Dockerfile

# =============================================================================
# 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

# =============================================================================
# METADADOS
# =============================================================================
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"
# 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"

# =============================================================================
# VARIÁVEIS DE AMBIENTE GLOBAIS
# =============================================================================
ENV DEBIAN_FRONTEND=noninteractive
ENV TZ=UTC
ENV LANG=C.UTF-8
ENV LC_ALL=C.UTF-8
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1
ENV PIP_NO_CACHE_DIR=1
ENV PIP_DISABLE_PIP_VERSION_CHECK=1

# Otimizações de CUDA e Build
ENV NVIDIA_VISIBLE_DEVICES=all
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV TORCH_CUDA_ARCH_LIST="8.9"
ENV MAX_JOBS=90

# Caminhos da Aplicação
ENV APP_HOME=/app
WORKDIR $APP_HOME

# =============================================================================
# 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

# =============================================================================
# INSTALAÇÃO DE BIBLIOTECAS DE ALTA PERFORMANCE
# =============================================================================

# 1. Instala PyTorch 2.8.0 e ferramentas de build
RUN pip install \
    torch==2.8.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 \
    packaging wheel ninja setuptools

# 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

# 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

# =============================================================================
# INSTALAÇÃO DO RESTANTE DAS DEPENDÊNCIAS
# =============================================================================
COPY requirements.txt .

# 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

# =============================================================================
# CLONAGEM E INSTALAÇÃO DOS REPOSITÓRIOS DA APLICAÇÃO
# =============================================================================
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 .

# =============================================================================
# COPIA O CÓDIGO DA APLICAÇÃO E CONFIGURA PERMISSÕES
# =============================================================================
COPY . .

RUN useradd -m -u 1000 -s /bash appuser && \
    chown -R appuser:appuser $APP_HOME && \
    mkdir -p /app/deformes_workspace && chown -R appuser:appuser /app/deformes_workspace

USER appuser

# =============================================================================
# PONTO DE ENTRADA
# =============================================================================
RUN chmod +x start.sh

ENTRYPOINT ["./start.sh"]
CMD ["gradio"]