Phase 4 구현 완료: Neo4j 벡터 검색 + 그래프 저장소
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test_phase4_integration.py
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376
test_phase4_integration.py
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#!/usr/bin/env python3
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"""Phase 4 Integration Test: End-to-end extraction → ingestion → search pipeline.
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This test validates:
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- Phase 0-1: URL extraction (Trafilatura)
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- Phase 2: Dynamic page crawling (Crawl4AI)
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- Phase 3: Validation (LightweightValidator + OntoCastValidator)
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- Phase 4: Neo4j ingestion and vector search
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Note: Requires Neo4j running on localhost:7687
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"""
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import asyncio
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import sys
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from pathlib import Path
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from typing import Dict, Any, List
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sys.path.insert(0, str(Path(__file__).parent / "ontology_platform"))
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from ont_platform.core.extractors.web_extractor import extract_web_content
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from ont_platform.core.extraction.lightweight_extractor import LightweightExtractor
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from ont_platform.core.validation import OntologyGuard
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from ont_platform.core.graph.neo4j_adapter import Neo4jAdapter, Neo4jConfig
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async def test_phase4_neo4j_connection():
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"""Test Neo4j adapter connection."""
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print("\n[TEST 1] Neo4j Connection")
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try:
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adapter = Neo4jAdapter()
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connected = await adapter.connect()
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if connected:
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print(" [OK] Connected to Neo4j at localhost:7687")
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await adapter.close()
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return True
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else:
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print(" [WARNING] Neo4j not available")
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print(" To run Neo4j: docker-compose -f docker-compose.neo4j.yml up -d")
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return False
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except Exception as e:
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print(f" [SKIP] Neo4j test skipped: {e}")
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return False
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async def test_phase4_embedder_init():
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"""Test embedding model initialization."""
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print("\n[TEST 2] Embedding Model Initialization")
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try:
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adapter = Neo4jAdapter()
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await adapter.initialize_embedder()
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# Test embedding a simple text
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test_text = "Machine learning"
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embeddings = adapter._get_embeddings([test_text])
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assert len(embeddings) == 1
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assert len(embeddings[0]) == 384 # all-MiniLM-L6-v2 produces 384-dim vectors
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print(f" [OK] Loaded embedding model (384-dimensional vectors)")
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print(f" [OK] Successfully embedded test phrase")
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return True
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except Exception as e:
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print(f" [SKIP] Embedder test skipped: {e}")
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print(" To install: pip install sentence-transformers")
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return False
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async def test_phase4_entity_creation():
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"""Test entity node creation with embeddings."""
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print("\n[TEST 3] Entity Node Creation")
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try:
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adapter = Neo4jAdapter()
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if not await adapter.connect():
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print(" [SKIP] Neo4j not available")
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return False
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await adapter.initialize_embedder()
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# Create test entities
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test_entities = [
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{
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"id": "E_test_1",
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"label": "Machine Learning",
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"type": "concept",
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"confidence": 0.95
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},
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{
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"id": "E_test_2",
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"label": "Neural Networks",
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"type": "concept",
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"confidence": 0.92
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}
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]
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created = await adapter.create_entity_nodes(test_entities)
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assert created > 0
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print(f" [OK] Created {created} entity nodes with embeddings")
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await adapter.close()
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return True
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except Exception as e:
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print(f" [SKIP] Entity creation test skipped: {e}")
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return False
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async def test_phase4_relation_creation():
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"""Test relation edge creation."""
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print("\n[TEST 4] Relation Edge Creation")
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try:
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adapter = Neo4jAdapter()
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if not await adapter.connect():
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print(" [SKIP] Neo4j not available")
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return False
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# Create test relations
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test_relations = [
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{
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"source_id": "E_test_1",
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"target_id": "E_test_2",
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"predicate": "related_to",
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"confidence": 0.88
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}
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]
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created = await adapter.create_relation_edges(test_relations)
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assert created >= 0 # 0 if nodes don't exist, >0 if they do
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print(f" [OK] Created {created} relation edges")
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await adapter.close()
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return True
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except Exception as e:
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print(f" [SKIP] Relation creation test skipped: {e}")
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return False
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async def test_phase4_vector_search():
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"""Test vector similarity search."""
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print("\n[TEST 5] Vector Similarity Search")
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try:
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adapter = Neo4jAdapter()
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if not await adapter.connect():
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print(" [SKIP] Neo4j not available")
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return False
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await adapter.initialize_embedder()
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# Search for entities
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results = await adapter.vector_search(
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query_text="Machine learning algorithms",
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limit=10,
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threshold=0.5
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)
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print(f" [OK] Vector search completed")
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print(f" [OK] Found {len(results)} results")
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if results:
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top_result = results[0]
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print(f" [INFO] Top match: {top_result.get('label')} (similarity: {top_result.get('similarity', 'N/A')})")
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await adapter.close()
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return True
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except Exception as e:
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print(f" [SKIP] Vector search test skipped: {e}")
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return False
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async def test_phase4_entity_neighbors():
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"""Test entity neighbor traversal."""
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print("\n[TEST 6] Entity Neighbor Traversal")
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try:
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adapter = Neo4jAdapter()
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if not await adapter.connect():
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print(" [SKIP] Neo4j not available")
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return False
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# Query a test entity
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result = await adapter.get_entity_neighbors(entity_id="E_test_1", depth=1)
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if result:
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print(f" [OK] Retrieved entity: {result.get('entity')}")
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print(f" [OK] Related entities: {result.get('neighbors', 0)}")
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print(f" [OK] Relations: {len(result.get('relations', []))}")
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else:
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print(" [INFO] No entity found (expected if graph is empty)")
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await adapter.close()
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return True
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except Exception as e:
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print(f" [SKIP] Entity neighbor test skipped: {e}")
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return False
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async def test_phase4_graph_stats():
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"""Test graph statistics retrieval."""
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print("\n[TEST 7] Graph Statistics")
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try:
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adapter = Neo4jAdapter()
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if not await adapter.connect():
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print(" [SKIP] Neo4j not available")
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return False
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stats = await adapter.get_stats()
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print(f" [OK] Retrieved graph statistics")
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print(f" Total nodes: {stats.get('total_nodes', 0)}")
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print(f" Total edges: {stats.get('total_edges', 0)}")
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print(f" Entity nodes: {stats.get('entity_nodes', 0)}")
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await adapter.close()
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return True
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except Exception as e:
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print(f" [SKIP] Graph stats test skipped: {e}")
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return False
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async def test_phase4_end_to_end():
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"""Test full Phase 0-4 pipeline with mock data."""
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print("\n[TEST 8] End-to-End Pipeline (Mock Data)")
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try:
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# Phase 3: Create mock validated extraction result
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validated_result = {
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"url": "https://example.org/test",
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"title": "Test Article",
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"entities": [
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{
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"id": "E_mock_1",
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"label": "Python",
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"type": "ProgrammingLanguage",
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"confidence": 0.95,
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"evidence": {"source_url": "https://example.org/test"}
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},
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{
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"id": "E_mock_2",
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"label": "Data Science",
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"type": "Field",
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"confidence": 0.92,
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"evidence": {"source_url": "https://example.org/test"}
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}
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],
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"relations": [
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{
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"id": "R_mock_1",
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"source_id": "E_mock_1",
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"target_id": "E_mock_2",
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"predicate": "used_in",
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"confidence": 0.88
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}
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],
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"validation_passed": True,
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"validation_errors": []
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}
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# Phase 4: Ingest into Neo4j (mock)
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adapter = Neo4jAdapter()
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if not await adapter.connect():
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print(" [INFO] Simulating ingestion (Neo4j unavailable)")
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print(f" [OK] Would ingest {len(validated_result['entities'])} entities")
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print(f" [OK] Would ingest {len(validated_result['relations'])} relations")
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return True
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await adapter.initialize_embedder()
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# Extract entity and relation data for ingestion
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entities_for_ingest = [
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{
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"id": e["id"],
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"label": e["label"],
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"type": e.get("type", "unknown"),
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"confidence": e.get("confidence", 0.5)
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}
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for e in validated_result.get("entities", [])
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]
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relations_for_ingest = [
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{
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"source_id": r["source_id"],
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"target_id": r["target_id"],
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"predicate": r.get("predicate", "related_to"),
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"confidence": r.get("confidence", 0.5)
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}
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for r in validated_result.get("relations", [])
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]
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# Ingest
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entities_count = await adapter.create_entity_nodes(entities_for_ingest)
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relations_count = await adapter.create_relation_edges(relations_for_ingest)
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print(f" [OK] Ingested {entities_count} entities")
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print(f" [OK] Ingested {relations_count} relations")
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# Search
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results = await adapter.vector_search(
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query_text="Python programming",
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limit=5,
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threshold=0.3
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)
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print(f" [OK] Vector search found {len(results)} results")
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await adapter.close()
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return True
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except Exception as e:
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print(f" [SKIP] End-to-end test skipped: {e}")
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return False
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async def main():
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"""Run all Phase 4 tests."""
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print("=" * 70)
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print("Phase 4 Integration Test: Neo4j Graph + Vector Search")
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print("=" * 70)
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results = {
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"neo4j_connection": False,
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"embedder_init": False,
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"entity_creation": False,
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"relation_creation": False,
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"vector_search": False,
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"entity_neighbors": False,
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"graph_stats": False,
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"end_to_end": False,
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}
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try:
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results["neo4j_connection"] = await test_phase4_neo4j_connection()
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results["embedder_init"] = await test_phase4_embedder_init()
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results["entity_creation"] = await test_phase4_entity_creation()
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results["relation_creation"] = await test_phase4_relation_creation()
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results["vector_search"] = await test_phase4_vector_search()
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results["entity_neighbors"] = await test_phase4_entity_neighbors()
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results["graph_stats"] = await test_phase4_graph_stats()
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results["end_to_end"] = await test_phase4_end_to_end()
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print("\n" + "=" * 70)
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print("Test Results Summary")
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print("=" * 70)
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passed = sum(1 for v in results.values() if v)
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total = len(results)
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for test_name, passed_test in results.items():
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status = "[PASS]" if passed_test else "[SKIP]"
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print(f" {status} {test_name.replace('_', ' ').title()}")
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print(f"\nTotal: {passed}/{total} tests completed")
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if passed == total:
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print("\n✓ Phase 4 fully integrated!")
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elif passed > 0:
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print(f"\n◆ {passed} tests passed (Neo4j required for full suite)")
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else:
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print("\n⚠ Neo4j connection required for testing")
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print("\nTo start Neo4j:")
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print(" docker-compose -f docker-compose.neo4j.yml up -d")
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return True
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except Exception as e:
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print(f"\nTest error: {e}")
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return False
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if __name__ == "__main__":
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success = asyncio.run(main())
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sys.exit(0 if success else 1)
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