linting

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

@@ -1,5 +1,4 @@
-import contextlib
+from typing import Dict, List
-from typing import Dict, Iterable
 
 from langchain.agents import loading
 
@@ -33,7 +32,8 @@ class AgentCreator(LangChainTypeCreator):
             raise ValueError("Agent not found") from exc
 
     # Now this is a generator
-    def to_list(self) -> Iterable:
+    def to_list(self) -> List[str]:
+        names = []
         for name, agent in self.type_to_loader_dict.items():
             agent_name = (
                 agent.function_name()
@@ -41,7 +41,8 @@ class AgentCreator(LangChainTypeCreator):
                 else agent.__name__
             )
             if agent_name in settings.agents or settings.dev:
-                yield agent_name
+                names.append(name)
+        return names
 
 
 agent_creator = AgentCreator()

src/backend/langflow/interface/agents/prebuilt.py

@@ -1,4 +1,3 @@
-from typing import Optional
 
 from langchain import LLMChain
 from langchain.agents import AgentExecutor, ZeroShotAgent
@@ -6,7 +5,6 @@ from langchain.agents.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
 from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
 from langchain.schema import BaseLanguageModel
-from pydantic import BaseModel
 
 
 class MalfoyAgent(AgentExecutor):

src/backend/langflow/interface/prompts/custom.py

@@ -1,4 +1,4 @@
-from typing import Any, List, Optional
+from typing import List, Optional
 
 from langchain.prompts import PromptTemplate
 from langflow.graph.utils import extract_input_variables_from_prompt
@@ -13,8 +13,8 @@ You must know all of the knowledge of {character}."""
 
 
 class BaseCustomPrompt(PromptTemplate):
-    template: Optional[str] = None
+    template: str = ""
-    description: str
+    description: Optional[str]
     human_text: str = "\n {input}"
 
     @root_validator(pre=False)
@@ -41,17 +41,19 @@ class BaseCustomPrompt(PromptTemplate):
                     for field in self.input_variables
                 ],
             ),
-            description=self.description,
+            description=self.description or "",
         )
 
 
 class SeriesCharacterPrompt(BaseCustomPrompt):
     # Add a very descriptive description for the prompt generator
-    description = "A prompt that asks the AI to act like a character from a series."
+    description: Optional[
+        str
+    ] = "A prompt that asks the AI to act like a character from a series."
     character: str
     series: str
     human_text: str = "\n {input}"
-    template: Optional[str] = CHARACTER_PROMPT
+    template: str = CHARACTER_PROMPT
 
     input_variables: List[str] = ["character", "series"]
 

src/backend/langflow/template/base.py

@@ -162,7 +162,7 @@ class FrontendNode(BaseModel):
         # Check for list type
         if "List" in _type:
             _type = _type.replace("List[", "")[:-1]
-            self.is_list = True
+            field.is_list = True
 
         # Replace 'Mapping' with 'dict'
         if "Mapping" in _type:

src/backend/langflow/template/nodes.py

@@ -1,3 +1,4 @@
+from typing import Optional
 from langchain.agents.mrkl import prompt
 
 from langflow.template.base import FrontendNode, Template, TemplateField
@@ -194,7 +195,7 @@ class InitializeAgentNode(FrontendNode):
         return super().to_dict()
 
     @staticmethod
-    def format_field(field: TemplateField, name: str):
+    def format_field(field: TemplateField, name: Optional[str] = None) -> None:
         # do nothing and don't return anything
         pass
 

tests/conftest.py

@@ -2,7 +2,6 @@ from pathlib import Path
 
 import pytest
 from fastapi.testclient import TestClient
-from langflow.graph.graph import Graph
 
 
 def pytest_configure():

tests/test_template.py

@@ -1,5 +1,4 @@
 import importlib
-import re
 from typing import Dict, List, Optional
 
 import pytest