import gradio as gr
import gradio as gr

# Define the function to generate an image from text
def generate_image(prompt):
    # Dummy implementation: Replace with your image generation logic
    return "path/to/generated_image.png"  # Ensure this returns an actual image file or PIL.Image object

# Define the function to process speech
def process_voice(audio_file, text_to_speak, transcribe):
    # Dummy implementations: Replace with your actual logic
    if transcribe:
        transcription = "This is a transcription of the uploaded audio."
    else:
        transcription = "No transcription requested."

    if text_to_speak:
        synthesized_audio = "path/to/synthesized_audio.wav"  # Replace with synthesized audio generation
    else:
        synthesized_audio = None  # Return None if no text is provided

    return synthesized_audio, transcription

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("## Unified Gradio App for Text-to-Image and Speech Processing")

    with gr.Tab("Text-to-Image"):
        gr.Markdown("### Generate Images from Text")
        text_to_image_prompt = gr.Textbox(label="Enter your prompt", placeholder="Describe the image you want...")
        text_to_image_output = gr.Image(label="Generated Image", type="pil")
        text_to_image_button = gr.Button("Generate Image")
        text_to_image_button.click(generate_image, inputs=text_to_image_prompt, outputs=text_to_image_output)

    with gr.Tab("Speech Processing"):
        gr.Markdown("### Speech-to-Text and Text-to-Speech")
        audio_input = gr.Audio(type="filepath", label="Upload voice sample (WAV file)")
        tts_text_input = gr.Textbox(label="Text to speak (optional if transcribing)")
        transcribe_checkbox = gr.Checkbox(label="Transcribe input audio")
        audio_output = gr.Audio(label="Synthesized Voice Output")
        transcription_output = gr.Textbox(label="Transcription/Status")
        process_button = gr.Button("Process Voice")
        process_button.click(process_voice, 
                             inputs=[audio_input, tts_text_input, transcribe_checkbox], 
                             outputs=[audio_output, transcription_output])

# Launch the app
demo.launch(share=True)