dongarandClaude Fable 5
0c2021fced
PR 2 of the steps-3/4 plan. - llm.py: LLMClient protocol — complete(events, tools, model) -> canonical events — present from the first real LLM call. LiteLLMClient renders requests via the A10 renderer, targets the proxy's OpenAI-compatible route, and maps provider tool-call IDs to locally-minted canonical IDs at the boundary - RoleMap (A11): executor/planner/delegate/consultant resolved from env; pinned() returns the mapping to record at task start - Config strictly from env: NISSE_LLM_BASE_URL, NISSE_LLM_TOKEN; envfile.py is a minimal .env loader where real env wins; .env now gitignored with a committed .env.example documenting all variables (Matrix ones included for the upcoming transport PR) - Live smoke test against the proxy is integration-marked and skips without credentials — CI stays credential-free per operator decision; the test runs locally once .env exists - httpx added as nisse-dev's HTTP client Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Nisse
Two self-hosted AI agents sharing a common library, named for the Nordic farm spirit that keeps the place running overnight and expects to be treated well in return.
| Package | Role |
|---|---|
nisse-core/ |
Shared library both agents sit on (Part A) |
nisse-dev/ |
Dev Agent — plans and implements software projects (Part B) |
nisse-ops/ |
Sysadmin Agent — operates infrastructure (Part C) |
One repository, three packages. The library does not exist as code yet: it is
extracted from nisse-dev once that agent works (build-order step 10), as a
package split within this tree.
Architecture
The system-level specification lives at
docs/Architecture-Build-Spec.md. It covers the
shared library, both agents, the supporting services, the build order, and the
remaining open decisions.