app.py

import base64
import tempfile
import os
import requests
import gradio as gr
import random
import time
from openai import OpenAI
from requests.exceptions import RequestException, Timeout, ConnectionError

# 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"
]

# Supported languages for translation
SUPPORTED_LANGUAGES = [
    "Afrikaans", "Arabic", "Armenian", "Azerbaijani", "Belarusian", "Bosnian", 
    "Bulgarian", "Catalan", "Chinese", "Croatian", "Czech", "Danish", "Dutch", 
    "English", "Estonian", "Finnish", "French", "Galician", "German", "Greek", 
    "Hebrew", "Hindi", "Hungarian", "Icelandic", "Indonesian", "Italian", "Japanese", 
    "Kannada", "Kazakh", "Korean", "Latvian", "Lithuanian", "Macedonian", "Malay", 
    "Marathi", "Maori", "Nepali", "Norwegian", "Persian", "Polish", "Portuguese", 
    "Romanian", "Russian", "Serbian", "Slovak", "Slovenian", "Spanish", "Swahili", 
    "Swedish", "Tagalog", "Tamil", "Thai", "Turkish", "Ukrainian", "Urdu", 
    "Vietnamese", "Welsh"
]

# Max retries for API calls
MAX_RETRIES = 3
RETRY_DELAY = 2  # seconds

def create_openai_client(api_key):
    """Create an OpenAI client with proper timeout settings"""
    return OpenAI(
        api_key=api_key,
        timeout=60.0,  # 60 second timeout
        max_retries=3  # Allow 3 retries
    )

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 = create_openai_client(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 ConnectionError as e:
        return f"Connection error: {str(e)}. Please check your internet connection and try again.", None
    except Timeout as e:
        return f"Timeout error: {str(e)}. The request took too long to complete. Please try again.", None
    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 = create_openai_client(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 ConnectionError as e:
        return f"Connection error: {str(e)}. Please check your internet connection and try again.", None
    except Timeout as e:
        return f"Timeout error: {str(e)}. The request took too long to complete. Please try again.", None
    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 = create_openai_client(api_key)
        
        # Make sure the file exists and is readable
        if not os.path.exists(audio_path):
            return "Audio file not found or inaccessible."
            
        # Check file size
        file_size = os.path.getsize(audio_path)
        if file_size == 0:
            return "Audio file is empty."
            
        with open(audio_path, "rb") as audio_file:
            for attempt in range(MAX_RETRIES):
                try:
                    transcription = client.audio.transcriptions.create(
                        model="gpt-4o-transcribe", 
                        file=audio_file
                    )
                    return transcription.text
                except (ConnectionError, Timeout) as e:
                    if attempt < MAX_RETRIES - 1:
                        time.sleep(RETRY_DELAY)
                        # Reset file pointer
                        audio_file.seek(0)
                        continue
                    else:
                        return f"Transcription failed after {MAX_RETRIES} attempts: {str(e)}"
                except Exception as e:
                    return f"Transcription error: {str(e)}"
        
    except Exception as e:
        return f"Transcription error: {str(e)}"

def translate_audio(api_key, audio_path):
    """Translate audio to English using OpenAI's Whisper model with improved error handling"""
    try:
        if not audio_path:
            return "No audio file provided for translation."
            
        # Verify file exists and is accessible
        if not os.path.exists(audio_path):
            return "Audio file not found or inaccessible."
            
        # Check file size
        file_size = os.path.getsize(audio_path)
        if file_size == 0:
            return "Audio file is empty."
        
        client = create_openai_client(api_key)
        
        # Implement retry mechanism
        for attempt in range(MAX_RETRIES):
            try:
                with open(audio_path, "rb") as audio_file:
                    translation = client.audio.translations.create(
                        model="whisper-1", 
                        file=audio_file,
                        timeout=90.0  # Extended timeout for translation
                    )
                return translation.text
            except (ConnectionError, Timeout) as e:
                if attempt < MAX_RETRIES - 1:
                    # Wait before retrying
                    time.sleep(RETRY_DELAY * (attempt + 1))  # Exponential backoff
                    continue
                else:
                    return f"Translation failed after {MAX_RETRIES} attempts: Connection error. Please check your internet connection and try again."
            except Exception as e:
                # Handle other exceptions
                error_message = str(e)
                if "connection" in error_message.lower():
                    return f"Connection error: {error_message}. Please check your internet connection and try again."
                else:
                    return f"Translation error: {error_message}"
        
    except Exception as e:
        return f"Translation error: {str(e)}"

def download_example_audio():
    """Download a random example audio file for testing with improved error handling"""
    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]
        
        # Implement retry mechanism
        for attempt in range(MAX_RETRIES):
            try:
                response = requests.get(url, timeout=30)
                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 (ConnectionError, Timeout) as e:
                if attempt < MAX_RETRIES - 1:
                    time.sleep(RETRY_DELAY)
                    continue
                else:
                    return None, f"Failed to download example after {MAX_RETRIES} attempts: {str(e)}"
            except Exception as e:
                return None, f"Error loading example: {str(e)}"
                
    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

def check_api_key(api_key):
    """Validate if the API key is provided"""
    if not api_key or api_key.strip() == "":
        return False
    return True

# 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):
            if not check_api_key(api_key):
                return "Please enter your OpenAI API key first.", None, "No API key provided."
                
            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):
            if not check_api_key(api_key):
                return "Please enter your OpenAI API key first.", None, "No API key provided.", "No API key provided."
                
            # First transcribe the input audio
            input_transcription = "N/A"
            if audio_path:
                input_transcription = transcribe_audio(api_key, audio_path)
            else:
                return "Please upload or record audio first.", None, "No audio to transcribe.", "No audio provided."
            
            # 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):
            if not check_api_key(api_key):
                return "Please enter your OpenAI API key first.", None, "No API key provided."
                
            try:
                client = create_openai_client(api_key)
                
                # Use retry mechanism
                for attempt in range(MAX_RETRIES):
                    try:
                        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 (ConnectionError, Timeout) as e:
                        if attempt < MAX_RETRIES - 1:
                            time.sleep(RETRY_DELAY)
                            continue
                        else:
                            return f"Connection error after {MAX_RETRIES} attempts: {str(e)}. Please check your internet connection.", None, "No sample generated."
            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]
        )
    
    # New tab for audio translation with improved error handling
    with gr.Tab("Audio Translation"):
        gr.Markdown("## Translate audio from other languages to English")
        gr.Markdown("Supports 50+ languages including: Arabic, Chinese, French, German, Japanese, Spanish, and many more.")
        
        with gr.Row():
            with gr.Column():
                translation_audio_input = gr.Audio(
                    label="Audio to Translate", 
                    type="filepath",
                    sources=["microphone", "upload"]
                )
                
                translate_btn = gr.Button("Translate to English")
                connection_status = gr.Textbox(label="Connection Status", value="Ready", interactive=False)
            
            with gr.Column():
                translation_output = gr.Textbox(label="English Translation", lines=5)
                original_transcription = gr.Textbox(label="Original Transcription (if available)", lines=5)
        
        def translate_audio_input(api_key, audio_path):
            """Handle the translation of uploaded audio with better connection handling"""
            if not check_api_key(api_key):
                return "Please enter your OpenAI API key first.", "No API key provided.", "No API key provided."
                
            try:
                if not audio_path:
                    return "Please upload or record audio first.", "No audio to translate.", "Connection ready"
                
                # Update connection status
                yield "Processing...", "Preparing audio for translation...", "Connecting to OpenAI API..."
                
                # Get the translation
                translation = translate_audio(api_key, audio_path)
                
                # If there's a connection error message in the translation
                if "connection error" in translation.lower():
                    yield translation, "Translation failed due to connection issues.", "Connection failed"
                    return
                
                # Try to get original transcription (this might be in the original language)
                try:
                    original = transcribe_audio(api_key, audio_path)
                    if "error" in original.lower():
                        original = "Could not transcribe original audio due to connection issues."
                except Exception:
                    original = "Could not transcribe original audio."
                
                yield translation, original, "Connection successful"
            except ConnectionError as e:
                yield f"Connection error: {str(e)}. Please check your internet connection and try again.", "Translation failed.", "Connection failed"
            except Timeout as e:
                yield f"Timeout error: {str(e)}. The request took too long to complete. Please try again.", "Translation timed out.", "Connection timed out"
            except Exception as e:
                yield f"Translation error: {str(e)}", "Error occurred during processing.", "Error occurred"
        
        translate_btn.click(
            fn=translate_audio_input,
            inputs=[api_key, translation_audio_input],
            outputs=[translation_output, original_transcription, connection_status]
        )
        
        # Show supported languages
        with gr.Accordion("Supported Languages", open=False):
            gr.Markdown(", ".join(SUPPORTED_LANGUAGES))
        
        # Connection troubleshooting tips
        with gr.Accordion("Connection Troubleshooting", open=False):
            gr.Markdown("""
            ### If you experience connection errors:
            
            1. **Check your internet connection** - Ensure you have a stable internet connection
            2. **Verify your API key** - Make sure your OpenAI API key is valid and has sufficient credits
            3. **Try a smaller audio file** - Large audio files may time out during upload
            4. **Wait and retry** - OpenAI servers might be experiencing high traffic
            5. **Check file format** - Make sure your audio file is in a supported format (MP3, WAV, etc.)
            6. **Try on a different network** - Some networks might block API calls to OpenAI
            
            The app will automatically retry failed connections up to 3 times.
            """)
    
    gr.Markdown("""
    ## Notes:
    - You must provide your OpenAI API key in the field above
    - The model used is `gpt-4o-audio-preview` for conversation, `gpt-4o-transcribe` for transcriptions, and `whisper-1` for translations
    - Audio inputs should be in WAV format for chat and any supported format for translation
    - 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
    - The translation feature supports 50+ languages, translating them to English
    - If you experience connection errors, the app will automatically retry up to 3 times
    """)

if __name__ == "__main__":
    app.launch()