whisper-server: move to port 8085 (8080 taken on the host)
Consistent across compose, entrypoint default, Dockerfile EXPOSE, healthcheck, and README examples.
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@@ -39,5 +39,5 @@ COPY --from=build /src/build/bin/whisper-server /usr/local/bin/whisper-server
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COPY entrypoint.sh /usr/local/bin/entrypoint.sh
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RUN chmod +x /usr/local/bin/entrypoint.sh
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EXPOSE 8080
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EXPOSE 8085
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ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
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@@ -3,7 +3,7 @@
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The transcription backend for meetrec clients: the same pinned whisper.cpp
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release (v1.9.3) as the Android app, exposed as an HTTP inference API with
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**Vulkan GPU support** (AMD Radeon AI PRO R9700) and reachable over
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Tailscale at `100.103.83.12:8080`.
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Tailscale at `100.103.83.12:8085`.
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The Fairphone 6 transcribes at roughly 0.6–0.8× realtime on-device; the
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R9700 (Strix Halo, RDNA 3.5, ~256 GB/s shared memory) is bandwidth-bound
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@@ -28,12 +28,12 @@ Configuration lives in `docker-compose.yml`:
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| ---------- | --------- | ------------------------------------------ |
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| `MODEL` | `large-v3`| `tiny`/`base`/`small`/`medium`/`large-v3` (downloaded to `./models` on first start) |
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| `THREADS` | `8` | CPU threads per inference |
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| `PORT` | `8080` | Port inside the container |
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| `PORT` | `8085` | Port inside the container |
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## Try it
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```sh
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curl http://100.103.83.12:8080/inference \
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curl http://100.103.83.12:8085/inference \
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-F file=@meeting.wav \
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-F response_format=verbose_json \
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-F language=auto
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@@ -51,7 +51,7 @@ Notes:
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override), so the live/final beam split of the clients doesn't apply
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here — one beam for all requests.
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- The server also has a `/load` endpoint to swap models at runtime.
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- **No authentication**: the compose file binds `100.103.83.12:8080`
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- **No authentication**: the compose file binds `100.103.83.12:8085`
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(Tailscale interface only) for that reason. Do not switch this to
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`0.0.0.0` unless the host is otherwise firewalled.
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- The image builds with CPU feature auto-detection (`-march=native`):
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@@ -66,6 +66,6 @@ Notes:
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## Client status
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- Desktop `meetrec`: a `whisper-server` engine is planned
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(`--engine whisper-server --server-url http://100.103.83.12:8080`).
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(`--engine whisper-server --server-url http://100.103.83.12:8085`).
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- Android app: a remote engine option is planned (phone records, server
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transcribes; local JNI stays as the offline fallback).
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@@ -8,7 +8,7 @@
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# never exposed to the LAN or the internet. Tailscale must own that IP
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# before the container starts, otherwise the bind fails — start order:
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# tailscale first, then `docker compose up -d`. If you would rather
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# tolerate LAN exposure, use "8080:8080" instead.
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# tolerate LAN exposure, use "8085:8085" instead.
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services:
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whisper-server:
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@@ -22,14 +22,14 @@ services:
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MODEL: large-v3
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THREADS: 8
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HOST: 0.0.0.0 # inside the container; the host bind is below
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PORT: 8080
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PORT: 8085
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# NO_GPU: 1 # force CPU if the GPU ever misbehaves
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volumes:
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- ./models:/models # keep downloads across container rebuilds
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ports:
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- "100.103.83.12:8080:8080" # tailscale-only; see note above
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- "100.103.83.12:8085:8085" # tailscale-only; see note above
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# GPU passthrough: the render group must match the host's GID, hence
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# the RENDER_GID env var in the comment at the top of this file.
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@@ -41,7 +41,7 @@ services:
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healthcheck:
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# any HTTP response counts as healthy (the server has no /health)
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test: ["CMD-SHELL", "curl -s -o /dev/null http://localhost:8080/ || exit 1"]
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test: ["CMD-SHELL", "curl -s -o /dev/null http://localhost:8085/ || exit 1"]
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interval: 30s
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timeout: 5s
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retries: 3
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@@ -7,7 +7,7 @@ set -eu
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MODEL="${MODEL:-small}"
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THREADS="${THREADS:-4}"
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HOST="${HOST:-0.0.0.0}"
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PORT="${PORT:-8080}"
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PORT="${PORT:-8085}"
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MODEL_DIR="${MODEL_DIR:-/models}"
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FILE="$MODEL_DIR/ggml-$MODEL.bin"
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