Spaces:
Running on Zero
Running on Zero
| # 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"] | |