Delete v2.txt

v2.txt

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-import base64
-import tempfile
-import os
-import requests
-import gradio as gr
-import random
-from openai import OpenAI
-
-# Available voices for audio generation
-VOICES = ["alloy", "ash", "ballad", "coral", "echo", "fable", "onyx", "nova", "sage", "shimmer", "verse"]
-
-# Example audio URLs
-EXAMPLE_AUDIO_URLS = [
-    "https://cdn.openai.com/API/docs/audio/alloy.wav",
-    "https://cdn.openai.com/API/docs/audio/ash.wav",
-    "https://cdn.openai.com/API/docs/audio/coral.wav",
-    "https://cdn.openai.com/API/docs/audio/echo.wav",
-    "https://cdn.openai.com/API/docs/audio/fable.wav",
-    "https://cdn.openai.com/API/docs/audio/onyx.wav",
-    "https://cdn.openai.com/API/docs/audio/nova.wav",
-    "https://cdn.openai.com/API/docs/audio/sage.wav",
-    "https://cdn.openai.com/API/docs/audio/shimmer.wav"
-]
-
-def process_text_input(api_key, text_prompt, selected_voice):
-    """Generate audio response from text input"""
-    try:
-        # Initialize OpenAI client with the provided API key
-        client = OpenAI(api_key=api_key)
-        
-        completion = client.chat.completions.create(
-            model="gpt-4o-audio-preview",
-            modalities=["text", "audio"],
-            audio={"voice": selected_voice, "format": "wav"},
-            messages=[
-                {
-                    "role": "user",
-                    "content": text_prompt
-                }
-            ]
-        )
-        
-        # Save the audio to a temporary file
-        wav_bytes = base64.b64decode(completion.choices[0].message.audio.data)
-        temp_path = tempfile.mktemp(suffix=".wav")
-        with open(temp_path, "wb") as f:
-            f.write(wav_bytes)
-        
-        # Get the text response directly from the API
-        text_response = completion.choices[0].message.content
-        
-        return text_response, temp_path
-    except Exception as e:
-        return f"Error: {str(e)}", None
-
-def process_audio_input(api_key, audio_path, text_prompt, selected_voice):
-    """Process audio input and generate a response"""
-    try:
-        if not audio_path:
-            return "Please upload or record audio first.", None
-        
-        # Initialize OpenAI client with the provided API key
-        client = OpenAI(api_key=api_key)
-        
-        # Read audio file and encode to base64
-        with open(audio_path, "rb") as audio_file:
-            audio_data = audio_file.read()
-        encoded_audio = base64.b64encode(audio_data).decode('utf-8')
-        
-        # Create message content with both text and audio
-        message_content = []
-        
-        if text_prompt:
-            message_content.append({
-                "type": "text",
-                "text": text_prompt
-            })
-        
-        message_content.append({
-            "type": "input_audio",
-            "input_audio": {
-                "data": encoded_audio,
-                "format": "wav"
-            }
-        })
-        
-        # Call OpenAI API
-        completion = client.chat.completions.create(
-            model="gpt-4o-audio-preview",
-            modalities=["text", "audio"],
-            audio={"voice": selected_voice, "format": "wav"},
-            messages=[
-                {
-                    "role": "user",
-                    "content": message_content
-                }
-            ]
-        )
-        
-        # Save the audio response
-        wav_bytes = base64.b64decode(completion.choices[0].message.audio.data)
-        temp_path = tempfile.mktemp(suffix=".wav")
-        with open(temp_path, "wb") as f:
-            f.write(wav_bytes)
-        
-        # Get the text response
-        text_response = completion.choices[0].message.content
-        
-        return text_response, temp_path
-    except Exception as e:
-        return f"Error: {str(e)}", None
-
-def transcribe_audio(api_key, audio_path):
-    """Transcribe an audio file using OpenAI's API"""
-    try:
-        if not audio_path:
-            return "No audio file provided for transcription."
-        
-        client = OpenAI(api_key=api_key)
-        
-        with open(audio_path, "rb") as audio_file:
-            transcription = client.audio.transcriptions.create(
-                model="gpt-4o-transcribe", 
-                file=audio_file
-            )
-        
-        return transcription.text
-    except Exception as e:
-        return f"Transcription error: {str(e)}"
-
-def download_example_audio():
-    """Download a random example audio file for testing"""
-    try:
-        # Randomly select one of the example audio URLs
-        url = random.choice(EXAMPLE_AUDIO_URLS)
-        
-        # Get the voice name from the URL for feedback
-        voice_name = url.split('/')[-1].split('.')[0]
-        
-        response = requests.get(url)
-        response.raise_for_status()
-        
-        # Save to a temporary file
-        temp_path = tempfile.mktemp(suffix=".wav")
-        with open(temp_path, "wb") as f:
-            f.write(response.content)
-        
-        return temp_path, f"Loaded example voice: {voice_name}"
-    except Exception as e:
-        return None, f"Error loading example: {str(e)}"
-
-def use_example_audio():
-    """Load random example audio for the interface"""
-    audio_path, message = download_example_audio()
-    return audio_path, message
-
-# Create Gradio Interface
-with gr.Blocks(title="OpenAI Audio Chat App") as app:
-    gr.Markdown("# OpenAI Audio Chat App")
-    gr.Markdown("Interact with GPT-4o audio model through text and audio inputs")
-    
-    # API Key input (used across all tabs)
-    api_key = gr.Textbox(
-        label="OpenAI API Key", 
-        placeholder="Enter your OpenAI API key here",
-        type="password"
-    )
-    
-    with gr.Tab("Text to Audio"):
-        with gr.Row():
-            with gr.Column():
-                text_input = gr.Textbox(
-                    label="Text Prompt", 
-                    placeholder="Enter your question or prompt here...",
-                    lines=3
-                )
-                text_voice = gr.Dropdown(
-                    choices=VOICES,
-                    value="alloy",
-                    label="Voice"
-                )
-                text_submit = gr.Button("Generate Response")
-            
-            with gr.Column():
-                text_output = gr.Textbox(label="AI Response (Checks Error)", lines=5)
-                audio_output = gr.Audio(label="AI Response (Audio)")
-                transcribed_output = gr.Textbox(label="Transcription of Audio Response", lines=3)
-        
-        # Function to process text input and then transcribe the resulting audio
-        def text_input_with_transcription(api_key, text_prompt, voice):
-            text_response, audio_path = process_text_input(api_key, text_prompt, voice)
-            
-            # Get transcription of the generated audio
-            if audio_path:
-                transcription = transcribe_audio(api_key, audio_path)
-            else:
-                transcription = "No audio generated to transcribe."
-                
-            return text_response, audio_path, transcription
-        
-        text_submit.click(
-            fn=text_input_with_transcription,
-            inputs=[api_key, text_input, text_voice],
-            outputs=[text_output, audio_output, transcribed_output]
-        )
-    
-    with gr.Tab("Audio Input to Audio Response"):
-        with gr.Row():
-            with gr.Column():
-                audio_input = gr.Audio(
-                    label="Audio Input", 
-                    type="filepath",
-                    sources=["microphone", "upload"]
-                )
-                example_btn = gr.Button("Use Random Example Audio")
-                example_message = gr.Textbox(label="Example Status", interactive=False)
-                
-                accompanying_text = gr.Textbox(
-                    label="Accompanying Text (Optional)", 
-                    placeholder="Add any text context or question about the audio...",
-                    lines=2
-                )
-                audio_voice = gr.Dropdown(
-                    choices=VOICES,
-                    value="alloy",
-                    label="Response Voice"
-                )
-                audio_submit = gr.Button("Process Audio & Generate Response")
-            
-            with gr.Column():
-                audio_text_output = gr.Textbox(label="AI Response (Checks Error)", lines=5)
-                audio_audio_output = gr.Audio(label="AI Response (Audio)")
-                audio_transcribed_output = gr.Textbox(label="Transcription of Audio Response", lines=3)
-                input_transcription = gr.Textbox(label="Transcription of Input Audio", lines=3)
-        
-        # Function to process audio input, generate response, and provide transcriptions
-        def audio_input_with_transcription(api_key, audio_path, text_prompt, voice):
-            # First transcribe the input audio
-            input_transcription = "N/A"
-            if audio_path:
-                input_transcription = transcribe_audio(api_key, audio_path)
-            
-            # Process the audio input and get response
-            text_response, response_audio_path = process_audio_input(api_key, audio_path, text_prompt, voice)
-            
-            # Transcribe the response audio
-            response_transcription = "No audio generated to transcribe."
-            if response_audio_path:
-                response_transcription = transcribe_audio(api_key, response_audio_path)
-                
-            return text_response, response_audio_path, response_transcription, input_transcription
-        
-        audio_submit.click(
-            fn=audio_input_with_transcription,
-            inputs=[api_key, audio_input, accompanying_text, audio_voice],
-            outputs=[audio_text_output, audio_audio_output, audio_transcribed_output, input_transcription]
-        )
-        
-        example_btn.click(
-            fn=use_example_audio,
-            inputs=[],
-            outputs=[audio_input, example_message]
-        )
-    
-    with gr.Tab("Voice Samples"):
-        gr.Markdown("## Listen to samples of each voice")
-        
-        def generate_voice_sample(api_key, voice_type):
-            try:
-                if not api_key:
-                    return "Please enter your OpenAI API key first.", None, "No transcription available."
-                
-                client = OpenAI(api_key=api_key)
-                completion = client.chat.completions.create(
-                    model="gpt-4o-audio-preview",
-                    modalities=["text", "audio"],
-                    audio={"voice": voice_type, "format": "wav"},
-                    messages=[
-                        {
-                            "role": "user",
-                            "content": f"This is a sample of the {voice_type} voice. It has its own unique tone and character."
-                        }
-                    ]
-                )
-                
-                # Save the audio to a temporary file
-                wav_bytes = base64.b64decode(completion.choices[0].message.audio.data)
-                temp_path = tempfile.mktemp(suffix=".wav")
-                with open(temp_path, "wb") as f:
-                    f.write(wav_bytes)
-                
-                # Get transcription
-                transcription = transcribe_audio(api_key, temp_path)
-                
-                return f"Sample generated with voice: {voice_type}", temp_path, transcription
-            except Exception as e:
-                return f"Error: {str(e)}", None, "No transcription available."
-        
-        with gr.Row():
-            sample_voice = gr.Dropdown(
-                choices=VOICES,
-                value="alloy",
-                label="Select Voice Sample"
-            )
-            sample_btn = gr.Button("Generate Sample")
-        
-        with gr.Row():
-            sample_text = gr.Textbox(label="Status")
-            sample_audio = gr.Audio(label="Voice Sample")
-            sample_transcription = gr.Textbox(label="Transcription", lines=3)
-        
-        sample_btn.click(
-            fn=generate_voice_sample,
-            inputs=[api_key, sample_voice],
-            outputs=[sample_text, sample_audio, sample_transcription]
-        )
-    
-    gr.Markdown("""
-    ## Notes:
-    - You must provide your OpenAI API key in the field above
-    - The model used is `gpt-4o-audio-preview` for conversation and `gpt-4o-transcribe` for transcriptions
-    - Audio inputs should be in WAV format
-    - Available voices: alloy, ash, ballad, coral, echo, fable, onyx, nova, sage, shimmer, and verse
-    - Each audio response is automatically transcribed for verification
-    - The "Use Random Example Audio" button will load a random sample from OpenAI's demo voices
-    """)
-
-if __name__ == "__main__":
-    app.launch()