feat(app): implement audio/video transcription with Groq API

- Replace letter counter with audio/video transcription functionality
- Implement two-column layout with upload controls and transcript display
- Add file validation for supported audio/video formats with 25MB size limit
- Integrate with Groq's Whisper-large-v3-turbo API for transcription
- Add secure API key input field with password protection
- Include helpful information and links for user guidance
- Implement comprehensive error handling with user-friendly messages
- Add detailed docstrings with MCP integration documentation
- Document input parameters with constraints and requirements
- Include usage examples to improve user understanding
- Format docstrings to comply with MCP protocol requirements
- Ensure proper tool exposure with mcp_server=True parameter

app.py

@@ -0,0 +1,139 @@
+import gradio as gr
+import os
+from groq import Groq
+import tempfile
+
+def validate_file(file):
+    """Validate uploaded file type and size."""
+    if file is None:
+        return False, "No file uploaded"
+    
+    # Check file size (25MB limit)
+    file_size_mb = os.path.getsize(file.name) / (1024 * 1024)
+    if file_size_mb > 25:
+        return False, f"File size ({file_size_mb:.1f}MB) exceeds 25MB limit"
+    
+    # Check file extension
+    valid_extensions = ['.mp3', '.mp4', '.mpeg', '.mpga', '.m4a', '.wav', '.webm', '.flac', '.ogg', '.aac']
+    file_extension = os.path.splitext(file.name)[1].lower()
+    
+    if file_extension not in valid_extensions:
+        return False, f"Invalid file type. Supported formats: {', '.join(valid_extensions)}"
+    
+    return True, "File is valid"
+
+def transcribe_audio(audio_file, api_key):
+    """Transcribe audio/video files into text using Groq's Whisper model.
+    
+    This tool converts spoken content from audio and video files into written text.
+    It supports multiple audio formats and handles files up to 25MB in size.
+    
+    Parameters:
+        audio_file: An audio or video file to transcribe. 
+                   Supported formats: MP3, MP4, MPEG, MPGA, M4A, WAV, WebM, FLAC, OGG, AAC.
+                   Maximum size: 25MB.
+        api_key: Your Groq API key, required for authentication.
+                You can obtain this from https://console.groq.com/
+    
+    Returns:
+        A text transcript of the spoken content in the audio file.
+        
+    Example:
+        Upload a podcast episode to get a complete text transcript.
+    """
+    try:
+        # Validate inputs
+        if not api_key:
+            return "Error: Please provide your Groq API key"
+        
+        if audio_file is None:
+            return "Error: Please upload an audio or video file"
+        
+        # Validate file
+        is_valid, message = validate_file(audio_file)
+        if not is_valid:
+            return f"Error: {message}"
+        
+        # Initialize Groq client
+        client = Groq(api_key=api_key)
+        
+        # Read the audio file
+        with open(audio_file.name, "rb") as file:
+            # Create transcription
+            transcription = client.audio.transcriptions.create(
+                file=(os.path.basename(audio_file.name), file.read()),
+                model="whisper-large-v3-turbo"
+            )
+        
+        return transcription.text
+        
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create the Gradio interface with custom layout
+with gr.Blocks(title="Audio/Video Transcription with Groq", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🎵 Audio/Video Transcription with Groq Whisper")
+    gr.Markdown("Upload an audio or video file and get an AI-generated transcript using Groq's Whisper model.")
+    
+    with gr.Row():
+        # Left column - Input controls
+        with gr.Column(scale=1):
+            gr.Markdown("### 📤 Upload & Settings")
+            
+            audio_input = gr.File(
+                label="Upload Audio/Video File",
+                file_types=[".mp3", ".mp4", ".mpeg", ".mpga", ".m4a", ".wav", ".webm", ".flac", ".ogg", ".aac"],
+                file_count="single"
+            )
+            
+            api_key_input = gr.Textbox(
+                label="Groq API Key",
+                placeholder="Enter your Groq API key here...",
+                type="password",
+                lines=1
+            )
+            
+            transcribe_btn = gr.Button(
+                "🎯 Transcribe Audio",
+                variant="primary",
+                size="lg"
+            )
+            
+            gr.Markdown("### ℹ️ File Requirements")
+            gr.Markdown("""
+            - **Max file size**: 25MB
+            - **Supported formats**: MP3, MP4, MPEG, MPGA, M4A, WAV, WebM, FLAC, OGG, AAC
+            - **Get API key**: [Groq Console](https://console.groq.com/)
+            """)
+        
+        # Right column - Output
+        with gr.Column(scale=1):
+            gr.Markdown("### 📝 Transcript")
+            
+            transcript_output = gr.Textbox(
+                label="Generated Transcript",
+                placeholder="Your transcript will appear here...",
+                lines=20,
+                max_lines=30,
+                show_copy_button=True,
+                interactive=False
+            )
+    
+    # Connect the button to the transcription function
+    transcribe_btn.click(
+        fn=transcribe_audio,
+        inputs=[audio_input, api_key_input],
+        outputs=transcript_output,
+        show_progress=True
+    )
+    
+    # Add examples section
+    gr.Markdown("### 🔗 Useful Links")
+    gr.Markdown("""
+    - [Get your Groq API key](https://console.groq.com/)
+    - [Groq Documentation](https://console.groq.com/docs)
+    - [Supported audio formats](https://platform.openai.com/docs/guides/speech-to-text)
+    """)
+
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)