Create app.py

app.py

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+import gradio as gr
+import whisper
+
+# Load Whisper model
+model = whisper.load_model("base")  # You can change to "small", "medium", or "large"
+
+def transcribe_audio(audio):
+    # Transcribe the uploaded audio file
+    result = model.transcribe(audio)
+    text = result['text']
+
+    # Simple Tagalog detection (checks for common Tagalog words)
+    tagalog_words = ["ang", "si", "ni", "ay", "sa", "ng"]
+    flagged = any(word in text.split() for word in tagalog_words)
+
+    # Return transcript and flag
+    return text, "⚠ Tagalog detected!" if flagged else "No Tagalog detected"
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=transcribe_audio,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs=[gr.Textbox(label="Transcript"), gr.Textbox(label="Flag")],
+    title="ClassWatch Audio Transcriber",
+    description="Upload classroom audio to get a transcript and detect if Tagalog is used."
+)
+
+iface.launch()