feat: enhance chat service with documentation indexing and improved Docker configuration

scripts/index_docs.py

@@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""
+Script to index documentation into ChromaDB vector store.
+This script should be run once to initialize the documentation search capability.
+"""
+
+import asyncio
+import logging
+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
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+)
+logger = logging.getLogger(__name__)
+
+
+async def main() -> None:
+    """Index all documentation files into vector store."""
+
+    # Paths
+    docs_path = Path("/app/output")  # In Docker container
+    if not docs_path.exists():
+        # Fallback to local path
+        docs_path = Path(__file__).parent.parent / "output"
+
+    vector_store_path = Path("/app/data/chroma_db")  # In Docker container
+    if not vector_store_path.parent.exists():
+        # Fallback to local path
+        vector_store_path = Path(__file__).parent.parent / "data" / "chroma_db"
+
+    logger.info(f"Indexing documentation from: {docs_path}")
+    logger.info(f"Vector store location: {vector_store_path}")
+
+    # Check if docs exist
+    md_files = list(docs_path.glob("**/*.md"))
+    if not md_files:
+        logger.warning(f"No markdown files found in {docs_path}")
+        logger.info("Creating sample documentation...")
+        # Could optionally create sample docs here
+        return
+
+    logger.info(f"Found {len(md_files)} markdown files to index")
+
+    try:
+        # Initialize agent (without MCP client for indexing only)
+        logger.info("Initializing Documentation Agent...")
+        agent = DocumentationAgent(
+            mcp_client=None,
+            llm_client=None,
+            vector_store_path=str(vector_store_path)
+        )
+
+        # Index documentation
+        logger.info("Starting indexing process...")
+        await agent.index_documentation(docs_path)
+
+        logger.info("✓ Documentation indexed successfully!")
+        logger.info(f"Vector store saved to: {vector_store_path}")
+
+        # Test search
+        logger.info("\nTesting search functionality...")
+        test_queries = [
+            "How to troubleshoot VLAN connectivity?",
+            "What are the backup schedules?",
+            "How to check UPS status?"
+        ]
+
+        for query in test_queries:
+            results = await agent.search_documentation(query, limit=2)
+            logger.info(f"\nQuery: {query}")
+            logger.info(f"Found {len(results)} results:")
+            for i, result in enumerate(results, 1):
+                logger.info(f"  {i}. {result['section']} (score: {result['relevance_score']:.2f})")
+
+        logger.info("\n✓ Indexing and testing complete!")
+
+    except Exception as e:
+        logger.error(f"Failed to index documentation: {e}", exc_info=True)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())