Merge branch 'main' into fix-knowledgestorage-default-instantiation

src/crewai/agent.py

@@ -23,7 +23,6 @@ from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_F
 from crewai.utilities.converter import generate_model_description
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
-from crewai.utilities.typing import AgentConfig
 
 agentops = None
 
@@ -89,7 +88,6 @@ class Agent(BaseAgent):
     function_calling_llm: Optional[Any] = Field(
         description="Language model that will run the agent.", default=None
     )
-    config: Optional[Union[Dict[str, Any], AgentConfig]] = Field(default=None)
     system_template: Optional[str] = Field(
         default=None, description="System format for the agent."
     )

src/crewai/knowledge/knowledge.py

@@ -14,13 +14,13 @@ class Knowledge(BaseModel):
     Knowledge is a collection of sources and setup for the vector store to save and query relevant context.
     Args:
         sources: List[BaseKnowledgeSource] = Field(default_factory=list)
-        storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+        storage: Optional[KnowledgeStorage] = Field(default=None)
         embedder_config: Optional[Dict[str, Any]] = None
     """
 
     sources: List[BaseKnowledgeSource] = Field(default_factory=list)
     model_config = ConfigDict(arbitrary_types_allowed=True)
-    storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+    storage: Optional[KnowledgeStorage] = Field(default=None)
     embedder_config: Optional[Dict[str, Any]] = None
     collection_name: Optional[str] = None
 

src/crewai/knowledge/source/base_file_knowledge_source.py

@@ -22,7 +22,7 @@ class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
         default_factory=list, description="The path to the file"
     )
     content: Dict[Path, str] = Field(init=False, default_factory=dict)
-    storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+    storage: Optional[KnowledgeStorage] = Field(default=None)
     safe_file_paths: List[Path] = Field(default_factory=list)
 
     @field_validator("file_path", "file_paths", mode="before")
@@ -62,7 +62,10 @@ class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
 
     def _save_documents(self):
         """Save the documents to the storage."""
-        self.storage.save(self.chunks)
+        if self.storage:
+            self.storage.save(self.chunks)
+        else:
+            raise ValueError("No storage found to save documents.")
 
     def convert_to_path(self, path: Union[Path, str]) -> Path:
         """Convert a path to a Path object."""

src/crewai/knowledge/source/base_knowledge_source.py

@@ -16,7 +16,7 @@ class BaseKnowledgeSource(BaseModel, ABC):
     chunk_embeddings: List[np.ndarray] = Field(default_factory=list)
 
     model_config = ConfigDict(arbitrary_types_allowed=True)
-    storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+    storage: Optional[KnowledgeStorage] = Field(default=None)
     metadata: Dict[str, Any] = Field(default_factory=dict)  # Currently unused
     collection_name: Optional[str] = Field(default=None)
 
@@ -46,4 +46,7 @@ class BaseKnowledgeSource(BaseModel, ABC):
         Save the documents to the storage.
         This method should be called after the chunks and embeddings are generated.
         """
-        self.storage.save(self.chunks)
+        if self.storage:
+            self.storage.save(self.chunks)
+        else:
+            raise ValueError("No storage found to save documents.")

src/crewai/project/annotations.py

@@ -16,12 +16,6 @@ def after_kickoff(func):
 
 
 def task(func):
-    """Decorator to mark a method as a task creator.
-    
-    When applied to a method in a class decorated with @CrewBase,
-    this makes the method's return value accessible as an element
-    of the self.tasks list.
-    """
     func.is_task = True
 
     @wraps(func)
@@ -35,12 +29,6 @@ def task(func):
 
 
 def agent(func):
-    """Decorator to mark a method as an agent creator.
-    
-    When applied to a method in a class decorated with @CrewBase,
-    this makes the method's return value accessible as an element
-    of the self.agents list.
-    """
     func.is_agent = True
     func = memoize(func)
     return func

src/crewai/project/crew_base.py

@@ -1,6 +1,6 @@
 import inspect
 from pathlib import Path
-from typing import Any, Callable, Dict, List, TypeVar, cast
+from typing import Any, Callable, Dict, TypeVar, cast
 
 import yaml
 from dotenv import load_dotenv
@@ -66,9 +66,6 @@ def CrewBase(cls: T) -> T:
             self._kickoff = self._filter_functions(
                 self._original_functions, "is_kickoff"
             )
-            
-            self.agents = []  # type: List[Any]
-            self.tasks = []   # type: List[Any]
 
         @staticmethod
         def load_yaml(config_path: Path):

src/crewai/task.py

@@ -41,7 +41,6 @@ from crewai.tools.base_tool import BaseTool
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter, convert_to_model
 from crewai.utilities.i18n import I18N
-from crewai.utilities.typing import TaskConfig
 
 
 class Task(BaseModel):
@@ -75,7 +74,7 @@ class Task(BaseModel):
     expected_output: str = Field(
         description="Clear definition of expected output for the task."
     )
-    config: Optional[Union[Dict[str, Any], TaskConfig]] = Field(
+    config: Optional[Dict[str, Any]] = Field(
         description="Configuration for the agent",
         default=None,
     )

src/crewai/utilities/typing/__init__.py

@@ -1,14 +0,0 @@
-from typing import Dict, List, Optional, Any, TypedDict, Union
-
-class AgentConfig(TypedDict, total=False):
-    """TypedDict for agent configuration loaded from YAML."""
-    role: str
-    goal: str
-    backstory: str
-    verbose: bool
-
-class TaskConfig(TypedDict, total=False):
-    """TypedDict for task configuration loaded from YAML."""
-    description: str
-    expected_output: str
-    agent: str  # Role of the agent to execute this task

tests/typing_test.py

@@ -1,55 +0,0 @@
-from typing import Dict, Any
-
-import pytest
-
-from crewai.agent import Agent
-from crewai.task import Task
-from crewai.utilities.typing import AgentConfig, TaskConfig
-
-
-def test_agent_with_config_dict():
-    config: AgentConfig = {
-        "role": "Test Agent", 
-        "goal": "Test Goal", 
-        "backstory": "Test Backstory",
-        "verbose": True
-    }
-    
-    agent = Agent(config=config)
-    
-    assert agent.role == "Test Agent"
-    assert agent.goal == "Test Goal"
-    assert agent.backstory == "Test Backstory"
-    assert agent.verbose is True
-
-
-def test_agent_with_yaml_config():
-    config: Dict[str, Any] = {
-        "researcher": {
-            "role": "Researcher",
-            "goal": "Research Goal",
-            "backstory": "Researcher Backstory",
-            "verbose": True
-        }
-    }
-    
-    agent = Agent(config=config["researcher"])
-    
-    assert agent.role == "Researcher"
-    assert agent.goal == "Research Goal"
-    assert agent.backstory == "Researcher Backstory"
-
-
-def test_task_with_config_dict():
-    config: TaskConfig = {
-        "description": "Test Task",
-        "expected_output": "Test Output",
-        "agent": "researcher"
-    }
-    
-    agent = Agent(role="Researcher", goal="Goal", backstory="Backstory")
-    task = Task(config=config, agent=agent)
-    
-    assert task.description == "Test Task"
-    assert task.expected_output == "Test Output"
-    assert task.agent == agent