Update aduc_orchestrator.py
Browse files- aduc_orchestrator.py +149 -100
aduc_orchestrator.py
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# Copyright (C) 4 de Agosto de 2025 Carlos Rodrigues dos Santos
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# Carlos Rodrigues dos Santos
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# carlex22@gmail.com
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#
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# GitHub: https://github.com/carlex22/Aduc-sdr
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# YouTube (Resultados): https://m.youtube.com/channel/UC3EgoJi_Fv7yuDpvfYNtoIQ
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# (
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# mas SEM QUALQUER GARANTIA; sem mesmo a garantia implícita de
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# COMERCIALIZAÇÃO ou ADEQUAÇÃO A UM DETERMINADO FIM. Consulte a
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# Licença Pública Geral Affero da GNU para mais detalhes.
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#
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# Você deve ter recebido uma cópia da Licença Pública Geral Affero da GNU
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# junto com este programa. Se não, veja <https://www.gnu.org/licenses/>.
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#
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# AVISO DE PATENTE PENDENTE: O método e sistema ADUC implementado neste
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# software está em processo de patenteamento. Consulte NOTICE.md.
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import os
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import time
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@@ -38,131 +24,133 @@ from ltx_manager_helpers import ltx_manager_singleton
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from gemini_helpers import gemini_singleton
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from image_specialist import image_specialist_singleton
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#
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logger = logging.getLogger(__name__)
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class AducDirector:
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"""
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"""
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def __init__(self, workspace_dir: str):
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"""
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Args:
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workspace_dir (str):
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"""
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self.workspace_dir = workspace_dir
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os.makedirs(self.workspace_dir, exist_ok=True)
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self.state: Dict[str, Any] = {}
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logger.info(f"
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def update_state(self, key: str, value: Any) -> None:
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"""
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Args:
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key (str):
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value (Any):
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"""
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logger.info(f"
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self.state[key] = value
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def get_state(self, key: str, default: Any = None) -> Any:
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"""
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Args:
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key (str):
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default (Any, optional):
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Returns:
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Any:
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"""
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return self.state.get(key, default)
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class AducOrchestrator:
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"""
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"""
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def __init__(self, workspace_dir: str):
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"""
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Args:
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workspace_dir (str):
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"""
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self.director = AducDirector(workspace_dir)
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self.editor = Deformes4DEngine(ltx_manager_singleton, workspace_dir)
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self.painter = image_specialist_singleton
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logger.info("Maestro
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def process_image_for_story(self, image_path: str, size: int, filename: str) -> str:
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"""
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Args:
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image_path (str):
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size (int):
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filename (str):
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Returns:
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str:
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"""
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img = Image.open(image_path).convert("RGB")
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img_square = ImageOps.fit(img, (size, size), Image.Resampling.LANCZOS)
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processed_path = os.path.join(self.director.workspace_dir, filename)
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img_square.save(processed_path)
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logger.info(f"
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return processed_path
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progress: gr.Progress) -> Tuple[List[str], str, Any]:
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"""
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"""
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logger.info(f"
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progress(0.2, desc="
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storyboard = gemini_singleton.generate_storyboard(prompt, num_keyframes, ref_image_paths)
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logger.info(f"
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self.director.update_state("storyboard", storyboard)
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self.director.update_state("processed_ref_paths", ref_image_paths)
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return storyboard, ref_image_paths[0], gr.update(visible=True, open=True)
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def task_select_keyframes(self, storyboard: List[str], base_ref_paths: List[str],
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pool_ref_paths: List[str]) -> List[str]:
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"""
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"""
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logger.info(f"
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selected_paths = gemini_singleton.select_keyframes_from_pool(storyboard, base_ref_paths, pool_ref_paths)
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logger.info(f"Editor
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self.director.update_state("keyframes", selected_paths)
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return selected_paths
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def task_generate_keyframes(self, storyboard: List[str], initial_ref_path: str, global_prompt: str,
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keyframe_resolution: int, progress_callback_factory=None) -> List[str]:
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"""
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"""
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logger.info("
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general_ref_paths = self.director.get_state("processed_ref_paths", [])
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final_keyframes = self.painter.generate_keyframes_from_storyboard(
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storyboard=storyboard,
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initial_ref_path=initial_ref_path,
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general_ref_paths=general_ref_paths,
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progress_callback_factory=progress_callback_factory
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)
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self.director.update_state("keyframes", final_keyframes)
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logger.info("Maestro:
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return final_keyframes
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"""
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"""
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logger.info("Maestro:
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storyboard = self.director.get_state("storyboard", [])
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storyboard=storyboard,
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seconds_per_fragment=seconds_per_fragment,
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trim_percent=trim_percent,
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handler_strength=handler_strength,
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destination_convergence_strength=destination_convergence_strength,
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progress=progress
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):
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if "final_path" in update and update["final_path"]:
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yield {"final_path": final_movie_path}
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break
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# aduc_orchestrator.py
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#
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# Copyright (C) August 4, 2025 Carlos Rodrigues dos Santos
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#
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# Version: 2.0.0
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#
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# This file contains the core ADUC (Automated Discovery and Orchestration of Complex tasks)
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# orchestrator, known as the "Maestro" (Γ). Its responsibility is to manage the high-level
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# creative workflow of film production. It receives user intent from the UI, delegates
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# specific tasks (like storyboarding, keyframe generation, video rendering, and post-production)
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# to the appropriate AI "Specialists," and manages the state of the production via the
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# "Director" component. It does not perform AI inference itself but acts as the central conductor.
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import os
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import time
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from gemini_helpers import gemini_singleton
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from image_specialist import image_specialist_singleton
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# The logger is configured in app.py; here we just get the instance.
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logger = logging.getLogger(__name__)
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class AducDirector:
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"""
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Represents the Scene Director, responsible for managing the production state.
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Acts as the "score" for the orchestra, keeping track of all generated artifacts
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(script, keyframes, etc.) during the creative process.
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"""
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def __init__(self, workspace_dir: str):
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"""
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Initializes the Director, creating the workspace directory.
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Args:
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workspace_dir (str): The path to the directory where all generation
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artifacts will be stored.
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"""
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self.workspace_dir = workspace_dir
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os.makedirs(self.workspace_dir, exist_ok=True)
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self.state: Dict[str, Any] = {}
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logger.info(f"The stage is set. Workspace at '{self.workspace_dir}'.")
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def update_state(self, key: str, value: Any) -> None:
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"""
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Notes new information on the "score," updating the production state.
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Args:
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key (str): The key for the state to be saved (e.g., "storyboard").
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value (Any): The value of the state (e.g., the list of storyboard scenes).
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"""
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logger.info(f"Notating on the score: State '{key}' updated.")
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self.state[key] = value
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def get_state(self, key: str, default: Any = None) -> Any:
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"""
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Consults information from the "score," retrieving a saved state.
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Args:
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key (str): The key of the state to be retrieved.
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default (Any, optional): The value to return if the key does not exist.
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Returns:
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Any: The value of the saved state or the default value.
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"""
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return self.state.get(key, default)
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class AducOrchestrator:
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"""
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Implements the Maestro (Γ), the central orchestration layer of the ADUC architecture.
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It does not execute AI tasks directly but delegates each step of the creative
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process (scriptwriting, art direction, cinematography) to the appropriate Specialists.
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"""
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def __init__(self, workspace_dir: str):
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"""
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Initializes the Maestro and its musicians (the AI specialists).
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Args:
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workspace_dir (str): The path to the workspace, which will be managed
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by the AducDirector.
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"""
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self.director = AducDirector(workspace_dir)
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self.editor = Deformes4DEngine(ltx_manager_singleton, workspace_dir)
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self.painter = image_specialist_singleton
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logger.info("ADUC Maestro is on the podium. Musicians (specialists) are ready.")
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def process_image_for_story(self, image_path: str, size: int, filename: str) -> str:
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"""
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Pre-processes a reference image, standardizing it for use by the Specialists.
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Converts to RGB, resizes to a square format, and saves to the workspace.
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Args:
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image_path (str): Path of the original image.
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size (int): Width and height of the final image.
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filename (str): Filename for the processed image.
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Returns:
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str: The path to the processed and saved image.
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"""
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img = Image.open(image_path).convert("RGB")
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img_square = ImageOps.fit(img, (size, size), Image.Resampling.LANCZOS)
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processed_path = os.path.join(self.director.workspace_dir, filename)
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img_square.save(processed_path)
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logger.info(f"Reference image processed and saved to: {processed_path}")
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return processed_path
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# --- PRE-PRODUCTION TASKS ---
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def task_generate_storyboard(self, prompt: str, num_keyframes: int, ref_image_paths: List[str],
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progress: gr.Progress) -> Tuple[List[str], str, Any]:
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"""
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Delegates the task of creating the storyboard to the Scriptwriter (Gemini).
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"""
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logger.info(f"Act 1, Scene 1: Script. Instructing Scriptwriter (Gemini) to create {num_keyframes} scenes from: '{prompt}'")
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progress(0.2, desc="Consulting AI Scriptwriter (Gemini)...")
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storyboard = gemini_singleton.generate_storyboard(prompt, num_keyframes, ref_image_paths)
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logger.info(f"Scriptwriter returned the score: {storyboard}")
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self.director.update_state("storyboard", storyboard)
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self.director.update_state("processed_ref_paths", ref_image_paths)
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return storyboard, ref_image_paths[0], gr.update(visible=True, open=True)
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def task_select_keyframes(self, storyboard: List[str], base_ref_paths: List[str],
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pool_ref_paths: List[str]) -> List[str]:
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"""
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Delegates to the Editor/Photographer (Gemini) the task of selecting the best images
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from a "scene bank" to match the script (Photographer Mode).
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"""
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logger.info(f"Act 1, Scene 2 (Photographer Mode): Instructing Editor (Gemini) to select {len(storyboard)} keyframes.")
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selected_paths = gemini_singleton.select_keyframes_from_pool(storyboard, base_ref_paths, pool_ref_paths)
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logger.info(f"Editor selected the following scenes: {[os.path.basename(p) for p in selected_paths]}")
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self.director.update_state("keyframes", selected_paths)
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return selected_paths
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def task_generate_keyframes(self, storyboard: List[str], initial_ref_path: str, global_prompt: str,
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keyframe_resolution: int, progress_callback_factory=None) -> List[str]:
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"""
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Delegates to the Art Director (ImageSpecialist) the task of generating the visual
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keyframes from the script (Art Director Mode).
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"""
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logger.info("Act 1, Scene 2 (Art Director Mode): Delegating to Image Specialist.")
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general_ref_paths = self.director.get_state("processed_ref_paths", [])
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final_keyframes = self.painter.generate_keyframes_from_storyboard(
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storyboard=storyboard,
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initial_ref_path=initial_ref_path,
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general_ref_paths=general_ref_paths,
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progress_callback_factory=progress_callback_factory
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)
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self.director.update_state("keyframes", final_keyframes)
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logger.info("Maestro: Image Specialist has completed keyframe generation.")
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return final_keyframes
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# --- PRODUCTION & POST-PRODUCTION TASKS ---
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def task_produce_original_movie(self, keyframes: List[str], global_prompt: str, seconds_per_fragment: float,
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trim_percent: int, handler_strength: float,
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destination_convergence_strength: float,
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guidance_scale: float, stg_scale: float, inference_steps: int,
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video_resolution: int, use_continuity_director: bool,
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progress: gr.Progress) -> Dict[str, Any]:
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"""
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Delegates the production of the original master video to the Deformes4DEngine.
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This is the core video generation step.
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"""
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logger.info("Maestro: Delegating production of the original movie to Deformes4DEngine.")
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storyboard = self.director.get_state("storyboard", [])
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# The engine will now handle the full generation and return the final paths
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result = self.editor.generate_original_movie(
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keyframes=keyframes,
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global_prompt=global_prompt,
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storyboard=storyboard,
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seconds_per_fragment=seconds_per_fragment,
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trim_percent=trim_percent,
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handler_strength=handler_strength,
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destination_convergence_strength=destination_convergence_strength,
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video_resolution=video_resolution,
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| 192 |
+
use_continuity_director=use_continuity_director,
|
| 193 |
+
# New LTX pipeline parameters
|
| 194 |
+
guidance_scale=guidance_scale,
|
| 195 |
+
stg_scale=stg_scale,
|
| 196 |
+
num_inference_steps=inference_steps,
|
| 197 |
+
progress=progress
|
| 198 |
+
)
|
| 199 |
+
|
| 200 |
+
self.director.update_state("final_video_path", result["final_path"])
|
| 201 |
+
self.director.update_state("latent_paths", result["latent_paths"])
|
| 202 |
+
logger.info("Maestro: Original movie production complete.")
|
| 203 |
+
return result
|
| 204 |
+
|
| 205 |
+
def task_run_latent_upscaler(self, latent_paths: List[str], chunk_size: int, progress: gr.Progress) -> Generator[Dict[str, Any], None, None]:
|
| 206 |
+
"""
|
| 207 |
+
Orchestrates the latent upscaling task.
|
| 208 |
+
"""
|
| 209 |
+
logger.info(f"Maestro: Delegating latent upscaling task for {len(latent_paths)} fragments.")
|
| 210 |
+
|
| 211 |
+
# This is a generator function to allow for UI updates
|
| 212 |
+
for update in self.editor.upscale_latents_and_create_video(
|
| 213 |
+
latent_paths=latent_paths,
|
| 214 |
+
chunk_size=chunk_size,
|
| 215 |
+
progress=progress
|
| 216 |
+
):
|
| 217 |
+
if "final_path" in update and update["final_path"]:
|
| 218 |
+
self.director.update_state("final_video_path", update["final_path"])
|
| 219 |
+
yield update["final_path"]
|
| 220 |
+
break
|
| 221 |
+
|
| 222 |
+
logger.info("Maestro: Latent upscaling complete.")
|
| 223 |
+
|
| 224 |
+
def task_run_hd_mastering(self, source_video_path: str, model_version: str, steps: int, progress: gr.Progress) -> Generator[Dict[str, Any], None, None]:
|
| 225 |
+
"""
|
| 226 |
+
Orchestrates the HD mastering task.
|
| 227 |
+
"""
|
| 228 |
+
logger.info(f"Maestro: Delegating HD mastering task using SeedVR {model_version}.")
|
| 229 |
+
|
| 230 |
+
# We'll need a new method in the editor to handle this
|
| 231 |
+
for update in self.editor.master_video_hd(
|
| 232 |
+
source_video_path=source_video_path,
|
| 233 |
+
model_version=model_version,
|
| 234 |
+
steps=steps,
|
| 235 |
+
prompt=self.director.get_state("storyboard", ["A cinematic high-quality movie."])[0],
|
| 236 |
progress=progress
|
| 237 |
):
|
| 238 |
if "final_path" in update and update["final_path"]:
|
| 239 |
+
self.director.update_state("final_video_path", update["final_path"])
|
| 240 |
+
yield update["final_path"]
|
|
|
|
| 241 |
break
|
| 242 |
+
|
| 243 |
+
logger.info("Maestro: HD mastering complete.")
|
| 244 |
|
| 245 |
+
def task_run_audio_generation(self, source_video_path: str, audio_prompt: str, progress: gr.Progress) -> Generator[Dict[str, Any], None, None]:
|
| 246 |
+
"""
|
| 247 |
+
Orchestrates the audio generation task.
|
| 248 |
+
"""
|
| 249 |
+
logger.info(f"Maestro: Delegating audio generation task.")
|
| 250 |
+
|
| 251 |
+
# Another new method in the editor
|
| 252 |
+
for update in self.editor.generate_audio_for_final_video(
|
| 253 |
+
source_video_path=source_video_path,
|
| 254 |
+
audio_prompt=audio_prompt,
|
| 255 |
+
progress=progress
|
| 256 |
+
):
|
| 257 |
+
if "final_path" in update and update["final_path"]:
|
| 258 |
+
self.director.update_state("final_video_path", update["final_path"])
|
| 259 |
+
yield update["final_path"]
|
| 260 |
+
break
|
| 261 |
+
|
| 262 |
+
logger.info("Maestro: Audio generation complete.")
|