Three scenarios in features/semantic_context_search.feature were erroring
during behave execution, surfacing as test setup/teardown errors in CI's
unit_tests gate. Each had a distinct root cause:
1. "Filter fragments by minimum similarity threshold" (line 30) referenced
context.ranked_fragments inside step_filter_by_threshold, but the
scenario filters directly without first running the "rank fragments"
step that populates that attribute. The filter step now computes
per-fragment similarity inline from context.fragments +
context.query_embedding so it works regardless of whether a prior
ranking step ran.
2. "Semantic strategy selects relevant files" (line 41) constructed
ContextFragment with a FragmentProvenance imported from
cleveragents.domain.models.acms.crp. The core ContextFragment's
provenance field is annotated with the core FragmentProvenance subclass
(which adds resource_type), and pydantic v2's strict model_type check
rejects a bare CRP-base instance. Switched the import to the core
FragmentProvenance so the type matches.
3. "Embedding provider configuration" (line 53) stored its provider config
on context.config. Behave's Context reserves the config attribute for
its own Configuration object; user assignment raises KeyError inside
Behave's scope-tracking __setattr__. Renamed to embedding_config.
Verified locally: behave on features/semantic_context_search.feature now
reports 6 scenarios passed / 0 errored. lint + typecheck both pass.
ISSUES CLOSED: #5254
HAL9000
475e2a7843