123 lines
3.8 KiB
Python
123 lines
3.8 KiB
Python
# asr_module/api.py
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from fastapi import FastAPI, File, UploadFile, HTTPException
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from fastapi.responses import JSONResponse
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from pathlib import Path
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import tempfile
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import time
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from datetime import datetime
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from loguru import logger
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from src.modules.asr_module.asr_core.fast_whisper import create_asr, ASRConfig
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# 初始化FastAPI应用
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app = FastAPI(
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title="Yosuga ASR API",
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description="基于faster-whisper Turbo的高性能多语种语音转文本服务",
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version="1.0.0"
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)
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# 全局单例ASR实例（延迟加载）
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_asr_instance = None
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def get_asr():
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"""获取或创建ASR实例（单例）"""
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global _asr_instance
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if _asr_instance is None:
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logger.info("初始化ASR服务...")
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_asr_instance = create_asr(
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ASRConfig(
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model_name="deepdml/faster-whisper-large-v3-turbo-ct2",
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device="auto",
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compute_type="int8_float16", # 如果你是gtx老卡，换成float32
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cache_dir=Path("asr_models/faster_whisper_large_v3_ct2"),
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beam_size=1, # 贪婪搜索，速度最快
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vad_filter=True, # 过滤静音，节省30%时间
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)
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)
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logger.info("ASR服务初始化完成")
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return _asr_instance
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@app.on_event("startup")
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async def startup_event():
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"""应用启动时预加载模型"""
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get_asr()
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@app.on_event("shutdown")
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async def shutdown_event():
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"""应用关闭时清理资源"""
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global _asr_instance
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if _asr_instance:
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_asr_instance.shutdown()
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logger.info("ASR服务已关闭")
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@app.post("/transcribe", response_class=JSONResponse)
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async def transcribe_audio(
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file: UploadFile = File(..., description="音频文件 (WAV, FLAC, MP3等格式)")
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):
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"""
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语音转文本API
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- **file**: 音频文件，支持WAV/FLAC/MP3等格式
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- **返回**: JSON格式结果，包含text/language/confidence
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"""
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start_time = time.time()
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# 验证文件类型
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if file.content_type and not file.content_type.startswith("audio/"):
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raise HTTPException(status_code=400, detail="请上传音频文件 (MIME类型: audio/*)")
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try:
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# 创建临时文件
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with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as tmp_file:
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content = await file.read()
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tmp_file.write(content)
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tmp_path = Path(tmp_file.name)
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logger.info(f"接收文件: {file.filename} ({len(content)} bytes)")
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# 调用ASR识别
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asr = get_asr()
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text, language, confidence = asr.transcribe_wav(tmp_path)
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# 清理临时文件
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tmp_path.unlink(missing_ok=True)
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processing_time = time.time() - start_time
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logger.info(f"识别完成: {language} | {len(text)}字符 | 置信度:{confidence:.2f} | 耗时:{processing_time:.3f}s")
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return {
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"success": True,
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"data": {
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"text": text,
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"language": language,
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"confidence": confidence,
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"processing_time": round(processing_time, 3)
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}
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}
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except Exception as e:
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logger.error(f"识别失败: {e}")
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raise HTTPException(status_code=500, detail=f"识别失败: {str(e)}")
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@app.get("/health")
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async def health_check():
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"""健康检查接口"""
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asr = get_asr()
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health = asr.health_check()
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return {
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"status": "healthy" if health["status"] == "healthy" else "unhealthy",
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"timestamp": datetime.now().isoformat(),
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"device": health["device"],
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"model_loaded": health["model_loaded"]
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}
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@app.get("/")
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async def root():
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"""API根路径"""
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return {
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"message": "Yosuga ASR API 正在运行",
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"docs": "/docs",
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"health": "/health",
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"transcribe": "/transcribe (POST)"
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} |