The full end-to-end live_gui FR1 test would require mock injection into
the live_gui subprocess (patches in the test process do NOT propagate).
The mock-based regression coverage for FR1 is already in:
- tests/test_live_gui_integration_v2.py::test_user_request_error_handling
(full controller flow with mock_app fixture)
- tests/test_ai_loop_regressions_20260614.py::test_fr1_*
(unit-level)
This smoke test verifies the live_gui's ai_status field is reachable via
the Hook API, establishing the integration substrate exists for
follow-up work to add subprocess mock injection.
The 2 tests in test_live_gui_integration_v2.py were mocking the old
ai_client.send() and asserting on the old error format. The FR1 fix
migrated _handle_request_event to ai_client.send_result() and routes
errors via ErrorInfo.ui_message() instead of f'ERROR: {e}'.
Updated:
- test_user_request_integration_flow: mock send_result instead of send
- test_user_request_error_handling: mock send_result returning an error
Result; assert new error format (just the message, no 'ERROR:' prefix)
Per AGENTS.md 'do not skip tests just because they fail' -- adapted
the tests to test the new (correct) behavior, not skipped or simplified.
Replaces deprecated ai_client.send() in _handle_request_event with
send_result() and branches on result.ok. On error, the first ErrorInfo
is routed to the event_queue as a 'response' with status='error',
allowing _on_comms_entry to add it to the discussion history.
The previous code called the @deprecated send() shim which silently
returns '' on error. The empty string was then filtered out by
_on_comms_entry (text_content.strip() check at line 3801), so users
saw no discussion entry for failed AI requests.
This also removes the dead 'except ai_client.ProviderError' clause at
line 3692 (the class was removed in commit 64b787b8). The 2 remaining
dead clauses at lines 305, 313 are fixed in the next commit (FR2).
This resolves the 401 Unauthorized/invalid api_id error by letting the MiniMax client default to api.minimax.io/v1 (like the model listing logic) or read a custom base_url from credentials.toml.
This resolves the issue where calling 'send_openai_compatible' discarded the NormalizedResponse details, resulting in an AttributeError when accessing 'raw_response' inside the tool loop.
ed