Update main.py

main.py

@@ -1,7 +1,44 @@
-from fastapi import FastAPI
+from fastapi import FastAPI, WebSocket
+from transformers import pipeline
+import torchaudio.transforms as T
+import soundfile as sf
+import io
 
-app= FastAPI()
+app = FastAPI()
 
-@app.get("/hello")
-def hello():
-    return {"Hi :" "Try again"}
+pipe = pipeline(model="AsemBadr/whisper-small-final-v3", task="automatic-speech-recognition")
+TARGET_SAMPLE_RATE = 16000
+
+@app.get("/hi")
+async def root():
+    return {"message": "Eid Mubarek"}
+
+def preprocess_audio(audio_data: bytes):
+    audio_file = io.BytesIO(audio_data)
+    audio, sample_rate = sf.read(audio_file, dtype='float32')
+
+    if sample_rate != TARGET_SAMPLE_RATE:
+        resampler = T.Resample(sample_rate, TARGET_SAMPLE_RATE)
+        audio = resampler(audio)
+
+    return audio
+
+def transcribe_audio(waveform):
+    result = pipe(waveform)
+    return result['text']
+
+@app.websocket("/transcribe")
+async def transcribe(websocket: WebSocket):
+    await websocket.accept()
+    while True:
+        data = await websocket.receive_bytes()
+        if data:
+            waveform = preprocess_audio(data)
+            transcription = transcribe_audio(waveform)
+            await websocket.send_text(transcription)
+        else:
+            break
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)