feat: add Docker Compose configuration for MongoDB, Redis, FastAPI, Chat, Worker, Flower, and Frontend services; include health checks and volume management

deploy/docker/compose.yml

@@ -2,8 +2,9 @@ services:
   # MongoDB Database
   mongodb:
     image: docker.io/library/mongo:7-jammy
-    container_name: datacenter-docs-mongodb-dev
+    container_name: datacenter-docs-mongodb
     hostname: mongodb
+    restart: always
     ports:
       - "${MONGODB_PORT}:27017"
     env_file:
@@ -26,8 +27,9 @@ services:
   # Redis Cache & Message Broker
   redis:
     image: docker.io/library/redis:7-alpine
-    container_name: datacenter-docs-redis-dev
+    container_name: datacenter-docs-redis
     hostname: redis
+    restart: always
     ports:
       - "${REDIS_PORT}:6379"
     env_file:
@@ -48,8 +50,9 @@ services:
     build:
       context: ../..
       dockerfile: deploy/docker/Dockerfile.api
-    container_name: datacenter-docs-api-dev
+    container_name: datacenter-docs-api
     hostname: api
+    restart: always
     ports:
       - "${API_PORT}:8000"
     env_file:
@@ -67,15 +70,15 @@ services:
         condition: service_healthy
     networks:
       - datacenter-network
-    restart: unless-stopped
 
   # Chat Service
   chat:
     build:
       context: ../..
       dockerfile: deploy/docker/Dockerfile.chat
-    container_name: datacenter-docs-chat-dev
+    container_name: datacenter-docs-chat
     hostname: chat
+    restart: always
     ports:
       - "${CHAT_PORT}:8001"
     env_file:
@@ -94,15 +97,15 @@ services:
         condition: service_healthy
     networks:
       - datacenter-network
-    restart: unless-stopped
 
   # Celery Worker
   worker:
     build:
       context: ../..
       dockerfile: deploy/docker/Dockerfile.worker
-    container_name: datacenter-docs-worker-dev
+    container_name: datacenter-docs-worker
     hostname: worker
+    restart: always
     env_file:
       - ../../.env
     volumes:
@@ -118,13 +121,19 @@ services:
         condition: service_healthy
     networks:
       - datacenter-network
-    restart: unless-stopped
+    healthcheck:
+      test: ["CMD-SHELL", "celery -A datacenter_docs.workers.celery_app inspect ping -d celery@worker || exit 1"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 40s
 
   # Flower - Celery Monitoring
   flower:
     image: docker.io/mher/flower:2.0
-    container_name: datacenter-docs-flower-dev
+    container_name: datacenter-docs-flower
     hostname: flower
+    restart: always
     ports:
       - "${FLOWER_PORT}:5555"
     env_file:
@@ -136,15 +145,15 @@ services:
         condition: service_healthy
     networks:
       - datacenter-network
-    restart: unless-stopped
 
   # Frontend
   frontend:
     build:
       context: ../..
       dockerfile: deploy/docker/Dockerfile.frontend
-    container_name: datacenter-docs-frontend-dev
+    container_name: datacenter-docs-frontend
     hostname: frontend
+    restart: always
     ports:
       - "${FRONTEND_PORT}:80"
     env_file:
@@ -154,27 +163,26 @@ services:
       - chat
     networks:
       - datacenter-network
-    restart: unless-stopped
 
 volumes:
   mongodb-data:
-    name: datacenter-docs-mongodb-data-dev
+    name: datacenter-docs-mongodb-data
   mongodb-config:
-    name: datacenter-docs-mongodb-config-dev
+    name: datacenter-docs-mongodb-config
   redis-data:
-    name: datacenter-docs-redis-data-dev
+    name: datacenter-docs-redis-data
   api-logs:
-    name: datacenter-docs-api-logs-dev
+    name: datacenter-docs-api-logs
   chat-logs:
-    name: datacenter-docs-chat-logs-dev
+    name: datacenter-docs-chat-logs
   chat-data:
-    name: datacenter-docs-chat-data-dev
+    name: datacenter-docs-chat-data
   worker-logs:
-    name: datacenter-docs-worker-logs-dev
+    name: datacenter-docs-worker-logs
   worker-output:
-    name: datacenter-docs-worker-output-dev
+    name: datacenter-docs-worker-output
 
 networks:
   datacenter-network:
-    name: datacenter-docs-network-dev
+    name: datacenter-docs-network
     driver: bridge

scripts/test_chat_rag.py

@@ -0,0 +1,59 @@
+#!/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())

src/datacenter_docs/chat/agent.py

@@ -177,16 +177,21 @@ class DocumentationAgent:
             # Format results
             formatted_results = []
             for doc, score in results:
+                # ChromaDB returns distance scores (lower is better)
+                # Normalize to similarity score (0-1, higher is better)
+                # Using 1/(1+distance) ensures values are always between 0 and 1
+                relevance_score = 1.0 / (1.0 + score)
+
                 formatted_results.append(
                     {
                         "content": doc.page_content,
                         "section": doc.metadata.get("section", "unknown"),
                         "source": doc.metadata.get("source", ""),
-                        "relevance_score": float(1 - score),  # Convert distance to similarity
+                        "relevance_score": float(relevance_score),
                         "last_updated": doc.metadata.get("indexed_at", ""),
                     }
                 )
-                logger.info(f"  ✓ Section: {doc.metadata.get('section')} (relevance: {(1-score)*100:.1f}%)")
+                logger.info(f"  ✓ Section: {doc.metadata.get('section')} (relevance: {relevance_score*100:.1f}%, distance: {score:.3f})")
 
             return formatted_results