# Wan 2.2 Text-to-Video Backend — Dockerfile (custom GPU server)
#
# For Hugging Face Spaces you do NOT need this Dockerfile — just upload
# `app.py`, `requirements.txt`, and `README.md` (with `sdk: gradio` in the
# front matter). HF Spaces pre-installs torch 2.8.0 + gradio + spaces.
#
# Use this Dockerfile when you want to deploy to a custom GPU server:
#   - RunPod / Lambda Labs / Vast.ai / AWS EC2 with GPU
#   - Any container orchestrator that can attach a CUDA-capable GPU
#
# Build & run:
#   docker build -t wan22-backend .
#   docker run --gpus all -p 7860:7860 \
#       -e HF_TOKEN=hf_xxx \
#       -e WAN_MODEL_ID=Wan-AI/Wan2.1-T2V-1.3B-Diffusers \
#       wan22-backend

FROM nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04

# Prevent Python from buffering stdout (so logs appear immediately)
ENV PYTHONUNBUFFERED=1 \
    PIP_NO_CACHE_DIR=1 \
    PIP_DISABLE_PIP_VERSION_CHECK=1

RUN apt-get update && apt-get install -y --no-install-recommends \
        python3.10 python3-pip python3.10-venv \
        ffmpeg \
    && rm -rf /var/lib/apt/lists/*

RUN ln -sf /usr/bin/python3.10 /usr/bin/python && \
    ln -sf /usr/bin/python3.10 /usr/bin/python3

WORKDIR /app

# ─── Step 1: install torch + torchvision separately ────────────────────────
# Use the official PyTorch CUDA 12.1 wheel index. These versions are paired:
#   torch 2.4.0  ↔  torchvision 0.19.0
# (For Hugging Face Spaces, torch is pre-installed and you do NOT need this
#  step — the HF template handles it.)
RUN pip install --upgrade pip && \
    pip install --no-cache-dir \
        torch==2.4.0 \
        torchvision==0.19.0 \
        --index-url https://download.pytorch.org/whl/cu121

# ─── Step 2: install the rest of the deps ─────────────────────────────────
# requirements.txt does NOT pin torch / torchvision (so it can also be used
# by HF Spaces where torch is pre-installed). For this Dockerfile path, torch
# was already installed in Step 1 above.
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# ─── Step 3: copy the app ─────────────────────────────────────────────────
COPY app.py .

EXPOSE 7860
ENV PORT=7860

CMD ["python", "app.py"]