vectordb-genai-101/chat-app-code/backend/services/inference_service.py [5:19]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(module)s:%(lineno)d - %(message)s',
    datefmt='%Y-%m-%d %H:%M:%S'
)


# TODO move this to central location so this and search_service don't create separate connections
# Initialize the Elasticsearch client
es_client = Elasticsearch(
    hosts=os.getenv('ES_URL', 'http://kubernetes-vm:9200'),
    # api_key=os.getenv('ES_API_KEY'),
    basic_auth=(
        os.getenv('ES_USER', 'elastic'),
        os.getenv('ES_PASSWORD', 'changeme')
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



vectordb-genai-101/chat-app-code/backend/services/search_service.py [6:18]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(module)s:%(lineno)d - %(message)s',
    datefmt='%Y-%m-%d %H:%M:%S'
)

# Initialize the Elasticsearch client
es_client = Elasticsearch(
    hosts=os.getenv('ES_URL', 'http://kubernetes-vm:9200'),
    # api_key=os.getenv('ES_API_KEY')
    basic_auth=(
        os.getenv('ES_USER', 'elastic'),
        os.getenv('ES_PASSWORD', 'changeme')
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -