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#!/usr/bin/env bash
set -euo pipefail
cd tensorflow
export TF_NEED_CUDA=1
export TF_NEED_TENSORRT=1
export TF_TENSORRT_VERSION=8
export TF_CUDA_PATHS=/usr,/usr/local/cuda
export TF_CUDA_VERSION=12.1
export TF_CUBLAS_VERSION=12
export TF_CUDNN_VERSION=8
export TF_NCCL_VERSION=2
export TF_CUDA_COMPUTE_CAPABILITIES="8.0,9.0"
export TF_ENABLE_XLA=1
export TF_NEED_HDFS=0
export CC_OPT_FLAGS="-march=sandybridge -mtune=broadwell"
yes "" | ./configure
tree -L 4 /app
tree -L 4 /data
echo "🚀 Iniciando o script de setup e lançamento do LTX-Video..."
echo "Usuário atual: $(whoami)"
# Define as variáveis de ambiente que o LTXServer irá consumir
export HF_HOME="${HF_HOME:-/data/.cache/huggingface}"
export OUTPUT_ROOT="${OUTPUT_ROOT:-/app/outputs/ltx}"
export LTXV_FRAME_LOG_EVERY=8
export LTXV_DEBUG=1
nvcc -V
pip install --extra-index-url=https://pypi.ngc.nvidia.com --trusted-host pypi.ngc.nvidia.com nvidia-tensorflow
python -c "import torch; print('PyTorch CUDA disponível:', torch.cuda.is_available()); print('Dispositivos:', torch.cuda.device_count())"
# --- Garante que Diretórios Existam ---
mkdir -p "$OUTPUT_ROOT" "$HF_HOME"
# 1) Builder (garante Apex/Flash e deps CUDA)
#echo "🛠️ Iniciando o builder.sh para compilar/instalar dependências CUDA..."
#if [ -f "/app/builder.sh" ]; then
# /bin/bash /app/builder.sh
# echo "✅ Builder finalizado."
#else
# echo "⚠️ Aviso: builder.sh não encontrado. Pulando etapa de compilação de dependências."
#fi
#python3 - <<'PY'
#import os
#from services.ltx_server import ltx_server_singleton as server
#try:
# server.setup_dependencies()
#except Exception as e:
# print("Erro no setup")
#PY
#cp -r /data/LTX-Video/ltx_video /app/ltx_video
export OUTPUT_ROOT="${OUTPUT_ROOT:-/app/outputs}"
export INPUT_ROOT="${INPUT_ROOT:-/app/inputs}"
mkdir -p "$OUTPUT_ROOT" "$INPUT_ROOT"
echo "[aduc][start] Verificando ambiente como usuário: $(whoami)"
# Env da UI
export GRADIO_SERVER_NAME="0.0.0.0"
export GRADIO_SERVER_PORT="${PORT:-7860}"
export GRADIO_ENABLE_QUEUE="True"
echo "[ltx][start] Lançando app_ltx.py..."
# Executa diretamente o python.
exec python /app/app_seedvr.py |