Fix linter issues

cognee/api/v1/permissions/routers/get_permissions_router.py

@@ -47,7 +47,7 @@ def get_permissions_router() -> APIRouter:
                     group_id=group.id, permission_id=permission_entity.id
                 )
             )
-        except IntegrityError as e:
+        except IntegrityError:
             raise EntityAlreadyExistsError(message="Group permission already exists.")
 
         await db.session.commit()
@@ -70,7 +70,7 @@ def get_permissions_router() -> APIRouter:
             # Add association directly to the association table
             stmt = insert(UserGroup).values(user_id=user_id, group_id=group_id)
             await db.session.execute(stmt)
-        except IntegrityError as e:
+        except IntegrityError:
             raise EntityAlreadyExistsError(message="User is already part of group.")
 
         await db.session.commit()

cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py

@@ -87,7 +87,7 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine):
 
         except litellm.exceptions.RateLimitError:
             if self.retry_count >= self.MAX_RETRIES:
-                raise Exception(f"Rate limit exceeded and no more retries left.")
+                raise Exception("Rate limit exceeded and no more retries left.")
 
             await exponential_backoff(self.retry_count)
 

cognee/modules/users/get_user_db.py

@@ -1,5 +1,6 @@
 from typing import AsyncGenerator
 from fastapi import Depends
+from contextlib import asynccontextmanager
 from sqlalchemy.ext.asyncio import AsyncSession
 from fastapi_users.db import SQLAlchemyUserDatabase
 from cognee.infrastructure.databases.relational import get_relational_engine
@@ -16,6 +17,6 @@ async def get_user_db(session: AsyncSession = Depends(get_async_session)):
     yield SQLAlchemyUserDatabase(session, User)
 
 
-from contextlib import asynccontextmanager
+
 
 get_user_db_context = asynccontextmanager(get_user_db)

cognee/shared/utils.py

@@ -8,17 +8,19 @@ import hashlib
 from datetime import datetime, timezone
 import graphistry
 import networkx as nx
-import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
 import tiktoken
 import nltk
 import base64
-import networkx as nx
-from bokeh.io import output_file, save
 from bokeh.plotting import figure, from_networkx
 from bokeh.models import Circle, MultiLine, HoverTool, ColumnDataSource, Range1d
+from bokeh.plotting import output_file, show
 
+from bokeh.embed import file_html
+from bokeh.resources import CDN
+import cairosvg
+import logging
 
 from cognee.base_config import get_base_config
 from cognee.infrastructure.databases.graph import get_graph_engine
@@ -272,16 +274,7 @@ def extract_pos_tags(sentence):
     return pos_tags
 
 
-import networkx as nx
-from bokeh.plotting import figure, output_file, show
-from bokeh.models import Circle, MultiLine, HoverTool, Range1d
-from bokeh.io import output_notebook
-from bokeh.embed import file_html
-from bokeh.resources import CDN
-from bokeh.plotting import figure, from_networkx
-import base64
-import cairosvg
-import logging
+
 
 logging.basicConfig(level=logging.INFO)
 

cognee/tests/unit/interfaces/graph/get_graph_from_model_test.py

@@ -49,7 +49,7 @@ async def get_graph_from_model_test():
     for document_chunk in document_chunks:
         document_chunk.contains.append(
             Entity(
-                name=f"Entity",
+                name="Entity",
                 is_type=EntityType(
                     name="Type 1",
                 ),

cognee/tests/unit/processing/utils/utils_test.py

@@ -102,8 +102,6 @@ def test_prepare_nodes():
     assert len(nodes_df) == 1
 
 
-from unittest.mock import DEFAULT
-
 
 def test_create_cognee_style_network_with_logo():
     import networkx as nx

evals/simple_rag_vs_cognee_eval.py

@@ -1,14 +1,19 @@
 from deepeval.dataset import EvaluationDataset
 from pydantic import BaseModel
-
+import os
 
 from typing import List, Type
 from deepeval.test_case import LLMTestCase
 import dotenv
+from cognee.infrastructure.llm.get_llm_client import get_llm_client
+from cognee.infrastructure.databases.vector import get_vector_engine
+from cognee.base_config import get_base_config
 
+import logging
+
+logger = logging.getLogger(__name__)
 dotenv.load_dotenv()
 
-from cognee.infrastructure.llm.get_llm_client import get_llm_client
 
 dataset = EvaluationDataset()
 dataset.add_test_cases_from_json_file(
@@ -39,9 +44,6 @@ print(dataset.goldens)
 print(dataset)
 
 
-import logging
-
-logger = logging.getLogger(__name__)
 
 
 class AnswerModel(BaseModel):
@@ -78,9 +80,6 @@ async def run_cognify_base_rag():
     pass
 
 
-import os
-from cognee.base_config import get_base_config
-from cognee.infrastructure.databases.vector import get_vector_engine
 
 
 async def cognify_search_base_rag(content: str, context: str):