mirror of
https://github.com/rishikanthc/Scriberr.git
synced 2026-03-03 03:47:02 +00:00
8f537548d4
Add support for NVIDIA RTX 50-series GPUs (Blackwell architecture) which require CUDA 12.8+ and PyTorch cu128 wheels due to the new sm_120 compute capability. Changes: - Add configurable PYTORCH_CUDA_VERSION environment variable to control PyTorch wheel version at runtime (cu126 for legacy, cu128 for Blackwell) - Update all model adapters to use dynamic CUDA version instead of hardcoded cu126 URLs - Update Dockerfile.cuda.12.9 for Blackwell with CUDA 12.9.1 base image, PYTORCH_CUDA_VERSION=cu128, and missing WHISPERX_ENV/yt-dlp - Update Dockerfile.cuda with explicit PYTORCH_CUDA_VERSION=cu126 - Add docker-compose.blackwell.yml for pre-built Blackwell image - Add docker-compose.build.blackwell.yml for local Blackwell builds - Add GPU compatibility documentation to README Fixes: rishikanthc/Scriberr#104
123 lines
4.0 KiB
Docker
123 lines
4.0 KiB
Docker
# Multi-stage build for Scriberr with CUDA support
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# Builds React UI and Go server, then ships with NVIDIA CUDA runtime
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########################
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# UI build stage
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########################
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FROM node:20-alpine AS ui-builder
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WORKDIR /web
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# Install deps and build web/frontend
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COPY web/frontend/package*.json ./frontend/
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RUN cd frontend \
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&& npm ci
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COPY web/frontend ./frontend
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RUN cd frontend \
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&& npm run build
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########################
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# Go build stage
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########################
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FROM golang:1.24-bookworm AS go-builder
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WORKDIR /src
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# Pre-cache modules
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COPY go.mod go.sum ./
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RUN go mod download
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# Copy source
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COPY . .
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# Copy built UI into embed path
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RUN rm -rf internal/web/dist && mkdir -p internal/web
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COPY --from=ui-builder /web/frontend/dist internal/web/dist
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# Build binary (arch matches builder platform)
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RUN CGO_ENABLED=0 \
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go build -o /out/scriberr cmd/server/main.go
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# Build CLI binaries (cross-platform)
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RUN mkdir -p /out/bin/cli \
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&& GOOS=linux GOARCH=amd64 go build -o /out/bin/cli/scriberr-linux-amd64 ./cmd/scriberr-cli \
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&& GOOS=darwin GOARCH=amd64 go build -o /out/bin/cli/scriberr-darwin-amd64 ./cmd/scriberr-cli \
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&& GOOS=darwin GOARCH=arm64 go build -o /out/bin/cli/scriberr-darwin-arm64 ./cmd/scriberr-cli \
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&& GOOS=windows GOARCH=amd64 go build -o /out/bin/cli/scriberr-windows-amd64.exe ./cmd/scriberr-cli
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########################
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# CUDA Runtime stage
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########################
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FROM nvidia/cuda:12.6.3-cudnn-runtime-ubuntu24.04 AS runtime
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ENV PYTHONUNBUFFERED=1 \
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HOST=0.0.0.0 \
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PORT=8080 \
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DATABASE_PATH=/app/data/scriberr.db \
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UPLOAD_DIR=/app/data/uploads \
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WHISPERX_ENV=/app/whisperx-env \
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APP_ENV=production \
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PUID=1000 \
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PGID=1000 \
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NVIDIA_VISIBLE_DEVICES=all \
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NVIDIA_DRIVER_CAPABILITIES=compute,utility \
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# PyTorch CUDA wheel version: cu126 for legacy GPUs (GTX 10-series through RTX 40-series)
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PYTORCH_CUDA_VERSION=cu126
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WORKDIR /app
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# System deps: curl for uv install, ca-certs, ffmpeg for yt-dlp, git for git+ installs, gosu for user switching
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# Ubuntu 24.04 comes with Python 3.12 which works fine with WhisperX
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RUN apt-get update \
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&& DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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curl ca-certificates ffmpeg git gosu unzip \
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build-essential gcc g++ make python3-dev \
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python3 python3-venv python3-pip \
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&& rm -rf /var/lib/apt/lists/*
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# Install uv (fast Python package manager) directly to system PATH
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RUN curl -LsSf https://astral.sh/uv/install.sh | sh \
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&& cp /root/.local/bin/uv /usr/local/bin/uv \
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&& chmod 755 /usr/local/bin/uv \
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&& uv --version
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# Install yt-dlp standalone binary
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RUN curl -L https://github.com/yt-dlp/yt-dlp/releases/latest/download/yt-dlp -o /usr/local/bin/yt-dlp \
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&& chmod a+rx /usr/local/bin/yt-dlp \
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&& yt-dlp --version
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# Install Deno (JavaScript runtime required for yt-dlp YouTube downloads)
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# YouTube now requires JS execution for video cipher decryption
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# See: https://github.com/yt-dlp/yt-dlp/issues/14404
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RUN curl -fsSL https://deno.land/install.sh | sh \
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&& cp /root/.deno/bin/deno /usr/local/bin/deno \
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&& chmod 755 /usr/local/bin/deno \
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&& deno --version
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# Create default user (will be modified at runtime if needed)
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# Use 10001 to avoid conflicts with existing users in CUDA base image
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RUN groupadd -g 10001 appuser \
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&& useradd -m -u 10001 -g 10001 appuser \
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&& mkdir -p /app/data/uploads /app/data/transcripts \
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&& chown -R appuser:appuser /app
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# Copy binary and entrypoint script
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COPY --from=go-builder /out/scriberr /app/scriberr
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COPY --from=go-builder /out/bin/cli /app/bin/cli
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COPY docker-entrypoint.sh /usr/local/bin/docker-entrypoint.sh
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# Make entrypoint script executable and set up basic permissions
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RUN chmod +x /usr/local/bin/docker-entrypoint.sh \
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&& chown appuser:appuser /app/scriberr
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# Expose port and declare volume for persistence
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EXPOSE 8080
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VOLUME ["/app/data"]
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# Start as root to allow user ID changes, entrypoint script will switch users
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# Verify uv is available
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RUN uv --version
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# Use entrypoint script that handles user switching and permissions
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ENTRYPOINT ["docker-entrypoint.sh"]
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CMD ["/app/scriberr"]
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