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v0.3.0

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@evgenii-engineer evgenii-engineer released this 22 Jun 16:28
· 7 commits to master since this release

openLigtht v0.3.0

Compared with v0.2.0, this release introduces an edge/brain network topology
that lets Raspberry Pi edge nodes offload LLM inference, voice transcription,
and skill execution to a central brain node over a lightweight HTTP API, while
keeping the full single-node path intact for deployments that don't need it.
Voice handling is tightened and the status command is wired through a new hooks
layer.

What shipped

  • Added an edge/brain network architecture: a brain node (Mac mini or server)
    exposes an HTTP API (internal/brain/server.go); edge nodes (Raspberry Pi)
    can route LLM calls, voice transcription, and skill invocations to it via new
    remote providers (internal/llm/remote.go, internal/voice/remote.go,
    internal/skills/remote.go). New example configs
    (configs/agent.brain.example.yaml, configs/agent.edge.example.yaml)
    document the topology end-to-end.
  • Added a display skill and a Python display dashboard
    (scripts/display-dashboard.py) for Raspberry Pi nodes with a screen, plus
    a deploy script (scripts/deploy-rpi-display.sh) and systemd unit
    (deployments/systemd/openlight-display.service).
  • Added a think skill (internal/skills/chat/think_skill.go) that exposes
    an explicit reasoning step through the normal routing pipeline.
  • Improved voice handling: extended config validation for whisper_path,
    model_path, and language; tightened the Telegram voice-message client;
    added Russian-language routing tests; expanded openlight doctor voice
    probes.
  • Fixed the /status command by wiring it through a new runtime hooks layer
    (internal/runtime/), replacing the previous direct call path.

Upgrade notes

  • Existing v0.2.0 configs work unchanged. The edge/brain topology is entirely
    opt-in: copy configs/agent.brain.example.yaml to the brain node and
    configs/agent.edge.example.yaml to each edge node, fill in the shared
    token, and restart.
  • The display dashboard requires Python 3 and its dependencies on the Pi.
    Run scripts/deploy-rpi-display.sh to install them; the script is
    idempotent.
  • The think skill is registered automatically alongside other chat skills;
    no config change is needed to enable it.