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* feat(run): propagate model_name from gateway request context to persistence layer Pass model_name through the full run creation pipeline — from RunCreateRequest.context in the gateway, through RunManager, to the RunStore interface and SQL persistence. This enables client-specified model selection to be recorded per-run in the database. * feat(run): add model allowlist validation and effective model name capture - Validate model_name against allowlist in gateway services.py using get_app_config().get_model_config() - Truncate model_name to 128 chars to match DB column constraint - In worker.py, capture effective model name from agent.metadata after agent creation and persist if resolved differently than requested * feat(run): add defense-in-depth model_name normalization and round-trip persistence tests - Add _normalize_model_name() to RunRepository for whitespace stripping and 128-char truncation before DB writes. - Add round-trip unit tests for model_name creation and default None in test_run_manager.py. * fix(run): coerce non-string model_name values before strip/truncate in _normalize_model_name * fix(gateway): add runtime type guard for model_name coercion in gateway services Add isinstance check and str() coercion before calling .strip() to prevent AttributeError when non-string types (int, None, etc.) flow through the gateway. Paired with SQL integration test for end-to-end model_name persistence across gateway → langgraph → persistence layer. * fix(run): drop Alembic migration for model_name (no-op) and expose public update method on RunManager - Drop a1b2c3d4e5f6 migration: model_name already exists in RunRow schema and is auto-created via Base.metadata.create_all() at startup - Add update_model_name() public method to RunManager to replace the private _persist_to_store call in worker.py, preserving internal locking/persistence