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src/modules/asr_module/api.py

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+# asr_module/api.py
+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.responses import JSONResponse
+from pathlib import Path
+import tempfile
+import time
+from datetime import datetime
+from loguru import logger
+from src.modules.asr_module.asr_core.fast_whisper import create_asr, ASRConfig
+
+# 初始化FastAPI应用
+app = FastAPI(
+    title="Yosuga ASR API",
+    description="基于faster-whisper Turbo的高性能多语种语音转文本服务",
+    version="1.0.0"
+)
+
+# 全局单例ASR实例（延迟加载）
+_asr_instance = None
+
+def get_asr():
+    """获取或创建ASR实例（单例）"""
+    global _asr_instance
+    if _asr_instance is None:
+        logger.info("🚀 初始化ASR服务...")
+        _asr_instance = create_asr(
+            ASRConfig(
+                model_name="deepdml/faster-whisper-large-v3-turbo-ct2",
+                device="auto",
+                compute_type="int8_float16",
+                cache_dir=Path("asr_models/faster_whisper_large_v3_ct2"),
+                beam_size=1,        # 贪婪搜索，速度最快
+                vad_filter=True,    # 过滤静音，节省30%时间
+            )
+        )
+        logger.info("✅ ASR服务初始化完成")
+    return _asr_instance
+
+@app.on_event("startup")
+async def startup_event():
+    """应用启动时预加载模型"""
+    get_asr()
+
+@app.on_event("shutdown")
+async def shutdown_event():
+    """应用关闭时清理资源"""
+    global _asr_instance
+    if _asr_instance:
+        _asr_instance.shutdown()
+        logger.info("🛑 ASR服务已关闭")
+
+@app.post("/transcribe", response_class=JSONResponse)
+async def transcribe_audio(
+    file: UploadFile = File(..., description="音频文件 (WAV, FLAC, MP3等格式)")
+):
+    """
+    语音转文本API
+    
+    - **file**: 音频文件，支持WAV/FLAC/MP3等格式
+    - **返回**: JSON格式结果，包含text/language/confidence
+    """
+    start_time = time.time()
+    
+    # 验证文件类型
+    if file.content_type and not file.content_type.startswith("audio/"):
+        raise HTTPException(status_code=400, detail="❌ 请上传音频文件 (MIME类型: audio/*)")
+    
+    try:
+        # 创建临时文件
+        with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as tmp_file:
+            content = await file.read()
+            tmp_file.write(content)
+            tmp_path = Path(tmp_file.name)
+        
+        logger.info(f"📥 接收文件: {file.filename} ({len(content)} bytes)")
+        
+        # 调用ASR识别
+        asr = get_asr()
+        text, language, confidence = asr.transcribe_wav(tmp_path)
+        
+        # 清理临时文件
+        tmp_path.unlink(missing_ok=True)
+        
+        processing_time = time.time() - start_time
+        
+        logger.info(f"✅ 识别完成: {language} | {len(text)}字符 | 置信度:{confidence:.2f} | 耗时:{processing_time:.3f}s")
+        
+        return {
+            "success": True,
+            "data": {
+                "text": text,
+                "language": language,
+                "confidence": confidence,
+                "processing_time": round(processing_time, 3)
+            }
+        }
+        
+    except Exception as e:
+        logger.error(f"❌ 识别失败: {e}")
+        raise HTTPException(status_code=500, detail=f"识别失败: {str(e)}")
+
+@app.get("/health")
+async def health_check():
+    """健康检查接口"""
+    asr = get_asr()
+    health = asr.health_check()
+    
+    return {
+        "status": "healthy" if health["status"] == "healthy" else "unhealthy",
+        "timestamp": datetime.now().isoformat(),
+        "device": health["device"],
+        "model_loaded": health["model_loaded"]
+    }
+
+@app.get("/")
+async def root():
+    """API根路径"""
+    return {
+        "message": "Yosuga ASR API 正在运行",
+        "docs": "/docs",
+        "health": "/health",
+        "transcribe": "/transcribe (POST)"
+    }