# app.py
#
# Copyright (C) August 4, 2025  Carlos Rodrigues dos Santos
#
# Versão 6.0.0 (Clean, Interactive & Consolidated UI) - Final

import gradio as gr
import yaml
import logging
import os
import sys
import shutil
import time
import json

# --- 1. IMPORTAÇÃO DO FRAMEWORK E CONFIGURAÇÃO ---
import aduc_framework
from aduc_framework.types import PreProductionParams, ProductionParams

# Configuração de Tema Cinemático
cinematic_theme = gr.themes.Base(
    primary_hue=gr.themes.colors.indigo,
    secondary_hue=gr.themes.colors.purple,
    neutral_hue=gr.themes.colors.slate,
    font=(gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui", "sans-serif"),
).set(
    body_background_fill="#111827", body_text_color="#E5E7EB",
    button_primary_background_fill="linear-gradient(90deg, #4F46E5, #8B5CF6)",
    button_primary_text_color="#FFFFFF", button_secondary_background_fill="#374151",
    button_secondary_border_color="#4B5563", button_secondary_text_color="#E5E7EB",
    block_background_fill="#1F2937", block_border_width="1px", block_border_color="#374151",
    block_label_background_fill="#374151", block_label_text_color="#E5E7EB",
    block_title_text_color="#FFFFFF", input_background_fill="#374151",
    input_border_color="#4B5563", input_placeholder_color="#9CA3AF",
)

# Configuração de Logging
LOG_FILE_PATH = "aduc_log.txt"
if os.path.exists(LOG_FILE_PATH): os.remove(LOG_FILE_PATH)
log_format = '%(asctime)s - %(levelname)s - [%(name)s:%(funcName)s] - %(message)s'
root_logger = logging.getLogger()
root_logger.setLevel(logging.INFO)
root_logger.handlers.clear()
stream_handler = logging.StreamHandler(sys.stdout)
stream_handler.setFormatter(logging.Formatter(log_format))
root_logger.addHandler(stream_handler)
file_handler = logging.FileHandler(LOG_FILE_PATH, mode='w', encoding='utf-8')
file_handler.setFormatter(logging.Formatter(log_format))
root_logger.addHandler(file_handler)
logger = logging.getLogger(__name__)

# Inicialização do Aduc Framework
try:
    with open("config.yaml", 'r') as f: config = yaml.safe_load(f)
    WORKSPACE_DIR = config['application']['workspace_dir']
    aduc = aduc_framework.create_aduc_instance(workspace_dir=WORKSPACE_DIR)
    logger.info("Interface Gradio inicializada e conectada ao Aduc Framework.")
except Exception as e:
    logger.critical(f"ERRO CRÍTICO durante a inicialização: {e}", exc_info=True)
    with gr.Blocks() as demo:
        gr.Markdown("# ERRO CRÍTICO NA INICIALIZAÇÃO")
        gr.Markdown("Não foi possível iniciar o Aduc Framework. Verifique os logs para mais detalhes.")
        gr.Textbox(value=str(e), label="Detalhes do Erro", lines=10)
    demo.launch()
    exit()

# --- 2. FUNÇÕES WRAPPER (UI <-> FRAMEWORK) ---
def run_pre_production_wrapper(prompt, num_keyframes, ref_files, resolution_str, duration_per_fragment, progress=gr.Progress()):
    if not ref_files: raise gr.Error("Por favor, forneça pelo menos uma imagem de referência.")
    target_resolution = int(resolution_str.split('x')[0])
    ref_paths = [aduc.process_image_for_story(f.name, target_resolution, f"ref_processed_{i}.png") for i, f in enumerate(ref_files)]
    params = PreProductionParams(prompt=prompt, num_keyframes=int(num_keyframes), ref_paths=ref_paths, resolution=target_resolution, duration_per_fragment=duration_per_fragment)
    final_result = {}
    for update in aduc.task_pre_production(params, progress):
        yield {
            generation_state_holder: update.get("updated_state", gr.skip()),
            storyboard_output: update.get("storyboard", gr.skip()),
            keyframe_gallery: gr.update(value=update.get("final_keyframes", [])),
        }
        final_result = update
    yield {
        generation_state_holder: final_result.get("updated_state"),
        step3_accordion: gr.update(visible=True, open=True)
    }

def run_original_production_wrapper(current_state_dict, trim_percent, handler_strength, dest_strength, guidance_scale, stg_scale, steps, progress=gr.Progress()):
    yield {final_video_output: gr.update(value=None, visible=True, label="🎬 Produzindo seu filme...")}
    production_params = ProductionParams(trim_percent=int(trim_percent), handler_strength=handler_strength, destination_convergence_strength=dest_strength, guidance_scale=guidance_scale, stg_scale=stg_scale, inference_steps=int(steps))
    final_video_path, latent_paths, updated_state = aduc.task_produce_original_movie(params=production_params, progress_callback=progress)
    yield {
        final_video_output: gr.update(value=final_video_path, label="✅ Filme Original Master"),
        step4_accordion: gr.update(visible=True, open=True),
        original_latents_paths_state: latent_paths,
        current_source_video_state: final_video_path,
        generation_state_holder: updated_state.model_dump(),
    }

def run_upscaler_wrapper(source_video, latent_paths, chunk_size, progress=gr.Progress()):
    if not source_video or not latent_paths: raise gr.Error("Fonte de vídeo ou latentes originais não encontrados para o Upscaler.")
    yield {final_video_output: gr.update(label="Pós-Produção: Upscaler Latente...")}
    final_path = source_video
    for update in aduc.task_run_latent_upscaler(latent_paths, int(chunk_size), progress):
        if "final_path" in update: final_path = update['final_path']
    yield {final_video_output: gr.update(value=final_path, label="✅ Upscale Latente Concluído"), current_source_video_state: final_path}

def run_hd_wrapper(source_video, steps, global_prompt, progress=gr.Progress()):
    if not source_video: raise gr.Error("Fonte de vídeo não encontrada para a Masterização HD.")
    yield {final_video_output: gr.update(label="Pós-Produção: Masterização HD...")}
    final_path = source_video
    for update in aduc.task_run_hd_mastering(source_video, int(steps), global_prompt, progress):
        if "final_path" in update: final_path = update['final_path']
    yield {final_video_output: gr.update(value=final_path, label="✅ Masterização HD Concluída"), current_source_video_state: final_path}

def run_audio_wrapper(source_video, audio_prompt, global_prompt, progress=gr.Progress()):
    if not source_video: raise gr.Error("Fonte de vídeo não encontrada para a Geração de Áudio.")
    yield {final_video_output: gr.update(label="Pós-Produção: Geração de Áudio...")}
    final_audio_prompt = audio_prompt if audio_prompt and audio_prompt.strip() else global_prompt
    final_path = source_video
    for update in aduc.task_run_audio_generation(source_video, final_audio_prompt, progress):
        if "final_path" in update: final_path = update['final_path']
    yield {final_video_output: gr.update(value=final_path, label="✅ Filme Final com Áudio")}

def get_log_content():
    try:
        with open(LOG_FILE_PATH, "r", encoding="utf-8") as f: return f.read()
    except FileNotFoundError: return "Arquivo de log ainda não criado."

# --- 3. DEFINIÇÃO DA UI ---
with gr.Blocks(theme=cinematic_theme, css="style.css") as demo:
    generation_state_holder = gr.State(value={})
    original_latents_paths_state = gr.State(value=[])
    current_source_video_state = gr.State(value=None)
    gr.Markdown("<h1>ADUC-SDR 🎬 - O Diretor de Cinema IA</h1>")
    gr.Markdown("<p>Crie um filme completo com vídeo e áudio, orquestrado por uma equipe de IAs especialistas.</p>")
    with gr.Accordion("Etapa 1: Roteiro e Cenas-Chave (Pré-Produção)", open=True) as step1_accordion:
        prompt_input = gr.Textbox(label="Ideia Geral do Filme", value="Um leão majestoso caminha pela savana, senta-se e ruge para o sol poente.")
        with gr.Row():
            lang_selector = gr.Radio(["🇧🇷", "🇺🇸", "🇨🇳"], value="🇧🇷", label="Idioma / Language")
            resolution_selector = gr.Radio(["512x512", "768x768", "1024x1024"], value="512x512", label="Resolução Base")
        ref_image_input = gr.File(label="Grupo de Imagens do Usuário", file_count="multiple", file_types=["image"], type="filepath")
        with gr.Row():
            num_keyframes_slider = gr.Slider(minimum=2, maximum=42, value=4, step=2, label="Número de Cenas-Chave (Par)")
            duration_per_fragment_slider = gr.Slider(label="Duração de cada Clipe (s)", minimum=2.0, maximum=10.0, value=4.0, step=0.1)
        storyboard_and_keyframes_button = gr.Button("Gerar Roteiro e Keyframes", variant="primary")
    with gr.Accordion("Etapa 2: Produção do Vídeo Original", open=False, visible=False) as step3_accordion:
        trim_percent_slider = gr.Slider(minimum=10, maximum=90, value=50, step=5, label="Poda Causal (%)")
        handler_strength = gr.Slider(label="Força do Déjà-Vu", minimum=0.0, maximum=1.0, value=0.5, step=0.05)
        dest_strength = gr.Slider(label="Força da Âncora Final", minimum=0.0, maximum=1.0, value=0.75, step=0.05)
        guidance_scale_slider = gr.Slider(minimum=1.0, maximum=10.0, value=2.0, step=0.1, label="Escala de Orientação")
        stg_scale_slider = gr.Slider(minimum=0.0, maximum=1.0, value=0.025, step=0.005, label="Escala STG")
        inference_steps_slider = gr.Slider(minimum=10, maximum=50, value=20, step=1, label="Passos de Inferência")
        produce_original_button = gr.Button("🎬 Produzir Vídeo Original", variant="primary")
    with gr.Accordion("Etapa 3: Pós-Produção (Opcional)", open=False, visible=False) as step4_accordion:
        gr.Markdown("Aplique melhorias ao filme. Cada etapa usa o resultado da anterior como fonte.")
        with gr.Accordion("A. Upscaler Latente 2x", open=True):
            upscaler_chunk_size_slider = gr.Slider(minimum=1, maximum=10, value=2, step=1, label="Fragmentos por Lote")
            run_upscaler_button = gr.Button("Executar Upscaler Latente", variant="secondary")
        with gr.Accordion("B. Masterização HD (SeedVR)", open=True):
            hd_steps_slider = gr.Slider(minimum=20, maximum=150, value=100, step=5, label="Passos de Inferência HD")
            run_hd_button = gr.Button("Executar Masterização HD", variant="secondary")
        with gr.Accordion("C. Geração de Áudio", open=True):
            audio_prompt_input = gr.Textbox(label="Prompt de Áudio Detalhado (Opcional)", lines=2, placeholder="Descreva os sons, efeitos e música.")
            run_audio_button = gr.Button("Gerar Áudio", variant="secondary")
    final_video_output = gr.Video(label="Filme Final (Resultado da Última Etapa)", visible=False, interactive=False)
    with gr.Accordion("Grupo das Keyframes", open=False) as keyframes_accordion:
        keyframe_gallery = gr.Gallery(label="Keyframes Gerados", visible=True, object_fit="contain", height="auto", type="filepath")
    with gr.Accordion("🧬 DNA Digital da Geração (JSON)", open=False) as data_accordion:
        storyboard_output = gr.JSON(label="Roteiro Gerado (Storyboard)")
        generation_data_output = gr.JSON(label="Estado de Geração Completo")
    with gr.Accordion("📝 Log de Geração (Detalhado)", open=False) as log_accordion:
        log_display = gr.Textbox(label="Log da Sessão", lines=20, interactive=False, autoscroll=True)
        update_log_button = gr.Button("Atualizar Log")

    # --- 4. CONEXÕES DE EVENTOS ---
    storyboard_and_keyframes_button.click(fn=run_pre_production_wrapper, inputs=[prompt_input, num_keyframes_slider, ref_image_input, resolution_selector, duration_per_fragment_slider], outputs=[generation_state_holder, storyboard_output, keyframe_gallery, step3_accordion])
    produce_original_button.click(fn=run_original_production_wrapper, inputs=[generation_state_holder, trim_percent_slider, handler_strength, dest_strength, guidance_scale_slider, stg_scale_slider, inference_steps_slider], outputs=[final_video_output, step4_accordion, original_latents_paths_state, current_source_video_state, generation_state_holder])
    run_upscaler_button.click(fn=run_upscaler_wrapper, inputs=[current_source_video_state, original_latents_paths_state, upscaler_chunk_size_slider], outputs=[final_video_output, current_source_video_state])
    run_hd_button.click(fn=run_hd_wrapper, inputs=[current_source_video_state, hd_steps_slider, prompt_input], outputs=[final_video_output, current_source_video_state])
    run_audio_button.click(fn=run_audio_wrapper, inputs=[current_source_video_state, audio_prompt_input, prompt_input], outputs=[final_video_output])
    generation_state_holder.change(fn=lambda state: state, inputs=generation_state_holder, outputs=generation_data_output)
    update_log_button.click(fn=get_log_content, inputs=[], outputs=[log_display])

# --- 5. INICIALIZAÇÃO DA APLICAÇÃO ---
if __name__ == "__main__":
    if os.path.exists(WORKSPACE_DIR): shutil.rmtree(WORKSPACE_DIR)
    os.makedirs(WORKSPACE_DIR)
    logger.info("Aplicação Gradio iniciada. Lançando interface...")
    demo.queue().launch()