llm-automation-docs-and-remediation-engine/scripts/test_chat_rag.py

#!/usr/bin/env python3
"""
Test script for RAG system in chat service
"""

import asyncio
import sys
from pathlib import Path

# Add src to path
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))

from datacenter_docs.chat.agent import DocumentationAgent
from datacenter_docs.utils.llm_client import get_llm_client


async def test_rag_search():
    """Test RAG search and retrieval"""
    print("🧪 Testing RAG system...\n")

    # Initialize agent
    print("1️⃣ Initializing DocumentationAgent...")
    agent = DocumentationAgent(vector_store_path="./data/chroma_db")
    print("✅ Agent initialized\n")

    # Test queries
    test_queries = [
        "Come è configurato smarthome-services?",
        "Quali VM sono in esecuzione?",
        "Come faccio il backup dei container?",
        "Configurazione di storage su Proxmox",
    ]

    for i, query in enumerate(test_queries, 1):
        print(f"\n{'='*60}")
        print(f"Query {i}: {query}")
        print('='*60)

        # Search documentation
        results = await agent.search_documentation(query, limit=3)

        if results:
            print(f"\n📚 Found {len(results)} results:\n")
            for j, result in enumerate(results, 1):
                print(f"  {j}. Section: {result['section']}")
                print(f"     Relevance: {result['relevance_score']:.3f} ({result['relevance_score']*100:.1f}%)")
                print(f"     Source: {Path(result['source']).name}")
                print(f"     Content preview: {result['content'][:100]}...")
                print()
        else:
            print("❌ No results found")

    print("\n" + "="*60)
    print("✅ RAG test completed successfully!")
    print("="*60)


if __name__ == "__main__":
    asyncio.run(test_rag_search())