Install

You need Rust 1.91+ and a C++ toolchain. Two dependencies compile llama.cpp and whisper.cpp from source, so expect a long first build.

git clone https://github.com/bennyhodl/centinel
cd centinel
./install.sh

The script checks the host before it builds anything, and names the command for whatever is missing rather than installing a toolchain behind your back.

What the script does that cargo install cannot

It selects the GPU backend. Metal on macOS, CUDA or ROCm on Linux when their toolchains are present.

It tunes for the CPU it is building on. This matters more than it sounds like. llama-cpp-sys-2 reads target-cpu back out of the Rust flags, and when it is not native it sets GGML_NATIVE=OFF and derives ggml’s instruction-set flags from the baseline target features instead. On x86_64-unknown-linux-gnu those are fxsr,sse,sse2,x87 — so a plain cargo install compiles llama.cpp’s CPU kernels with no AVX, no AVX2 and no FMA, and nothing recovers it at runtime. whisper.cpp has no such handling and builds native already. So the untuned case is not “both a little slow”. It is the transcriber tuned and the embedder not, and embedding is the stage measured in days.

The cost is that the binary is then built for the CPU that built it. --portable is the way out, and it leaves RUSTFLAGS alone, so a middle tier that still carries AVX2 and FMA is:

RUSTFLAGS="-C target-cpu=x86-64-v3" ./install.sh --portable

It installs both binaries into one directory. Which is the thing transcription does not work without.

Why two binaries

whisper.cpp and llama.cpp each vendor their own copy of ggml, and both export the same ~534 ggml_* symbols. Linked into one binary, the linker keeps one copy and silently resolves the other library’s calls to it. The two versions are not the same.

Measured on identical audio and model, the linked crates the only variable:

It links without a warning, runs without a crash, and transcribes nothing. There is no error to catch. So centinel links llama.cpp, centinel-whisper links whisper.cpp, and the two meet over a pipe.

centinel finds the worker beside itself first, then $CENTINEL_WHISPER_BIN, then PATH. Installing both with the same command puts them in the same directory, which is all it needs.

By hand

cargo cannot take two --path arguments, and the workspace root is a virtual manifest, so from a clone it is two commands:

cargo install --path crates/centinel
cargo install --path crates/centinel-whisper

Without a clone, one command does both:

cargo install --git https://github.com/bennyhodl/centinel centinel centinel-whisper

Any GPU backend other than Metal is a --features flag on each of the two commands. Passing --features cuda to one and not the other leaves half the pipeline on the CPU.

External tools

Centinel shells out rather than running a second language runtime.

brew install yt-dlp ffmpeg          # macOS
sudo apt install yt-dlp ffmpeg      # Debian/Ubuntu

Keep yt-dlp current. It ships releases in emergency clusters when YouTube changes, and centinel doctor warns once yours is past ninety days.

Then

centinel doctor         # what this machine is missing, and the command for each gap
centinel models pull    # weights for search and transcription

Run doctor first and after every step. It names the fix beside each gap it finds. See Models for what models pull fetches and how much disk it wants.

Next: Your first corpus.