fix: Refactor import statements and enhance error logging (langflow-a…

…i#4071)

* Refactor import paths for `get_patched_openai_client` in astra_assistants components

* Enhance error logging with file information in directory_reader.py

* Refactor MetaphorToolkit to use new input/output structure and update imports

* Enhance error message with code snippet preview in class validation function

* update import statements and refactoring input handling in JSON files.

* [autofix.ci] apply automated fixes

* Remove unused import of 'Tool' from Metaphor.py

---------

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

src/backend/base/langflow/components/astra_assistants/astra_assistant_manager.py

@@ -2,7 +2,7 @@
 
 from astra_assistants.astra_assistants_manager import AssistantManager
 
-from langflow.components.astra_assistants.util import (
+from langflow.base.astra_assistants.util import (
     get_patched_openai_client,
     litellm_model_names,
     tool_names,

src/backend/base/langflow/components/astra_assistants/create_assistant.py

@@ -1,4 +1,4 @@
-from langflow.components.astra_assistants.util import get_patched_openai_client
+from langflow.base.astra_assistants.util import get_patched_openai_client
 from langflow.custom.custom_component.component_with_cache import ComponentWithCache
 from langflow.inputs import MultilineInput, StrInput
 from langflow.schema.message import Message

src/backend/base/langflow/components/astra_assistants/create_thread.py

@@ -1,4 +1,4 @@
-from langflow.components.astra_assistants.util import get_patched_openai_client
+from langflow.base.astra_assistants.util import get_patched_openai_client
 from langflow.custom.custom_component.component_with_cache import ComponentWithCache
 from langflow.inputs import MultilineInput
 from langflow.schema.message import Message

src/backend/base/langflow/components/astra_assistants/get_assistant.py

@@ -1,4 +1,4 @@
-from langflow.components.astra_assistants.util import get_patched_openai_client
+from langflow.base.astra_assistants.util import get_patched_openai_client
 from langflow.custom.custom_component.component_with_cache import ComponentWithCache
 from langflow.inputs import MultilineInput, StrInput
 from langflow.schema.message import Message

src/backend/base/langflow/components/astra_assistants/list_assistants.py

@@ -1,4 +1,4 @@
-from langflow.components.astra_assistants.util import get_patched_openai_client
+from langflow.base.astra_assistants.util import get_patched_openai_client
 from langflow.custom.custom_component.component_with_cache import ComponentWithCache
 from langflow.schema.message import Message
 from langflow.template.field.base import Output

src/backend/base/langflow/components/astra_assistants/run.py

@@ -4,18 +4,14 @@
 from openai import OpenAI
 from openai.lib.streaming import AssistantEventHandler
 
-from langflow.components.astra_assistants.util import get_patched_openai_client
+from langflow.base.astra_assistants.util import get_patched_openai_client
 from langflow.custom.custom_component.component_with_cache import ComponentWithCache
 from langflow.inputs import MultilineInput
 from langflow.schema import dotdict
 from langflow.schema.message import Message
 from langflow.template import Output
 
 
-class AssistantsRunError(Exception):
-    """Error running assistant"""
-
-
 class AssistantsRun(ComponentWithCache):
     display_name = "Run Assistant"
     description = "Executes an Assistant Run against a thread"
@@ -101,3 +97,7 @@ def on_exception(self, exception: Exception) -> None:
             print(e)
             msg = f"Error running assistant: {e}"
             raise AssistantsRunError(msg) from e
+
+
+class AssistantsRunError(Exception):
+    """AssistantsRun error"""

src/backend/base/langflow/components/langchain_utilities/SpiderTool.py

@@ -6,10 +6,6 @@
 from langflow.schema import Data
 
 
-class SpiderToolError(Exception):
-    """SpiderTool error"""
-
-
 class SpiderTool(Component):
     display_name: str = "Spider Web Crawler & Scraper"
     description: str = "Spider API for web crawling and scraping."
@@ -130,3 +126,7 @@ def crawl(self) -> list[Data]:
             else:
                 records.append(Data(data={"content": record["content"], "url": record["url"]}))
         return records
+
+
+class SpiderToolError(Exception):
+    """SpiderTool error"""

src/backend/base/langflow/components/toolkits/Metaphor.py

@@ -1,36 +1,51 @@
-from langchain_community.agent_toolkits.base import BaseToolkit
-from langchain_core.tools import Tool, tool
+from langchain_core.tools import tool
 from metaphor_python import Metaphor
 
-from langflow.custom import CustomComponent
+from langflow.custom import Component
+from langflow.field_typing import Tool
+from langflow.io import BoolInput, IntInput, Output, SecretStrInput
 
 
-class MetaphorToolkit(CustomComponent):
-    display_name: str = "Metaphor"
-    description: str = "Metaphor Toolkit"
+class MetaphorToolkit(Component):
+    display_name = "Metaphor"
+    description = "Metaphor Toolkit for search and content retrieval"
     documentation = "https://python.langchain.com/docs/integrations/tools/metaphor_search"
-    beta: bool = True
-    name = "Metaphor"
-    # api key should be password = True
-    field_config = {
-        "metaphor_api_key": {"display_name": "Metaphor API Key", "password": True},
-        "code": {"advanced": True},
-    }
-
-    def build(
-        self,
-        metaphor_api_key: str,
-        use_autoprompt: bool = True,
-        search_num_results: int = 5,
-        similar_num_results: int = 5,
-    ) -> Tool | BaseToolkit:
-        # If documents, then we need to create a Vectara instance using .from_documents
-        client = Metaphor(api_key=metaphor_api_key)
+    beta = True
+
+    inputs = [
+        SecretStrInput(
+            name="metaphor_api_key",
+            display_name="Metaphor API Key",
+            password=True,
+        ),
+        BoolInput(
+            name="use_autoprompt",
+            display_name="Use Autoprompt",
+            value=True,
+        ),
+        IntInput(
+            name="search_num_results",
+            display_name="Search Number of Results",
+            value=5,
+        ),
+        IntInput(
+            name="similar_num_results",
+            display_name="Similar Number of Results",
+            value=5,
+        ),
+    ]
+
+    outputs = [
+        Output(name="tools", display_name="Tools", method="build_toolkit"),
+    ]
+
+    def build_toolkit(self) -> Tool:
+        client = Metaphor(api_key=self.metaphor_api_key)
 
         @tool
         def search(query: str):
             """Call search engine with a query."""
-            return client.search(query, use_autoprompt=use_autoprompt, num_results=search_num_results)
+            return client.search(query, use_autoprompt=self.use_autoprompt, num_results=self.search_num_results)
 
         @tool
         def get_contents(ids: list[str]):
@@ -46,6 +61,6 @@ def find_similar(url: str):
 
             The url passed in should be a URL returned from `search`
             """
-            return client.find_similar(url, num_results=similar_num_results)
+            return client.find_similar(url, num_results=self.similar_num_results)
 
         return [search, get_contents, find_similar]

src/backend/base/langflow/custom/custom_component/component.py

@@ -8,7 +8,6 @@
 
 import nanoid
 import yaml
-from loguru import logger
 from pydantic import BaseModel
 
 from langflow.base.tools.constants import TOOL_OUTPUT_NAME
@@ -340,7 +339,6 @@ def _set_output_required_inputs(self):
                 source_code = inspect.getsource(method)
                 ast_tree = ast.parse(dedent(source_code))
             except Exception:  # noqa: BLE001
-                logger.opt(exception=True).debug(f"Could not get source code for method {method}")
                 source_code = self._code
                 ast_tree = ast.parse(dedent(source_code))
 

src/backend/base/langflow/custom/directory_reader/directory_reader.py

@@ -78,7 +78,7 @@ def filter_loaded_components(self, data: dict, with_errors: bool) -> dict:
                         component_tuple = (*build_component(component), component)
                         components.append(component_tuple)
                 except Exception:  # noqa: BLE001
-                    logger.opt(exception=True).debug(f"Error while loading component {component['name']}")
+                    logger.debug(f"Error while loading component {component['name']} from {component['file']}")
                     continue
             items.append({"name": menu["name"], "path": menu["path"], "components": components})
         filtered = [menu for menu in items if menu["components"]]

src/backend/base/langflow/graph/vertex/base.py

@@ -370,9 +370,12 @@ def _build_params(self):
                 val = field.get("value")
                 if field.get("type") == "code":
                     try:
-                        params[field_name] = ast.literal_eval(val) if val else None
+                        if field_name == "code":
+                            params[field_name] = val
+                        else:
+                            params[field_name] = ast.literal_eval(val) if val else None
                     except Exception:  # noqa: BLE001
-                        logger.opt(exception=True).debug(f"Error evaluating code for {field_name}")
+                        logger.debug(f"Error evaluating code for {field_name}")
                         params[field_name] = val
                 elif field.get("type") in ["dict", "NestedDict"]:
                     # When dict comes from the frontend it comes as a