"""
Tests for LLM-Driven Modular Strategy

Phase 18: Advanced Search Strategies - Modular Strategy Tests
Tests modular components and strategy orchestration.
"""

from unittest.mock import patch, MagicMock


class TestModularComponents:
    """Tests for modular component functionality"""

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_initialization(self, mock_strategy_cls):
        """Test modules are properly initialized"""
        mock_strategy = MagicMock()
        mock_strategy.modules = {
            "constraint_processor": MagicMock(),
            "rejection_manager": MagicMock(),
        }

        assert "constraint_processor" in mock_strategy.modules

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_dependency_resolution(self, mock_strategy_cls):
        """Test module dependencies are resolved"""
        mock_strategy = MagicMock()
        mock_strategy._resolve_dependencies.return_value = [
            "module_a",
            "module_b",
            "module_c",
        ]

        order = mock_strategy._resolve_dependencies(
            ["module_c", "module_a", "module_b"]
        )

        assert len(order) == 3

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_execution_order(self, mock_strategy_cls):
        """Test modules execute in correct order"""
        mock_strategy = MagicMock()
        mock_strategy._get_execution_order.return_value = [1, 2, 3, 4, 5, 6, 7]

        order = mock_strategy._get_execution_order()

        assert order == [1, 2, 3, 4, 5, 6, 7]

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_output_passing(self, mock_strategy_cls):
        """Test module outputs are passed between modules"""
        mock_strategy = MagicMock()
        mock_strategy._pass_output.return_value = {"processed_data": "value"}

        output = mock_strategy._pass_output("module_a", {"raw_data": "value"})

        assert "processed_data" in output

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_error_isolation(self, mock_strategy_cls):
        """Test errors in one module don't crash others"""
        mock_strategy = MagicMock()
        mock_strategy._execute_with_isolation.return_value = {
            "success": False,
            "error": "Module failed",
            "fallback_used": True,
        }

        result = mock_strategy._execute_with_isolation("failing_module")

        assert result["fallback_used"] is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_retry_logic(self, mock_strategy_cls):
        """Test module retry on failure"""
        mock_strategy = MagicMock()
        mock_strategy._retry_module.return_value = {
            "success": True,
            "retries": 2,
        }

        result = mock_strategy._retry_module("flaky_module", max_retries=3)

        assert result["success"] is True
        assert result["retries"] <= 3

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_timeout_handling(self, mock_strategy_cls):
        """Test module timeout is handled"""
        mock_strategy = MagicMock()
        mock_strategy._execute_with_timeout.return_value = {
            "success": False,
            "error": "Timeout",
            "elapsed_ms": 30000,
        }

        result = mock_strategy._execute_with_timeout(
            "slow_module", timeout_ms=30000
        )

        assert result["success"] is False

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_parallel_execution(self, mock_strategy_cls):
        """Test modules can execute in parallel"""
        mock_strategy = MagicMock()
        mock_strategy._execute_parallel.return_value = {
            "module_a": {"result": "a"},
            "module_b": {"result": "b"},
        }

        results = mock_strategy._execute_parallel(["module_a", "module_b"])

        assert len(results) == 2

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_sequential_execution(self, mock_strategy_cls):
        """Test modules execute sequentially when needed"""
        mock_strategy = MagicMock()
        execution_log = []

        def log_execution(module_name):
            execution_log.append(module_name)
            return {"module": module_name}

        mock_strategy._execute_sequential.side_effect = lambda modules: [
            log_execution(m) for m in modules
        ]

        mock_strategy._execute_sequential(["m1", "m2", "m3"])

        assert execution_log == ["m1", "m2", "m3"]

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_conditional_execution(self, mock_strategy_cls):
        """Test conditional module execution"""
        mock_strategy = MagicMock()
        mock_strategy._should_execute.return_value = True

        should_run = mock_strategy._should_execute(
            "optional_module", {"condition": True}
        )

        assert should_run is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_result_aggregation(self, mock_strategy_cls):
        """Test module results are aggregated"""
        mock_strategy = MagicMock()
        mock_strategy._aggregate_results.return_value = {
            "total_candidates": 15,
            "filtered_candidates": 10,
            "final_candidates": 5,
        }

        aggregated = mock_strategy._aggregate_results(
            [{"candidates": 15}, {"filtered": 10}, {"final": 5}]
        )

        assert aggregated["total_candidates"] == 15

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_state_management(self, mock_strategy_cls):
        """Test module state is managed"""
        mock_strategy = MagicMock()
        mock_strategy.state = {"phase": 1, "candidates": []}

        mock_strategy._update_state({"phase": 2})

        mock_strategy._update_state.assert_called_once()

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_checkpoint_saving(self, mock_strategy_cls):
        """Test checkpoint is saved"""
        mock_strategy = MagicMock()
        mock_strategy._save_checkpoint.return_value = {
            "checkpoint_id": "cp_123"
        }

        checkpoint = mock_strategy._save_checkpoint(
            {"phase": 3, "data": "state"}
        )

        assert "checkpoint_id" in checkpoint

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_checkpoint_restoration(self, mock_strategy_cls):
        """Test checkpoint can be restored"""
        mock_strategy = MagicMock()
        mock_strategy._restore_checkpoint.return_value = {
            "phase": 3,
            "data": "restored",
        }

        state = mock_strategy._restore_checkpoint("cp_123")

        assert state["phase"] == 3

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_progress_reporting(self, mock_strategy_cls):
        """Test progress is reported"""
        mock_strategy = MagicMock()
        mock_callback = MagicMock()
        mock_strategy.progress_callback = mock_callback

        mock_strategy._report_progress(50, "Halfway done")

        mock_strategy._report_progress.assert_called_once()

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_resource_allocation(self, mock_strategy_cls):
        """Test resources are allocated per module"""
        mock_strategy = MagicMock()
        mock_strategy._allocate_resources.return_value = {
            "max_tokens": 1000,
            "timeout_ms": 30000,
        }

        resources = mock_strategy._allocate_resources("analysis_module")

        assert "max_tokens" in resources

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_llm_selection(self, mock_strategy_cls):
        """Test LLM is selected per module"""
        mock_strategy = MagicMock()
        mock_strategy._select_llm.return_value = "gpt-4"

        llm = mock_strategy._select_llm("complex_reasoning_module")

        assert llm is not None

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_prompt_templating(self, mock_strategy_cls):
        """Test prompt templates are used"""
        mock_strategy = MagicMock()
        mock_strategy._render_prompt.return_value = (
            "Analyze the following query: test"
        )

        prompt = mock_strategy._render_prompt(
            "analysis_template", {"query": "test"}
        )

        assert "test" in prompt

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_output_validation(self, mock_strategy_cls):
        """Test module output is validated"""
        mock_strategy = MagicMock()
        mock_strategy._validate_output.return_value = {
            "valid": True,
            "errors": [],
        }

        validation = mock_strategy._validate_output({"candidates": [1, 2, 3]})

        assert validation["valid"] is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_module_quality_assessment(self, mock_strategy_cls):
        """Test module output quality is assessed"""
        mock_strategy = MagicMock()
        mock_strategy._assess_quality.return_value = 0.85

        quality = mock_strategy._assess_quality(
            {"candidates": ["good", "quality"]}
        )

        assert quality >= 0.8


class TestStrategyOrchestration:
    """Tests for strategy orchestration"""

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_configuration(self, mock_strategy_cls):
        """Test strategy is configurable"""
        mock_strategy = MagicMock()
        mock_strategy.config = {
            "max_iterations": 10,
            "confidence_threshold": 0.8,
        }

        assert mock_strategy.config["max_iterations"] == 10

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_execution_flow(self, mock_strategy_cls):
        """Test execution flows through all phases"""
        mock_strategy = MagicMock()
        mock_strategy.analyze_topic.return_value = {
            "phases_completed": [1, 2, 3, 4, 5, 6, 7],
            "answer": "Test answer",
        }

        result = mock_strategy.analyze_topic("test query")

        assert len(result["phases_completed"]) == 7

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_adaptation(self, mock_strategy_cls):
        """Test strategy adapts to query type"""
        mock_strategy = MagicMock()
        mock_strategy._adapt_strategy.return_value = {
            "search_depth": "deep",
            "parallel_searches": True,
        }

        adaptation = mock_strategy._adapt_strategy("complex research query")

        assert "search_depth" in adaptation

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_fallback_handling(self, mock_strategy_cls):
        """Test fallback is used on failure"""
        mock_strategy = MagicMock()
        mock_strategy._execute_with_fallback.return_value = {
            "success": True,
            "used_fallback": True,
            "fallback_type": "simplified_search",
        }

        result = mock_strategy._execute_with_fallback("main_search")

        assert result["used_fallback"] is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_quality_threshold(self, mock_strategy_cls):
        """Test quality threshold is enforced"""
        mock_strategy = MagicMock()
        mock_strategy._meets_quality_threshold.return_value = False

        meets_threshold = mock_strategy._meets_quality_threshold(
            {"confidence": 0.5}, threshold=0.8
        )

        assert meets_threshold is False

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_early_termination(self, mock_strategy_cls):
        """Test early termination on high confidence"""
        mock_strategy = MagicMock()
        mock_strategy._should_terminate_early.return_value = True

        should_stop = mock_strategy._should_terminate_early(
            {"confidence": 0.98}
        )

        assert should_stop is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_result_synthesis(self, mock_strategy_cls):
        """Test results are synthesized"""
        mock_strategy = MagicMock()
        mock_strategy._synthesize_results.return_value = {
            "answer": "Synthesized answer",
            "sources": ["source1", "source2"],
        }

        synthesis = mock_strategy._synthesize_results(
            [{"text": "result1"}, {"text": "result2"}]
        )

        assert "answer" in synthesis

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_cost_optimization(self, mock_strategy_cls):
        """Test cost optimization is applied"""
        mock_strategy = MagicMock()
        mock_strategy._optimize_for_cost.return_value = {
            "reduced_searches": True,
            "estimated_savings": 0.15,
        }

        optimization = mock_strategy._optimize_for_cost({"budget": 1.0})

        assert "reduced_searches" in optimization

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_latency_optimization(self, mock_strategy_cls):
        """Test latency optimization is applied"""
        mock_strategy = MagicMock()
        mock_strategy._optimize_for_latency.return_value = {
            "parallel_execution": True,
            "cached_results_used": True,
        }

        optimization = mock_strategy._optimize_for_latency(
            {"max_latency_ms": 5000}
        )

        assert optimization["parallel_execution"] is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_quality_optimization(self, mock_strategy_cls):
        """Test quality optimization is applied"""
        mock_strategy = MagicMock()
        mock_strategy._optimize_for_quality.return_value = {
            "deep_search": True,
            "verification_enabled": True,
        }

        optimization = mock_strategy._optimize_for_quality({"min_quality": 0.9})

        assert optimization["verification_enabled"] is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_multi_objective(self, mock_strategy_cls):
        """Test multi-objective optimization"""
        mock_strategy = MagicMock()
        mock_strategy._optimize_multi_objective.return_value = {
            "balance": "quality_first",
            "compromises": ["slightly_slower"],
        }

        optimization = mock_strategy._optimize_multi_objective(
            {"quality": 0.9, "cost": 0.5, "latency": 0.7}
        )

        assert "balance" in optimization

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_user_preference(self, mock_strategy_cls):
        """Test user preferences are respected"""
        mock_strategy = MagicMock()
        mock_strategy._apply_user_preferences.return_value = {
            "search_engines": ["google", "bing"],
            "max_sources": 10,
        }

        preferences = mock_strategy._apply_user_preferences(
            {"preferred_engines": ["google"]}
        )

        assert "search_engines" in preferences

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_context_awareness(self, mock_strategy_cls):
        """Test strategy is context-aware"""
        mock_strategy = MagicMock()
        mock_strategy._apply_context.return_value = {
            "previous_searches": ["search1"],
            "accumulated_knowledge": {"fact1": True},
        }

        context = mock_strategy._apply_context({"history": ["search1"]})

        assert "accumulated_knowledge" in context

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_learning_integration(self, mock_strategy_cls):
        """Test learning from past executions"""
        mock_strategy = MagicMock()
        mock_strategy._apply_learning.return_value = {
            "improved_patterns": True,
            "success_rate_improvement": 0.05,
        }

        learning = mock_strategy._apply_learning({"past_executions": 100})

        assert learning["improved_patterns"] is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMDrivenModularStrategy"
    )
    def test_strategy_feedback_incorporation(self, mock_strategy_cls):
        """Test feedback is incorporated"""
        mock_strategy = MagicMock()
        mock_strategy._incorporate_feedback.return_value = {
            "adjustments_made": ["increased_depth"],
            "feedback_applied": True,
        }

        feedback_result = mock_strategy._incorporate_feedback(
            {"rating": 3, "comment": "Need more depth"}
        )

        assert feedback_result["feedback_applied"] is True


class TestLLMConstraintProcessor:
    """Tests for LLM constraint processor"""

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMConstraintProcessor"
    )
    def test_decompose_constraints_intelligently(self, mock_processor_cls):
        """Test intelligent constraint decomposition"""
        mock_processor = MagicMock()
        mock_processor.decompose_constraints_intelligently.return_value = {
            "atomic_elements": ["element1", "element2"],
            "variations": ["var1", "var2"],
        }

        result = mock_processor.decompose_constraints_intelligently(
            ["constraint1"]
        )

        assert "atomic_elements" in result

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMConstraintProcessor"
    )
    def test_generate_intelligent_combinations(self, mock_processor_cls):
        """Test generating search combinations"""
        mock_processor = MagicMock()
        mock_processor.generate_intelligent_combinations.return_value = [
            {"query": "combination1", "priority": "high"},
            {"query": "combination2", "priority": "medium"},
        ]

        combinations = mock_processor.generate_intelligent_combinations(
            {"elements": ["e1", "e2"]}
        )

        assert len(combinations) == 2

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMConstraintProcessor"
    )
    def test_generate_creative_search_angles(self, mock_processor_cls):
        """Test creative search angle generation"""
        mock_processor = MagicMock()
        mock_processor.generate_creative_search_angles.return_value = [
            "alternative perspective 1",
            "alternative perspective 2",
        ]

        angles = mock_processor.generate_creative_search_angles(
            "query", {"constraints": []}
        )

        assert len(angles) == 2

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.LLMConstraintProcessor"
    )
    def test_optimize_search_combinations(self, mock_processor_cls):
        """Test search combination optimization"""
        mock_processor = MagicMock()
        mock_processor.optimize_search_combinations.return_value = [
            {"query": "optimized1", "score": 0.9},
            {"query": "optimized2", "score": 0.8},
        ]

        optimized = mock_processor.optimize_search_combinations(
            [
                {"query": "q1", "score": 0.9},
                {"query": "q2", "score": 0.5},
                {"query": "q3", "score": 0.8},
            ]
        )

        # Should be sorted by score
        assert len(optimized) == 2


class TestEarlyRejectionManager:
    """Tests for early rejection manager"""

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.EarlyRejectionManager"
    )
    def test_quick_confidence_check(self, mock_manager_cls):
        """Test quick confidence checking"""
        mock_manager = MagicMock()
        mock_manager.quick_confidence_check.return_value = {
            "positive_confidence": 0.8,
            "negative_confidence": 0.2,
        }

        check = mock_manager.quick_confidence_check(
            "candidate", ["constraint1"]
        )

        assert "positive_confidence" in check

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.EarlyRejectionManager"
    )
    def test_should_reject_early(self, mock_manager_cls):
        """Test early rejection decision"""
        mock_manager = MagicMock()
        mock_manager.should_reject_early.return_value = True

        should_reject = mock_manager.should_reject_early(
            {"positive_confidence": 0.1}
        )

        assert should_reject is True

    @patch(
        "local_deep_research.advanced_search_system.strategies.llm_driven_modular_strategy.EarlyRejectionManager"
    )
    def test_should_continue_search(self, mock_manager_cls):
        """Test search continuation decision"""
        mock_manager = MagicMock()
        mock_manager.should_continue_search.return_value = False

        should_continue = mock_manager.should_continue_search(
            all_candidates=[{"confidence": 0.95}], high_confidence_count=1
        )

        assert should_continue is False
