* 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
de253e4a0a