#!/usr/bin/env python3 """ Test script for LLM integration with existing RAG system Run this to test the LLM components step by step """ import os import sys import logging from pathlib import Path # Add project root to path project_root = Path(__file__).parent.parent sys.path.insert(0, str(project_root)) # Configure logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' ) logger = logging.getLogger(__name__) def test_step_1_imports(): """Test 1: Check if all imports work""" print("๐Ÿงช Step 1: Testing imports...") try: # Test RAG system import from src.generators.rag_system import CVERAGSystem print("โœ… RAG System import successful") # Test LLM client import from src.generation.llm_client import LLMClient, TechnologyDetector, EnhancedQueryProcessor print("โœ… LLM Client imports successful") return True except ImportError as e: print(f"โŒ Import failed: {e}") print("๐Ÿ’ก Make sure you saved the llm_client.py file in src/generation/") return False def test_step_2_rag_system(): """Test 2: Check if RAG system works""" print("\n๐Ÿงช Step 2: Testing RAG System...") try: from src.generators.rag_system import CVERAGSystem # Initialize RAG system rag_system = CVERAGSystem() print("โœ… RAG System initialized") # Test basic search results = rag_system.search_cves("SQL injection", n_results=3) print(f"โœ… Basic search works: Found {len(results)} results") if results: sample = results[0] print(f" Sample result: {sample['metadata'].get('cve_id', 'Unknown')} - Score: {sample['score']:.3f}") return rag_system except Exception as e: print(f"โŒ RAG System test failed: {e}") return None def test_step_3_technology_detection(): """Test 3: Check technology detection""" print("\n๐Ÿงช Step 3: Testing Technology Detection...") try: from src.generation.llm_client import TechnologyDetector test_queries = [ "log4j vulnerabilities", "apache web server RCE", "SQL injection in MySQL", "Java deserialization attacks" ] for query in test_queries: analysis = TechnologyDetector.detect_technologies(query) print(f"โœ… Query: '{query}'") print(f" Technologies: {analysis['technologies']}") print(f" Critical years: {analysis['critical_years']}") print(f" Priority: {analysis['priority_level']}") return True except Exception as e: print(f"โŒ Technology detection failed: {e}") return False def test_step_4_llm_client(): """Test 4: Check LLM client (without requiring Ollama)""" print("\n๐Ÿงช Step 4: Testing LLM Client...") try: from src.generation.llm_client import LLMClient # Initialize LLM client (should work even without Ollama) llm_client = LLMClient() print(f"โœ… LLM Client initialized (Available: {llm_client.available})") if llm_client.available: print("๐ŸŽ‰ Ollama service detected and working!") else: print("โš ๏ธ Ollama not available - will use fallback mode") # Test query expansion (works without LLM) test_query = "SQL injection vulnerabilities" expanded = llm_client.expand_query(test_query) print(f"โœ… Query expansion works: {len(expanded)} variations") for i, exp in enumerate(expanded[:3], 1): print(f" {i}. {exp}") # Test fallback response generation mock_context = [ { 'metadata': {'cve_id': 'CVE-2021-34527', 'severity': 'Critical'}, 'text': 'Windows Print Spooler Remote Code Execution Vulnerability', 'score': 0.95 } ] response = llm_client._generate_fallback_response("windows print spooler", mock_context) print("โœ… Fallback response generation works:") print(f" {response[:100]}...") return llm_client except Exception as e: print(f"โŒ LLM Client test failed: {e}") import traceback traceback.print_exc() return None def test_step_5_integration(): """Test 5: Full integration test""" print("\n๐Ÿงช Step 5: Testing Full Integration...") try: from src.generators.rag_system import CVERAGSystem from src.generation.llm_client import LLMClient, EnhancedQueryProcessor # Initialize components rag_system = CVERAGSystem() llm_client = LLMClient() processor = EnhancedQueryProcessor(rag_system, llm_client) print("โœ… All components initialized") # Test enhanced query processing test_queries = [ "log4j vulnerability", "CVE-2021-44228", "apache remote code execution" ] for query in test_queries: print(f"\n๐Ÿ“ Testing query: '{query}'") try: result = processor.process_query(query, top_k=5, use_llm=True) print(f"โœ… Processing successful") print(f" Results found: {len(result['search_results'])}") print(f" Processing time: {result['metadata'].get('processing_time', 0):.2f}s") print(f" LLM used: {result['metadata'].get('llm_used', False)}") if result.get('llm_response'): print(f" LLM response: {result['llm_response'][:150]}...") # Show top result if result['search_results']: top_result = result['search_results'][0] cve_id = top_result['metadata'].get('cve_id', 'Unknown') score = top_result.get('score', 0) print(f" Top result: {cve_id} (Score: {score:.3f})") except Exception as e: print(f"โŒ Query processing failed: {e}") return True except Exception as e: print(f"โŒ Integration test failed: {e}") import traceback traceback.print_exc() return False def test_step_6_ollama_setup(): """Test 6: Guide for Ollama setup""" print("\n๐Ÿงช Step 6: Ollama Setup Guide...") try: import requests # Test Ollama connection response = requests.get("http://localhost:11434/api/tags", timeout=5) if response.status_code == 200: models = response.json() print("๐ŸŽ‰ Ollama is running!") print(f" Available models: {len(models.get('models', []))}") # Check for Llama 3 llama_models = [m for m in models.get('models', []) if 'llama3' in m.get('name', '')] if llama_models: print(f"โœ… Llama 3 models found: {[m['name'] for m in llama_models]}") return True else: print("โš ๏ธ Llama 3 not found. Run: ollama pull llama3:8b") return False else: print("โŒ Ollama not responding correctly") return False except Exception as e: print("โš ๏ธ Ollama not running or not accessible") print("\n๐Ÿ“‹ To install and run Ollama:") print("1. Install: curl -fsSL https://ollama.com/install.sh | sh") print("2. Start: ollama serve") print("3. Pull model: ollama pull llama3:8b") print("4. Re-run this test") return False def main(): """Run all tests""" print("๐Ÿš€ Testing LLM Integration with RAG System") print("=" * 50) # Create src/generation directory if it doesn't exist generation_dir = Path("src/generation") generation_dir.mkdir(parents=True, exist_ok=True) # Create __init__.py if it doesn't exist init_file = generation_dir / "__init__.py" if not init_file.exists(): init_file.touch() print("๐Ÿ“ Created src/generation directory structure") # Run tests step by step tests = [ test_step_1_imports, test_step_2_rag_system, test_step_3_technology_detection, test_step_4_llm_client, test_step_5_integration, test_step_6_ollama_setup ] results = [] for test_func in tests: try: result = test_func() results.append(result) except Exception as e: print(f"โŒ Test {test_func.__name__} crashed: {e}") results.append(False) import traceback traceback.print_exc() # Summary print("\n" + "=" * 50) print("๐Ÿ“Š Test Results Summary:") test_names = [ "Imports", "RAG System", "Technology Detection", "LLM Client", "Full Integration", "Ollama Setup" ] for i, (name, result) in enumerate(zip(test_names, results)): status = "โœ… PASS" if result else "โŒ FAIL" print(f" {i + 1}. {name}: {status}") passed_tests = sum(1 for r in results if r) total_tests = len(results) print(f"\n๐ŸŽฏ Overall: {passed_tests}/{total_tests} tests passed") if passed_tests >= 4: # Basic functionality works print("\n๐ŸŽ‰ LLM integration is working! You can now:") print(" - Use enhanced query processing") print(" - Get technology-aware search results") print(" - Benefit from query expansion and reranking") if results[5]: # Ollama working print(" - Generate intelligent LLM responses") else: print(" - Install Ollama for full LLM responses") else: print("\nโš ๏ธ Some issues need to be resolved before using LLM integration") if __name__ == "__main__": main()