With no production instance yet, there is no reason to carry two ways
of configuring the agent. Every environment variable that duplicated a
config key is gone; the environment now supplies only the secrets the
file references by ${…}, plus NISSE_CONFIG and NISSE_ENV to find the
files.
- AgentConfig loads from a file (load, from_file) or a parsed tree
(from_tree, for tests); a missing file is an error naming the example
- The from_env constructors on LiteLLMClient, AnthropicPassthroughClient,
GiteaClient, MatrixConfig and RoleMap are removed, with the env
reading for max output tokens; clients take their settings from config
- The live integration tests share a committed agent config,
tests/integration/nisse-test.yaml, aimed at test resources, and one
conftest that loads it and builds clients. NISSE_LIVE_PLANNER_MODEL
becomes its planner role; NISSE_CAPABILITY_MODELS stays as a per-run
switch
- A missing secret now fails the live tests instead of skipping them
- CI passes only the three tokens
- .env.example is secrets only; spec A5 says config comes from the file
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
- planner.py: LLMPlanningAgent offers exactly two tools, submit_plan
and ask_human, so gating stays structural at the tool layer; no
proceed tool exists. System prompt requires explicit, low-inference
plans because a weaker model executes them (A13)
- Model output is appended to the canonical log as it arrives, before
being interpreted, so a crash mid-planning leaves a truthful
transcript
- A bad turn (prose instead of a tool call, malformed arguments, or a
failed call) retries once, then raises PlanningError; the
orchestrator gates to AWAIT_INPUT rather than inventing a plan
- Orchestrator: appends every operator message, plan_submitted, and
gate_opened to the transcript, so re-planning sees rejection
feedback as conversation rather than out-of-band parameters; pins
the A11 role mapping at task start
- llm.py: non-JSON or non-object tool arguments now raise LLMError
instead of escaping as JSONDecodeError — observed from llama3.2,
which emits truncated argument strings
- Live planning test is opt-in on NISSE_LIVE_PLANNER_MODEL: planning
escalates unconditionally (A12) and the local model does not hold
the tool-call contract, so it awaits a frontier route
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>