[autofix.ci] apply automated fixes (attempt 2/3)

src/backend/base/langflow/components/agents/agent.py

@@ -47,18 +47,13 @@ def set_advanced_true(component_input):
 
 class AgentComponent(ToolCallingAgentComponent):
     display_name: str = "Agent"
-    description: str = (
-        "Define the agent's instructions, then enter a task to complete using tools."
-    )
+    description: str = "Define the agent's instructions, then enter a task to complete using tools."
     documentation: str = "https://docs.langflow.org/agents"
     icon = "bot"
     beta = False
     name = "Agent"
 
-    memory_inputs = [
-        set_advanced_true(component_input)
-        for component_input in MemoryComponent().inputs
-    ]
+    memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]
 
     # Filter out json_mode from OpenAI inputs since we handle structured output differently
     openai_inputs_filtered = [
@@ -153,9 +148,7 @@ class AgentComponent(ToolCallingAgentComponent):
                     "display_name": "Type",
                     "type": "str",
                     "edit_mode": EditMode.INLINE,
-                    "description": (
-                        "Indicate the data type of the output field (e.g., str, int, float, bool, dict)."
-                    ),
+                    "description": ("Indicate the data type of the output field (e.g., str, int, float, bool, dict)."),
                     "options": ["str", "int", "float", "bool", "dict"],
                     "default": "str",
                 },
@@ -207,9 +200,7 @@ async def get_agent_requirements(self):
         if self.add_current_date_tool:
             if not isinstance(self.tools, list):  # type: ignore[has-type]
                 self.tools = []
-            current_date_tool = (
-                await CurrentDateComponent(**self.get_base_args()).to_toolkit()
-            ).pop(0)
+            current_date_tool = (await CurrentDateComponent(**self.get_base_args()).to_toolkit()).pop(0)
             if not isinstance(current_date_tool, StructuredTool):
                 msg = "CurrentDateComponent must be converted to a StructuredTool"
                 raise TypeError(msg)
@@ -218,9 +209,7 @@ async def get_agent_requirements(self):
 
     async def message_response(self) -> Message:
         try:
-            llm_model, self.chat_history, self.tools = (
-                await self.get_agent_requirements()
-            )
+            llm_model, self.chat_history, self.tools = await self.get_agent_requirements()
             # Set up and run agent
             self.set(
                 llm=llm_model,
@@ -290,11 +279,7 @@ async def build_structured_output_base(self, content: str):
                 return {"content": content, "error": schema_error_msg}
 
         # If no output schema provided, return parsed JSON without validation
-        if (
-            not hasattr(self, "output_schema")
-            or not self.output_schema
-            or len(self.output_schema) == 0
-        ):
+        if not hasattr(self, "output_schema") or not self.output_schema or len(self.output_schema) == 0:
             return json_data
 
         # Use BaseModel validation with schema
@@ -313,9 +298,7 @@ async def build_structured_output_base(self, content: str):
                     except ValidationError as e:
                         await logger.aerror(f"Validation error for item: {e}")
                         # Include invalid items with error info
-                        validated_objects.append(
-                            {"data": item, "validation_error": str(e)}
-                        )
+                        validated_objects.append({"data": item, "validation_error": str(e)})
                 return validated_objects
 
             # Single object
@@ -348,11 +331,7 @@ async def json_response(self) -> Data:
                 system_components.append(f"Format instructions: {format_instructions}")
 
             # 3. Schema Information from BaseModel
-            if (
-                hasattr(self, "output_schema")
-                and self.output_schema
-                and len(self.output_schema) > 0
-            ):
+            if hasattr(self, "output_schema") and self.output_schema and len(self.output_schema) > 0:
                 try:
                     processed_schema = self._preprocess_schema(self.output_schema)
                     output_model = build_model_from_schema(processed_schema)
@@ -370,17 +349,11 @@ async def json_response(self) -> Data:
                     )
                     system_components.append(schema_info)
                 except (ValidationError, ValueError, TypeError, KeyError) as e:
-                    await logger.aerror(
-                        f"Could not build schema for prompt: {e}", exc_info=True
-                    )
+                    await logger.aerror(f"Could not build schema for prompt: {e}", exc_info=True)
 
             # Combine all components
-            combined_instructions = (
-                "\n\n".join(system_components) if system_components else ""
-            )
-            llm_model, self.chat_history, self.tools = (
-                await self.get_agent_requirements()
-            )
+            combined_instructions = "\n\n".join(system_components) if system_components else ""
+            llm_model, self.chat_history, self.tools = await self.get_agent_requirements()
             self.set(
                 llm=llm_model,
                 tools=self.tools or [],
@@ -454,9 +427,7 @@ async def get_memory_data(self):
             .retrieve_messages()
         )
         return [
-            message
-            for message in messages
-            if getattr(message, "id", None) != getattr(self.input_value, "id", None)
+            message for message in messages if getattr(message, "id", None) != getattr(self.input_value, "id", None)
         ]
 
     async def get_llm(self):
@@ -477,9 +448,7 @@ async def get_llm(self):
             return self._build_llm_model(component_class, inputs, prefix), display_name
 
         except (AttributeError, ValueError, TypeError, RuntimeError) as e:
-            await logger.aerror(
-                f"Error building {self.agent_llm} language model: {e!s}"
-            )
+            await logger.aerror(f"Error building {self.agent_llm} language model: {e!s}")
             msg = f"Failed to initialize language model: {e!s}"
             raise ValueError(msg) from e
 
@@ -554,9 +523,7 @@ async def update_build_config(
                     self.delete_fields(build_config, fields)
 
                 # Add provider-specific fields
-                if field_value == "OpenAI" and not any(
-                    field in build_config for field in fields_to_add
-                ):
+                if field_value == "OpenAI" and not any(field in build_config for field in fields_to_add):
                     build_config.update(fields_to_add)
                 else:
                     build_config.update(fields_to_add)
@@ -576,9 +543,7 @@ async def update_build_config(
                     refresh_button=False,
                     input_types=["LanguageModel"],
                     placeholder="Awaiting model input.",
-                    options_metadata=[
-                        MODELS_METADATA[key] for key in MODEL_PROVIDERS_LIST
-                    ],
+                    options_metadata=[MODELS_METADATA[key] for key in MODEL_PROVIDERS_LIST],
                     external_options={
                         "fields": {
                             "data": {
@@ -631,12 +596,7 @@ async def update_build_config(
                     build_config = await update_component_build_config(
                         component_class, build_config, field_value, "model_name"
                     )
-        return dotdict(
-            {
-                k: v.to_dict() if hasattr(v, "to_dict") else v
-                for k, v in build_config.items()
-            }
-        )
+        return dotdict({k: v.to_dict() if hasattr(v, "to_dict") else v for k, v in build_config.items()})
 
     async def _get_tools(self) -> list[Tool]:
         component_toolkit = _get_component_toolkit()
@@ -650,7 +610,5 @@ async def _get_tools(self) -> list[Tool]:
             callbacks=self.get_langchain_callbacks(),
         )
         if hasattr(self, "tools_metadata"):
-            tools = component_toolkit(
-                component=self, metadata=self.tools_metadata
-            ).update_tools_metadata(tools=tools)
+            tools = component_toolkit(component=self, metadata=self.tools_metadata).update_tools_metadata(tools=tools)
         return tools

src/backend/tests/unit/base/mcp/test_mcp_util.py

@@ -11,7 +11,6 @@
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
-
 from langflow.base.mcp import util
 from langflow.base.mcp.util import MCPSessionManager, MCPSseClient, MCPStdioClient, _process_headers, validate_headers