Hornet

Give a local model a coding goal. Keep the work when the conversation ends.

Hornet turns a goal into small cells with explicit file scopes, typed results, acceptance checks and attempt budgets. Each model request gets bounded working context. Files, failed attempts and recovery evidence stay on disk.

It is a command-line tool for developers using local models, including an OpenAI-compatible LM Studio server. Python 3.9+; no runtime Python dependencies.

Try one completed goal

1. Open the v0.15.1 release.
2. Download the starter ZIP, SHA256SUMS, SHA256SUMS.asc, the public signing key and VERIFY-RELEASE.md.
3. Verify the download, extract it, and follow START-HERE.md inside.

The walkthrough installs Hornet, checks a local file contract, creates a new Ubuntu worker VM and asks your local model to fix a small Python function. The starter VM setup currently targets Windows + VirtualBox. The model runs on the host; agent code runs inside the dedicated VM.

Read the first-goal walkthrough and worker setup before running the demo. Use the downloadable starter for the ready-to-install wheel; GitHub's automatic source archive does not contain that wheel.

What Hornet keeps track of

Workers currently execute sequentially. Separate goal directories share the VM account; the dedicated VM supplies the execution boundary. Passing generated checks is evidence of the checked behavior, and exported code still needs review.

Questions wait for you

hornet questions coding/recipes/RUN_ID
hornet answer coding/recipes/RUN_ID q-EXACT_QUESTION_ID --text "Use the existing configuration."
hornet autoresume coding/recipes/RUN_ID

An answer is saved before execution resumes. waiting_for_user is a pause; completed is a separate result. There is no background model polling while a required question waits. Use resume for standalone work runs.

A measured first run

In the 0.15.0 first-user trial, Gemma 12B completed the small coding demo using 16 model requests and 5 tool calls, with a peak input of 3,084 tokens. Only calculator.py changed; independent checks returned [-6, 0, 14]. The original worker baseline was preserved.

That was one focused goal on a fresh Python environment and Ubuntu VM on an existing Windows host. It is not a general model-reliability benchmark. See the validation record.

Install from source

git clone https://github.com/matrixswarm/hornet.git
cd hornet
python -m venv .venv

On Windows:

.\.venv\Scripts\python.exe -m pip install .
.\.venv\Scripts\hornet.exe --version

On Linux/macOS:

.venv/bin/python -m pip install .
.venv/bin/hornet --version

PyPI publication is a later step. The signed GitHub release is the current download path. See the CLI reference for goals, revisions, contracts and recovery commands.

Project

Created and led by Daniel F. MacDonald, with AI engineering collaboration credited in AUTHORS.md. See CONTRIBUTING.md for development and SECURITY.md for the execution boundary and reporting.

License

Copyright (c) 2026 Daniel F. MacDonald. Licensed under AGPL-3.0-only; see LICENSE.

Victory Always.