# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from pathlib import Path import numpy as np from cosmos_predict1.auxiliary.guardrail.blocklist.blocklist import Blocklist from cosmos_predict1.auxiliary.guardrail.common.core import GuardrailRunner from cosmos_predict1.auxiliary.guardrail.face_blur_filter.face_blur_filter import RetinaFaceFilter from cosmos_predict1.auxiliary.guardrail.llamaGuard3.llamaGuard3 import LlamaGuard3 from cosmos_predict1.auxiliary.guardrail.video_content_safety_filter.video_content_safety_filter import ( VideoContentSafetyFilter, ) from cosmos_predict1.utils import log def create_text_guardrail_runner(checkpoint_dir: str) -> GuardrailRunner: """Create the text guardrail runner.""" return GuardrailRunner(safety_models=[Blocklist(checkpoint_dir), LlamaGuard3(checkpoint_dir)]) def create_video_guardrail_runner(checkpoint_dir: str) -> GuardrailRunner: """Create the video guardrail runner.""" return GuardrailRunner( safety_models=[VideoContentSafetyFilter(checkpoint_dir)], postprocessors=[RetinaFaceFilter(checkpoint_dir)], ) def run_text_guardrail(prompt: str, guardrail_runner: GuardrailRunner) -> bool: """Run the text guardrail on the prompt, checking for content safety. Args: prompt: The text prompt. guardrail_runner: The text guardrail runner. Returns: bool: Whether the prompt is safe. """ is_safe, message = guardrail_runner.run_safety_check(prompt) if not is_safe: log.critical(f"GUARDRAIL BLOCKED: {message}") return is_safe def run_video_guardrail(frames: np.ndarray, guardrail_runner: GuardrailRunner) -> np.ndarray | None: """Run the video guardrail on the frames, checking for content safety and applying face blur. Args: frames: The frames of the generated video. guardrail_runner: The video guardrail runner. Returns: The processed frames if safe, otherwise None. """ is_safe, message = guardrail_runner.run_safety_check(frames) if not is_safe: log.critical(f"GUARDRAIL BLOCKED: {message}") return None frames = guardrail_runner.postprocess(frames) return frames