#!/usr/bin/env python3

"""
Failing Test for LV Framework Qdrant Integration
==============================================

This test demonstrates that the LV framework currently has placeholders
instead of real Qdrant integration. It must fail initially, then pass
after the fix is implemented.
"""

import sys
import os
import pytest
import asyncio
from unittest.mock import Mock, AsyncMock

# Add the src directory to path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src'))

from mcp_neocoder.lv_ecosystem import LVEcosystem, EntropyEstimator
from mcp_neocoder.lv_templates import LVKnowledgeExtractTemplate


class TestLVQdrantIntegration:
    """Test that LV framework actually uses Qdrant instead of placeholders"""

    def setup_method(self):
        """Set up test fixtures"""
        # Mock Neo4j and Qdrant clients
        self.mock_neo4j = AsyncMock()
        self.mock_qdrant = Mock()
        
        # Set up mock Qdrant methods that should be called
        self.mock_qdrant.search = AsyncMock()
        self.mock_qdrant.add = AsyncMock()
        self.mock_qdrant.upsert = AsyncMock()
        
        # Initialize LV components
        self.lv_ecosystem = LVEcosystem(self.mock_neo4j, self.mock_qdrant)
        self.lv_extract = LVKnowledgeExtractTemplate(self.mock_neo4j, self.mock_qdrant)

    @pytest.mark.asyncio
    async def test_novelty_calculation_uses_real_qdrant(self):
        """
        Test that novelty calculation actually uses Qdrant search
        
        This test MUST fail initially because the current implementation
        has a placeholder that returns random values instead of real Qdrant search.
        """
        from mcp_neocoder.lv_ecosystem import LVCandidate
        
        candidate = LVCandidate(content="Test content for novelty calculation")
        
        # This should call Qdrant search but currently has placeholder
        novelty_score = await self.lv_ecosystem._calculate_novelty_score(candidate)
        
        # Verify that Qdrant search was actually called
        # This will FAIL because current implementation uses placeholder
        assert self.mock_qdrant.search.called, "Qdrant search should be called for novelty calculation"
        assert 0.0 <= novelty_score <= 1.0, "Novelty score should be between 0 and 1"

    @pytest.mark.asyncio  
    async def test_knowledge_storage_uses_real_qdrant(self):
        """
        Test that knowledge extraction stores chunks in real Qdrant
        
        This test MUST fail initially because the current implementation
        has a placeholder that logs instead of actually storing in Qdrant.
        """
        knowledge = {
            'entities': [{'name': 'TestEntity', 'entityType': 'Test', 'observations': ['test']}],
            'relationships': [],
            'text_chunks': [
                {'content': 'Test chunk 1', 'chunk_id': 'test_1', 'metadata': {'test': True}},
                {'content': 'Test chunk 2', 'chunk_id': 'test_2', 'metadata': {'test': True}}
            ]
        }
        
        # This should store chunks in Qdrant but currently has placeholder
        result = await self.lv_extract._store_extracted_knowledge(
            knowledge, "/test/document.txt", "test prompt"
        )
        
        # Verify that Qdrant storage was actually called
        # This will FAIL because current implementation only logs a placeholder message
        assert self.mock_qdrant.upsert.called or self.mock_qdrant.add.called, \
            "Qdrant storage should be called for text chunks"
        assert result['chunks_count'] == 2, "Should report correct number of stored chunks"

    def test_no_placeholder_comments_in_code(self):
        """
        Test that there are no placeholder comments in the LV framework code
        
        This test MUST fail initially because placeholder comments exist.
        """
        import inspect
        
        # Check LVEcosystem for placeholder comments
        ecosystem_source = inspect.getsource(self.lv_ecosystem._calculate_novelty_score)
        assert "Placeholder" not in ecosystem_source, "LVEcosystem should not contain placeholder comments"
        
        # Check LVKnowledgeExtractTemplate for placeholder comments  
        extract_source = inspect.getsource(self.lv_extract._store_extracted_knowledge)
        assert "Placeholder" not in extract_source, "LVKnowledgeExtractTemplate should not contain placeholder comments"

    def test_no_simulation_code_in_production(self):
        """
        Test that there is no simulation code in production LV framework
        
        This test MUST fail initially because simulation code exists.
        """
        import inspect
        
        # Check for simulation code in LV ecosystem
        ecosystem_source = inspect.getsource(self.lv_ecosystem.__class__)
        assert "simulate" not in ecosystem_source.lower(), "LVEcosystem should not contain simulation code"
        assert "random" not in ecosystem_source.lower(), "LVEcosystem should not use random values for real calculations"


if __name__ == "__main__":
    # Run the failing tests
    pytest.main([__file__, "-v"])
