[Sincronização Automática] - 2025-09-23 15:50:50

.gitignore

@@ -13,4 +13,6 @@ __pycache__/
 # Ignorar logs e arquivos de ambiente
 *.log
 aduc_log.txt
-.env
+.env
+
+comid.sh

Dockerfile

@@ -1,480 +1,115 @@
 # =============================================================================
-# DOCKERFILE - Complete AI Video Suite v2.0.0
-# Optimized for 8x NVIDIA L40S GPUs (384GB Total VRAM)
-# Production-Ready Multi-GPU Video Generation Suite
+# DOCKERFILE - ADUC-SDR: AI Video Suite v4.1.0
+# Base: CUDA 12.8.0 | PyTorch 2.8.0+cu121
+# Otimizado para Hugging Face Spaces com 8x NVIDIA L40S GPUs
 # =============================================================================
 
+# Base CUDA 12.8.0
 FROM nvidia/cuda:12.8.0-devel-ubuntu22.04
 
 # =============================================================================
-# METADATA AND LABELS
+# METADADOS
 # =============================================================================
-
-LABEL maintainer="Complete AI Video Suite Team"
-LABEL description="Multi-GPU AI Video Generation Suite with LTX FP8, Q8 Kernels, SeedVR, Wan2.2, VINCIE, MMAudio"
-LABEL version="2.0.0"
-LABEL build_date="2025-09-18"
-LABEL cuda_version="12.4.0"
+LABEL maintainer="Carlos Rodrigues dos Santos & Development Partner"
+LABEL description="ADUC-SDR: Production-Ready Multi-GPU AI Video Generation Suite with Wan2.2, SeedVR, LTX, MMAudio"
+LABEL version="4.1.0"
+LABEL cuda_version="12.8.0"
 LABEL python_version="3.10"
-LABEL pytorch_version="2.8.0+cu128"
-LABEL architecture="amd64"
-LABEL gpu_optimized="8x_L40S"
-LABEL total_vram="384GB"
-LABEL license="MIT"
-
+# A wheel do PyTorch é compilada contra o CUDA Toolkit 12.1, mas é 100% compatível
+# com o driver mais recente (12.8) presente na imagem base.
+LABEL pytorch_version="2.8.0+cu121"
+LABEL gpu_optimized_for="8x_NVIDIA_L40S"
 
 # =============================================================================
-# ENVIRONMENT VARIABLES - PRODUCTION OPTIMIZED
+# VARIÁVEIS DE AMBIENTE GLOBAIS
 # =============================================================================
-
 ENV DEBIAN_FRONTEND=noninteractive
 ENV TZ=UTC
-ENV LC_ALL=C.UTF-8
 ENV LANG=C.UTF-8
-
-# Python optimization
+ENV LC_ALL=C.UTF-8
 ENV PYTHONUNBUFFERED=1
 ENV PYTHONDONTWRITEBYTECODE=1
-ENV PYTHONIOENCODING=utf-8
 ENV PIP_NO_CACHE_DIR=1
-ENV PIP_DISABLE_PIP_VERSION_CHECK=0
+ENV PIP_DISABLE_PIP_VERSION_CHECK=1
 
-# CUDA optimizations for 8x L40S GPUs
+# Otimizações de CUDA e Build
 ENV NVIDIA_VISIBLE_DEVICES=all
-ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility,graphics
-ENV NVIDIA_REQUIRE_CUDA="cuda>=12.8"
-ENV CUDA_LAUNCH_BLOCKING=0
+ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
 ENV TORCH_CUDA_ARCH_LIST="8.9"
-ENV CUDA_CACHE_MAXSIZE=2147483648
-
-# Multi-GPU distributed training
-ENV NCCL_DEBUG=DEBUG
-ENV NCCL_TREE_THRESHOLD=1
-ENV NCCL_P2P_DISABLE=0
-ENV NCCL_IB_DISABLE=0
-ENV NCCL_NVLS_ENABLE=1
-ENV NCCL_CROSS_NIC=1
-
-# PyTorch optimizations
-ENV PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512,roundup_power2_divisions:16
-ENV TORCH_BACKENDS_CUDNN_BENCHMARK=1
-ENV TORCH_BACKENDS_CUDA_MATMUL_ALLOW_TF32=1
-ENV TORCH_BACKENDS_CUDNN_ALLOW_TF32=1
+ENV MAX_JOBS=90
 
-# Application paths
+# Caminhos da Aplicação
 ENV APP_HOME=/app
-ENV HF_HOME=/app/model_cache
-ENV HF_HUB_CACHE=/app/model_cache/hub
-ENV TRANSFORMERS_CACHE=/app/model_cache/transformers
-ENV TORCH_HOME=/app/model_cache/torch
-ENV TMPDIR=/app/tmp
-ENV OUTPUT_DIR=/app/outputs
-
-# CPU optimizations
-ENV OMP_NUM_THREADS=8
-ENV MKL_NUM_THREADS=8
-ENV NUMEXPR_NUM_THREADS=8
-ENV OPENBLAS_NUM_THREADS=8
-
-# =============================================================================
-# SYSTEM PACKAGE INSTALLATION
-# =============================================================================
-
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    cmake \
-    ninja-build \
-    pkg-config \
-    python3.11 \
-    python3.11-dev \
-    python3.11-distutils \
-    python3-pip \
-    python3.11-venv \
-    git \
-    git-lfs \
-    curl \
-    wget \
-    rsync \
-    unzip \
-    zip \
-    ffmpeg \
-    libavcodec-dev \
-    libavformat-dev \
-    libavutil-dev \
-    libswscale-dev \
-    libgl1-mesa-glx \
-    libgl1-mesa-dev \
-    libglib2.0-0 \
-    libsm6 \
-    libxext6 \
-    libxrender-dev \
-    libgomp1 \
-    libglu1-mesa \
-    libglu1-mesa-dev \
-    htop \
-    nvtop \
-    tree \
-    vim \
-    nano \
-    tmux \
-    screen \
-    net-tools \
-    iproute2 \
-    iotop \
-    && apt-get autoremove -y \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/* \
-    && rm -rf /tmp/* \
-    && rm -rf /var/tmp/*
+WORKDIR $APP_HOME
 
 # =============================================================================
-# PYTHON SETUP AND OPTIMIZATION
+# PACOTES DO SISTEMA E PYTHON 3.10
 # =============================================================================
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+    build-essential cmake git git-lfs curl wget ffmpeg ninja-build \
+    python3.10 python3.10-dev python3.10-distutils python3-pip \
+    && apt-get clean && rm -rf /var/lib/apt/lists/*
 
 RUN ln -sf /usr/bin/python3.10 /usr/bin/python3 && \
     ln -sf /usr/bin/python3.10 /usr/bin/python && \
-    python3 -m pip install --upgrade pip==24.2 setuptools==70.0.0 wheel==0.43.0
-
-RUN pip install  \
-    packaging \
-    ninja \
-    cmake \
-    pybind11 \
-    scikit-build \
-    cython \
-    numpy>=1.24.3
+    python3 -m pip install --upgrade pip
 
 # =============================================================================
-# PYTORCH AND CUDA LIBRARIES
+# INSTALAÇÃO DE BIBLIOTECAS DE ALTA PERFORMANCE
 # =============================================================================
 
+# 1. Instala PyTorch 2.8.0 e ferramentas de build
 RUN pip install \
-    torch>=2.8.0+cu128 \
-    torchvision \
-    torchaudio \
-    --index-url https://download.pytorch.org/whl/cu128
+    torch==2.8.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 \
+    packaging wheel ninja setuptools
 
-RUN pip install torchao
+# 2. Instala a wheel pré-compilada do Flash Attention 2.8.0
+#    Esta é a forma mais rápida e estável de instalar, evitando compilação demorada.
+#    Esta wheel é compatível com PyTorch 2.8.0 e CUDA 12.x
+RUN pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.5.8/flash_attn-2.5.8+cu122torch2.3.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
 
-RUN python3 -c "import torch; print(f'PyTorch: {torch.__version__}'); print(f'CUDA available: {torch.cuda.is_available()}'); print(f'CUDA version: {torch.version.cuda}'); print(f'Device count: {torch.cuda.device_count()}')"
+# 3. Compila e instala o NVIDIA Apex
+RUN git clone https://github.com/NVIDIA/apex.git && \
+    cd apex && \
+    pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./ && \
+    cd .. && rm -rf apex
 
+# 4. Instala os Kernels customizados do LTX
+RUN pip install --no-build-isolation git+https://github.com/Lightricks/LTX-Video-Q8-Kernels.git
 
 # =============================================================================
-# AI/ML LIBRARIES INSTALLATION
+# INSTALAÇÃO DO RESTANTE DAS DEPENDÊNCIAS
 # =============================================================================
+COPY requirements.txt .
 
-WORKDIR $APP_HOME
-COPY . .
-
+# Instala os pacotes restantes do requirements.txt
+# A linha do flash-attention no arquivo será ignorada se já estiver instalado, mas é bom limpá-la.
 RUN pip install -r requirements.txt
 
 # =============================================================================
-# APPLICATION STRUCTURE SETUP
+# CLONAGEM E INSTALAÇÃO DOS REPOSITÓRIOS DA APLICAÇÃO
 # =============================================================================
-
-RUN mkdir -p \
-    $APP_HOME/installer \
-    $APP_HOME/monitoring \
-    $APP_HOME/tools \
-    $APP_HOME/configs \
-    $APP_HOME/build_cache \
-    $APP_HOME/model_cache/hub \
-    $APP_HOME/model_cache/transformers \
-    $APP_HOME/model_cache/torch \
-    $APP_HOME/model_cache/ltx_models \
-    $APP_HOME/tmp \
-    $APP_HOME/outputs \
-    $APP_HOME/logs \
-    && chmod -R 755 $APP_HOME
+RUN git clone https://github.com/Lightricks/LTX-Video.git && cd LTX-Video && pip install -e .[inference]
+RUN git clone https://github.com/Wan-Video/Wan2.2.git && cd Wan2.2 && pip install -r requirements.txt && pip install -r requirements_s2v.txt
+RUN git clone https://github.com/bytedance-seed/SeedVR.git && cd SeedVR && pip install -r requirements.txt
+RUN git clone https://github.com/hkchengrex/MMAudio.git && cd MMAudio && pip install -e .
 
 # =============================================================================
-# DOWNLOAD PREREQUISITE FILES
+# COPIA O CÓDIGO DA APLICAÇÃO E CONFIGURA PERMISSÕES
 # =============================================================================
-
-
 COPY . .
 
-COPY configs/ ./configs/
-
-
-RUN chmod +x start.sh && \
-    find . -name "*.sh" -exec chmod +x {} \; && \
-    find . -name "*.py" -exec chmod +x {} \;
-
-# =============================================================================
-# CREATE OPTIMIZATION PATCHES AND TOOLS (FIXED SYNTAX)
-# =============================================================================
-
-
-# =============================================================================
-# CONFIGURATION FILES
-# =============================================================================
-
-# Create default LTX FP8 configuration
-RUN cat <<'YAML_CONFIG' > $APP_HOME/configs/ltxv-13b-0.9.8-distilled-fp8.yaml
-# LTX Video FP8 Distilled Configuration
-# Optimized for 8x L40S GPUs (384GB VRAM)
-model:
-  target: "ltx_video.models.transformer_temporal.TransformerTemporalModel"
-  params:
-    transformer_additional_kwargs:
-      attention_mode: "sdpa"
-      enable_flash_attention: true
-      memory_efficient_attention: true
-    network_config:
-      model_name: "ltxv-13b-0.9.8-distilled-fp8"
-      fp8_optimization: true
-      quantization: "fp8"
-      ada_optimized: true
-      multi_gpu_support: true
-
-scheduler:
-  target: "diffusers.LTXVideoScheduler"
-  params:
-    num_train_timesteps: 1000
-    beta_start: 0.0001
-    beta_end: 0.02
-    beta_schedule: "scaled_linear"
-
-vae:
-  target: "diffusers.AutoencoderKLLTXVideo"
-  params:
-    force_upcast: false
-    enable_slicing: true
-    enable_tiling: true
-
-text_encoder:
-  target: "transformers.T5EncoderModel"
-  params:
-    torch_dtype: "bfloat16"
-
-pipeline:
-  target: "diffusers.LTXVideoPipeline"
-  params:
-    scheduler_type: "LTXVideoScheduler"
-    num_inference_steps: 4
-    guidance_scale: 1.0
-    height: 704
-    width: 1216
-    num_frames: 121
-    fps: 30
-    enable_memory_efficient_attention: true
-    enable_cpu_offload: false
-    enable_model_cpu_offload: false
-    max_batch_size: 4
-
-multi_gpu:
-  enabled: true
-  num_gpus: 8
-  distribution_strategy: "data_parallel"
-  load_balancing: "memory_aware"
-  synchronize_gpus: true
-YAML_CONFIG
-
-# Create multi-GPU optimization config
-RUN cat <<'GPU_CONFIG' > $APP_HOME/configs/multi_gpu_config.yaml
-# Multi-GPU Configuration for 8x L40S Setup
-system:
-  gpu_count: 8
-  total_vram: "384GB"
-  compute_capability: "8.9"
-  architecture: "ADA_LOVELACE"
-
-distributed_training:
-  backend: "nccl"
-  init_method: "env://"
-  world_size: 8
-  rank: 0
-
-memory_optimization:
-  gradient_checkpointing: true
-  mixed_precision: "bf16"
-  max_batch_size_per_gpu: 8
-  gradient_accumulation_steps: 4
-  memory_fraction: 0.95
-
-performance:
-  torch_compile: true
-  cuda_graphs: true
-  tensor_cores: true
-  flash_attention: true
-  memory_efficient_attention: true
-
-load_balancing:
-  strategy: "memory_aware"
-  rebalance_interval: 30
-  utilization_threshold: 0.8
-
-thermal_management:
-  max_temperature: 83
-  fan_curve: "aggressive"
-  throttle_threshold: 80
-  monitoring_interval: 10
-
-power_management:
-  max_power_limit: 300
-  efficiency_mode: false
-  power_monitoring: true
-GPU_CONFIG
-
-# =============================================================================
-# HEALTH CHECK SCRIPT
-# =============================================================================
-
-RUN cat <<'HEALTHCHECK_SCRIPT' > $APP_HOME/healthcheck.py
-#!/usr/bin/env python3
-"""
-Health check script for Complete AI Video Suite
-"""
-import sys
-import requests
-import torch
-import time
-import logging
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-def check_cuda():
-    """Check CUDA availability and GPU status"""
-    if not torch.cuda.is_available():
-        logger.error("CUDA not available")
-        return False
-    
-    gpu_count = torch.cuda.device_count()
-    logger.info(f"CUDA available with {gpu_count} GPUs")
-    
-    for i in range(gpu_count):
-        try:
-            torch.cuda.set_device(i)
-            props = torch.cuda.get_device_properties(i)
-            memory_allocated = torch.cuda.memory_allocated() / 1024**3
-            memory_total = props.total_memory / 1024**3
-            
-            logger.info(f"GPU {i}: {props.name} ({memory_allocated:.2f}GB/{memory_total:.1f}GB)")
-            
-            x = torch.randn(100, 100, device=f'cuda:{i}')
-            y = torch.matmul(x, x)
-            torch.cuda.synchronize()
-            
-        except Exception as e:
-            logger.error(f"GPU {i} test failed: {e}")
-            return False
-    
-    return True
-
-def check_web_service():
-    """Check if web service is responding"""
-    try:
-        response = requests.get("http://localhost:7860/", timeout=10)
-        if response.status_code == 200:
-            logger.info("Web service is responding")
-            return True
-        else:
-            logger.error(f"Web service returned status code: {response.status_code}")
-            return False
-    except requests.RequestException as e:
-        logger.error(f"Web service check failed: {e}")
-        return False
-
-def main():
-    """Main health check routine"""
-    logger.info("Starting health check...")
-    
-    if not check_cuda():
-        sys.exit(1)
-    
-    if not check_web_service():
-        sys.exit(1)
-    
-    logger.info("All health checks passed")
-    sys.exit(0)
-
-if __name__ == "__main__":
-    main()
-HEALTHCHECK_SCRIPT
-
-RUN chmod +x $APP_HOME/healthcheck.py
-
-# =============================================================================
-# USER SETUP AND SECURITY
-# =============================================================================
-
-RUN mkdir -p /etc/sudoers.d && \
-    useradd -m -u 1000 -s /bin/bash appuser && \
-    usermod -aG sudo appuser && \
+RUN useradd -m -u 1000 -s /bash appuser && \
     chown -R appuser:appuser $APP_HOME && \
-    echo "appuser ALL=(ALL) NOPASSWD: /usr/bin/nvidia-smi, /usr/bin/nvidia-ml-py" > /etc/sudoers.d/appuser
+    mkdir -p /app/deformes_workspace && chown -R appuser:appuser /app/deformes_workspace
 
 USER appuser
 
-WORKDIR $APP_HOME
-
-# =============================================================================
-# RUNTIME CONFIGURATION
-# =============================================================================
-
-EXPOSE 7860 8001 8002 6006
-
-VOLUME ["/app/model_cache", "/app/outputs", "/app/logs", "/app/build_cache"]
-
-HEALTHCHECK --interval=60s --timeout=30s --start-period=300s --retries=3 \
-    CMD python3 /app/healthcheck.py
-
-# =============================================================================
-# FINAL SETUP AND ENTRY POINT
-# =============================================================================
-
-RUN cat <<'ENTRYPOINT_SCRIPT' > $APP_HOME/docker-entrypoint.sh
-#!/bin/bash
-set -euo pipefail
-
-echo "🚀 Complete AI Suite - Docker Container Starting..."
-echo "🐳 Container: $(hostname)"
-echo "👤 User: $(whoami)"
-echo "🎮 GPUs: $(nvidia-smi --list-gpus | wc -l || echo '0')"
-
-if command -v nvidia-smi >/dev/null 2>&1; then
-    echo "💾 CUDA Memory:"
-    nvidia-smi --query-gpu=memory.total,memory.used --format=csv,noheader,nounits | nl
-fi
-
-echo "🔧 Applying optimization patches..."
-python3 /app/tools/optimization_patch.py
-
-echo "📁 Setting up permissions..."
-chmod -R 755 /app/installer
-chmod -R 755 /app/monitoring
-chmod +x /app/start.sh
-
-mkdir -p /app/logs /app/outputs /app/tmp
-chmod 777 /app/logs /app/outputs /app/tmp
-
-echo "✅ Docker container initialization complete"
-echo "🚀 Starting Complete AI Video Suite..."
-
-exec /app/start.sh "$@"
-ENTRYPOINT_SCRIPT
-
-RUN chmod +x $APP_HOME/docker-entrypoint.sh
-
-ENTRYPOINT ["/app/docker-entrypoint.sh"]
-
-CMD ["--listen", "--multi-gpu", "--optimize"]
-
 # =============================================================================
-# FINAL METADATA
+# PONTO DE ENTRADA
 # =============================================================================
+RUN chmod +x start.sh
 
-RUN echo "Complete AI Video Suite v2.0.0" > /app/VERSION && \
-    echo "Build Date: 2025-09-18T$(date +%H:%M:%S)" >> /app/VERSION && \
-    echo "CUDA: 12.4.1" >> /app/VERSION && \
-    echo "PyTorch: $(python3 -c 'import torch; print(torch.__version__)')" >> /app/VERSION && \
-    echo "Optimized for: 8x NVIDIA L40S GPUs" >> /app/VERSION
-
-LABEL org.opencontainers.image.title="Complete AI Video Suite"
-LABEL org.opencontainers.image.description="Production-ready multi-GPU video generation with LTX FP8, Q8 Kernels, and more"
-LABEL org.opencontainers.image.version="2.0.0"
-LABEL org.opencontainers.image.created="2025-09-18T17:42:00Z"
-LABEL org.opencontainers.image.revision="main"
-LABEL org.opencontainers.image.licenses="MIT"
+ENTRYPOINT ["./start.sh"]
+CMD ["gradio"]

requirements.txt

@@ -1,14 +1,10 @@
-torch==2.6.0
-torchvision==0.21.0
-torchaudio==2.6.0
-opencv-python==4.9.0.80
+opencv-python>=4.9.0.80
 torchao
 transformers
 accelerate
 safetensors
 einops
 sentencepiece
-git+https://github.com/hkchengrex/MMAudio.git@main
 git+https://github.com/huggingface/diffusers.git@main
 gradio>=5.23.1
 gradio[oauth]
@@ -41,9 +37,7 @@ isort
 pre-commit               
 expecttest           
 hypothesis     
-numpy<2
+numpy
 ninja
 psutil
 packaging
-https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.6cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
-#https://huggingface.co/ByteDance-Seed/SeedVR2-3B/resolve/main/apex-0.1-cp310-cp310-linux_x86_64.whl