merging branch local two edges

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

@@ -1,4 +1,3 @@
-from typing import Optional
 
 from langchain_anthropic.chat_models import ChatAnthropic
 from pydantic.v1 import SecretStr

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

@@ -1,4 +1,4 @@
-from typing import Any, Dict, Optional
+from typing import Optional
 
 from langchain_community.chat_models.litellm import ChatLiteLLM, ChatLiteLLMException
 from langflow.base.constants import STREAM_INFO_TEXT
@@ -177,4 +177,4 @@ class ChatLiteLLMModelComponent(LCModelComponent):
         )
 
         return output
-    
+    

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

@@ -1,4 +1,3 @@
-from typing import Optional
 
 from langchain_groq import ChatGroq
 from langflow.base.models.groq_constants import MODEL_NAMES
@@ -103,4 +102,4 @@ class GroqModel(LCModelComponent):
             streaming=stream,
         )
 
-        return output
+        return output

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

@@ -1,4 +1,3 @@
-from typing import Optional
 
 from langchain_community.chat_models.huggingface import ChatHuggingFace
 from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
@@ -65,4 +64,4 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
             raise ValueError("Could not connect to HuggingFace Endpoints API.") from e
 
         output = ChatHuggingFace(llm=llm)
-        return output
+        return output

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

@@ -1,4 +1,3 @@
-from typing import Any, Dict, List, Optional
 
 from langchain_community.chat_models import ChatOllama
 from langflow.base.constants import STREAM_INFO_TEXT
@@ -226,4 +225,4 @@ class ChatOllamaComponent(LCModelComponent):
         except Exception as e:
             raise ValueError("Could not initialize Ollama LLM.") from e
 
-        return output
+        return output

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

@@ -21,7 +21,6 @@ from langflow.type_extraction.type_extraction import (
     extract_union_types_from_generic_alias,
 )
 from langflow.utils import validate
-from pydantic import BaseModel
 
 if TYPE_CHECKING:
     from langflow.graph.graph.base import Graph

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

@@ -13,7 +13,7 @@ from langflow.graph.utils import UnbuiltObject, UnbuiltResult
 from langflow.interface.initialize import loading
 from langflow.interface.listing import lazy_load_dict
 from langflow.schema.artifact import ArtifactType
-from langflow.schema.schema import INPUT_FIELD_NAME, Log, build_logs
+from langflow.schema.schema import INPUT_FIELD_NAME, Log
 from langflow.services.deps import get_storage_service
 from langflow.services.monitor.utils import log_transaction
 from langflow.utils.constants import DIRECT_TYPES

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

@@ -117,51 +117,3 @@ def set_langchain_cache(settings):
             logger.warning(f"Could not import {cache_type}. ")
     else:
         logger.info("No LLM cache set.")
-
-
-def build_template_from_class(name: str, type_to_cls_dict: Dict, add_function: bool = False):
-    classes = [item.__name__ for item in type_to_cls_dict.values()]
-
-    # Raise error if name is not in chains
-    if name not in classes:
-        raise ValueError(f"{name} not found.")
-
-    for _type, v in type_to_cls_dict.items():
-        if v.__name__ == name:
-            _class = v
-
-            # Get the docstring
-            docs = parse(_class.__doc__)
-
-            variables = {"_type": _type}
-
-            if "__fields__" in _class.__dict__:
-                for class_field_items, value in _class.__fields__.items():
-                    if class_field_items in ["callback_manager"]:
-                        continue
-                    variables[class_field_items] = {}
-                    for name_, value_ in value.__repr_args__():
-                        if name_ == "default_factory":
-                            try:
-                                variables[class_field_items]["default"] = get_default_factory(
-                                    module=_class.__base__.__module__,
-                                    function=value_,
-                                )
-                            except Exception:
-                                variables[class_field_items]["default"] = None
-                        elif name_ not in ["name"]:
-                            variables[class_field_items][name_] = value_
-
-                    variables[class_field_items]["placeholder"] = (
-                        docs.params[class_field_items] if class_field_items in docs.params else ""
-                    )
-            base_classes = get_base_classes(_class)
-            # Adding function to base classes to allow
-            # the output to be a function
-            if add_function:
-                base_classes.append("Callable")
-            return {
-                "template": format_dict(variables, name),
-                "description": docs.short_description or "",
-                "base_classes": base_classes,
-            }

src/backend/base/langflow/schema/schema.py

@@ -1,4 +1,4 @@
-from typing import Any, Literal
+from typing import Literal
 
 from typing_extensions import TypedDict