Installation
Rust
Add Jammi to your Cargo.toml:
[dependencies]
jammi-db = "0.25"
jammi-ai = "0.25"
tokio = { version = "1", features = ["full"] }
CLI
The jammi CLI registers sources, runs SQL, and starts the server. There are
three ways to get it.
cargo install (CPU)
Builds from source on your machine. Needs the build dependencies below.
cargo install jammi-cli
The installed binary is jammi.
Prebuilt binary (CPU)
Download a stripped, ready-to-run binary from the GitHub releases. No build toolchain required. Assets are published per release:
jammi-<version>-x86_64-unknown-linux-gnu.tar.gz— Linux x86-64 (built on a glibc 2.28 floor, so it runs on any newer Linux)jammi-<version>-aarch64-apple-darwin.tar.gz— macOS on Apple silicon
tar -xzf jammi-0.25.0-x86_64-unknown-linux-gnu.tar.gz
./jammi --help
GPU (CUDA 12)
GPU inference ships as a container image, not a bare binary. The
jammi-ai-server-cu12 image runs jammi-server as its entrypoint and also
carries the jammi admin CLI; it is turnkey:
docker run --gpus all \
-p 8080:8080 -p 8081:8081 \
ghcr.io/f-inverse/jammi-ai-server-cu12:latest
That runs jammi-server with zero config. See
Deploy as a Server for GPU configuration and
persistence.
Alternatively, install the CUDA server as a pip wheel — it ships the same
jammi-server binary and pulls the CUDA runtime from nvidia-*-cu12 wheels, so
no system CUDA install is required (only an NVIDIA driver on the host):
pip install jammi-server-cu12
jammi-server
The jammi-ai embed wheel is CPU-only; GPU inference runs in the server, reached
from Python via jammi.connect("grpc://…").
Build dependencies (Linux)
If building from source, you need a C compiler and protoc:
# Debian/Ubuntu
apt-get install protobuf-compiler gcc g++ pkg-config
# RHEL/AlmaLinux
yum install protobuf-compiler gcc gcc-c++ pkg-config
All other native libraries (lzma, zstd, zlib, sqlite) are vendored and compiled from source automatically. These tools are pre-installed in the devcontainer and CI images.
Python
pip install jammi-ai
Requires Python 3.8+. Pre-built wheels are available for Linux, macOS, and Windows.
From source
git clone https://github.com/f-inverse/jammi-ai.git
cd jammi-ai
cargo build --release
The CLI binary is at target/release/jammi (a strict gRPC client) and the
server binary at target/release/jammi-server.
For the Python package from source:
pip install maturin
maturin develop --release
Runtime requirements
Jammi has no mandatory runtime dependencies beyond the binary itself.
Optional:
- CUDA toolkit + cuDNN for GPU inference (CPU works out of the box)
- HuggingFace Hub access for downloading models (first run downloads ~90MB for MiniLM, cached thereafter)
- PostgreSQL / MySQL client libraries if using federated database sources
Set HF_TOKEN for gated models, or HF_HOME to control the cache location.