fix linter failures

Author: esxr

backend/app/api/assistants.py

@@ -94,7 +94,9 @@ async def delete_assistant(
     assistant = await storage.get_assistant(user["user_id"], aid)
     if not assistant:
         raise HTTPException(status_code=404, detail="Assistant not found")
-    if not assistant.get('public') and assistant.get('user_id') != user["user_id"]:
-        raise HTTPException(status_code=403, detail="Unauthorized to delete this assistant")
+    if not assistant.get("public") and assistant.get("user_id") != user["user_id"]:
+        raise HTTPException(
+            status_code=403, detail="Unauthorized to delete this assistant"
+        )
     await storage.delete_assistant(user["user_id"], aid)
     return {"status": "ok"}

backend/app/auth/handlers.py

@@ -41,12 +41,10 @@ async def __call__(self, request: Request) -> User:
         return user
 
     @abstractmethod
-    def decode_token(self, token: str, decode_key: str) -> dict:
-        ...
+    def decode_token(self, token: str, decode_key: str) -> dict: ...
 
     @abstractmethod
-    def get_decode_key(self, token: str) -> str:
-        ...
+    def get_decode_key(self, token: str) -> str: ...
 
 
 class JWTAuthLocal(JWTAuthBase):

backend/app/auth/settings.py

@@ -39,8 +39,7 @@ def set_decode_key(cls, v, values):
         return b64decode(values["decode_key_b64"]).decode("utf-8")
 
 
-class JWTSettingsOIDC(JWTSettingsBase):
-    ...
+class JWTSettingsOIDC(JWTSettingsBase): ...
 
 
 class Settings(BaseSettings):

backend/app/chatbot.py

@@ -1,11 +1,12 @@
 from typing import Annotated, List
 
-from app.message_types import add_messages_liberal
 from langchain_core.language_models.base import LanguageModelLike
 from langchain_core.messages import BaseMessage, SystemMessage
 from langgraph.checkpoint import BaseCheckpointSaver
 from langgraph.graph.state import StateGraph
 
+from app.message_types import add_messages_liberal
+
 
 def get_chatbot_executor(
     llm: LanguageModelLike,

backend/app/ingest.py

@@ -6,6 +6,7 @@
 This code should be agnostic to how the blob got generated; i.e., it does not
 know about server/uploading etc.
 """
+
 from typing import List
 
 from langchain.text_splitter import TextSplitter

backend/app/message_types.py

@@ -6,7 +6,7 @@
     MessageLikeRepresentation,
     ToolMessage,
 )
-from langgraph.graph.message import add_messages, Messages
+from langgraph.graph.message import Messages, add_messages
 
 
 class LiberalFunctionMessage(FunctionMessage):
@@ -18,7 +18,7 @@ class LiberalToolMessage(ToolMessage):
 
 
 def _convert_pydantic_dict_to_message(
-    data: MessageLikeRepresentation
+    data: MessageLikeRepresentation,
 ) -> MessageLikeRepresentation:
     if (
         isinstance(data, dict)

backend/app/parsing.py

@@ -1,4 +1,5 @@
 """Module contains logic for parsing binary blobs into text."""
+
 from langchain_community.document_loaders.parsers import BS4HTMLParser, PDFMinerParser
 from langchain_community.document_loaders.parsers.generic import MimeTypeBasedParser
 from langchain_community.document_loaders.parsers.msword import MsWordParser

backend/app/storage.py

@@ -212,16 +212,10 @@ async def delete_thread(user_id: str, thread_id: str):
 
 
 async def delete_assistant(user_id: str, assistant_id: str):
-    """Delete an assistant by ID.
-    
-    Args:
-        user_id: The user's ID.
-        assistant_id: The assistant's ID.
-        
-    """
+    """Delete an assistant by ID."""
     async with get_pg_pool().acquire() as conn:
         await conn.execute(
             "DELETE FROM assistant WHERE assistant_id = $1 AND user_id = $2",
             assistant_id,
             user_id,
-        )
+        )

backend/app/tools.py

@@ -60,8 +60,7 @@ class AvailableTools(str, Enum):
     DALL_E = "dall_e"
 
 
-class ToolConfig(TypedDict):
-    ...
+class ToolConfig(TypedDict): ...
 
 
 class BaseTool(BaseModel):

backend/app/upload.py

@@ -12,8 +12,8 @@
 import os
 from typing import BinaryIO, List, Optional
 
-from langchain_core.document_loaders.blob_loaders import Blob
 from langchain_community.vectorstores.pgvector import PGVector
+from langchain_core.document_loaders.blob_loaders import Blob
 from langchain_core.runnables import (
     ConfigurableField,
     RunnableConfig,

backend/tests/unit_tests/agent_executor/test_parsing.py

@@ -1,4 +1,5 @@
 """Test parsing logic."""
+
 import mimetypes
 
 from langchain_community.document_loaders import Blob

backend/tests/unit_tests/utils.py

@@ -1,4 +1,5 @@
 """Test ingestion utilities."""
+
 from typing import Any, Dict, Iterable, List, Optional, Sequence, Type
 
 from langchain.schema import Document