GenieHive

GenieHive is a local-first control plane for heterogeneous generative AI services running across one or more hosts.

V1 scope:

• chat completions
• embeddings
• transcription

Core goals:

• register hosts and services
• track health, inventory, and observed performance
• expose a stable client-facing API
• support direct model addressing and higher-level role addressing
• route requests to healthy loaded services first

Repository layout:

• docs/architecture.md: system overview and v1 scope
• docs/roadmap.md: current milestones and near-term priorities
• docs/schemas.md: canonical data models
• docs/deployment.md: intended deployment approach
• docs/demo.md: first end-to-end control-plus-node demo flow
• docs/llm_demo.md: detailed master/peer/client LLM demo runbook
• docs/reverse_proxy.md: safer external exposure patterns
• configs/: example control-plane, node, and role configs
• scripts/: small launch and inspection helpers
• src/geniehive_control/: control-plane package
• src/geniehive_node/: node-agent package

There is now a documented single-machine path as well as the cluster-oriented path, so GenieHive can be exercised as a useful local router even without multiple hosts.

This repository is intended as the clean successor to narrower local gateway experiments. OpenAI-compatible routing remains important, but it is treated as one client facade within a broader cluster control-plane design.

Development

Local development setup:

cd /home/netuser/bin/geniehive
python -m venv .venv
. .venv/bin/activate
pip install -e '.[dev]'

Common commands:

make test
make smoke
make health

Repository conventions:

• local runtime state lives under state/ and should not be committed
• example configs under configs/ should remain runnable
• operator scripts under scripts/ are part of the supported workflow