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128 lines
7.0 KiB
Markdown
128 lines
7.0 KiB
Markdown
# Build and release targets
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Use stable Rust, Node 24 LTS, Python 3.11+, Git, CMake, and a native C/C++
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toolchain. Python provisions the pinned Google runtime and model; inference
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runs in a native process. Default Rust tests do not download model assets.
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Windows needs Visual Studio C++ build tools, a Windows SDK, and WebView2.
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Linux desktop builds need WebKitGTK 4.1 development libraries; macOS needs
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Xcode command-line tools. Follow the [Tauri prerequisites](https://v2.tauri.app/start/prerequisites/).
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Headless Linux CLI/worker builds do not need WebKitGTK or a display server.
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They still need a C/C++ compiler, linker, CMake, and Rust: SQLite, USearch,
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NumKong, and the Google worker contain native code.
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## Windows CPU development
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Run from the repository root. Building the worker clones a pinned llama.cpp
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revision and verifies/applies its memory patch. Model provisioning explicitly
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uses the network and verifies both Google assets, approximately 865 MB total.
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The Python CMake package is needed only when CMake is absent from PATH.
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```powershell
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python -m pip install cmake
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python tools/embeddinggemma2/build_runtime.py --backend cpu --jobs 2
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python tools/embeddinggemma2/stage_runtime.py --backend cpu
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python tools/media-runtime/provision.py --stage
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python tools/embeddinggemma2/download.py
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$env:SEARCHI_FORCE_CPU = '1'
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$env:SEARCHI_GEMMA_MODEL_DIR = (Resolve-Path .searchi/models/embeddinggemma2).Path
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$env:SEARCHI_GEMMA_WORKER = (Resolve-Path .searchi/runtime/cpu/Release/searchi-gemma-worker.exe).Path
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cargo fmt --all --check
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cargo clippy --workspace --all-targets --locked -- -D warnings
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cargo test --workspace --locked
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cargo test -p searchi-semantic --test gemma_cpu -- --ignored --nocapture
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cargo test -p searchi-service --test google_cpu -- --ignored --nocapture
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cargo test -p searchi-service --lib google_cpu_preserves -- --ignored --nocapture
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```
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The worker is statically linked with the MSVC CRT on Windows. Staging copies
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it and the llama.cpp license into the desktop resources directory. Add
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`--bundle-model` to staging for an offline model bundle after downloading;
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otherwise desktop setup provisions verified models on first launch. Search
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itself performs no network inference or downloads. The worker now uses the verified media projector for genuine image/audio embeddings. The FFmpeg script stages verified standalone decoders and their notices.
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The desktop is a standalone Cargo workspace and needs separate validation:
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```powershell
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cargo test --manifest-path apps/desktop/src-tauri/Cargo.toml --locked
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Set-Location apps/desktop
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npm ci
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npm run format:check
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npm test
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npm run build
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$env:WEBVIEW2_ADDITIONAL_BROWSER_ARGUMENTS = '--disable-gpu --disable-accelerated-video-decode'
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npm run tauri -- dev
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```
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Every Windows VM inference/rendering test must stay CPU only. Production
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supports `--backend auto|metal|vulkan|cuda` builds with CPU fallback; do not
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exercise those acceleration backends in this VM. Their execution and failure
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recovery require validation on the corresponding release hardware.
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## Headless Linux Google search
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These are the current script and CLI interfaces, not evidence of an executed
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Linux release. On a native Linux build host, run from the repository root:
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```sh
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python3 tools/embeddinggemma2/build_runtime.py --backend cpu --jobs 2
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python3 tools/embeddinggemma2/download.py
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python3 tools/media-runtime/provision.py
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export SEARCHI_FORCE_CPU=1
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cargo build --release -p searchi-cli --locked
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./target/release/searchi index --db searchi.sqlite --root /path/to/documents
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./target/release/searchi embed --db searchi.sqlite --model-dir .searchi/models/embeddinggemma2 --embedding-worker .searchi/runtime/cpu/searchi-gemma-worker --ffmpeg .searchi/media-runtime/bin/ffmpeg --ffprobe .searchi/media-runtime/bin/ffprobe --cpu-threads 1
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./target/release/searchi search --db searchi.sqlite 'supplier cancellation terms' --model-dir .searchi/models/embeddinggemma2 --embedding-worker .searchi/runtime/cpu/searchi-gemma-worker --cpu-threads 1
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```
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`embed` builds document, image, video and audio/music vectors by default. Use
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`--text-only` explicitly to omit media. Default media indexing needs paired
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FFmpeg/FFprobe paths or packaged helpers beside the installed CLI.
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`searchi setup --model-dir PATH` is an alternative verified model-provisioning
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command. It provisions model assets, not the native worker. Package the worker
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separately and pass its path to headless embedding/search. Each short-lived CLI
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search starts a model process; the desktop retains a prewarmed query worker.
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## Cross-compilation and native release matrix
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The shared Rust engine/service has no GUI dependency. Install a destination
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Rust target with `rustup target add TARGET`, then build using
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`cargo build -p searchi-cli --target TARGET --locked`. This also requires the
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target C/C++ toolchain, linker, and SDK for bundled SQLite and the vector index.
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The separate native Google worker must be compiled for the same destination;
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installing a Rust target does not cross-compile it. The current Python runtime
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script configures the host toolchain; it does not expose a CMake cross-toolchain
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file interface. Record each verified host/target pair before claiming support.
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| Release host | Intended artifacts | Remaining validation |
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| --- | --- | --- |
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| Windows | Windows CLI, worker, desktop installer | Installer, upgrade, signing, GPU hardware |
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| macOS | Apple Silicon/Intel CLI, worker, desktop bundle | Native builds, architecture parity, Metal, notarization |
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| Linux | CLI, worker, desktop packages | Native builds, distribution ABI, webview, acceleration |
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Use native runners for dependable desktop releases. Platform webviews,
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packaging tools, SDKs, and signing impose additional constraints. macOS
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signing/notarization requires Apple tooling and credentials. See the
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[Tauri Windows installer cross-build caveats](https://v2.tauri.app/distribute/windows-installer/).
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## CI and packaging gates
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GitHub and Gitea workflows define native OS matrices. Gitea requires registered
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runners matching its configured labels. A workflow declaration does not prove
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a platform was tested; Linux/macOS gates remain open until actual job evidence
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exists. Current workflow checks do not certify the separately built Google
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worker or execute downloaded-model tests automatically.
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Desktop bundles remain disabled during development. Before enabling release
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installers, stage the target worker, retain dependency/model notices, verify
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clean-machine launch and setup, run native Google smoke tests, and complete
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upgrade/migration, signatures, and rollback checks. Optional offline bundles
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need both verified model files. See [semantic bounds and evidence](SEMANTIC.md)
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for current corpus, localization, and performance limitations. Keep signing keys,
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repository tokens, and model credentials outside source control.
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FFmpeg provisioning supports manifest-pinned Windows/Linux x86-64 and ARM64 artifacts;
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only Windows x86-64 has executed here. macOS decoder packaging remains a gate.
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See [media runtime provenance](../tools/media-runtime/README.md) and
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[measured media limitations](MEDIA-QUALITY.md).
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