"""Tests for agents/gap_analyzer.py — LLM-based gap detection."""

from __future__ import annotations

from unittest.mock import patch, MagicMock

from agents.gap_analyzer import (
    DetectedGap,
    GeneratedQuestionCard,
    GapAnalysisResult,
)


class TestModels:
    def test_detected_gap_creation(self):
        gap = DetectedGap(
            category="bolt_pattern",
            description="Bolt circle diameter not specified",
            severity="blocking",
        )
        assert gap.category == "bolt_pattern"
        assert gap.severity == "blocking"

    def test_generated_question_card_defaults(self):
        card = GeneratedQuestionCard(
            category="material",
            question="What material?",
            responsible_agent="engineering",
            suggestions=["Aluminum 6061"],
            allow_custom=True,
        )
        assert card.agent_name == ""
        assert card.agent_color == ""

    def test_gap_analysis_result_no_gaps(self):
        result = GapAnalysisResult(has_gaps=False, gaps=[], question_cards=[])
        assert not result.has_gaps
        assert result.gaps == []
        assert result.question_cards == []

    def test_gap_analysis_result_with_gaps(self):
        result = GapAnalysisResult(
            has_gaps=True,
            gaps=[DetectedGap(category="material", description="missing", severity="blocking")],
            question_cards=[GeneratedQuestionCard(
                category="material",
                question="What material?",
                responsible_agent="engineering",
                suggestions=[],
                allow_custom=True,
            )],
        )
        assert result.has_gaps
        assert len(result.gaps) == 1
        assert len(result.question_cards) == 1

    def test_severity_literal_validation(self):
        """Severity must be one of the allowed values."""
        import pytest
        with pytest.raises(Exception):
            DetectedGap(category="x", description="y", severity="invalid")

    def test_question_card_severity_default(self):
        card = GeneratedQuestionCard(
            category="material",
            question="What material?",
            responsible_agent="engineering",
        )
        assert card.severity == "recommended"

    def test_question_card_severity_blocking(self):
        card = GeneratedQuestionCard(
            category="material",
            question="What material?",
            responsible_agent="engineering",
            severity="blocking",
        )
        assert card.severity == "blocking"

    def test_question_card_severity_validation(self):
        import pytest
        with pytest.raises(Exception):
            GeneratedQuestionCard(
                category="x",
                question="q",
                responsible_agent="design",
                severity="invalid",
            )


from agents.agent_flow import AgentResponse
from agents.design_state import DesignState
from agents.gap_analyzer import analyze_gaps


class TestAnalyzeGaps:
    def _mock_llm_response(self, result: GapAnalysisResult):
        """Create a mock LLM that returns a structured result."""
        mock_llm_instance = MagicMock()
        mock_llm_instance.call.return_value = result
        return mock_llm_instance

    @patch("agents.gap_analyzer._build_llm")
    def test_returns_gaps_from_llm(self, mock_build_llm):
        expected = GapAnalysisResult(
            has_gaps=True,
            gaps=[DetectedGap(category="material", description="No material specified", severity="blocking")],
            question_cards=[GeneratedQuestionCard(
                category="material",
                question="What material should the bracket be made from?",
                responsible_agent="engineering",
                suggestions=["Aluminum 6061", "Steel 304"],
                allow_custom=True,
            )],
        )
        mock_build_llm.return_value = self._mock_llm_response(expected)

        responses = [AgentResponse.from_agent("design", "I suggest an L-bracket.")]
        result = analyze_gaps(responses, DesignState(), user_message="design a bracket")

        assert result.has_gaps
        assert result.gaps[0].category == "material"
        assert result.question_cards[0].question == "What material should the bracket be made from?"

    @patch("agents.gap_analyzer._build_llm")
    def test_enriches_agent_metadata(self, mock_build_llm):
        expected = GapAnalysisResult(
            has_gaps=True,
            gaps=[DetectedGap(category="machining", description="missing", severity="recommended")],
            question_cards=[GeneratedQuestionCard(
                category="machining",
                question="What machining approach?",
                responsible_agent="cnc",
                suggestions=[],
                allow_custom=True,
            )],
        )
        mock_build_llm.return_value = self._mock_llm_response(expected)

        result = analyze_gaps(
            [AgentResponse.from_agent("design", "A bracket design.")],
            DesignState(),
        )
        card = result.question_cards[0]
        assert card.agent_name == "CNC Agent"
        assert card.agent_color == "#00e676"

    @patch("agents.gap_analyzer._build_llm")
    def test_returns_empty_on_no_gaps(self, mock_build_llm):
        expected = GapAnalysisResult(has_gaps=False, gaps=[], question_cards=[])
        mock_build_llm.return_value = self._mock_llm_response(expected)

        result = analyze_gaps(
            [AgentResponse.from_agent("design", "Everything looks good.")],
            DesignState(material="aluminum"),
        )
        assert not result.has_gaps
        assert result.question_cards == []

    @patch("agents.gap_analyzer._build_llm")
    def test_fallback_on_llm_failure(self, mock_build_llm):
        mock_llm = MagicMock()
        mock_llm.call.side_effect = RuntimeError("API timeout")
        mock_build_llm.return_value = mock_llm

        result = analyze_gaps(
            [AgentResponse.from_agent("cad", "NOT READY: need dimensions")],
            DesignState(),
        )
        assert not result.has_gaps
        assert result.gaps == []
        assert result.question_cards == []

    @patch("agents.gap_analyzer._build_llm")
    def test_prompt_includes_state_and_responses(self, mock_build_llm):
        mock_llm = MagicMock()
        mock_llm.call.return_value = GapAnalysisResult(has_gaps=False, gaps=[], question_cards=[])
        mock_build_llm.return_value = mock_llm

        state = DesignState(material="aluminum 6061", part_name="bracket")
        responses = [AgentResponse.from_agent("engineering", "Looks reasonable.")]
        analyze_gaps(responses, state, user_message="make it 50mm wide")

        call_args = mock_llm.call.call_args
        # First positional arg is the messages list
        messages = call_args[0][0]
        prompt_text = str(messages)
        assert "aluminum 6061" in prompt_text
        assert "bracket" in prompt_text
        assert "engineering" in prompt_text
        assert "Looks reasonable." in prompt_text
        assert "make it 50mm wide" in prompt_text