Update app.py

app.py

@@ -0,0 +1,46 @@
+import tempfile
+import torchaudio
+import whisper
+import gradio as gr
+
+# Load Whisper model
+model = whisper.load_model("base")
+
+def transcribe_audio(audio_file):
+    # Save uploaded audio
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_wav:
+        signal, sr = torchaudio.load(audio_file)
+
+        # Resample if needed
+        if sr != 16000:
+            signal = torchaudio.transforms.Resample(sr, 16000)(signal)
+        if signal.shape[0] > 1:
+            signal = signal.mean(dim=0, keepdim=True)
+
+        torchaudio.save(tmp_wav.name, signal, 16000)
+
+        # Transcribe with Whisper
+        result = model.transcribe(tmp_wav.name)
+        transcript = result['text']
+
+    # Save transcript to file
+    with tempfile.NamedTemporaryFile(suffix=".txt", delete=False, mode="w") as f:
+        f.write(transcript)
+        transcript_file_path = f.name
+
+    return transcript, transcript_file_path
+
+# Gradio Interface
+app = gr.Interface(
+    fn=transcribe_audio,
+    inputs=gr.Audio(type="filepath", label="🎙️ Upload Meeting Audio"),
+    outputs=[
+        gr.Textbox(label="📝 Transcript", lines=10),
+        gr.File(label="⬇️ Download Transcript (.txt)")
+    ],
+    title="🎧 Meeting Summarizer (STT Only)",
+    description="Upload your meeting audio and get a clean transcript you can read and download.",
+    theme="soft"
+)
+
+app.launch()