avrik

Run Avrik decision models on your own machine: avrik pull, avrik ask, avrik serve, avrik info.

An Avrik model reads a state and typed questions (yes/no, choice, score, multi-label) and returns a calibrated probability distribution over each question's options, in one forward pass with no generated text. Every answer carries the hashes that identify the exact model, calibration and prompt behind it.

Install

On a CPU:

pip install llama-cpp-python==0.3.35 --no-deps --only-binary=:all: \
  --index-url https://abetlen.github.io/llama-cpp-python/whl/cpu
pip install "avrik[cpu]"

The first line installs llama.cpp's prebuilt CPU wheel from its own index; without it, pip compiles llama.cpp, which needs a C++ compiler. On a GPU, pip install avrik and run vLLM on loopback (each model card gives the command), then pass --vllm-url.

Use

avrik pull Avrik-Lite-4B             # downloads avrik-ai/Avrik-Lite-4B-GGUF and verifies it
avrik ask Avrik-Lite-4B --state "Customer bought headphones 12 days ago, unopened, \
receipt attached. Policy: unopened items within 30 days get a full refund." \
  --noul "Should the refund be approved?" \
  --choice "Which action?=approve,deny,escalate" [--json]
avrik serve Avrik-Lite-4B --port 8080   # /v1/systemone on 127.0.0.1 only
avrik info Avrik-Lite-4B                # provenance: hashes, recipe, calibration

Names match in any case. --dir uses a local release directory instead of the cache ($AVRIK_HOME, default ~/.cache/avrik).

Integrity and privacy

• pull downloads a release at a commit pinned inside this package and refuses it unless its MANIFEST.sha256 has the pinned digest; then every file is checked.
• ask, serve and info re-check every file before anything loads. Code files, auto_map, symlinks and unlisted files are refused (exit 3).
• Only pull uses the network. Inference sends no telemetry and stores nothing.

Call the API from Python with avrik-sdk.

Built on Gemma 4 by Google (Apache-2.0). Licence: Apache-2.0. Security reports: avriktech.ai@gmail.com.

Website: www.avrik.ai · Models: huggingface.co/avrik-ai · Acceptable use policy