"""Unit tests for AI complexity analyzer agent setup."""
from types import SimpleNamespace
from mcp_server_mas_sequential_thinking.routing import ai_complexity_analyzer
class DummyAgent:
"""Capture initialization values for assertions."""
def __init__(self, **kwargs):
self.kwargs = kwargs
def test_get_agent_falls_back_to_enhanced_model(monkeypatch):
"""Analyzer should use enhanced model when create_agent_model is absent."""
monkeypatch.setattr(ai_complexity_analyzer, "Agent", DummyAgent)
monkeypatch.setattr(
ai_complexity_analyzer,
"create_learning_resources",
lambda: SimpleNamespace(learning_machine="lm", db="db"),
)
model_config = SimpleNamespace(create_enhanced_model=lambda: "enhanced-model")
analyzer = ai_complexity_analyzer.AIComplexityAnalyzer(model_config=model_config)
agent = analyzer._get_agent()
assert agent.kwargs["model"] == "enhanced-model"
assert agent.kwargs["learning"] == "lm"
assert agent.kwargs["db"] == "db"
def test_get_agent_prefers_create_agent_model_when_available(monkeypatch):
"""Analyzer should use dedicated agent model factory when present."""
monkeypatch.setattr(ai_complexity_analyzer, "Agent", DummyAgent)
monkeypatch.setattr(
ai_complexity_analyzer,
"create_learning_resources",
lambda: SimpleNamespace(learning_machine="lm", db="db"),
)
model_config = SimpleNamespace(
create_agent_model=lambda: "agent-model",
create_enhanced_model=lambda: "enhanced-model",
)
analyzer = ai_complexity_analyzer.AIComplexityAnalyzer(model_config=model_config)
agent = analyzer._get_agent()
assert agent.kwargs["model"] == "agent-model"
