Add bi_v100-sensevoice and bi_v100-whisper as subdirectories

bi_v100-sensevoice/Dockerfile_sensevoice

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+FROM corex:3.2.1
+
+WORKDIR /workspace
+COPY requirements_sensevoice.txt constraints_sensevoice.txt server_sensevoice.py launch_sensevoice.sh /workspace/
+RUN pip install -r requirements_sensevoice.txt -c constraints_sensevoice.txt
+
+ENTRYPOINT ["/bin/bash", "launch_sensevoice.sh"]

bi_v100-sensevoice/README.md

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+# tiangai100-sensevoice-funasr
+
+【语音识别】
+
+funasr可正常照nvidia方式使用。

bi_v100-sensevoice/constraints_sensevoice.txt

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+torch==2.1.0+corex.3.2.1

bi_v100-sensevoice/launch_sensevoice.sh

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+#!/bin/bash
+
+python3 asr_server.py
+

bi_v100-sensevoice/requirements_sensevoice.txt

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+funasr
+fastapi
+uvicorn[standard]

bi_v100-sensevoice/server_sensevoice.py

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+from fastapi import FastAPI, Request
+from contextlib import asynccontextmanager
+from funasr import AutoModel
+from funasr.utils.postprocess_utils import rich_transcription_postprocess
+import os
+import torch
+
+model_dir = os.getenv("MODEL_DIR", "/model/iic/SenseVoiceSmall")
+model = None
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    global model
+    if model is None:
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        model = AutoModel(model=model_dir, disable_update=True, device=device)
+    yield
+    pass
+
+app = FastAPI(lifespan=lifespan)
+
+@app.post("/recognition")
+async def asr(request: Request, language: str = "auto"):
+    audio_data = await request.body()
+    res = model.generate(input=audio_data, use_itn=True, ban_emo_unk=True)
+    text = rich_transcription_postprocess(res[0]["text"])
+    return {
+        "RecognitionStatus": "Success",
+        "DisplayText": text
+    }
+
+@app.get("/health")
+@app.get("/ready")
+def ready():
+    return {"status": "ok"}
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=80)
+