61 lines
1.9 KiB
Docker
61 lines
1.9 KiB
Docker
# ==========================================
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# Builder Stage: Compile React Frontend
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# ==========================================
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FROM oven/bun:1-alpine AS frontend-builder
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WORKDIR /app
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# Monorepo — bun workspace with lockfile at repo root. Copy manifests first
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# so `bun install` caches independently of source edits.
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COPY package.json bun.lock ./
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COPY frontend/package.json ./frontend/
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RUN bun install --frozen-lockfile
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# Build static files (output lands in /app/frontend/dist)
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COPY frontend/ ./frontend/
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RUN bun run --cwd frontend build
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# ==========================================
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# Runtime Stage: Python & PyTorch Backend
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# ==========================================
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FROM pytorch/pytorch:2.4.0-cuda12.1-cudnn9-runtime AS runtime
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WORKDIR /app
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# Enable unbuffered logs and optimizations
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV PYTHONUNBUFFERED=1
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ENV HF_HOME=/app/omnivoice_data/huggingface
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# Install system dependencies (FFmpeg is critical for torchaudio/scene splitting)
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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libsndfile1 \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# Install `uv` for blazing-fast reliable pip resolution
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RUN pip install --no-cache-dir uv
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# Copy python packaging specs
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COPY pyproject.toml uv.lock ./
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# Native wheels from PyPI embed CUDA matching `torch >= 2.4` standard index
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# By installing via `uv`, the process completes exponentially faster
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RUN uv pip install --system --no-cache -e .
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# Copy application source
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COPY backend/ ./backend/
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COPY omnivoice/ ./omnivoice/
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# Copy the pre-built React frontend from the builder stage
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COPY --from=frontend-builder /app/frontend/dist ./frontend/dist
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# Expose the single unified API and UI port
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EXPOSE 3900
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# Mount points for persistent data (sqlite db, user voices, huggingface cache)
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VOLUME ["/app/omnivoice_data"]
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# Bind to 0.0.0.0 for external access
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ENTRYPOINT ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "3900"]
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