""" app.py Gradio UI for interacting with the Anthropic API, Hume TTS API, and ElevenLabs TTS API. Users enter a prompt, which is processed using Claude by Anthropic to generate text. The text is then converted into speech using both Hume and ElevenLabs TTS APIs. Users can compare the outputs in an interactive UI. """ # Standard Library Imports from concurrent.futures import ThreadPoolExecutor from functools import partial import random # Third-Party Library Imports import gradio as gr # Local Application Imports from src.config import logger from src.constants import ( OPTION_ONE, OPTION_TWO, VOTE_FOR_OPTION_ONE, VOTE_FOR_OPTION_TWO, PROMPT_MAX_LENGTH, PROMPT_MIN_LENGTH, SAMPLE_PROMPTS ) from src.integrations import ( generate_text_with_claude, text_to_speech_with_hume, text_to_speech_with_elevenlabs ) from src.utils import truncate_text, validate_prompt_length def process_prompt(prompt: str): """ Generates text from Claude API and converts it to speech using Hume and ElevenLabs. Args: prompt (str): User-provided text prompt. Returns: tuple: Generated text, two audio file paths (Hume & ElevenLabs), and a dictionary mapping audio options to providers. """ logger.info(f'Processing prompt: {truncate_text(prompt, max_length=100)}') try: # Validate prompt length validate_prompt_length(prompt, PROMPT_MAX_LENGTH, PROMPT_MIN_LENGTH) # Generate text generated_text = generate_text_with_claude(prompt) logger.info(f'Generated text ({len(generated_text)} characters).') # Generate TTS output in parallel with ThreadPoolExecutor(max_workers=2) as executor: hume_audio, elevenlabs_audio = executor.map( lambda func: func(), [partial(text_to_speech_with_hume, prompt, generated_text), partial(text_to_speech_with_elevenlabs, generated_text)] ) logger.info( f'TTS generated: Hume={len(hume_audio)} bytes, ElevenLabs={len(elevenlabs_audio)} bytes' ) # Randomize audio order options = [(hume_audio, 'Hume AI'), (elevenlabs_audio, 'ElevenLabs')] random.shuffle(options) return ( generated_text, options[0][0], # Option 1 audio options[1][0], # Option 2 audio {OPTION_ONE: options[0][1], OPTION_TWO: options[1][1]}, # Option mapping ) except ValueError as ve: logger.warning(f'Validation error: {ve}') return str(ve), None, None, {} except Exception as e: logger.error(f'Unexpected error: {e}') return 'An error occurred. Please try again.', None, None, {} def run_process_prompt(prompt: str): """ Manages UI state while processing a prompt. Args: prompt (str): User input prompt. Yields: tuple: UI state updates in three stages: 1. Disables UI and clears previous outputs. 2. Displays generated content. 3. Re-enables UI after processing. """ # Disable UI, clear previous outputs yield ( gr.update(interactive=False, variant='secondary'), # Disable Generate Button gr.update(value=None), # Clear generated text gr.update(value=None), # Clear Option 1 audio gr.update(value=None), # Clear Option 2 audio None, # Clear option mapping gr.update(interactive=False, value=VOTE_FOR_OPTION_ONE, variant='secondary'), # Reset vote button 1 gr.update(interactive=False, value=VOTE_FOR_OPTION_TWO, variant='secondary'), # Reset vote button 2 None, # Reset Option 2 audio state ) # Process the prompt generated_text, option1_audio, option2_audio, option_mapping = process_prompt(prompt) # Display generated text and audio yield ( gr.update(interactive=True), # Re-enable Generate Button gr.update(value=generated_text), # Show generated text gr.update(value=option1_audio, autoplay=True), # Set Option 1 audio gr.update(value=option2_audio), # Set Option 2 audio option_mapping, # Store option mapping gr.update(), # Keep Vote button 1 disabled gr.update(), # Keep Vote button 2 disabled option2_audio, # Store Option 2 audio ) def vote(option_mapping: dict, selected_button: str): """ Updates both vote buttons to reflect the user's choice. Args: option_mapping (dict): Maps "Option 1" and "Option 2" to their TTS providers. selected_button (str): The label of the button that was clicked. Returns: tuple[gr.update, gr.update]: Updated properties for both vote buttons. """ if not option_mapping: return gr.update(), gr.update() # No updates if mapping is missing # Determine which option was clicked is_option_1 = selected_button == VOTE_FOR_OPTION_ONE selected_option = OPTION_ONE if is_option_1 else OPTION_TWO other_option = OPTION_TWO if is_option_1 else OPTION_ONE # Get provider names selected_provider = option_mapping.get(selected_option, 'Unknown') other_provider = option_mapping.get(other_option, 'Unknown') # Return updated button states return ( gr.update(value=f'{selected_provider} ✔', interactive=False, variant='primary') if is_option_1 else gr.update(value=other_provider, interactive=False, variant='secondary'), gr.update(value=other_provider, interactive=False, variant='secondary') if is_option_1 else gr.update(value=f'{selected_provider} ✔', interactive=False, variant='primary'), gr.update(variant='primary') ) def build_gradio_interface() -> gr.Blocks: """ Constructs the Gradio user interface. Returns: gr.Blocks: The Gradio UI layout. """ with gr.Blocks() as demo: # Title gr.Markdown('# Expressive TTS Arena') with gr.Column(variant='compact'): # Instructions gr.Markdown( 'Generate text using **Claude by Anthropic**, then compare text-to-speech outputs ' 'from **Hume AI** and **ElevenLabs**. Listen to both samples and vote for your favorite!' ) # Sample prompt select with gr.Row(): sample_prompt_dropdown = gr.Dropdown( choices=list(SAMPLE_PROMPTS.keys()), label='Choose a sample prompt (or enter your own)', value=None, interactive=True, ) # Prompt input with gr.Row(): prompt_input = gr.Textbox( label='Enter your prompt', placeholder='Or type your own...', lines=2, max_lines=2, show_copy_button=True, ) # Generate Button generate_button = gr.Button('Generate', variant='primary') with gr.Column(variant='compact'): # Output text output_text = gr.Textbox( label='Generated Text', interactive=False, autoscroll=False, lines=5, max_lines=5, show_copy_button=True, ) # Output audio with gr.Row(): with gr.Column(): option1_audio_player = gr.Audio(label=OPTION_ONE, type='filepath', interactive=False) vote_button_1 = gr.Button(VOTE_FOR_OPTION_ONE, interactive=False) with gr.Column(): option2_audio_player = gr.Audio(label=OPTION_TWO, type='filepath', interactive=False) vote_button_2 = gr.Button(VOTE_FOR_OPTION_TWO, interactive=False) # UI state components option_mapping_state = gr.State() option2_audio_state = gr.State() # Event handlers sample_prompt_dropdown.change( fn=lambda choice: SAMPLE_PROMPTS.get(choice, ''), inputs=[sample_prompt_dropdown], outputs=[prompt_input], ) generate_button.click( fn=run_process_prompt, inputs=[prompt_input], outputs=[ generate_button, output_text, option1_audio_player, option2_audio_player, option_mapping_state, vote_button_1, vote_button_2, option2_audio_state, ], ) vote_button_1.click( fn=vote, inputs=[option_mapping_state, vote_button_1], outputs=[vote_button_1, vote_button_2, generate_button] ) vote_button_2.click( fn=vote, inputs=[option_mapping_state, vote_button_2], outputs=[vote_button_1, vote_button_2, generate_button] ) # Auto-play second audio after first finishes option1_audio_player.stop( fn=lambda _: gr.update(value=None), inputs=[], outputs=[option2_audio_player], ).then( fn=lambda audio: gr.update(value=audio, autoplay=True), inputs=[option2_audio_state], outputs=[option2_audio_player], ) # Enable voting after 2nd audio option playback finishes option2_audio_player.stop( fn=lambda _: (gr.update(interactive=True), gr.update(interactive=True)), inputs=[], outputs=[vote_button_1, vote_button_2], ) logger.debug('Gradio interface built successfully') return demo if __name__ == '__main__': logger.info('Launching TTS Arena Gradio app...') demo = build_gradio_interface() demo.launch()