Create groq-gradio.py

groq-gradio.py

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+import gradio as gr
+import groq
+import io
+import numpy as np
+import soundfile as sf
+
+def transcribe_audio(audio, api_key):
+    if audio is None:
+        return ""
+    
+    client = groq.Client(api_key=api_key)
+    
+    # Convert audio to the format expected by the model
+    # The model supports mp3, mp4, mpeg, mpga, m4a, wav, and webm file types 
+    audio_data = audio[1]  # Get the numpy array from the tuple
+    buffer = io.BytesIO()
+    sf.write(buffer, audio_data, audio[0], format='wav')
+    buffer.seek(0)
+
+    bytes_audio = io.BytesIO()
+    np.save(bytes_audio, audio_data)
+    bytes_audio.seek(0)
+
+    try:
+        # Use Distil-Whisper English powered by Groq for transcription
+        completion = client.audio.transcriptions.create(
+            model="distil-whisper-large-v3-en",
+            file=("audio.wav", buffer),
+            response_format="text"
+        )
+        return completion
+    except Exception as e:
+        return f"Error in transcription: {str(e)}"
+
+def generate_response(transcription, api_key):
+    if not transcription:
+        return "No transcription available. Please try speaking again."
+    
+    client = groq.Client(api_key=api_key)
+    
+    try:
+        # Use Llama 3.1 70B powered by Groq for text generation
+        completion = client.chat.completions.create(
+            model="llama-3.1-70b-versatile",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": transcription}
+            ],
+            max_tokens=150,
+            temperature=0.7
+        )
+        return completion.choices[0].message.content
+    except Exception as e:
+        return f"Error in response generation: {str(e)}"
+
+def process_audio(audio, api_key):
+    if not api_key:
+        return "Please enter your Groq API key.", "API key is required."
+    transcription = transcribe_audio(audio, api_key)
+    response = generate_response(transcription, api_key)
+    return transcription, response
+
+# Custom CSS for the Groq badge and color scheme (feel free to edit however you wish)
+custom_css = """
+.gradio-container {
+    background-color: #f5f5f5;
+}
+.gr-button-primary {
+    background-color: #f55036 !important;
+    border-color: #f55036 !important;
+}
+.gr-button-secondary {
+    color: #f55036 !important;
+    border-color: #f55036 !important;
+}
+#groq-badge {
+    position: fixed;
+    bottom: 20px;
+    right: 20px;
+    z-index: 1000;
+}
+"""
+
+with gr.Blocks(theme=gr.themes.Default()) as demo:
+    gr.Markdown("# 🎙️ Groq x Gradio Voice-Powered AI Assistant")
+    
+    api_key_input = gr.Textbox(type="password", label="Enter your Groq API Key")
+    
+    with gr.Row():
+        audio_input = gr.Audio(label="Speak!", type="numpy")
+    
+    with gr.Row():
+        transcription_output = gr.Textbox(label="Transcription")
+        response_output = gr.Textbox(label="AI Assistant Response")
+    
+    submit_button = gr.Button("Process", variant="primary")
+    
+    # Add the Groq badge
+    gr.HTML("""
+    <div id="groq-badge">
+        <div style="color: #f55036; font-weight: bold;">POWERED BY GROQ</div>
+    </div>
+    """)
+    
+    submit_button.click(
+        process_audio,
+        inputs=[audio_input, api_key_input],
+        outputs=[transcription_output, response_output]
+    )
+    
+    gr.Markdown("""
+    ## How to use this app:
+    1. Enter your Groq API Key in the provided field.
+    2. Click on the microphone icon and speak your message (or forever hold your peace)! You can also provide a supported audio file. Supported audio files include mp3, mp4, mpeg, mpga, m4a, wav, and webm file types.
+    3. Click the "Process" button to transcribe your speech and generate a response from our AI assistant.
+    4. The transcription and AI assistant response will appear in the respective text boxes.
+    
+    """)
+
+demo.launch()