fix: change ref, lint

.pre-commit-config.yaml

@@ -7,16 +7,18 @@ repos:
         language: system
         types: [python]
         files: ^lib/crewai/src/
+        exclude: ^lib/crewai/
       - id: ruff-format
         name: ruff-format
         entry: uv run ruff format
         language: system
         types: [python]
         files: ^lib/crewai/src/
+        exclude: ^lib/crewai/
       - id: mypy
         name: mypy
         entry: uv run mypy
         language: system
         types: [python]
         files: ^lib/crewai/src/
-        exclude: ^lib/crewai/tests/
+        exclude: ^lib/crewai/

lib/crewai/src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py

@@ -1,7 +1,6 @@
 from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
 from crewai.agents.agent_builder.base_agent import BaseAgent
-from typing import List
+from crewai.project import CrewBase, agent, crew, task
 
 # If you want to run a snippet of code before or after the crew starts,
 # you can use the @before_kickoff and @after_kickoff decorators
@@ -12,8 +11,8 @@ from typing import List
 class PoemCrew:
     """Poem Crew"""
 
-    agents: List[BaseAgent]
-    tasks: List[Task]
+    agents: list[BaseAgent]
+    tasks: list[Task]
 
     # Learn more about YAML configuration files here:
     # Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended

lib/crewai/src/crewai/cli/templates/flow/tools/custom_tool.py

@@ -1,7 +1,6 @@
-from typing import Type
+from pydantic import BaseModel, Field
 
 from crewai.tools import BaseTool
-from pydantic import BaseModel, Field
 
 
 class MyCustomToolInput(BaseModel):
@@ -12,10 +11,8 @@ class MyCustomToolInput(BaseModel):
 
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
-    description: str = (
-        "Clear description for what this tool is useful for, your agent will need this information to use it."
-    )
-    args_schema: Type[BaseModel] = MyCustomToolInput
+    description: str = "Clear description for what this tool is useful for, your agent will need this information to use it."
+    args_schema: type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here

lib/crewai/src/crewai/context.py

@@ -1,21 +1,23 @@
-import os
 import contextvars
-from typing import Optional
+import os
 from contextlib import contextmanager
 
-_platform_integration_token: contextvars.ContextVar[Optional[str]] = contextvars.ContextVar(
-    "platform_integration_token", default=None
+_platform_integration_token: contextvars.ContextVar[str | None] = (
+    contextvars.ContextVar("platform_integration_token", default=None)
 )
 
+
 def set_platform_integration_token(integration_token: str) -> None:
     _platform_integration_token.set(integration_token)
 
-def get_platform_integration_token() -> Optional[str]:
+
+def get_platform_integration_token() -> str | None:
     token = _platform_integration_token.get()
     if token is None:
         token = os.getenv("CREWAI_PLATFORM_INTEGRATION_TOKEN")
     return token
 
+
 @contextmanager
 def platform_context(integration_token: str):
     token = _platform_integration_token.set(integration_token)

lib/crewai/src/crewai/project/__init__.py

@@ -14,16 +14,16 @@ from .annotations import (
 from .crew_base import CrewBase
 
 __all__ = [
+    "CrewBase",
+    "after_kickoff",
     "agent",
+    "before_kickoff",
+    "cache_handler",
+    "callback",
     "crew",
-    "task",
+    "llm",
     "output_json",
     "output_pydantic",
+    "task",
     "tool",
-    "callback",
-    "CrewBase",
-    "llm",
-    "cache_handler",
-    "before_kickoff",
-    "after_kickoff",
 ]

lib/crewai/src/crewai/project/annotations.py

@@ -1,5 +1,5 @@
+from collections.abc import Callable
 from functools import wraps
-from typing import Callable
 
 from crewai import Crew
 from crewai.project.utils import memoize

lib/crewai/src/crewai/rag/chromadb/client.py

@@ -31,7 +31,7 @@ from crewai.rag.core.base_client import (
     BaseCollectionParams,
 )
 from crewai.rag.types import SearchResult
-from crewai.core.utilities.logger_utils import suppress_logging
+from crewai.utilities.logger_utils import suppress_logging
 
 
 class ChromaDBClient(BaseClient):

lib/crewai/src/crewai/rag/chromadb/constants.py

@@ -3,7 +3,7 @@
 import re
 from typing import Final
 
-from crewai.core.utilities.paths import db_storage_path
+from crewai.utilities.paths import db_storage_path
 
 DEFAULT_TENANT: Final[str] = "default_tenant"
 DEFAULT_DATABASE: Final[str] = "default_database"

lib/crewai/src/crewai/rag/config/utils.py

@@ -11,7 +11,7 @@ from crewai.rag.config.constants import (
 from crewai.rag.config.types import RagConfigType
 from crewai.rag.core.base_client import BaseClient
 from crewai.rag.factory import create_client
-from crewai.core.utilities.import_utils import require
+from crewai.utilities.import_utils import require
 
 
 class RagContext(BaseModel):

lib/crewai/src/crewai/rag/embeddings/factory.py

@@ -9,7 +9,7 @@ from typing_extensions import deprecated
 
 from crewai.rag.core.base_embeddings_callable import EmbeddingFunction
 from crewai.rag.core.base_embeddings_provider import BaseEmbeddingsProvider
-from crewai.core.utilities.import_utils import import_and_validate_definition
+from crewai.utilities.import_utils import import_and_validate_definition
 
 if TYPE_CHECKING:
     from chromadb.utils.embedding_functions.amazon_bedrock_embedding_function import (

lib/crewai/src/crewai/rag/factory.py

@@ -8,7 +8,7 @@ from crewai.rag.config.optional_imports.protocols import (
 )
 from crewai.rag.config.types import RagConfigType
 from crewai.rag.core.base_client import BaseClient
-from crewai.core.utilities.import_utils import require
+from crewai.utilities.import_utils import require
 
 
 def create_client(config: RagConfigType) -> BaseClient:

lib/crewai/src/crewai/rag/qdrant/constants.py

@@ -5,7 +5,7 @@ from typing import Final
 
 from qdrant_client.models import Distance, VectorParams
 
-from crewai.core.utilities.paths import db_storage_path
+from crewai.utilities.paths import db_storage_path
 
 DEFAULT_VECTOR_PARAMS: Final = VectorParams(size=384, distance=Distance.COSINE)
 DEFAULT_EMBEDDING_MODEL: Final[str] = "sentence-transformers/all-MiniLM-L6-v2"