fix: tolerate expert_op4grid_recommender's typed-pipeline return shape#183
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The upstream expert_op4grid_recommender typed-pipeline refactor (R1, 0.2.7) replaced run_analysis_step1's (res_step1, context) 2-tuple with a single AnalysisContext (proceed) or AnalysisResult (no-overload short-circuit). AnalysisMixin.run_analysis_step1 now normalises both shapes via _normalize_step1_outcome, so the backend keeps working against both the legacy and the refactored recommender releases (same version-tolerance pattern as _upstream_step1_supports_prebuilt_obs). The new AnalysisContext / AnalysisResult dataclasses expose a dict-compatible view, so every context[...] / result.get(...) access in the service layer is unchanged. Verified against the real refactored recommender: this fixes the two tests that drive the live step1 (test_step1_detects_single_overload, test_step2_returns_prioritized_action_set) with zero regressions across the backend suite. Also: annotate _normalize_step1_outcome's return type (backend code-quality ratchet: 61 -> 60), and add expert_backend/tests/test_step1_outcome_normalization.py covering the tuple / isinstance / structural-fallback paths and the service-level short-circuit-vs-proceed decision (real-dataclass cases skip under the mock layer). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LGzwaP2SnQCbLKo4ZNuwSg Signed-off-by: Antoine Marot <amarot91@gmail.com>
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The upstream expert_op4grid_recommender typed-pipeline refactor (R1, 0.2.7) replaced run_analysis_step1's (res_step1, context) 2-tuple with a single AnalysisContext (proceed) or AnalysisResult (no-overload short-circuit).
AnalysisMixin.run_analysis_step1 now normalises both shapes via _normalize_step1_outcome, so the backend keeps working against both the legacy and the refactored recommender releases (same version-tolerance pattern as _upstream_step1_supports_prebuilt_obs). The new AnalysisContext / AnalysisResult dataclasses expose a dict-compatible view, so every context[...] / result.get(...) access in the service layer is unchanged.
Verified against the real refactored recommender: this fixes the two tests that drive the live step1 (test_step1_detects_single_overload, test_step2_returns_prioritized_action_set) with zero regressions across the backend suite.
Also: annotate _normalize_step1_outcome's return type (backend code-quality ratchet: 61 -> 60), and add
expert_backend/tests/test_step1_outcome_normalization.py covering the tuple / isinstance / structural-fallback paths and the service-level short-circuit-vs-proceed decision (real-dataclass cases skip under the mock layer).
Claude-Session: https://claude.ai/code/session_01LGzwaP2SnQCbLKo4ZNuwSg