app.py

import gradio as gr
from PIL import Image
import os
import imageio

# Importa a instância do nosso serviço
# O modelo será carregado quando este módulo for importado
from video_service import video_generation_service

# --- FUNÇÕES DE AJUDA PARA A UI (não relacionadas ao modelo) ---

TARGET_FIXED_SIDE = 768
MIN_DIM_SLIDER = 256
MAX_IMAGE_SIZE = 1280

def calculate_new_dimensions(orig_w, orig_h):
    if orig_w == 0 or orig_h == 0: return int(TARGET_FIXED_SIDE), int(TARGET_FIXED_SIDE)
    if orig_w >= orig_h:
        new_h, aspect_ratio = TARGET_FIXED_SIDE, orig_w / orig_h
        new_w = round((new_h * aspect_ratio) / 32) * 32
        new_w = max(MIN_DIM_SLIDER, min(new_w, MAX_IMAGE_SIZE))
        new_h = max(MIN_DIM_SLIDER, min(new_h, MAX_IMAGE_SIZE)) 
    else:
        new_w, aspect_ratio = TARGET_FIXED_SIDE, orig_h / orig_w
        new_h = round((new_w * aspect_ratio) / 32) * 32
        new_h = max(MIN_DIM_SLIDER, min(new_h, MAX_IMAGE_SIZE))
        new_w = max(MIN_DIM_SLIDER, min(new_w, MAX_IMAGE_SIZE))
    return int(new_h), int(new_w)

def handle_media_upload_for_dims(filepath, current_h, current_w):
    if not filepath or not os.path.exists(str(filepath)): return gr.update(value=current_h), gr.update(value=current_w)
    try:
        if str(filepath).lower().endswith(('.png', '.jpg', '.jpeg', '.webp')):
            with Image.open(filepath) as img:
                orig_w, orig_h = img.size
        else: # Assumir que é um vídeo
            with imageio.get_reader(filepath) as reader:
                meta = reader.get_meta_data()
                orig_w, orig_h = meta.get('size', (current_w, current_h))
        new_h, new_w = calculate_new_dimensions(orig_w, orig_h)
        return gr.update(value=new_h), gr.update(value=new_w)
    except Exception as e:
        print(f"Erro ao processar mídia para dimensões: {e}")
        return gr.update(value=current_h), gr.update(value=current_w)

# --- FUNÇÃO WRAPPER PARA CHAMAR O SERVIÇO A PARTIR DO GRADIO ---

def gradio_generate_wrapper(prompt, negative_prompt, input_image, input_video,
                            height, width, mode, duration, frames_to_use,
                            seed, randomize_seed, guidance_scale, improve_texture,
                            progress=gr.Progress(track_tqdm=True)):
    """
    Esta função atua como uma ponte entre a interface Gradio e o nosso VideoService.
    """
    try:
        # Define a função de callback para a barra de progresso do Gradio
        def progress_handler(step, total_steps):
            progress(step / total_steps, desc="Salvando vídeo...")

        output_path, used_seed = video_generation_service.generate(
            prompt=prompt,
            negative_prompt=negative_prompt,
            input_image_filepath=input_image,
            input_video_filepath=input_video,
            height=int(height),
            width=int(width),
            mode=mode,
            duration=float(duration),
            frames_to_use=int(frames_to_use),
            seed=int(seed),
            randomize_seed=bool(randomize_seed),
            guidance_scale=float(guidance_scale),
            improve_texture=bool(improve_texture),
            progress_callback=progress_handler # Passamos o handler para o serviço
        )
        return output_path, used_seed
    except ValueError as e:
        # Captura erros de validação do serviço e os exibe na UI
        raise gr.Error(str(e))
    except Exception as e:
        # Captura outros erros inesperados
        print(f"Erro inesperado na geração: {e}")
        raise gr.Error("Ocorreu um erro inesperado. Verifique os logs.")


# --- DEFINIÇÃO DA INTERFACE GRADIO ---

css = "#col-container { margin: 0 auto; max-width: 900px; }"
with gr.Blocks(css=css) as demo:
    gr.Markdown("# LTX Video 0.9.8 13B Distilled")
    gr.Markdown("Geração de vídeo rápida e de alta qualidade.")

    with gr.Row():
        with gr.Column():
            # ... (Layout das abas e componentes exatamente como antes) ...
            with gr.Tab("image-to-video") as image_tab:
                video_i_hidden = gr.Textbox(label="video_i", visible=False, value=None)
                image_i2v = gr.Image(label="Input Image", type="filepath", sources=["upload", "webcam", "clipboard"])
                i2v_prompt = gr.Textbox(label="Prompt", value="The creature from the image starts to move", lines=3)
                i2v_button = gr.Button("Generate Image-to-Video", variant="primary")
            with gr.Tab("text-to-video") as text_tab:
                image_n_hidden = gr.Textbox(label="image_n", visible=False, value=None)
                video_n_hidden = gr.Textbox(label="video_n", visible=False, value=None)
                t2v_prompt = gr.Textbox(label="Prompt", value="A majestic dragon flying over a medieval castle", lines=3)
                t2v_button = gr.Button("Generate Text-to-Video", variant="primary")
            with gr.Tab("video-to-video", visible=True) as video_tab:
                image_v_hidden = gr.Textbox(label="image_v", visible=False, value=None)
                video_v2v = gr.Video(label="Input Video", sources=["upload", "webcam"])
                frames_to_use = gr.Slider(label="Frames to use from input video", minimum=9, maximum=257, value=9, step=8, info="Must be N*8+1.")
                v2v_prompt = gr.Textbox(label="Prompt", value="Change the style to cinematic anime", lines=3)
                v2v_button = gr.Button("Generate Video-to-Video", variant="primary")

            duration_input = gr.Slider(label="Video Duration (seconds)", minimum=0.3, maximum=8.5, value=2, step=0.1)
            improve_texture = gr.Checkbox(label="Improve Texture (multi-scale)", value=True, visible=True)

        with gr.Column():
            output_video = gr.Video(label="Generated Video", interactive=False)

    with gr.Accordion("Advanced settings", open=False):
        mode = gr.Dropdown(["text-to-video", "image-to-video", "video-to-video"], label="task", value="image-to-video", visible=False)
        negative_prompt_input = gr.Textbox(label="Negative Prompt", value="worst quality, inconsistent motion, blurry, jittery, distorted", lines=2)
        with gr.Row():
            seed_input = gr.Number(label="Seed", value=42, precision=0)
            randomize_seed_input = gr.Checkbox(label="Randomize Seed", value=True)
        guidance_scale_input = gr.Slider(label="Guidance Scale (CFG)", minimum=1.0, maximum=10.0, value=3.0, step=0.1)
        with gr.Row():
            height_input = gr.Slider(label="Height", value=512, step=32, minimum=MIN_DIM_SLIDER, maximum=MAX_IMAGE_SIZE)
            width_input = gr.Slider(label="Width", value=704, step=32, minimum=MIN_DIM_SLIDER, maximum=MAX_IMAGE_SIZE)

    # --- LÓGICA DE EVENTOS DA UI ---

    image_i2v.upload(fn=handle_media_upload_for_dims, inputs=[image_i2v, height_input, width_input], outputs=[height_input, width_input])
    video_v2v.upload(fn=handle_media_upload_for_dims, inputs=[video_v2v, height_input, width_input], outputs=[height_input, width_input])

    image_tab.select(fn=lambda: "image-to-video", outputs=[mode])
    text_tab.select(fn=lambda: "text-to-video", outputs=[mode])
    video_tab.select(fn=lambda: "video-to-video", outputs=[mode])
    
    common_inputs = [negative_prompt_input, height_input, width_input, mode, duration_input, frames_to_use, seed_input, randomize_seed_input, guidance_scale_input, improve_texture]
    common_outputs = [output_video, seed_input]
    
    t2v_button.click(fn=gradio_generate_wrapper, inputs=[t2v_prompt, *common_inputs[:1], image_n_hidden, video_n_hidden, *common_inputs[1:]], outputs=common_outputs, api_name="text_to_video")
    i2v_button.click(fn=gradio_generate_wrapper, inputs=[i2v_prompt, *common_inputs[:1], image_i2v, video_i_hidden, *common_inputs[1:]], outputs=common_outputs, api_name="image_to_video")
    v2v_button.click(fn=gradio_generate_wrapper, inputs=[v2v_prompt, *common_inputs[:1], image_v_hidden, video_v2v, *common_inputs[1:]], outputs=common_outputs, api_name="video_to_video")


if __name__ == "__main__":
    demo.queue().launch(debug=True, share=False)