Upload app (1).py

api/ltx/app (1).py

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+# FILE: app.py
+# DESCRIPTION: Final Gradio web interface for the ADUC-SDR Video Suite.
+# This version is refactored to use the central LtxAducOrchestrator, simplifying the UI logic
+# and making it a pure client of the backend services.
+
+import gradio as gr
+import traceback
+import sys
+import os
+import logging
+from PIL import Image
+
+# ==============================================================================
+# --- IMPORTAÇÃO DOS SERVIÇOS DE BACKEND E UTILS ---
+# ==============================================================================
+
+#try:
+    # --- MUDANÇA PRINCIPAL: Importamos apenas o ORQUESTRADOR ---
+    # O orquestrador é agora nosso único ponto de entrada para a geração de vídeo.
+from api.ltx.ltx_aduc_orchestrator import ltx_aduc_orchestrator
+    
+    # O SeedVR (upscaler de resolução) ainda é um serviço separado que pode ser chamado após a geração.
+from api.seedvr.seedvr_aduc_pipeline import seed_aduc_pipeline
+    
+    # Nosso decorador de logging para depuração
+from utils.debug_utils import log_function_io
+    
+logging.info("All backend services (Orchestrator, SeedVR) and debug utils imported successfully.")
+
+
+
+# ==============================================================================
+# --- FUNÇÕES WRAPPER (PONTE ENTRE UI E BACKEND) ---
+# ==============================================================================
+
+@log_function_io
+def run_orchestrated_generation(
+    prompt: str, start_img_path: str, 
+    height: int, width: int, duration: float,
+    fp_guidance_preset: str, fp_guidance_scale_list: str, fp_stg_scale_list: str,
+    fp_num_inference_steps: int,
+    progress=gr.Progress(track_tqdm=True)
+) -> tuple:
+    """
+    Função wrapper simplificada que coleta dados da UI e chama o orquestrador principal.
+    """
+    try:
+        logging.info("[UI] Request received. Submitting job to the main orchestrator...")
+        
+        # Monta o dicionário de configurações avançadas LTX a partir da UI
+        ltx_configs = {
+            "guidance_preset": fp_guidance_preset,
+            "guidance_scale_list": fp_guidance_scale_list,
+            "stg_scale_list": fp_stg_scale_list,
+            "num_inference_steps": fp_num_inference_steps
+        }
+
+        # Carrega a imagem inicial para um objeto PIL, que é o que o orquestrador espera.
+        initial_image_pil = Image.open(start_img_path).convert("RGB") if start_img_path else None
+
+        # --- CHAMADA ÚNICA E LIMPA PARA O ORQUESTRADOR ---
+        video_path = ltx_aduc_orchestrator(
+            prompt=prompt,
+            initial_image=initial_image_pil,
+            height=height,
+            width=width,
+            duration_in_seconds=duration,
+            ltx_configs=ltx_configs
+        )
+        
+        if not video_path:
+            raise RuntimeError("Orchestrator failed to return a valid video path. Check backend logs for details.")
+
+        logging.info(f"[UI] Orchestrator job successful. Video path: {video_path}")
+        
+        # O estado agora pode ser mais simples, apenas guardando o caminho do vídeo gerado para o próximo passo (SeedVR).
+        new_state = {"low_res_video": video_path}
+        return video_path, new_state, gr.update(visible=True)
+        
+    except Exception as e:
+        error_message = f"❌ An error occurred during the orchestrated generation:\n{e}"
+        logging.error(f"{error_message}\nDetails: {traceback.format_exc()}", exc_info=True)
+        raise gr.Error(error_message)
+
+
+@log_function_io
+def run_seedvr_upscaling(state: dict, seed: int, resolution: int, batch_size: int, fps: int, progress=gr.Progress(track_tqdm=True)) -> tuple:
+    """Wrapper para o upscale de resolução SeedVR. Esta função permanece a mesma."""
+    if not state or not state.get("low_res_video"):
+        raise gr.Error("Error: Please generate a base video in Step 1 before upscaling.")
+    if not seed_aduc_pipeline:
+        raise gr.Error("Error: The SeedVR upscaling server is not available.")
+    
+    try:
+        logging.info(f"[UI] Requesting SeedVR upscaling for video: {state.get('low_res_video')}")
+        def progress_wrapper(p, desc=""): progress(p, desc=desc)
+        
+        output_filepath = seed_aduc_pipeline.run_inference(
+            file_path=state["low_res_video"], seed=int(seed), resolution=int(resolution),
+            batch_size=int(batch_size), fps=float(fps), progress=progress_wrapper
+        )
+        
+        status_message = f"✅ Upscaling complete!\nSaved to: {output_filepath}"
+        logging.info(f"[UI] SeedVR upscaling successful. Path: {output_filepath}")
+        return gr.update(value=output_filepath), gr.update(value=status_message)
+    except Exception as e:
+        error_message = f"❌ An error occurred during SeedVR Upscaling:\n{e}"
+        logging.error(f"{error_message}\nDetails: {traceback.format_exc()}", exc_info=True)
+        return None, gr.update(value=error_message)
+
+# ==============================================================================
+# --- CONSTRUÇÃO DA INTERFACE GRADIO ---
+# ==============================================================================
+
+def build_ui():
+    """Constrói a interface completa do Gradio."""
+    with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo")) as demo:
+        app_state = gr.State(value={"low_res_video": None})
+        ui_components = {}
+        gr.Markdown("# ADUC-SDR Video Suite - Orchestrated Workflow", elem_id="main-title")
+        with gr.Row():
+            with gr.Column(scale=1): _build_generation_controls(ui_components)
+            with gr.Column(scale=1):
+                gr.Markdown("### Etapa 1: Vídeo Base Gerado pelo Orquestrador")
+                ui_components['low_res_video_output'] = gr.Video(label="O resultado aparecerá aqui", interactive=False)
+        _build_postprod_controls(ui_components)
+        _register_event_handlers(app_state, ui_components)
+    return demo
+
+def _build_generation_controls(ui: dict):
+    """Constrói os componentes da UI para a Etapa 1: Geração."""
+    gr.Markdown("### Configurações de Geração")
+    ui['prompt'] = gr.Textbox(label="Prompt(s) de Geração", 
+                              info="Escreva sua história. Cada nova linha será tratada como uma nova cena.",
+                              value="Um leão majestoso caminha pela savana\nEle sobe em uma grande pedra e olha o horizonte", 
+                              lines=4)
+    ui['start_image'] = gr.Image(label="Imagem de Início (Opcional)", type="filepath", sources=["upload"])
+    
+    with gr.Accordion("Parâmetros Principais", open=True):
+        ui['duration'] = gr.Slider(label="Duração Total (s)", value=4, step=1, minimum=1, maximum=30)
+        with gr.Row():
+            ui['height'] = gr.Slider(label="Altura", value=432, step=8, minimum=256, maximum=1024)
+            ui['width'] = gr.Slider(label="Largura", value=768, step=8, minimum=256, maximum=1024)
+
+    with gr.Accordion("Opções Avançadas LTX", open=False):
+        ui['fp_num_inference_steps'] = gr.Slider(label="Número de Passos", minimum=1, maximum=100, step=1, value=20)
+        ui['fp_guidance_preset'] = gr.Dropdown(label="Preset de Guiagem", choices=["Padrão (Recomendado)", "Customizado"], value="Padrão (Recomendado)")
+        with gr.Group(visible=False) as ui['custom_guidance_group']:
+            gr.Markdown("⚠️ Edite as listas em formato JSON. Ex: `[1.0, 2.5, 3.0]`")
+            ui['fp_guidance_scale_list'] = gr.Textbox(label="Lista de Guidance Scale", value="[1, 1, 6, 8, 6, 1, 1]")
+            ui['fp_stg_scale_list'] = gr.Textbox(label="Lista de STG Scale (Movimento)", value="[0, 0, 4, 4, 4, 2, 1]")
+    
+    ui['generate_low_btn'] = gr.Button("1. Gerar Vídeo via Orquestrador", variant="primary")
+
+def _build_postprod_controls(ui: dict):
+    """Constrói os componentes da UI para a Etapa 2: Pós-Produção (Upscaling)."""
+    with gr.Group(visible=False) as ui['post_prod_group']:
+        gr.Markdown("--- \n## Etapa 2: Pós-Produção")
+        with gr.Tabs():
+            with gr.TabItem("✨ Upscaler de Resolução (SeedVR)"):
+                is_seedvr_available = seed_aduc_pipeline is not None
+                if not is_seedvr_available:
+                    gr.Markdown("🔴 **AVISO: O serviço SeedVR não está disponível.**")
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        ui['seedvr_seed'] = gr.Slider(minimum=0, maximum=999999, value=42, step=1, label="Seed")
+                        ui['seedvr_resolution'] = gr.Slider(minimum=720, maximum=2160, value=1080, step=8, label="Resolução Vertical Alvo")
+                        ui['seedvr_batch_size'] = gr.Slider(minimum=1, maximum=16, value=4, step=1, label="Batch Size por GPU")
+                        ui['seedvr_fps'] = gr.Number(label="FPS de Saída (0 = original)", value=0)
+                        ui['run_seedvr_btn'] = gr.Button("2. Iniciar Upscaling SeedVR", variant="primary", interactive=is_seedvr_available)
+                    with gr.Column(scale=1):
+                        ui['seedvr_video_output'] = gr.Video(label="Vídeo com Upscale SeedVR", interactive=False)
+                        ui['seedvr_status_box'] = gr.Textbox(label="Status do SeedVR", value="Aguardando...", lines=3, interactive=False)
+
+def _register_event_handlers(app_state: gr.State, ui: dict):
+    """Registra todos os manipuladores de eventos do Gradio."""
+    def toggle_custom_guidance(preset_choice: str) -> gr.update:
+        return gr.update(visible=(preset_choice == "Customizado"))
+    
+    ui['fp_guidance_preset'].change(fn=toggle_custom_guidance, inputs=ui['fp_guidance_preset'], outputs=ui['custom_guidance_group'])
+
+    gen_inputs = [
+        ui['prompt'], ui['start_image'],
+        ui['height'], ui['width'], ui['duration'],
+        ui['fp_guidance_preset'], ui['fp_guidance_scale_list'], ui['fp_stg_scale_list'],
+        ui['fp_num_inference_steps'],
+    ]
+    gen_outputs = [ui['low_res_video_output'], app_state, ui['post_prod_group']]
+    
+    ui['generate_low_btn'].click(fn=run_orchestrated_generation, inputs=gen_inputs, outputs=gen_outputs)
+    
+    if 'run_seedvr_btn' in ui and ui['run_seedvr_btn'].interactive:
+        seedvr_inputs = [app_state, ui['seedvr_seed'], ui['seedvr_resolution'], ui['seedvr_batch_size'], ui['seedvr_fps']]
+        seedvr_outputs = [ui['seedvr_video_output'], ui['seedvr_status_box']]
+        ui['run_seedvr_btn'].click(fn=run_seedvr_upscaling, inputs=seedvr_inputs, outputs=seedvr_outputs)
+
+# ==============================================================================
+# --- PONTO DE ENTRADA DA APLICAÇÃO ---
+# ==============================================================================
+
+if __name__ == "__main__":
+    demo = build_ui()
+    demo.queue().launch(server_name="0.0.0.0", server_port=7860, debug=True, show_error=True)