Updated messages to be more readable

src/api/auth.py

@@ -1,5 +1,6 @@
 from starlette.requests import Request
 from starlette.responses import JSONResponse
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 
 async def auth_init(request: Request, auth_service, session_manager):
@@ -40,8 +41,11 @@ async def auth_callback(request: Request, auth_service, session_manager):
             connection_id, authorization_code, state, request
         )
 
+        await TelemetryClient.send_event(Category.AUTHENTICATION, MessageId.ORB_AUTH_OAUTH_CALLBACK)
+
         # If this is app auth, set JWT cookie
         if result.get("purpose") == "app_auth" and result.get("jwt_token"):
+            await TelemetryClient.send_event(Category.AUTHENTICATION, MessageId.ORB_AUTH_SUCCESS)
             response = JSONResponse(
                 {k: v for k, v in result.items() if k != "jwt_token"}
             )
@@ -61,6 +65,7 @@ async def auth_callback(request: Request, auth_service, session_manager):
         import traceback
 
         traceback.print_exc()
+        await TelemetryClient.send_event(Category.AUTHENTICATION, MessageId.ORB_AUTH_OAUTH_FAILED)
         return JSONResponse({"error": f"Callback failed: {str(e)}"}, status_code=500)
 
 
@@ -72,6 +77,7 @@ async def auth_me(request: Request, auth_service, session_manager):
 
 async def auth_logout(request: Request, auth_service, session_manager):
     """Logout user by clearing auth cookie"""
+    await TelemetryClient.send_event(Category.AUTHENTICATION, MessageId.ORB_AUTH_LOGOUT)
     response = JSONResponse(
         {"status": "logged_out", "message": "Successfully logged out"}
     )

src/api/connectors.py

@@ -1,6 +1,7 @@
 from starlette.requests import Request
 from starlette.responses import JSONResponse, PlainTextResponse
 from utils.logging_config import get_logger
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 logger = get_logger(__name__)
 
@@ -25,6 +26,7 @@ async def connector_sync(request: Request, connector_service, session_manager):
     selected_files = data.get("selected_files")
 
     try:
+        await TelemetryClient.send_event(Category.CONNECTOR_OPERATIONS, MessageId.ORB_CONN_SYNC_START)
         logger.debug(
             "Starting connector sync",
             connector_type=connector_type,
@@ -102,6 +104,7 @@ async def connector_sync(request: Request, connector_service, session_manager):
                 jwt_token=jwt_token,
             )
         task_ids = [task_id]
+        await TelemetryClient.send_event(Category.CONNECTOR_OPERATIONS, MessageId.ORB_CONN_SYNC_COMPLETE)
         return JSONResponse(
             {
                 "task_ids": task_ids,
@@ -114,6 +117,7 @@ async def connector_sync(request: Request, connector_service, session_manager):
 
     except Exception as e:
         logger.error("Connector sync failed", error=str(e))
+        await TelemetryClient.send_event(Category.CONNECTOR_OPERATIONS, MessageId.ORB_CONN_SYNC_FAILED)
         return JSONResponse({"error": f"Sync failed: {str(e)}"}, status_code=500)
 
 
@@ -185,6 +189,7 @@ async def connector_webhook(request: Request, connector_service, session_manager
         config=temp_config,
     )
     try:
+        await TelemetryClient.send_event(Category.CONNECTOR_OPERATIONS, MessageId.ORB_CONN_WEBHOOK_RECV)
         temp_connector = connector_service.connection_manager._create_connector(
             temp_connection
         )
@@ -336,6 +341,7 @@ async def connector_webhook(request: Request, connector_service, session_manager
 
     except Exception as e:
         logger.error("Webhook processing failed", error=str(e))
+        await TelemetryClient.send_event(Category.CONNECTOR_OPERATIONS, MessageId.ORB_CONN_WEBHOOK_FAILED)
         return JSONResponse(
             {"error": f"Webhook processing failed: {str(e)}"}, status_code=500
         )

src/api/settings.py

@@ -4,6 +4,7 @@ import time
 from starlette.responses import JSONResponse
 from utils.container_utils import transform_localhost_url
 from utils.logging_config import get_logger
+from utils.telemetry import TelemetryClient, Category, MessageId
 from config.settings import (
     DISABLE_INGEST_WITH_LANGFLOW,
     LANGFLOW_URL,
@@ -409,16 +410,32 @@ async def update_settings(request, session_manager):
 
         # Update agent settings
         if "llm_model" in body:
+            old_model = current_config.agent.llm_model
             current_config.agent.llm_model = body["llm_model"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_LLM_MODEL
+            )
+            logger.info(f"LLM model changed from {old_model} to {body['llm_model']}")
 
         if "llm_provider" in body:
+            old_provider = current_config.agent.llm_provider
             current_config.agent.llm_provider = body["llm_provider"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_LLM_PROVIDER
+            )
+            logger.info(f"LLM provider changed from {old_provider} to {body['llm_provider']}")
 
         if "system_prompt" in body:
             current_config.agent.system_prompt = body["system_prompt"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_SYSTEM_PROMPT
+            )
 
             # Also update the chat flow with the new system prompt
             try:
@@ -431,17 +448,33 @@ async def update_settings(request, session_manager):
 
         # Update knowledge settings
         if "embedding_model" in body:
+            old_model = current_config.knowledge.embedding_model
             new_embedding_model = body["embedding_model"].strip()
             current_config.knowledge.embedding_model = new_embedding_model
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_EMBED_MODEL
+            )
+            logger.info(f"Embedding model changed from {old_model} to {new_embedding_model}")
 
         if "embedding_provider" in body:
+            old_provider = current_config.knowledge.embedding_provider
             current_config.knowledge.embedding_provider = body["embedding_provider"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_EMBED_PROVIDER
+            )
+            logger.info(f"Embedding provider changed from {old_provider} to {body['embedding_provider']}")
 
         if "table_structure" in body:
             current_config.knowledge.table_structure = body["table_structure"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_DOCLING_UPDATED
+            )
 
             # Also update the flow with the new docling settings
             try:
@@ -453,6 +486,10 @@ async def update_settings(request, session_manager):
         if "ocr" in body:
             current_config.knowledge.ocr = body["ocr"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_DOCLING_UPDATED
+            )
 
             # Also update the flow with the new docling settings
             try:
@@ -464,6 +501,10 @@ async def update_settings(request, session_manager):
         if "picture_descriptions" in body:
             current_config.knowledge.picture_descriptions = body["picture_descriptions"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_DOCLING_UPDATED
+            )
 
             # Also update the flow with the new docling settings
             try:
@@ -475,6 +516,10 @@ async def update_settings(request, session_manager):
         if "chunk_size" in body:
             current_config.knowledge.chunk_size = body["chunk_size"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_CHUNK_UPDATED
+            )
 
             # Also update the ingest flow with the new chunk size
             try:
@@ -491,6 +536,10 @@ async def update_settings(request, session_manager):
         if "chunk_overlap" in body:
             current_config.knowledge.chunk_overlap = body["chunk_overlap"]
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_CHUNK_UPDATED
+            )
 
             # Also update the ingest flow with the new chunk overlap
             try:
@@ -507,35 +556,48 @@ async def update_settings(request, session_manager):
                 # The config will still be saved
 
         # Update provider-specific settings
+        provider_updated = False
         if "openai_api_key" in body and body["openai_api_key"].strip():
             current_config.providers.openai.api_key = body["openai_api_key"]
             current_config.providers.openai.configured = True
             config_updated = True
+            provider_updated = True
 
         if "anthropic_api_key" in body and body["anthropic_api_key"].strip():
             current_config.providers.anthropic.api_key = body["anthropic_api_key"]
             current_config.providers.anthropic.configured = True
             config_updated = True
+            provider_updated = True
 
         if "watsonx_api_key" in body and body["watsonx_api_key"].strip():
             current_config.providers.watsonx.api_key = body["watsonx_api_key"]
             current_config.providers.watsonx.configured = True
             config_updated = True
+            provider_updated = True
 
         if "watsonx_endpoint" in body:
             current_config.providers.watsonx.endpoint = body["watsonx_endpoint"].strip()
             current_config.providers.watsonx.configured = True
             config_updated = True
+            provider_updated = True
 
         if "watsonx_project_id" in body:
             current_config.providers.watsonx.project_id = body["watsonx_project_id"].strip()
             current_config.providers.watsonx.configured = True
             config_updated = True
+            provider_updated = True
 
         if "ollama_endpoint" in body:
             current_config.providers.ollama.endpoint = body["ollama_endpoint"].strip()
             current_config.providers.ollama.configured = True
             config_updated = True
+            provider_updated = True
+        
+        if provider_updated:
+            await TelemetryClient.send_event(
+                Category.SETTINGS_OPERATIONS, 
+                MessageId.ORB_SETTINGS_PROVIDER_CREDS
+            )
 
         if not config_updated:
             return JSONResponse(
@@ -577,10 +639,18 @@ async def update_settings(request, session_manager):
         logger.info(
             "Configuration updated successfully", updated_fields=list(body.keys())
         )
+        await TelemetryClient.send_event(
+            Category.SETTINGS_OPERATIONS, 
+            MessageId.ORB_SETTINGS_UPDATED
+        )
         return JSONResponse({"message": "Configuration updated successfully"})
 
     except Exception as e:
         logger.error("Failed to update settings", error=str(e))
+        await TelemetryClient.send_event(
+            Category.SETTINGS_OPERATIONS, 
+            MessageId.ORB_SETTINGS_UPDATE_FAILED
+        )
         return JSONResponse(
             {"error": f"Failed to update settings: {str(e)}"}, status_code=500
         )
@@ -589,6 +659,8 @@ async def update_settings(request, session_manager):
 async def onboarding(request, flows_service, session_manager=None):
     """Handle onboarding configuration setup"""
     try:
+        await TelemetryClient.send_event(Category.ONBOARDING, MessageId.ORB_ONBOARD_START)
+        
         # Get current configuration
         current_config = get_openrag_config()
 
@@ -631,13 +703,23 @@ async def onboarding(request, flows_service, session_manager=None):
         config_updated = False
 
         # Update agent settings (LLM)
+        llm_model_selected = None
+        llm_provider_selected = None
+        
         if "llm_model" in body:
             if not isinstance(body["llm_model"], str) or not body["llm_model"].strip():
                 return JSONResponse(
                     {"error": "llm_model must be a non-empty string"}, status_code=400
                 )
-            current_config.agent.llm_model = body["llm_model"].strip()
+            llm_model_selected = body["llm_model"].strip()
+            current_config.agent.llm_model = llm_model_selected
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_LLM_MODEL,
+                metadata={"llm_model": llm_model_selected}
+            )
+            logger.info(f"LLM model selected during onboarding: {llm_model_selected}")
 
         if "llm_provider" in body:
             if (
@@ -653,10 +735,20 @@ async def onboarding(request, flows_service, session_manager=None):
                     {"error": "llm_provider must be one of: openai, anthropic, watsonx, ollama"},
                     status_code=400,
                 )
-            current_config.agent.llm_provider = body["llm_provider"].strip()
+            llm_provider_selected = body["llm_provider"].strip()
+            current_config.agent.llm_provider = llm_provider_selected
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_LLM_PROVIDER,
+                metadata={"llm_provider": llm_provider_selected}
+            )
+            logger.info(f"LLM provider selected during onboarding: {llm_provider_selected}")
 
         # Update knowledge settings (embedding)
+        embedding_model_selected = None
+        embedding_provider_selected = None
+        
         if "embedding_model" in body and not DISABLE_INGEST_WITH_LANGFLOW:
             if (
                 not isinstance(body["embedding_model"], str)
@@ -666,8 +758,15 @@ async def onboarding(request, flows_service, session_manager=None):
                     {"error": "embedding_model must be a non-empty string"},
                     status_code=400,
                 )
-            current_config.knowledge.embedding_model = body["embedding_model"].strip()
+            embedding_model_selected = body["embedding_model"].strip()
+            current_config.knowledge.embedding_model = embedding_model_selected
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_EMBED_MODEL,
+                metadata={"embedding_model": embedding_model_selected}
+            )
+            logger.info(f"Embedding model selected during onboarding: {embedding_model_selected}")
 
         if "embedding_provider" in body:
             if (
@@ -684,8 +783,15 @@ async def onboarding(request, flows_service, session_manager=None):
                     {"error": "embedding_provider must be one of: openai, watsonx, ollama"},
                     status_code=400,
                 )
-            current_config.knowledge.embedding_provider = body["embedding_provider"].strip()
+            embedding_provider_selected = body["embedding_provider"].strip()
+            current_config.knowledge.embedding_provider = embedding_provider_selected
             config_updated = True
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_EMBED_PROVIDER,
+                metadata={"embedding_provider": embedding_provider_selected}
+            )
+            logger.info(f"Embedding provider selected during onboarding: {embedding_provider_selected}")
 
         # Update provider-specific credentials
         if "openai_api_key" in body and body["openai_api_key"].strip():
@@ -771,6 +877,12 @@ async def onboarding(request, flows_service, session_manager=None):
                     {"error": "sample_data must be a boolean value"}, status_code=400
                 )
             should_ingest_sample_data = body["sample_data"]
+            if should_ingest_sample_data:
+                await TelemetryClient.send_event(
+                    Category.ONBOARDING, 
+                    MessageId.ORB_ONBOARD_SAMPLE_DATA
+                )
+                logger.info("Sample data ingestion requested during onboarding")
 
         if not config_updated:
             return JSONResponse(
@@ -913,8 +1025,38 @@ async def onboarding(request, flows_service, session_manager=None):
                 "Onboarding configuration updated successfully",
                 updated_fields=updated_fields,
             )
+            
+            # Mark config as edited and send telemetry with model information
+            current_config.edited = True
+            
+            # Build metadata with selected models
+            onboarding_metadata = {}
+            if llm_provider_selected:
+                onboarding_metadata["llm_provider"] = llm_provider_selected
+            if llm_model_selected:
+                onboarding_metadata["llm_model"] = llm_model_selected
+            if embedding_provider_selected:
+                onboarding_metadata["embedding_provider"] = embedding_provider_selected
+            if embedding_model_selected:
+                onboarding_metadata["embedding_model"] = embedding_model_selected
+            
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_CONFIG_EDITED,
+                metadata=onboarding_metadata
+            )
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_COMPLETE,
+                metadata=onboarding_metadata
+            )
+            logger.info("Configuration marked as edited after onboarding")
 
         else:
+            await TelemetryClient.send_event(
+                Category.ONBOARDING, 
+                MessageId.ORB_ONBOARD_FAILED
+            )
             return JSONResponse(
                 {"error": "Failed to save configuration"}, status_code=500
             )
@@ -929,6 +1071,10 @@ async def onboarding(request, flows_service, session_manager=None):
 
     except Exception as e:
         logger.error("Failed to update onboarding settings", error=str(e))
+        await TelemetryClient.send_event(
+            Category.ONBOARDING, 
+            MessageId.ORB_ONBOARD_FAILED
+        )
         return JSONResponse(
             {"error": str(e)},
             status_code=500,
@@ -1214,11 +1360,11 @@ async def update_docling_preset(request, session_manager):
         flows_service = _get_flows_service()
         await flows_service.update_flow_docling_preset("custom", preset_config)
 
-        logger.info(f"Successfully updated docling settings in ingest flow")
+        logger.info("Successfully updated docling settings in ingest flow")
 
         return JSONResponse(
             {
-                "message": f"Successfully updated docling settings",
+                "message": "Successfully updated docling settings",
                 "settings": settings,
                 "preset_config": preset_config,
             }

src/api/tasks.py

@@ -1,5 +1,6 @@
 from starlette.requests import Request
 from starlette.responses import JSONResponse
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 
 async def task_status(request: Request, task_service, session_manager):
@@ -28,8 +29,10 @@ async def cancel_task(request: Request, task_service, session_manager):
 
     success = await task_service.cancel_task(user.user_id, task_id)
     if not success:
+        await TelemetryClient.send_event(Category.TASK_OPERATIONS, MessageId.ORB_TASK_CANCEL_FAILED)
         return JSONResponse(
             {"error": "Task not found or cannot be cancelled"}, status_code=400
         )
 
+    await TelemetryClient.send_event(Category.TASK_OPERATIONS, MessageId.ORB_TASK_CANCELLED)
     return JSONResponse({"status": "cancelled", "task_id": task_id})

src/main.py

@@ -5,6 +5,7 @@ from services.flows_service import FlowsService
 from utils.container_utils import detect_container_environment
 from utils.embeddings import create_dynamic_index_body
 from utils.logging_config import configure_from_env, get_logger
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 configure_from_env()
 logger = get_logger(__name__)
@@ -100,6 +101,7 @@ async def wait_for_opensearch():
         try:
             await clients.opensearch.info()
             logger.info("OpenSearch is ready")
+            await TelemetryClient.send_event(Category.OPENSEARCH_SETUP, MessageId.ORB_OS_CONN_ESTABLISHED)
             return
         except Exception as e:
             logger.warning(
@@ -111,6 +113,7 @@ async def wait_for_opensearch():
             if attempt < max_retries - 1:
                 await asyncio.sleep(retry_delay)
             else:
+                await TelemetryClient.send_event(Category.OPENSEARCH_SETUP, MessageId.ORB_OS_TIMEOUT)
                 raise Exception("OpenSearch failed to become ready")
 
 
@@ -154,6 +157,7 @@ async def _ensure_opensearch_index():
                 "dimension"
             ],
         )
+        await TelemetryClient.send_event(Category.OPENSEARCH_INDEX, MessageId.ORB_OS_INDEX_CREATED)
 
     except Exception as e:
         logger.error(
@@ -161,6 +165,7 @@ async def _ensure_opensearch_index():
             error=str(e),
             index_name=INDEX_NAME,
         )
+        await TelemetryClient.send_event(Category.OPENSEARCH_INDEX, MessageId.ORB_OS_INDEX_CREATE_FAIL)
         # Don't raise the exception to avoid breaking the initialization
         # The service can still function, document operations might fail later
 
@@ -193,12 +198,14 @@ async def init_index():
             index_name=INDEX_NAME,
             embedding_model=embedding_model,
         )
+        await TelemetryClient.send_event(Category.OPENSEARCH_INDEX, MessageId.ORB_OS_INDEX_CREATED)
     else:
         logger.info(
             "Index already exists, skipping creation",
             index_name=INDEX_NAME,
             embedding_model=embedding_model,
         )
+        await TelemetryClient.send_event(Category.OPENSEARCH_INDEX, MessageId.ORB_OS_INDEX_EXISTS)
 
     # Create knowledge filters index
     knowledge_filter_index_name = "knowledge_filters"
@@ -226,6 +233,7 @@ async def init_index():
         logger.info(
             "Created knowledge filters index", index_name=knowledge_filter_index_name
         )
+        await TelemetryClient.send_event(Category.OPENSEARCH_INDEX, MessageId.ORB_OS_KF_INDEX_CREATED)
     else:
         logger.info(
             "Knowledge filters index already exists, skipping creation",
@@ -279,6 +287,7 @@ def generate_jwt_keys():
             logger.info("Generated RSA keys for JWT signing")
         except subprocess.CalledProcessError as e:
             logger.error("Failed to generate RSA keys", error=str(e))
+            TelemetryClient.send_event_sync(Category.SERVICE_INITIALIZATION, MessageId.ORB_SVC_JWT_KEY_FAIL)
             raise
     else:
         # Ensure correct permissions on existing keys
@@ -297,6 +306,7 @@ async def init_index_when_ready():
         logger.info("OpenSearch index initialization completed successfully")
     except Exception as e:
         logger.error("OpenSearch index initialization failed", error=str(e))
+        await TelemetryClient.send_event(Category.OPENSEARCH_INDEX, MessageId.ORB_OS_INDEX_INIT_FAIL)
         logger.warning(
             "OIDC endpoints will still work, but document operations may fail until OpenSearch is ready"
         )
@@ -324,6 +334,7 @@ async def ingest_default_documents_when_ready(services):
             "Ingesting default documents when ready",
             disable_langflow_ingest=DISABLE_INGEST_WITH_LANGFLOW,
         )
+        await TelemetryClient.send_event(Category.DOCUMENT_INGESTION, MessageId.ORB_DOC_DEFAULT_START)
         base_dir = _get_documents_dir()
         if not os.path.isdir(base_dir):
             logger.info(
@@ -350,9 +361,12 @@ async def ingest_default_documents_when_ready(services):
             await _ingest_default_documents_openrag(services, file_paths)
         else:
             await _ingest_default_documents_langflow(services, file_paths)
+        
+        await TelemetryClient.send_event(Category.DOCUMENT_INGESTION, MessageId.ORB_DOC_DEFAULT_COMPLETE)
 
     except Exception as e:
         logger.error("Default documents ingestion failed", error=str(e))
+        await TelemetryClient.send_event(Category.DOCUMENT_INGESTION, MessageId.ORB_DOC_DEFAULT_FAILED)
 
 
 async def _ingest_default_documents_langflow(services, file_paths):
@@ -502,6 +516,7 @@ async def _update_mcp_servers_with_provider_credentials(services):
 async def startup_tasks(services):
     """Startup tasks"""
     logger.info("Starting startup tasks")
+    await TelemetryClient.send_event(Category.APPLICATION_STARTUP, MessageId.ORB_APP_START_INIT)
     # Only initialize basic OpenSearch connection, not the index
     # Index will be created after onboarding when we know the embedding model
     await wait_for_opensearch()
@@ -527,25 +542,34 @@ async def startup_tasks(services):
                 logger.info(
                     f"Detected reset flows: {', '.join(reset_flows)}. Reapplying all settings."
                 )
+                await TelemetryClient.send_event(Category.FLOW_OPERATIONS, MessageId.ORB_FLOW_RESET_DETECTED)
                 from api.settings import reapply_all_settings
                 await reapply_all_settings(session_manager=services["session_manager"])
                 logger.info("Successfully reapplied settings after detecting flow resets")
+                await TelemetryClient.send_event(Category.FLOW_OPERATIONS, MessageId.ORB_FLOW_SETTINGS_REAPPLIED)
             else:
                 logger.info("No flows detected as reset, skipping settings reapplication")
         else:
             logger.debug("Configuration not yet edited, skipping flow reset check")
     except Exception as e:
         logger.error(f"Failed to check flows reset or reapply settings: {str(e)}")
+        await TelemetryClient.send_event(Category.FLOW_OPERATIONS, MessageId.ORB_FLOW_RESET_CHECK_FAIL)
         # Don't fail startup if this check fails
 
 
 async def initialize_services():
     """Initialize all services and their dependencies"""
+    await TelemetryClient.send_event(Category.SERVICE_INITIALIZATION, MessageId.ORB_SVC_INIT_START)
     # Generate JWT keys if they don't exist
     generate_jwt_keys()
 
     # Initialize clients (now async to generate Langflow API key)
-    await clients.initialize()
+    try:
+        await clients.initialize()
+    except Exception as e:
+        logger.error("Failed to initialize clients", error=str(e))
+        await TelemetryClient.send_event(Category.SERVICE_INITIALIZATION, MessageId.ORB_SVC_OS_CLIENT_FAIL)
+        raise
 
     # Initialize session manager
     session_manager = SessionManager(SESSION_SECRET)
@@ -608,8 +632,11 @@ async def initialize_services():
             logger.warning(
                 "Failed to load persisted connections on startup", error=str(e)
             )
+            await TelemetryClient.send_event(Category.CONNECTOR_OPERATIONS, MessageId.ORB_CONN_LOAD_FAILED)
     else:
         logger.info("[CONNECTORS] Skipping connection loading in no-auth mode")
+    
+    await TelemetryClient.send_event(Category.SERVICE_INITIALIZATION, MessageId.ORB_SVC_INIT_SUCCESS)
 
     langflow_file_service = LangflowFileService()
 
@@ -1223,6 +1250,7 @@ async def create_app():
     # Add startup event handler
     @app.on_event("startup")
     async def startup_event():
+        await TelemetryClient.send_event(Category.APPLICATION_STARTUP, MessageId.ORB_APP_STARTED)
         # Start index initialization in background to avoid blocking OIDC endpoints
         t1 = asyncio.create_task(startup_tasks(services))
         app.state.background_tasks.add(t1)
@@ -1270,9 +1298,13 @@ async def create_app():
     # Add shutdown event handler
     @app.on_event("shutdown")
     async def shutdown_event():
+        await TelemetryClient.send_event(Category.APPLICATION_SHUTDOWN, MessageId.ORB_APP_SHUTDOWN)
         await cleanup_subscriptions_proper(services)
         # Cleanup async clients
         await clients.cleanup()
+        # Cleanup telemetry client
+        from utils.telemetry.client import cleanup_telemetry_client
+        await cleanup_telemetry_client()
 
     return app
 

src/services/document_service.py

@@ -14,6 +14,7 @@ logger = get_logger(__name__)
 
 from config.settings import clients, INDEX_NAME, get_embedding_model
 from utils.document_processing import extract_relevant, process_document_sync
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 
 def get_token_count(text: str, model: str = None) -> int:
@@ -98,6 +99,7 @@ class DocumentService:
         """Recreate the process pool if it's broken"""
         if self._process_pool_broken and self.process_pool:
             logger.warning("Attempting to recreate broken process pool")
+            TelemetryClient.send_event_sync(Category.DOCUMENT_PROCESSING, MessageId.ORB_DOC_POOL_RECREATE)
             try:
                 # Shutdown the old pool
                 self.process_pool.shutdown(wait=False)

src/services/flows_service.py

@@ -28,6 +28,7 @@ import copy
 from datetime import datetime
 from utils.logging_config import get_logger
 from utils.container_utils import transform_localhost_url
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 logger = get_logger(__name__)
 
@@ -228,6 +229,12 @@ class FlowsService:
             failed_count=len(backup_results["failed"]),
         )
 
+        # Send telemetry event
+        if backup_results["failed"]:
+            await TelemetryClient.send_event(Category.FLOW_OPERATIONS, MessageId.ORB_FLOW_BACKUP_FAILED)
+        else:
+            await TelemetryClient.send_event(Category.FLOW_OPERATIONS, MessageId.ORB_FLOW_BACKUP_COMPLETE)
+
         return backup_results
 
     async def _backup_flow(self, flow_id: str, flow_type: str, flow_data: dict = None):

src/services/task_service.py

@@ -7,6 +7,7 @@ from models.tasks import FileTask, TaskStatus, UploadTask
 from session_manager import AnonymousUser
 from utils.gpu_detection import get_worker_count
 from utils.logging_config import get_logger
+from utils.telemetry import TelemetryClient, Category, MessageId
 
 
 logger = get_logger(__name__)
@@ -131,6 +132,18 @@ class TaskService:
         # Store reference to background task for cancellation
         upload_task.background_task = background_task
 
+        # Send telemetry event for task creation with metadata
+        asyncio.create_task(
+            TelemetryClient.send_event(
+                Category.TASK_OPERATIONS,
+                MessageId.ORB_TASK_CREATED,
+                metadata={
+                    "total_files": len(items),
+                    "processor_type": processor.__class__.__name__,
+                }
+            )
+        )
+
         return task_id
 
     async def background_upload_processor(self, user_id: str, task_id: str) -> None:
@@ -174,6 +187,19 @@ class TaskService:
             if upload_task.processed_files >= upload_task.total_files:
                 upload_task.status = TaskStatus.COMPLETED
                 upload_task.updated_at = time.time()
+                
+                # Send telemetry for task completion
+                asyncio.create_task(
+                    TelemetryClient.send_event(
+                        Category.TASK_OPERATIONS,
+                        MessageId.ORB_TASK_COMPLETE,
+                        metadata={
+                            "total_files": upload_task.total_files,
+                            "successful_files": upload_task.successful_files,
+                            "failed_files": upload_task.failed_files,
+                        }
+                    )
+                )
 
         except Exception as e:
             logger.error(
@@ -183,8 +209,23 @@ class TaskService:
 
             traceback.print_exc()
             if user_id in self.task_store and task_id in self.task_store[user_id]:
-                self.task_store[user_id][task_id].status = TaskStatus.FAILED
+                failed_task = self.task_store[user_id][task_id]
-                self.task_store[user_id][task_id].updated_at = time.time()
+                failed_task.status = TaskStatus.FAILED
+                failed_task.updated_at = time.time()
+                
+                # Send telemetry for task failure
+                asyncio.create_task(
+                    TelemetryClient.send_event(
+                        Category.TASK_OPERATIONS,
+                        MessageId.ORB_TASK_FAILED,
+                        metadata={
+                            "total_files": failed_task.total_files,
+                            "processed_files": failed_task.processed_files,
+                            "successful_files": failed_task.successful_files,
+                            "failed_files": failed_task.failed_files,
+                        }
+                    )
+                )
 
     async def background_custom_processor(
         self, user_id: str, task_id: str, items: list
@@ -231,6 +272,19 @@ class TaskService:
             # Mark task as completed
             upload_task.status = TaskStatus.COMPLETED
             upload_task.updated_at = time.time()
+            
+            # Send telemetry for task completion
+            asyncio.create_task(
+                TelemetryClient.send_event(
+                    Category.TASK_OPERATIONS,
+                    MessageId.ORB_TASK_COMPLETE,
+                    metadata={
+                        "total_files": upload_task.total_files,
+                        "successful_files": upload_task.successful_files,
+                        "failed_files": upload_task.failed_files,
+                    }
+                )
+            )
 
         except asyncio.CancelledError:
             logger.info("Background processor cancelled", task_id=task_id)
@@ -246,8 +300,23 @@ class TaskService:
 
             traceback.print_exc()
             if user_id in self.task_store and task_id in self.task_store[user_id]:
-                self.task_store[user_id][task_id].status = TaskStatus.FAILED
+                failed_task = self.task_store[user_id][task_id]
-                self.task_store[user_id][task_id].updated_at = time.time()
+                failed_task.status = TaskStatus.FAILED
+                failed_task.updated_at = time.time()
+                
+                # Send telemetry for task failure
+                asyncio.create_task(
+                    TelemetryClient.send_event(
+                        Category.TASK_OPERATIONS,
+                        MessageId.ORB_TASK_FAILED,
+                        metadata={
+                            "total_files": failed_task.total_files,
+                            "processed_files": failed_task.processed_files,
+                            "successful_files": failed_task.successful_files,
+                            "failed_files": failed_task.failed_files,
+                        }
+                    )
+                )
 
     def get_task_status(self, user_id: str, task_id: str) -> dict | None:
         """Get the status of a specific upload task

src/utils/telemetry/__init__.py

@@ -0,0 +1,8 @@
+"""Telemetry module for OpenRAG backend."""
+
+from .client import TelemetryClient
+from .category import Category
+from .message_id import MessageId
+
+__all__ = ["TelemetryClient", "Category", "MessageId"]
+

src/utils/telemetry/category.py

@@ -0,0 +1,45 @@
+"""Telemetry categories for OpenRAG backend."""
+
+
+class Category:
+    """Telemetry event categories."""
+    
+    # Application lifecycle
+    APPLICATION_STARTUP = "APPLICATION_STARTUP"
+    APPLICATION_SHUTDOWN = "APPLICATION_SHUTDOWN"
+    
+    # Service initialization
+    SERVICE_INITIALIZATION = "SERVICE_INITIALIZATION"
+    
+    # OpenSearch operations
+    OPENSEARCH_SETUP = "OPENSEARCH_SETUP"
+    OPENSEARCH_INDEX = "OPENSEARCH_INDEX"
+    
+    # Document operations
+    DOCUMENT_INGESTION = "DOCUMENT_INGESTION"
+    DOCUMENT_PROCESSING = "DOCUMENT_PROCESSING"
+    
+    # Authentication
+    AUTHENTICATION = "AUTHENTICATION"
+    
+    # Connector operations
+    CONNECTOR_OPERATIONS = "CONNECTOR_OPERATIONS"
+    
+    # Flow operations
+    FLOW_OPERATIONS = "FLOW_OPERATIONS"
+    
+    # Task operations
+    TASK_OPERATIONS = "TASK_OPERATIONS"
+    
+    # Chat operations
+    CHAT_OPERATIONS = "CHAT_OPERATIONS"
+    
+    # Error conditions
+    ERROR_CONDITIONS = "ERROR_CONDITIONS"
+    
+    # Settings operations
+    SETTINGS_OPERATIONS = "SETTINGS_OPERATIONS"
+    
+    # Onboarding
+    ONBOARDING = "ONBOARDING"
+

src/utils/telemetry/client.py

@@ -0,0 +1,402 @@
+"""Telemetry client for OpenRAG backend using Scarf."""
+
+import asyncio
+import os
+import platform
+from datetime import datetime, timezone
+from typing import Optional
+from urllib.parse import urlencode
+
+import httpx
+from utils.logging_config import get_logger
+
+logger = get_logger(__name__)
+
+# Constants
+SCARF_BASE_URL_DEFAULT = "https://langflow.gateway.scarf.sh"
+SCARF_PATH = "openrag"
+CLIENT_TYPE = "backend"
+PLATFORM_TYPE = "backend"
+
+
+def _get_openrag_version() -> str:
+    """Get OpenRAG version from package metadata."""
+    try:
+        from importlib.metadata import version, PackageNotFoundError
+        
+        try:
+            return version("openrag")
+        except PackageNotFoundError:
+            # Fallback: try to read from pyproject.toml if package not installed (dev mode)
+            try:
+                import tomllib
+                from pathlib import Path
+                
+                # Try to find pyproject.toml relative to this file
+                current_file = Path(__file__)
+                project_root = current_file.parent.parent.parent.parent
+                pyproject_path = project_root / "pyproject.toml"
+                
+                if pyproject_path.exists():
+                    with open(pyproject_path, "rb") as f:
+                        data = tomllib.load(f)
+                        return data.get("project", {}).get("version", "dev")
+            except Exception:
+                pass
+            
+            return "dev"
+    except Exception as e:
+        logger.warning(f"Failed to get OpenRAG version: {e}")
+        return "unknown"
+
+
+# Get version dynamically
+OPENRAG_VERSION = _get_openrag_version()
+
+# HTTP timeouts
+HTTP_REQUEST_TIMEOUT = 10.0
+HTTP_CONNECT_TIMEOUT = 5.0
+
+# Retry configuration
+RETRY_BASE_MS = 250
+MAX_WAIT_INTERVAL_MS = 5000
+MAX_RETRIES = 3
+
+# Global HTTP client
+_http_client: Optional[httpx.AsyncClient] = None
+_base_url_override: Optional[str] = None
+
+
+def _get_http_client() -> Optional[httpx.AsyncClient]:
+    """Get or create the HTTP client for telemetry."""
+    global _http_client
+    if _http_client is None:
+        try:
+            _http_client = httpx.AsyncClient(
+                timeout=httpx.Timeout(
+                    connect=HTTP_CONNECT_TIMEOUT,
+                    read=HTTP_REQUEST_TIMEOUT,
+                    write=HTTP_REQUEST_TIMEOUT,
+                    pool=HTTP_CONNECT_TIMEOUT,
+                ),
+                headers={
+                    "User-Agent": f"OpenRAG-Backend/{OPENRAG_VERSION}",
+                },
+            )
+            logger.debug("Telemetry HTTP client initialized")
+        except Exception as e:
+            logger.error(f"Failed to initialize telemetry HTTP client: {e}")
+            return None
+    return _http_client
+
+
+def set_base_url(url: str) -> None:
+    """Override the default Scarf base URL (for testing)."""
+    global _base_url_override
+    _base_url_override = url
+    logger.info(f"Telemetry base URL overridden: {url}")
+
+
+def _get_effective_base_url() -> str:
+    """Get the effective base URL (override or default)."""
+    return _base_url_override or SCARF_BASE_URL_DEFAULT
+
+
+def is_do_not_track() -> bool:
+    """Check if DO_NOT_TRACK environment variable is set."""
+    do_not_track = os.environ.get("DO_NOT_TRACK", "").lower()
+    return do_not_track in ("true", "1", "yes", "on")
+
+
+def _get_os() -> str:
+    """Get the operating system identifier."""
+    system = platform.system().lower()
+    if system == "darwin":
+        return "macos"
+    elif system == "windows":
+        return "windows"
+    elif system == "linux":
+        return "linux"
+    else:
+        return "unknown"
+
+
+def _get_os_version() -> str:
+    """Get the operating system version."""
+    try:
+        system = platform.system().lower()
+        if system == "darwin":
+            # macOS version
+            return platform.mac_ver()[0] if platform.mac_ver()[0] else "unknown"
+        elif system == "windows":
+            # Windows version
+            return platform.win32_ver()[0] if platform.win32_ver()[0] else "unknown"
+        elif system == "linux":
+            # Linux - try to get distribution info
+            try:
+                import distro
+                return f"{distro.name()} {distro.version()}".strip() or platform.release()
+            except ImportError:
+                # Fallback to platform.release() if distro not available
+                return platform.release()
+        else:
+            return platform.release()
+    except Exception:
+        return "unknown"
+
+
+def _get_gpu_info() -> dict:
+    """Get GPU information for telemetry."""
+    gpu_info = {
+        "gpu_available": False,
+        "gpu_count": 0,
+        "cuda_available": False,
+        "cuda_version": None,
+    }
+    
+    try:
+        # Try to use the existing GPU detection utility
+        from utils.gpu_detection import detect_gpu_devices
+        
+        has_gpu, gpu_count = detect_gpu_devices()
+        gpu_info["gpu_available"] = has_gpu
+        gpu_info["gpu_count"] = gpu_count if isinstance(gpu_count, int) else 0
+        
+        # Also check CUDA availability via torch
+        try:
+            import torch
+            gpu_info["cuda_available"] = torch.cuda.is_available()
+            if torch.cuda.is_available():
+                gpu_info["cuda_version"] = torch.version.cuda or "unknown"
+        except ImportError:
+            pass
+    except Exception as e:
+        logger.debug(f"Failed to detect GPU info: {e}")
+    
+    return gpu_info
+
+
+def _get_current_utc() -> str:
+    """Get current UTC time as RFC 3339 formatted string."""
+    now = datetime.now(timezone.utc)
+    return now.isoformat().replace("+00:00", "Z")
+
+
+def _get_exponential_backoff_delay(attempt: int) -> float:
+    """Calculate exponential backoff delay with full jitter (in seconds).
+    
+    Formula:
+    temp = min(MAX_BACKOFF, base * 2^attempt)
+    sleep = random_between(0, temp)
+    """
+    import random
+    
+    exp = min(2 ** attempt, MAX_WAIT_INTERVAL_MS // RETRY_BASE_MS)
+    temp_ms = RETRY_BASE_MS * exp
+    temp_ms = min(temp_ms, MAX_WAIT_INTERVAL_MS)
+    
+    # Full jitter: random duration between 0 and temp_ms
+    sleep_ms = random.uniform(0, temp_ms) if temp_ms > 0 else 0
+    return sleep_ms / 1000.0  # Convert to seconds
+
+
+async def _send_scarf_event(
+    category: str,
+    message_id: str,
+    metadata: dict = None,
+) -> None:
+    """Send a telemetry event to Scarf.
+    
+    Args:
+        category: Event category
+        message_id: Event message ID
+        metadata: Optional dictionary of additional metadata to include in the event
+    """
+    if is_do_not_track():
+        logger.debug(
+            f"Telemetry event aborted: {category}:{message_id}. DO_NOT_TRACK is enabled"
+        )
+        return
+    
+    http_client = _get_http_client()
+    if http_client is None:
+        logger.error(
+            f"Telemetry event aborted: {category}:{message_id}. HTTP client not initialized"
+        )
+        return
+    
+    os_name = _get_os()
+    os_version = _get_os_version()
+    gpu_info = _get_gpu_info()
+    timestamp = _get_current_utc()
+    effective_base_url = _get_effective_base_url()
+    # Build URL with format: /openrag/{platform}.{version}
+    base_url = f"{effective_base_url}/{SCARF_PATH}/{PLATFORM_TYPE}.{OPENRAG_VERSION}"
+    
+    # Build query parameters
+    params = {
+        "clientType": CLIENT_TYPE,
+        "openrag_version": OPENRAG_VERSION,
+        "platform": PLATFORM_TYPE,
+        "os": os_name,
+        "os_version": os_version,
+        "gpu_available": str(gpu_info["gpu_available"]).lower(),
+        "gpu_count": str(gpu_info["gpu_count"]),
+        "cuda_available": str(gpu_info["cuda_available"]).lower(),
+        "category": category,
+        "message_id": message_id,
+        "timestamp": timestamp,
+    }
+    
+    # Add CUDA version if available
+    if gpu_info["cuda_version"]:
+        params["cuda_version"] = str(gpu_info["cuda_version"])
+    
+    # Add metadata if provided
+    if metadata:
+        for key, value in metadata.items():
+            if value is not None:
+                # URL encode the value
+                params[key] = str(value)
+    
+    url = f"{base_url}?{urlencode(params)}"
+    retry_count = 0
+    
+    while retry_count < MAX_RETRIES:
+        if retry_count == 0:
+            logger.info(f"Sending telemetry event: {category}:{message_id}...")
+        else:
+            logger.info(
+                f"Sending telemetry event: {category}:{message_id}. Retry #{retry_count}..."
+            )
+        
+        logger.debug(f"Telemetry URL: {url}")
+        
+        try:
+            response = await http_client.get(url)
+            status = response.status_code
+            
+            if 200 <= status < 300:
+                logger.info(
+                    f"Successfully sent telemetry event: {category}:{message_id}. Status: {status}"
+                )
+                return
+            elif 500 <= status < 600:
+                # Retry server errors
+                logger.error(
+                    f"Failed to send telemetry event: {category}:{message_id}. Status: {status}"
+                )
+            else:
+                # Non-retryable status codes (400, 401, 403, 404, 429, etc.)
+                logger.error(
+                    f"Failed to send telemetry event: {category}:{message_id}. "
+                    f"Status: {status} (non-retryable)"
+                )
+                return
+                
+        except httpx.TimeoutException as e:
+            # Retry timeout errors
+            logger.error(
+                f"Failed to send telemetry event: {category}:{message_id}. "
+                f"Timeout error: {e}"
+            )
+        except httpx.ConnectError as e:
+            # Retry connection errors
+            logger.error(
+                f"Failed to send telemetry event: {category}:{message_id}. "
+                f"Connection error: {e}"
+            )
+        except httpx.RequestError as e:
+            # Non-retryable request errors
+            logger.error(
+                f"Failed to send telemetry event: {category}:{message_id}. "
+                f"Request error: {e}"
+            )
+            return
+        except Exception as e:
+            logger.error(
+                f"Failed to send telemetry event: {category}:{message_id}. "
+                f"Unknown error: {e}"
+            )
+        
+        retry_count += 1
+        
+        if retry_count < MAX_RETRIES:
+            delay = _get_exponential_backoff_delay(retry_count)
+            await asyncio.sleep(delay)
+    
+    logger.error(
+        f"Failed to send telemetry event: {category}:{message_id}. "
+        f"Maximum retries exceeded: {MAX_RETRIES}"
+    )
+
+
+class TelemetryClient:
+    """Telemetry client for sending events to Scarf."""
+    
+    @staticmethod
+    async def send_event(category: str, message_id: str, metadata: dict = None) -> None:
+        """Send a telemetry event asynchronously.
+        
+        Args:
+            category: Event category
+            message_id: Event message ID
+            metadata: Optional dictionary of additional metadata (e.g., {"llm_model": "gpt-4o"})
+        """
+        if is_do_not_track():
+            logger.debug(
+                f"Telemetry event aborted: {category}:{message_id}. DO_NOT_TRACK is enabled"
+            )
+            return
+        
+        try:
+            await _send_scarf_event(category, message_id, metadata)
+        except Exception as e:
+            logger.error(f"Error sending telemetry event: {e}")
+    
+    @staticmethod
+    def send_event_sync(category: str, message_id: str, metadata: dict = None) -> None:
+        """Send a telemetry event synchronously (creates a task).
+        
+        This is a convenience method for use in synchronous contexts.
+        It creates an async task but doesn't wait for it.
+        
+        Args:
+            category: Event category
+            message_id: Event message ID
+            metadata: Optional dictionary of additional metadata
+        """
+        if is_do_not_track():
+            logger.debug(
+                f"Telemetry event aborted: {category}:{message_id}. DO_NOT_TRACK is enabled"
+            )
+            return
+        
+        try:
+            # Try to get the current event loop
+            try:
+                loop = asyncio.get_event_loop()
+                if loop.is_running():
+                    # If loop is running, create a task
+                    asyncio.create_task(_send_scarf_event(category, message_id, metadata))
+                else:
+                    # If loop exists but not running, run it
+                    loop.run_until_complete(_send_scarf_event(category, message_id, metadata))
+            except RuntimeError:
+                # No event loop, create a new one
+                asyncio.run(_send_scarf_event(category, message_id, metadata))
+        except Exception as e:
+            logger.error(f"Error sending telemetry event: {e}")
+
+
+async def cleanup_telemetry_client() -> None:
+    """Cleanup the telemetry HTTP client."""
+    global _http_client
+    if _http_client is not None:
+        try:
+            await _http_client.aclose()
+            _http_client = None
+            logger.debug("Telemetry HTTP client closed")
+        except Exception as e:
+            logger.error(f"Error closing telemetry HTTP client: {e}")
+

src/utils/telemetry/message_id.py

@@ -0,0 +1,201 @@
+"""Telemetry message IDs for OpenRAG backend.
+
+All message IDs start with ORB_ (OpenRAG Backend) followed by descriptive text.
+Format: ORB_<CATEGORY>_<ACTION>[_<STATUS>]
+"""
+
+
+class MessageId:
+    """Telemetry message IDs."""
+    
+    # Category: APPLICATION_STARTUP ------------------------------------------->
+    
+    # Message: Application started successfully
+    ORB_APP_STARTED = "ORB_APP_STARTED"
+    # Message: Application startup initiated
+    ORB_APP_START_INIT = "ORB_APP_START_INIT"
+    # Message: Application shutdown initiated
+    ORB_APP_SHUTDOWN = "ORB_APP_SHUTDOWN"
+    
+    # Category: SERVICE_INITIALIZATION ----------------------------------------->
+    
+    # Message: Services initialized successfully
+    ORB_SVC_INIT_SUCCESS = "ORB_SVC_INIT_SUCCESS"
+    # Message: Service initialization started
+    ORB_SVC_INIT_START = "ORB_SVC_INIT_START"
+    # Message: Failed to initialize services
+    ORB_SVC_INIT_FAILED = "ORB_SVC_INIT_FAILED"
+    # Message: Failed to initialize OpenSearch client
+    ORB_SVC_OS_CLIENT_FAIL = "ORB_SVC_OS_CLIENT_FAIL"
+    # Message: Failed to generate JWT keys
+    ORB_SVC_JWT_KEY_FAIL = "ORB_SVC_JWT_KEY_FAIL"
+    
+    # Category: OPENSEARCH_SETUP ---------------------------------------------->
+    
+    # Message: OpenSearch connection established
+    ORB_OS_CONN_ESTABLISHED = "ORB_OS_CONN_ESTABLISHED"
+    # Message: OpenSearch connection failed
+    ORB_OS_CONN_FAILED = "ORB_OS_CONN_FAILED"
+    # Message: Waiting for OpenSearch to be ready
+    ORB_OS_WAITING = "ORB_OS_WAITING"
+    # Message: OpenSearch ready check timeout
+    ORB_OS_TIMEOUT = "ORB_OS_TIMEOUT"
+    
+    # Category: OPENSEARCH_INDEX ---------------------------------------------->
+    
+    # Message: OpenSearch index created successfully
+    ORB_OS_INDEX_CREATED = "ORB_OS_INDEX_CREATED"
+    # Message: OpenSearch index already exists
+    ORB_OS_INDEX_EXISTS = "ORB_OS_INDEX_EXISTS"
+    # Message: Failed to create OpenSearch index
+    ORB_OS_INDEX_CREATE_FAIL = "ORB_OS_INDEX_CREATE_FAIL"
+    # Message: Failed to initialize index
+    ORB_OS_INDEX_INIT_FAIL = "ORB_OS_INDEX_INIT_FAIL"
+    # Message: Knowledge filters index created
+    ORB_OS_KF_INDEX_CREATED = "ORB_OS_KF_INDEX_CREATED"
+    # Message: Failed to create knowledge filters index
+    ORB_OS_KF_INDEX_FAIL = "ORB_OS_KF_INDEX_FAIL"
+    
+    # Category: DOCUMENT_INGESTION -------------------------------------------->
+    
+    # Message: Document ingestion started
+    ORB_DOC_INGEST_START = "ORB_DOC_INGEST_START"
+    # Message: Document ingestion completed successfully
+    ORB_DOC_INGEST_COMPLETE = "ORB_DOC_INGEST_COMPLETE"
+    # Message: Document ingestion failed
+    ORB_DOC_INGEST_FAILED = "ORB_DOC_INGEST_FAILED"
+    # Message: Default documents ingestion started
+    ORB_DOC_DEFAULT_START = "ORB_DOC_DEFAULT_START"
+    # Message: Default documents ingestion completed
+    ORB_DOC_DEFAULT_COMPLETE = "ORB_DOC_DEFAULT_COMPLETE"
+    # Message: Default documents ingestion failed
+    ORB_DOC_DEFAULT_FAILED = "ORB_DOC_DEFAULT_FAILED"
+    
+    # Category: DOCUMENT_PROCESSING -------------------------------------------->
+    
+    # Message: Document processing started
+    ORB_DOC_PROCESS_START = "ORB_DOC_PROCESS_START"
+    # Message: Document processing completed
+    ORB_DOC_PROCESS_COMPLETE = "ORB_DOC_PROCESS_COMPLETE"
+    # Message: Document processing failed
+    ORB_DOC_PROCESS_FAILED = "ORB_DOC_PROCESS_FAILED"
+    # Message: Process pool recreation attempted
+    ORB_DOC_POOL_RECREATE = "ORB_DOC_POOL_RECREATE"
+    
+    # Category: AUTHENTICATION ------------------------------------------------>
+    
+    # Message: Authentication successful
+    ORB_AUTH_SUCCESS = "ORB_AUTH_SUCCESS"
+    # Message: Authentication failed
+    ORB_AUTH_FAILED = "ORB_AUTH_FAILED"
+    # Message: User logged out
+    ORB_AUTH_LOGOUT = "ORB_AUTH_LOGOUT"
+    # Message: OAuth callback received
+    ORB_AUTH_OAUTH_CALLBACK = "ORB_AUTH_OAUTH_CALLBACK"
+    # Message: OAuth callback failed
+    ORB_AUTH_OAUTH_FAILED = "ORB_AUTH_OAUTH_FAILED"
+    
+    # Category: CONNECTOR_OPERATIONS ------------------------------------------->
+    
+    # Message: Connector connection established
+    ORB_CONN_CONNECTED = "ORB_CONN_CONNECTED"
+    # Message: Connector connection failed
+    ORB_CONN_CONNECT_FAILED = "ORB_CONN_CONNECT_FAILED"
+    # Message: Connector sync started
+    ORB_CONN_SYNC_START = "ORB_CONN_SYNC_START"
+    # Message: Connector sync completed
+    ORB_CONN_SYNC_COMPLETE = "ORB_CONN_SYNC_COMPLETE"
+    # Message: Connector sync failed
+    ORB_CONN_SYNC_FAILED = "ORB_CONN_SYNC_FAILED"
+    # Message: Connector webhook received
+    ORB_CONN_WEBHOOK_RECV = "ORB_CONN_WEBHOOK_RECV"
+    # Message: Connector webhook failed
+    ORB_CONN_WEBHOOK_FAILED = "ORB_CONN_WEBHOOK_FAILED"
+    # Message: Failed to load persisted connections
+    ORB_CONN_LOAD_FAILED = "ORB_CONN_LOAD_FAILED"
+    
+    # Category: FLOW_OPERATIONS ------------------------------------------------>
+    
+    # Message: Flow backup completed
+    ORB_FLOW_BACKUP_COMPLETE = "ORB_FLOW_BACKUP_COMPLETE"
+    # Message: Flow backup failed
+    ORB_FLOW_BACKUP_FAILED = "ORB_FLOW_BACKUP_FAILED"
+    # Message: Flow reset detected
+    ORB_FLOW_RESET_DETECTED = "ORB_FLOW_RESET_DETECTED"
+    # Message: Flow reset check failed
+    ORB_FLOW_RESET_CHECK_FAIL = "ORB_FLOW_RESET_CHECK_FAIL"
+    # Message: Settings reapplied after flow reset
+    ORB_FLOW_SETTINGS_REAPPLIED = "ORB_FLOW_SETTINGS_REAPPLIED"
+    
+    # Category: TASK_OPERATIONS ------------------------------------------------>
+    
+    # Message: Task created successfully
+    ORB_TASK_CREATED = "ORB_TASK_CREATED"
+    # Message: Task completed successfully
+    ORB_TASK_COMPLETE = "ORB_TASK_COMPLETE"
+    # Message: Task failed
+    ORB_TASK_FAILED = "ORB_TASK_FAILED"
+    # Message: Task cancelled
+    ORB_TASK_CANCELLED = "ORB_TASK_CANCELLED"
+    # Message: Task cancellation failed
+    ORB_TASK_CANCEL_FAILED = "ORB_TASK_CANCEL_FAILED"
+    
+    # Category: CHAT_OPERATIONS ------------------------------------------------>
+    
+    # Message: Chat request received
+    ORB_CHAT_REQUEST_RECV = "ORB_CHAT_REQUEST_RECV"
+    # Message: Chat request completed
+    ORB_CHAT_REQUEST_COMPLETE = "ORB_CHAT_REQUEST_COMPLETE"
+    # Message: Chat request failed
+    ORB_CHAT_REQUEST_FAILED = "ORB_CHAT_REQUEST_FAILED"
+    
+    # Category: ERROR_CONDITIONS ----------------------------------------------->
+    
+    # Message: Critical error occurred
+    ORB_ERROR_CRITICAL = "ORB_ERROR_CRITICAL"
+    # Message: Warning condition
+    ORB_ERROR_WARNING = "ORB_ERROR_WARNING"
+    
+    # Category: SETTINGS_OPERATIONS -------------------------------------------->
+    
+    # Message: Settings updated successfully
+    ORB_SETTINGS_UPDATED = "ORB_SETTINGS_UPDATED"
+    # Message: Settings update failed
+    ORB_SETTINGS_UPDATE_FAILED = "ORB_SETTINGS_UPDATE_FAILED"
+    # Message: LLM provider changed
+    ORB_SETTINGS_LLM_PROVIDER = "ORB_SETTINGS_LLM_PROVIDER"
+    # Message: LLM model changed
+    ORB_SETTINGS_LLM_MODEL = "ORB_SETTINGS_LLM_MODEL"
+    # Message: Embedding provider changed
+    ORB_SETTINGS_EMBED_PROVIDER = "ORB_SETTINGS_EMBED_PROVIDER"
+    # Message: Embedding model changed
+    ORB_SETTINGS_EMBED_MODEL = "ORB_SETTINGS_EMBED_MODEL"
+    # Message: System prompt updated
+    ORB_SETTINGS_SYSTEM_PROMPT = "ORB_SETTINGS_SYSTEM_PROMPT"
+    # Message: Chunk settings updated
+    ORB_SETTINGS_CHUNK_UPDATED = "ORB_SETTINGS_CHUNK_UPDATED"
+    # Message: Docling settings updated
+    ORB_SETTINGS_DOCLING_UPDATED = "ORB_SETTINGS_DOCLING_UPDATED"
+    # Message: Provider credentials updated
+    ORB_SETTINGS_PROVIDER_CREDS = "ORB_SETTINGS_PROVIDER_CREDS"
+    
+    # Category: ONBOARDING ----------------------------------------------------->
+    
+    # Message: Onboarding started
+    ORB_ONBOARD_START = "ORB_ONBOARD_START"
+    # Message: Onboarding completed successfully
+    ORB_ONBOARD_COMPLETE = "ORB_ONBOARD_COMPLETE"
+    # Message: Onboarding failed
+    ORB_ONBOARD_FAILED = "ORB_ONBOARD_FAILED"
+    # Message: LLM provider selected during onboarding
+    ORB_ONBOARD_LLM_PROVIDER = "ORB_ONBOARD_LLM_PROVIDER"
+    # Message: LLM model selected during onboarding
+    ORB_ONBOARD_LLM_MODEL = "ORB_ONBOARD_LLM_MODEL"
+    # Message: Embedding provider selected during onboarding
+    ORB_ONBOARD_EMBED_PROVIDER = "ORB_ONBOARD_EMBED_PROVIDER"
+    # Message: Embedding model selected during onboarding
+    ORB_ONBOARD_EMBED_MODEL = "ORB_ONBOARD_EMBED_MODEL"
+    # Message: Sample data ingestion requested
+    ORB_ONBOARD_SAMPLE_DATA = "ORB_ONBOARD_SAMPLE_DATA"
+    # Message: Configuration marked as edited
+    ORB_ONBOARD_CONFIG_EDITED = "ORB_ONBOARD_CONFIG_EDITED"