feat(docker): glibc base with nvenc ffmpeg + par2/7z extractors
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Alpine/musl can't run NVIDIA's glibc userspace (nvidia-smi, libnvidia-encode, the static nvenc ffmpeg), so HW transcode was impossible — every 4K/anamorphic HLS encode fell back to software or failed. Switch the runtime stage to debian:bookworm-slim + a static BtbN ffmpeg built with nvenc, add par2 (Usenet segment repair) + 7z (RAR/7z extraction), and set NVIDIA_DRIVER_CAPABILITIES=video,compute,utility so a plain --gpus all (or the compose device reservation) lights up nvenc with no extra flags. Falls back to libx264 automatically when no GPU is attached. Build stage cross-compiles (--platform=BUILDPLATFORM) so multi-arch stays fast; downloads forced over IPv4.
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2 changed files with 66 additions and 15 deletions
67
Dockerfile
67
Dockerfile
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@ -1,5 +1,8 @@
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# ---- Build stage ----
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FROM golang:1.25-alpine AS builder
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# Pin the builder to the host's native arch and cross-compile (CGO is off, so
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# Go cross-compiles trivially). During multi-arch buildx this keeps `go build`
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# at native speed instead of compiling under QEMU emulation for the foreign arch.
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FROM --platform=$BUILDPLATFORM golang:1.25-alpine AS builder
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RUN apk add --no-cache git ca-certificates
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@ -13,34 +16,63 @@ RUN go mod download
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COPY . .
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ARG VERSION=dev
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RUN CGO_ENABLED=0 go build -ldflags="-s -w -X github.com/torrentclaw/unarr/internal/cmd.Version=${VERSION}" -trimpath -o /unarr ./cmd/unarr/
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ARG TARGETOS
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ARG TARGETARCH
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RUN CGO_ENABLED=0 GOOS=${TARGETOS} GOARCH=${TARGETARCH} go build -ldflags="-s -w -X github.com/torrentclaw/unarr/internal/cmd.Version=${VERSION}" -trimpath -o /unarr ./cmd/unarr/
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# ---- Runtime stage ----
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FROM alpine:3.22
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# glibc base (not Alpine/musl). NVIDIA's userspace — nvidia-smi and the
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# libnvidia-encode / libcuda libs that `--gpus all` injects, plus the static
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# BtbN ffmpeg that links nvenc — are all glibc ELF. On musl they fail with
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# "no such file or directory" (missing glibc loader), so HW transcode is
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# impossible on Alpine. bookworm-slim is the smallest base that runs the full
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# NVIDIA stack while still falling back to software libx264 when no GPU is
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# passed in.
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FROM debian:bookworm-slim
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# Use Alpine's native musl ffmpeg + ffprobe instead of the johnvansickle /
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# BtbN static glibc builds — those need a glibc shim on Alpine and the
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# vector-math symbols the GPL builds reference are not satisfiable by
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# gcompat. Alpine ships ffmpeg ~7.x which is fine for the HLS transcoding
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# pipeline (libx264 + libfdk-aac alternatives included).
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RUN apk upgrade --no-cache && \
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apk add --no-cache ca-certificates tzdata ffmpeg wget
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# par2 → repair corrupted Usenet segments (without it a single bad segment
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# silently corrupts the output).
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# 7z → archive extractor for RAR/7z-packed downloads (p7zip-full also reads
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# RAR5, so unrar — unavailable as a free Debian package — isn't needed).
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# tzdata/ca-certificates → TLS + correct local time for schedules/logs.
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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ca-certificates tzdata wget xz-utils par2 p7zip-full && \
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rm -rf /var/lib/apt/lists/*
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# TARGETARCH is set automatically by Docker buildx during cross-builds.
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ARG TARGETARCH=amd64
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# Static GPL ffmpeg + ffprobe with nvenc compiled in (BtbN builds). nvenc is
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# linked but the actual libnvidia-encode.so is dlopen'd at runtime from the
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# host driver that `--gpus all` exposes — so the same binary does HW transcode
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# when a GPU is present and falls back to libx264 when it isn't. Placed in
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# /usr/local/bin so ResolveFFmpeg picks them up off PATH ahead of any distro
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# ffmpeg. arm64 has no nvenc but the build still serves software transcode.
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RUN case "$TARGETARCH" in \
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amd64) FF_ARCH=linux64 ;; \
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arm64) FF_ARCH=linuxarm64 ;; \
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*) echo "unsupported TARGETARCH=$TARGETARCH" >&2; exit 1 ;; \
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esac && \
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wget -4 --tries=3 --timeout=30 -qO /tmp/ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/latest/ffmpeg-master-latest-${FF_ARCH}-gpl.tar.xz" && \
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mkdir -p /tmp/ff && tar -xJf /tmp/ffmpeg.tar.xz -C /tmp/ff --strip-components=1 && \
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cp /tmp/ff/bin/ffmpeg /tmp/ff/bin/ffprobe /usr/local/bin/ && \
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chmod +x /usr/local/bin/ffmpeg /usr/local/bin/ffprobe && \
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rm -rf /tmp/ffmpeg.tar.xz /tmp/ff
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# Bundle cloudflared so `unarr funnel on` (default: on, see config defaults)
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# Just Works on a headless container with no first-run network round-trip.
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# TARGETARCH is set automatically by Docker buildx during cross-builds.
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ARG TARGETARCH=amd64
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RUN case "$TARGETARCH" in \
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amd64) CF_ARCH=amd64 ;; \
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arm64) CF_ARCH=arm64 ;; \
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arm) CF_ARCH=armhf ;; \
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*) echo "unsupported TARGETARCH=$TARGETARCH" >&2; exit 1 ;; \
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esac && \
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wget -qO /usr/local/bin/cloudflared "https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-$CF_ARCH" && \
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wget -4 --tries=3 --timeout=30 -qO /usr/local/bin/cloudflared "https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-$CF_ARCH" && \
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chmod +x /usr/local/bin/cloudflared
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# Non-root user (UID 1000 matches typical host user for volume permissions)
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RUN addgroup -g 1000 unarr && adduser -u 1000 -G unarr -D -h /home/unarr unarr
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RUN groupadd -g 1000 unarr && useradd -u 1000 -g 1000 -m -d /home/unarr unarr
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# Default directories
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RUN mkdir -p /config /downloads /data && \
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@ -55,6 +87,13 @@ ENV UNARR_CONFIG_DIR=/config
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ENV UNARR_DOWNLOAD_DIR=/downloads
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ENV XDG_DATA_HOME=/data
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# NVIDIA passthrough defaults. `--gpus all` alone only grants the "utility" +
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# "compute" capabilities; nvenc needs "video". Baking these here means a plain
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# `docker run --gpus all` (or the compose device reservation) lights up HW
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# transcode with zero extra flags. Harmless when no GPU is attached.
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ENV NVIDIA_VISIBLE_DEVICES=all
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ENV NVIDIA_DRIVER_CAPABILITIES=video,compute,utility
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VOLUME ["/config", "/downloads", "/data"]
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ENTRYPOINT ["unarr"]
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@ -45,9 +45,21 @@ services:
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# Named volume keeps this off your media drive (avoids NFS locking issues).
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- unarr-data:/data
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# Optional: limit CPU/RAM for transcoding on shared hosts
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# --- NVIDIA GPU: hardware transcode (nvenc) ---
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# Uncomment on a host with an NVIDIA GPU + nvidia-container-toolkit. The
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# image already bundles an nvenc-enabled ffmpeg and sets
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# NVIDIA_DRIVER_CAPABILITIES=video,compute,utility, so this device
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# reservation is the only thing needed to enable HW transcode. Without a GPU
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# the same image falls back to software (libx264) automatically — leave it
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# commented. (docker run equivalent: add --gpus all)
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# deploy:
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# resources:
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# reservations:
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# devices:
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# - driver: nvidia
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# count: all
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# capabilities: [gpu]
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# # Optional: cap CPU/RAM for transcoding on shared hosts
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# limits:
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# memory: 2G
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# cpus: "4.0"
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