Files
OpenJarvis/tests/cli/test_ask_router.py
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Jon Saad-FalconandClaude Opus 4.6 323d7ff032 Add TOML config system for eval suites, pillar-aligned config, and documentation
- Eval config: TOML-based suite configs defining models x benchmarks matrix,
  loaded via --config flag. Includes load_eval_config(), expand_suite(),
  7 config dataclasses, 3 example configs, and 61 new tests.
- Pillar-aligned config: generation params in IntelligenceConfig, nested
  engine/learning configs, agent objective/system_prompt/context_from_memory,
  structured learning sub-policies, TOML migration layer.
- Documentation: evaluations user guide, evals API reference, updated
  mkdocs.yml navigation, updated architecture docs.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-24 03:34:05 +00:00

113 lines
4.0 KiB
Python

"""Tests for model resolution fallback chain in jarvis ask."""
from __future__ import annotations
import importlib
from unittest import mock
from click.testing import CliRunner
from openjarvis.cli import cli
_ask_mod = importlib.import_module("openjarvis.cli.ask")
def _mock_engine():
"""Create a mock engine that returns a simple response."""
engine = mock.MagicMock()
engine.engine_id = "mock"
engine.health.return_value = True
engine.list_models.return_value = ["test-model"]
engine.generate.return_value = {
"content": "Hello!",
"usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
"model": "test-model",
"finish_reason": "stop",
}
return engine
def _patch_engine(engine):
"""Return context managers that patch engine discovery to use our mock."""
return (
mock.patch.object(
_ask_mod, "get_engine",
return_value=("mock", engine),
),
mock.patch.object(
_ask_mod, "discover_engines",
return_value={"mock": engine},
),
mock.patch.object(
_ask_mod, "discover_models",
return_value={"mock": ["test-model"]},
),
mock.patch.object(_ask_mod, "register_builtin_models"),
mock.patch.object(_ask_mod, "merge_discovered_models"),
mock.patch.object(_ask_mod, "TelemetryStore"),
)
class TestAskModelResolution:
def test_default_model_from_config(self) -> None:
"""When no -m flag, uses config.intelligence.default_model."""
engine = _mock_engine()
patches = _patch_engine(engine)
with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5]:
result = CliRunner().invoke(cli, ["ask", "Hello"])
assert result.exit_code == 0
assert "Hello!" in result.output
def test_explicit_model_flag(self) -> None:
"""The -m flag directly selects a model, bypassing fallback chain."""
engine = _mock_engine()
patches = _patch_engine(engine)
with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5]:
result = CliRunner().invoke(
cli, ["ask", "-m", "test-model", "Hello"],
)
assert result.exit_code == 0
assert "Hello!" in result.output
def test_fallback_to_engine_models(self) -> None:
"""When default_model is empty, falls back to first engine model."""
engine = _mock_engine()
patches = _patch_engine(engine)
with (
patches[0], patches[1], patches[2], patches[3], patches[4], patches[5],
mock.patch.object(
_ask_mod, "load_config",
) as mock_config,
):
cfg = mock_config.return_value
cfg.telemetry.enabled = False
cfg.intelligence.default_model = ""
cfg.intelligence.fallback_model = ""
cfg.agent.context_from_memory = False
result = CliRunner().invoke(cli, ["ask", "Hello"])
assert result.exit_code == 0
def test_fallback_to_fallback_model(self) -> None:
"""When default_model is empty and no engine models, uses fallback_model."""
engine = _mock_engine()
patches = _patch_engine(engine)
# Override discover_models to return empty list
with (
patches[0], patches[1],
mock.patch.object(
_ask_mod, "discover_models",
return_value={"mock": []},
),
patches[3], patches[4], patches[5],
mock.patch.object(
_ask_mod, "load_config",
) as mock_config,
):
cfg = mock_config.return_value
cfg.telemetry.enabled = False
cfg.intelligence.default_model = ""
cfg.intelligence.fallback_model = "fallback-model"
cfg.agent.context_from_memory = False
result = CliRunner().invoke(cli, ["ask", "Hello"])
assert result.exit_code == 0