qwen (default) and DeepL models via the 'model' parameter. """ # 允许 text 为字符串或字符串列表 if isinstance(request.text, list): if not request.text: raise HTTPException( status_code=400, detail="Text list cannot be empty" ) else: if not request.text or not request.text.strip(): raise HTTPException( status_code=400, detail="Text cannot be empty" ) if not request.target_lang: raise HTTPException( status_code=400, detail="target_lang is required" ) try: service = get_translation_service() scene = (request.scene or request.context or service.config.default_scene).strip() or "general" model = service.config.normalize_model_name(request.model or service.config.default_model) translator = service.get_backend(model) raw_text = request.text # 如果是列表,并且底层 provider 声明支持 batch,则直接传 list if isinstance(raw_text, list) and getattr(translator, "supports_batch", False): try: translated_list = service.translate( text=raw_text, target_lang=request.target_lang, source_lang=request.source_lang, model=model, scene=scene, prompt=request.prompt, ) except Exception as exc: logger.error("Batch translation failed: %s", exc, exc_info=True) # 回退到逐条拆分逻辑 translated_list = None if translated_list is not None: # 规范化为 List[Optional[str]],并保证长度对应 if not isinstance(translated_list, list): raise HTTPException( status_code=500, detail="Batch translation provider returned non-list result", ) normalized: List[Optional[str]] = [] for idx, item in enumerate(raw_text): if idx < len(translated_list): val = translated_list[idx] else: val = None # 失败语义:失败位置为 None normalized.append(val) return TranslationResponse( text=raw_text, target_lang=request.target_lang, source_lang=request.source_lang, translated_text=normalized, status="success", model=str(getattr(translator, "model", model)), scene=scene, ) # 否则:统一走逐条拆分逻辑(包括不支持 batch 的 provider) if isinstance(raw_text, list): results: List[Optional[str]] = [] for item in raw_text: if item is None or not str(item).strip(): # 空元素不视为失败,直接返回原值 results.append(item) # type: ignore[arg-type] continue try: out = service.translate( text=str(item), target_lang=request.target_lang, source_lang=request.source_lang, model=model, scene=scene, prompt=request.prompt, ) except Exception as exc: logger.warning("Per-item translation failed: %s", exc, exc_info=True) out = None # 失败语义:该元素为 None results.append(out) return TranslationResponse( text=raw_text, target_lang=request.target_lang, source_lang=request.source_lang, translated_text=results, status="success", model=str(getattr(translator, "model", model)), scene=scene, ) # 单文本模式:保持原有严格失败语义 translated_text = service.translate( text=raw_text, target_lang=request.target_lang, source_lang=request.source_lang, model=model, scene=scene, prompt=request.prompt, ) if translated_text is None: raise HTTPException( status_code=500, detail="Translation failed" ) return TranslationResponse( text=raw_text, target_lang=request.target_lang, source_lang=request.source_lang, translated_text=translated_text, status="success", model=str(getattr(translator, "model", model)), scene=scene, ) except HTTPException: raise except Exception as e: logger.error(f"Translation error: {e}", exc_info=True) raise HTTPException( status_code=500, detail=f"Translation error: {str(e)}" ) @app.get("/") async def root(): """Root endpoint with API information.""" return { "service": "Translation Service API", "version": "1.0.0", "status": "running", "endpoints": { "translate": "POST /translate", "health": "GET /health", "docs": "GET /docs" } } if __name__ == "__main__": parser = argparse.ArgumentParser(description='Start translation API service') parser.add_argument('--host', default='0.0.0.0', help='Host to bind to') parser.add_argument('--port', type=int, default=6006, help='Port to bind to') parser.add_argument('--reload', action='store_true', help='Enable auto-reload') args = parser.parse_args() # Run server uvicorn.run( "api.translator_app:app", host=args.host, port=args.port, reload=args.reload )