Create app.py

app.py

@@ -0,0 +1,35 @@
+from fastapi import FastAPI, HTTPException, UploadFile, File
+from pydantic import BaseModel
+from multiprocessing import Process, Queue
+import whisper
+import io
+import uvicorn
+
+app = FastAPI()
+
+model = whisper.load_model("large")
+
+class TranscriptionRequest(BaseModel):
+    file: UploadFile
+
+def transcribe_audio(file, queue):
+    try:
+        audio = io.BytesIO(file.file.read())
+        result = model.transcribe(audio)
+        queue.put(result["text"])
+    except Exception as e:
+        queue.put(f"Error: {str(e)}")
+
+@app.post("/transcribe_audio")
+async def transcribe_audio(file: UploadFile = File(...)):
+    queue = Queue()
+    p = Process(target=transcribe_audio, args=(file, queue))
+    p.start()
+    p.join()
+    response = queue.get()
+    if "Error" in response:
+        raise HTTPException(status_code=500, detail=response)
+    return {"transcription": response}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8006)