chore: import upstream snapshot with attribution

2026-07-13 13:25:10 +08:00
commit c397331b1e
3684 changed files with 990993 additions and 0 deletions
@@ -0,0 +1,133 @@
+import argparse
+import logging
+import os
+import uuid
+
+import aiofiles
+import ffmpeg
+import uvicorn
+from fastapi import FastAPI, File, UploadFile
+from modelscope.utils.logger import get_logger
+
+from funasr import AutoModel
+
+logger = get_logger(log_level=logging.INFO)
+logger.setLevel(logging.INFO)
+
+parser = argparse.ArgumentParser()
+parser.add_argument(
+    "--host", type=str, default="0.0.0.0", required=False, help="host ip, localhost, 0.0.0.0"
+)
+parser.add_argument("--port", type=int, default=8000, required=False, help="server port")
+parser.add_argument(
+    "--asr_model",
+    type=str,
+    default="paraformer-zh",
+    help="asr model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo",
+)
+parser.add_argument("--asr_model_revision", type=str, default="v2.0.4", help="")
+parser.add_argument(
+    "--vad_model",
+    type=str,
+    default="fsmn-vad",
+    help="vad model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo",
+)
+parser.add_argument("--vad_model_revision", type=str, default="v2.0.4", help="")
+parser.add_argument(
+    "--punc_model",
+    type=str,
+    default="ct-punc-c",
+    help="model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo",
+)
+parser.add_argument("--punc_model_revision", type=str, default="v2.0.4", help="")
+parser.add_argument("--ngpu", type=int, default=1, help="0 for cpu, 1 for gpu")
+parser.add_argument("--device", type=str, default="cuda", help="cuda, cpu")
+parser.add_argument("--ncpu", type=int, default=4, help="cpu cores")
+parser.add_argument(
+    "--hotword_path",
+    type=str,
+    default="hotwords.txt",
+    help="hot word txt path, only the hot word model works",
+)
+parser.add_argument("--certfile", type=str, default=None, required=False, help="certfile for ssl")
+parser.add_argument("--keyfile", type=str, default=None, required=False, help="keyfile for ssl")
+parser.add_argument("--temp_dir", type=str, default="temp_dir/", required=False, help="temp dir")
+args = parser.parse_args()
+logger.info("-----------  Configuration Arguments -----------")
+for arg, value in vars(args).items():
+    logger.info("%s: %s" % (arg, value))
+logger.info("------------------------------------------------")
+
+os.makedirs(args.temp_dir, exist_ok=True)
+
+logger.info("model loading")
+# load funasr model
+model = AutoModel(
+    model=args.asr_model,
+    model_revision=args.asr_model_revision,
+    vad_model=args.vad_model,
+    vad_model_revision=args.vad_model_revision,
+    punc_model=args.punc_model,
+    punc_model_revision=args.punc_model_revision,
+    ngpu=args.ngpu,
+    ncpu=args.ncpu,
+    device=args.device,
+    disable_pbar=True,
+    disable_log=True,
+)
+logger.info("loaded models!")
+
+app = FastAPI(title="FunASR")
+
+param_dict = {"sentence_timestamp": True, "batch_size_s": 300}
+if args.hotword_path is not None and os.path.exists(args.hotword_path):
+    with open(args.hotword_path, "r", encoding="utf-8") as f:
+        lines = f.readlines()
+        lines = [line.strip() for line in lines]
+    hotword = " ".join(lines)
+    logger.info(f"热词：{hotword}")
+    param_dict["hotword"] = hotword
+
+
+@app.post("/recognition")
+async def api_recognition(audio: UploadFile = File(..., description="audio file")):
+    suffix = audio.filename.split(".")[-1]
+    audio_path = f"{args.temp_dir}/{str(uuid.uuid1())}.{suffix}"
+    async with aiofiles.open(audio_path, "wb") as out_file:
+        content = await audio.read()
+        await out_file.write(content)
+    try:
+        audio_bytes, _ = (
+            ffmpeg.input(audio_path, threads=0)
+            .output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=16000)
+            .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True)
+        )
+    except Exception as e:
+        logger.error(f"读取音频文件发生错误，错误信息：{e}")
+        return {"msg": "读取音频文件发生错误", "code": 1}
+    rec_results = model.generate(input=audio_bytes, is_final=True, **param_dict)
+    # 结果为空
+    if len(rec_results[0]["text"] ) == 0:
+        return {"text": "", "sentences": [], "code": 0}
+    elif len(rec_results[0]["text"] ) > 0:
+        # 解析识别结果
+        rec_result = rec_results[0]
+        text = rec_result["text"]
+        sentences = []
+        for sentence in rec_result["sentence_info"]:
+            # 每句话的时间戳
+            sentences.append(
+                {"text": sentence["text"], "start": sentence["start"], "end": sentence["end"]}
+            )
+        ret = {"text": text, "sentences": sentences, "code": 0}
+        logger.info(f"识别结果：{ret}")
+        return ret
+    else:
+        logger.info(f"识别结果：{rec_results}")
+        return {"msg": "未知错误", "code": -1}
+
+
+if __name__ == "__main__":
+    uvicorn.run(
+        app, host=args.host, port=args.port, ssl_keyfile=args.keyfile, ssl_certfile=args.certfile
+    )