logs: suppress verbose warnings (#8003)

* suppress nvidia warnings about nim key

* Wrap import libs with the warnings handling

* Handle sigterm for docker exists

* makefile revert

* [autofix.ci] apply automated fixes

* ruff

* use sqlmodel paginate

* Try to update polling timeout

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

src/backend/base/langflow/api/v1/flows.py

@@ -15,7 +15,7 @@ from fastapi import APIRouter, Depends, File, HTTPException, Response, UploadFil
 from fastapi.encoders import jsonable_encoder
 from fastapi.responses import StreamingResponse
 from fastapi_pagination import Page, Params
-from fastapi_pagination.ext.sqlalchemy import apaginate
+from fastapi_pagination.ext.sqlmodel import apaginate
 from sqlmodel import and_, col, select
 from sqlmodel.ext.asyncio.session import AsyncSession
 

src/backend/base/langflow/base/astra_assistants/util.py

@@ -59,7 +59,14 @@ def tools_from_package(your_package) -> None:
         module_name = f"{package_name}.{module_info.name}"
 
         # Dynamically import the module
-        module = importlib.import_module(module_name)
+        import warnings
+
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                "ignore", message="Support for class-based `config` is deprecated", category=DeprecationWarning
+            )
+            warnings.filterwarnings("ignore", message="Valid config keys have changed in V2", category=UserWarning)
+            module = importlib.import_module(module_name)
 
         # Iterate over all members of the module
         for name, obj in inspect.getmembers(module, inspect.isclass):

src/backend/base/langflow/base/models/model.py

@@ -276,9 +276,17 @@ class LCModelComponent(Component):
             # Ensure component_inputs is a list of the expected types
             if not isinstance(component_inputs, list):
                 component_inputs = []
-            models_module = importlib.import_module("langflow.components.models")
-            component_class = getattr(models_module, str(module_name))
-            component = component_class()
+
+            import warnings
+
+            with warnings.catch_warnings():
+                warnings.filterwarnings(
+                    "ignore", message="Support for class-based `config` is deprecated", category=DeprecationWarning
+                )
+                warnings.filterwarnings("ignore", message="Valid config keys have changed in V2", category=UserWarning)
+                models_module = importlib.import_module("langflow.components.models")
+                component_class = getattr(models_module, str(module_name))
+                component = component_class()
 
             return self.build_llm_model_from_inputs(component, component_inputs)
         except Exception as e:

src/backend/base/langflow/components/models/nvidia.py

@@ -17,6 +17,10 @@ class NVIDIAModelComponent(LCModelComponent):
     icon = "NVIDIA"
 
     try:
+        import warnings
+
+        # Suppresses repeated warnings about NIM key in langchain_nvidia_ai_endpoints==0.3.8
+        warnings.filterwarnings("ignore", category=UserWarning, module="langchain_nvidia_ai_endpoints._common")
         from langchain_nvidia_ai_endpoints import ChatNVIDIA
 
         all_models = ChatNVIDIA().get_available_models()

src/backend/base/langflow/initial_setup/setup.py

@@ -492,7 +492,7 @@ async def load_starter_projects(retries=3, delay=1) -> list[tuple[anyio.Path, di
             try:
                 project = orjson.loads(content)
                 starter_projects.append((file, project))
-                logger.info(f"Loaded starter project {file}")
+                logger.debug(f"Loaded starter project {file}")
                 break  # Break if load is successful
             except orjson.JSONDecodeError as e:
                 attempt += 1
@@ -601,7 +601,7 @@ async def update_project_file(project_path: anyio.Path, project: dict, updated_p
     project["data"] = updated_project_data
     async with async_open(str(project_path), "w", encoding="utf-8") as f:
         await f.write(orjson.dumps(project, option=ORJSON_OPTIONS).decode())
-    logger.info(f"Updated starter project {project['name']} file")
+    logger.debug(f"Updated starter project {project['name']} file")
 
 
 def update_existing_project(

src/backend/base/langflow/interface/importing/utils.py

@@ -8,12 +8,26 @@ def import_module(module_path: str) -> Any:
     """Import module from module path."""
     if "from" not in module_path:
         # Import the module using the module path
-        return importlib.import_module(module_path)
+        import warnings
+
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                "ignore", message="Support for class-based `config` is deprecated", category=DeprecationWarning
+            )
+            warnings.filterwarnings("ignore", message="Valid config keys have changed in V2", category=UserWarning)
+            return importlib.import_module(module_path)
     # Split the module path into its components
     _, module_path, _, object_name = module_path.split()
 
     # Import the module using the module path
-    module = importlib.import_module(module_path)
+    import warnings
+
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore", message="Support for class-based `config` is deprecated", category=DeprecationWarning
+        )
+        warnings.filterwarnings("ignore", message="Valid config keys have changed in V2", category=UserWarning)
+        module = importlib.import_module(module_path)
 
     return getattr(module, object_name)
 

src/backend/base/langflow/interface/utils.py

@@ -115,4 +115,4 @@ def set_langchain_cache(settings) -> None:
         except ImportError:
             logger.warning(f"Could not import {cache_type}. ")
     else:
-        logger.info("No LLM cache set.")
+        logger.debug("No LLM cache set.")

src/backend/base/langflow/server.py

@@ -11,6 +11,7 @@ from langflow.logging.logger import InterceptHandler
 
 class LangflowUvicornWorker(UvicornWorker):
     CONFIG_KWARGS = {"loop": "asyncio"}
+    _has_exited = False
 
     def _install_sigint_handler(self) -> None:
         """Install a SIGQUIT handler on workers.
@@ -20,6 +21,14 @@ class LangflowUvicornWorker(UvicornWorker):
         """
         loop = asyncio.get_running_loop()
         loop.add_signal_handler(signal.SIGINT, self.handle_exit, signal.SIGINT, None)
+        loop.add_signal_handler(signal.SIGTERM, self.handle_exit, signal.SIGTERM, None)
+
+    def handle_exit(self, sig, frame):
+        if not self._has_exited:
+            print("👋 See you next time!")  # noqa: T201
+            self._has_exited = True
+
+        super().handle_exit(sig, frame)
 
     async def _serve(self) -> None:
         # We do this to not log the "Worker (pid:XXXXX) was sent SIGINT"

src/backend/base/langflow/services/database/service.py

@@ -336,7 +336,7 @@ class DatabaseService(Service):
                     logger.exception(msg)
                     raise RuntimeError(msg) from exc
             else:
-                logger.info("Alembic already initialized")
+                logger.info("Alembic initialized")
 
             logger.info(f"Running DB migrations in {self.script_location}")
 

src/backend/base/langflow/services/job_queue/service.py

@@ -117,7 +117,7 @@ class JobQueueService(Service):
         # Clean up each registered job queue.
         for job_id in list(self._queues.keys()):
             await self.cleanup_job(job_id)
-        logger.info("JobQueueService stopped: all job queues have been cleaned up.")
+        logger.debug("JobQueueService stopped: all job queues have been cleaned up.")
 
     async def teardown(self) -> None:
         await self.stop()
@@ -225,7 +225,7 @@ class JobQueueService(Service):
             logger.debug(f"No queue found for job_id {job_id} during cleanup.")
             return
 
-        logger.info(f"Commencing cleanup for job_id {job_id}")
+        logger.debug(f"Commencing cleanup for job_id {job_id}")
         main_queue, _event_manager, task, _ = self._queues[job_id]
 
         # Cancel the associated task if it is still running.
@@ -250,7 +250,7 @@ class JobQueueService(Service):
         logger.debug(f"Removed {items_cleared} items from queue for job_id {job_id}")
         # Remove the job entry from the registry
         self._queues.pop(job_id, None)
-        logger.info(f"Cleanup successful for job_id {job_id}: resources have been released.")
+        logger.debug(f"Cleanup successful for job_id {job_id}: resources have been released.")
 
     async def _periodic_cleanup(self) -> None:
         """Execute a periodic task that cleans up completed or cancelled job queues.

src/backend/base/langflow/utils/util.py

@@ -165,8 +165,15 @@ def get_default_factory(module: str, function: str):
     pattern = r"<function (\w+)>"
 
     if match := re.search(pattern, function):
-        imported_module = importlib.import_module(module)
-        return getattr(imported_module, match[1])()
+        import warnings
+
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                "ignore", message="Support for class-based `config` is deprecated", category=DeprecationWarning
+            )
+            warnings.filterwarnings("ignore", message="Valid config keys have changed in V2", category=UserWarning)
+            imported_module = importlib.import_module(module)
+            return getattr(imported_module, match[1])()
     return None
 
 

src/backend/tests/unit/components/helpers/test_structured_output_component.py

@@ -4,7 +4,6 @@ from unittest.mock import patch
 
 import openai
 import pytest
-from langchain_nvidia_ai_endpoints import ChatNVIDIA
 from langchain_openai import ChatOpenAI
 from langflow.components.helpers.structured_output import StructuredOutputComponent
 from langflow.helpers.base_model import build_model_from_schema
@@ -415,6 +414,12 @@ class TestStructuredOutputComponent(ComponentTestBaseWithoutClient):
     )
     def test_with_real_nvidia_model_simple_schema(self):
         # Create a real NVIDIA model
+        try:
+            from langchain_nvidia_ai_endpoints import ChatNVIDIA
+        except ImportError as e:
+            msg = "Please install langchain-nvidia-ai-endpoints to use the NVIDIA model."
+            raise ImportError(msg) from e
+
         llm = ChatNVIDIA(model="meta/llama-3.2-3b-instruct", temperature=0, max_tokens=10)
 
         # Create a component with a simple schema

src/backend/tests/unit/test_chat_endpoint.py

@@ -164,7 +164,7 @@ async def test_build_flow_polling(client, json_memory_chatbot_no_llm, logged_in_
             self.status_code = codes.OK
             self.max_total_events = 50  # Limit to prevent infinite loops
             self.max_empty_polls = 10  # Maximum number of empty polls before giving up
-            self.poll_timeout = 1.0  # Timeout for each polling request
+            self.poll_timeout = 3.0  # Timeout for each polling request
 
         async def aiter_lines(self):
             try: