Add application file

main.py

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+import gradio as gr
+import whisper
+from fastapi import FastAPI, UploadFile, File
+from fastapi.responses import JSONResponse
+import tempfile
+import os
+
+# Load the Whisper model once
+model = whisper.load_model("base")  # You can change this to "tiny", "small", "medium", "large"
+
+# FastAPI app
+app = FastAPI()
+
+# API endpoint: POST /api/transcribe
+@app.post("/api/transcribe")
+async def transcribe_audio(file: UploadFile = File(...)):
+    try:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp:
+            tmp.write(await file.read())
+            temp_path = tmp.name
+
+        result = model.transcribe(temp_path)
+        text = result.get("text", "")
+        os.remove(temp_path)
+        return {"transcript": text}
+
+    except Exception as e:
+        return JSONResponse(content={"error": str(e)}, status_code=500)
+
+# Gradio function
+def transcribe_from_ui(audio_file):
+    if audio_file is None:
+        return "Please upload an audio file."
+
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp:
+        tmp.write(audio_file.read())
+        temp_path = tmp.name
+
+    try:
+        result = model.transcribe(temp_path)
+        text = result.get("text", "")
+    except Exception as e:
+        text = f"Error: {str(e)}"
+    finally:
+        os.remove(temp_path)
+
+    return text
+
+# Gradio UI
+interface = gr.Interface(
+    fn=transcribe_from_ui,
+    inputs=gr.File(label="Upload Audio File (MP3/WAV/OGG/etc)"),
+    outputs=gr.Textbox(label="Transcript"),
+    title="🎙️ Audio to Text Transcriber",
+    description="Upload an audio file and get transcription using Whisper. No API key required."
+)
+
+# Mount Gradio app at /
+app = gr.mount_gradio_app(app, interface, path="/")
+
+# Run with: uvicorn app:app --reload
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)

requirements.txt

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+gradio
+fastapi
+uvicorn
+openai-whisper
+ffmpeg-python
+torch