Add application file

app.py

@@ -0,0 +1,189 @@
+"""
+This application provides an interface for transcription and summarization using models powered by Groq.
+The interface allows users to record audio or provide an audio file in supported formats.
+The user will receive a transcription and a generated summary.
+"""
+
+import gradio as gr
+import groq
+import io
+import numpy as np
+import soundfile as sf
+
+def transcribe_audio(audio: tuple, api_key: str) -> str:
+    """
+    Transcribes the given audio using the Whisper Large v3 Turbo model via the Groq API.
+    The model supports mp3, mp4, mpeg, mpga, m4a, wav, and webm file types.
+
+    Args:
+        audio (tuple): A tuple where the first element is the sample rate and the second is a numpy array with audio data.
+        api_key (str): API key for Groq.
+
+    Returns:
+        str: Transcription result or an error message.
+    """
+    if audio is None:
+        return ""
+    
+    client = groq.Client(api_key=api_key)
+    
+    # Convert the audio data to WAV format in-memory
+    audio_data = audio[1]  # Get the numpy array from the tuple
+    buffer = io.BytesIO()
+
+    # Write numpy array to buffer as WAV format
+    sf.write(buffer, audio_data, audio[0], format='wav')
+    buffer.seek(0)  # Reset buffer position
+
+    # Save audio data
+    bytes_audio = io.BytesIO()
+    np.save(bytes_audio, audio_data)
+    bytes_audio.seek(0)
+
+    try:
+        # Use Whisper Large v3 Turbo powered by Groq for transcription
+        completion = client.audio.transcriptions.create(
+            model="whisper-large-v3-turbo",
+            file=("audio.wav", buffer),
+            response_format="text"
+        )
+        return completion
+    
+    except Exception as e:
+        return f"Error in transcription: {str(e)}"
+
+def generate_response(transcription: str, api_key: str) -> str:
+    """
+    Generate a response summary from the provided transcription using a Groq model.
+
+    Args:
+        transcription (str): The text transcription of the audio.
+        api_key (str): The API key to authenticate the request to Groq.
+
+    Returns:
+        str: Generated response summary or an error message.
+    """
+    if not transcription:
+        return "No transcription available. Please try recording 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 powered by Groq's Language "
+                        "Processing Units (LPU), designed for fast AI inference. "
+                        "Use the following transcription of an audio file and generate 5 "
+                        "bullet points that summarize what is covered in the audio. "
+                        "Maintain a professional and conversational tone. Do not use "
+                        "images or emojis in your answer. Prioritize accuracy and only "
+                        "provide information directly supported by the text transcription."
+                    )
+                },
+                {"role": "user", "content": transcription}
+            ],
+        )
+        
+        return completion.choices[0].message.content
+    
+    except Exception as e:
+        return f"Error in response generation: {str(e)}"
+
+def process_audio(audio: object, api_key: str) -> tuple[str, str]:
+    """
+    Process the given audio by first transcribing it and then generating a response
+    using the Groq API.
+
+    Args:
+        audio (object): The audio file to be processed, expected as a numpy array or other format.
+        api_key (str): The API key to authenticate the request to Groq.
+
+    Returns:
+        tuple: A tuple containing the transcription of the audio and the generated response.
+    """
+    if not api_key:
+        return "Please enter your Groq API key.", "API key is required."
+
+    if not audio:
+        return "No audio provided.", "Audio input is required for transcription."
+
+    # Transcribe audio and generate response
+    transcription = transcribe_audio(audio, api_key)
+    response = generate_response(transcription, api_key)
+    
+    return transcription, response
+
+# Custom CSS for the Groq badge and color scheme
+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;
+}
+"""
+
+# Define the Gradio interface
+with gr.Blocks(theme=gr.themes.Default()) as demo:
+    gr.Markdown("# Groq Scribe")
+
+    # Input for Groq API key (password protected)
+    api_key_input = gr.Textbox(type="password", label="Enter your Groq API Key")
+
+    # Row for audio input
+    with gr.Row():
+        audio_input = gr.Audio(label="Audio", type="numpy")
+
+    # Row for transcription and summary outputs
+    with gr.Row():
+        transcription_output = gr.Textbox(label="Transcription")
+        response_output = gr.Textbox(label="Summary")
+
+    # Submit button
+    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>
+        """
+    )
+
+    # Connect button click to the process_audio function
+    submit_button.click(
+        process_audio,
+        inputs=[audio_input, api_key_input],
+        outputs=[transcription_output, response_output]
+    )
+
+    # Markdown instructions for using the app
+    gr.Markdown(
+        """
+        ## How to use this app:
+        1. Enter your [Groq API Key](https://console.groq.com/keys) in the provided field.
+        2. Click on the microphone icon to record audio or provide a file in mp3, mp4, mpeg, mpga, m4a, wav, or webm format.
+        3. Click the "Process" button to transcribe the audio and generate a summary.
+        4. The transcription and summary will appear in the respective text boxes.
+        """
+    )
+
+# Launch the Gradio interface
+demo.launch()