Upload app.py

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+
+def transcribe_audio(audio_file_path):
+    """Transcribe audio using an Inference Provider"""
+    client = InferenceClient(provider="auto")
+
+    # Pass the file path directly - the client handles file reading
+    transcript = client.automatic_speech_recognition(
+        audio=audio_file_path, model="openai/whisper-large-v3"
+    )
+
+    return transcript.text
+
+def generate_summary(transcript):
+    """Generate summary using an Inference Provider"""
+    client = InferenceClient(provider="auto")
+
+    prompt = f"""
+    Analyze this meeting transcript and provide:
+    1. A concise summary of key points
+    2. Action items with responsible parties
+    3. Important decisions made
+    
+    Transcript: {transcript}
+    
+    Format with clear sections:
+    ## Summary
+    ## Action Items  
+    ## Decisions Made
+    """
+
+    response = client.chat.completions.create(
+        model="deepseek-ai/DeepSeek-R1-0528",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=1000,
+    )
+
+    return response.choices[0].message.content
+
+def process_meeting_audio(audio_file):
+    """Main processing function"""
+    if audio_file is None:
+        return "Please upload an audio file.", ""
+
+    try:
+        # Step 1: Transcribe
+        transcript = transcribe_audio(audio_file)
+
+        # Step 2: Summarize
+        summary = generate_summary(transcript)
+
+        return transcript, summary
+
+    except Exception as e:
+        # Catch any errors during the AI calls
+        return f"Error processing audio: {str(e)}", ""
+
+# Create Gradio interface
+app = gr.Interface(
+    fn=process_meeting_audio,
+    inputs=gr.Audio(label="Upload Meeting Audio", type="filepath"),
+    outputs=[
+        gr.Textbox(label="Transcript", lines=10),
+        gr.Textbox(label="Summary & Action Items", lines=8),
+    ],
+    title="🎤 AI Meeting Notes",
+    description="Upload audio to get instant transcripts and summaries.",
+)
+
+if __name__ == "__main__":
+    app.launch()