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App file uploded

app.py

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+import torch
+from transformers import pipeline
+import gradio as gr
+
+asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en", chunk_length_s=30)
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def transcript_and_summarize(audio_file):
+    transcript = asr_pipe(audio_file)["text"]
+    summary = summarizer(transcript, max_length=100, min_length=30, do_sample=False)[0]["summary_text"]
+    return f"**Transcription:**\n{transcript}\n\n**Summary (Notes):**\n{summary}"
+
+iface = gr.Interface(
+    fn=transcript_and_summarize, 
+    inputs=gr.Audio(sources=["upload"], type="filepath"), 
+    outputs=gr.Textbox(), 
+    title="Audio Transcription & Note-Making",
+    description="Upload an audio file to transcribe and get summarized notes."
+)
+
+iface.launch()

requirements.txt

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+torch
+torchvision
+torchaudio
+transformers
+gradio