clean up. fix type safety. address memory config docs

docs/concepts/memory.mdx

@@ -185,7 +185,12 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=OpenAIEmbeddingFunction(api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"),
+    embedder={
+        "provider": "openai",
+        "config": {
+            "model": 'text-embedding-3-small'
+        }
+    }
 )
 ```
 
@@ -242,13 +247,16 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=OpenAIEmbeddingFunction(
+    embedder={
-        api_key="YOUR_API_KEY",
+        "provider": "openai",
-        api_base="YOUR_API_BASE_PATH",
+        "config": {
-        api_type="azure",
+            "api_key": "YOUR_API_KEY",
-        api_version="YOUR_API_VERSION",
+            "api_base": "YOUR_API_BASE_PATH",
-        model_name="text-embedding-3-small"
+            "api_type": "azure",
-    )
+            "api_version": "YOUR_API_VERSION",
+            "model_name": 'text-embedding-3-small'
+        }
+    }
 )
 ```
 
@@ -264,12 +272,15 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=GoogleVertexEmbeddingFunction(
+    embedder={
-        project_id="YOUR_PROJECT_ID",
+        "provider": "vertexai",
-        region="YOUR_REGION",
+        "config": {
-        api_key="YOUR_API_KEY",
+            "project_id"="YOUR_PROJECT_ID",
-        model_name="textembedding-gecko"
+            "region"="YOUR_REGION",
-    )
+            "api_key"="YOUR_API_KEY",
+            "model_name"="textembedding-gecko"
+        }
+    }
 )
 ```
 

src/crewai/agent.py

@@ -1,6 +1,6 @@
 import shutil
 import subprocess
-from typing import Any, Dict, List, Literal, Optional, Union
+from typing import Any, Dict, List, Literal, Optional, Sequence, Union
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -54,7 +54,6 @@ class Agent(BaseAgent):
             llm: The language model that will run the agent.
             function_calling_llm: The language model that will handle the tool calling for this agent, it overrides the crew function_calling_llm.
             max_iter: Maximum number of iterations for an agent to execute a task.
-            memory: Whether the agent should have memory or not.
             max_rpm: Maximum number of requests per minute for the agent execution to be respected.
             verbose: Whether the agent execution should be in verbose mode.
             allow_delegation: Whether the agent is allowed to delegate tasks to other agents.
@@ -71,9 +70,7 @@ class Agent(BaseAgent):
     )
     agent_ops_agent_name: str = None  # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
     agent_ops_agent_id: str = None  # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
-    cache_handler: InstanceOf[CacheHandler] = Field(
+
-        default=None, description="An instance of the CacheHandler class."
-    )
     step_callback: Optional[Any] = Field(
         default=None,
         description="Callback to be executed after each step of the agent execution.",
@@ -107,10 +104,6 @@ class Agent(BaseAgent):
         default=True,
         description="Keep messages under the context window size by summarizing content.",
     )
-    max_iter: int = Field(
-        default=20,
-        description="Maximum number of iterations for an agent to execute a task before giving it's best answer",
-    )
     max_retry_limit: int = Field(
         default=2,
         description="Maximum number of retries for an agent to execute a task when an error occurs.",
@@ -195,13 +188,15 @@ class Agent(BaseAgent):
             if task.output_json:
                 # schema = json.dumps(task.output_json, indent=2)
                 schema = generate_model_description(task.output_json)
+                task_prompt += "\n" + self.i18n.slice(
+                    "formatted_task_instructions"
+                ).format(output_format=schema)
 
             elif task.output_pydantic:
                 schema = generate_model_description(task.output_pydantic)
-
+                task_prompt += "\n" + self.i18n.slice(
-            task_prompt += "\n" + self.i18n.slice("formatted_task_instructions").format(
+                    "formatted_task_instructions"
-                output_format=schema
+                ).format(output_format=schema)
-            )
 
         if context:
             task_prompt = self.i18n.slice("task_with_context").format(
@@ -329,14 +324,14 @@ class Agent(BaseAgent):
         tools = agent_tools.tools()
         return tools
 
-    def get_multimodal_tools(self) -> List[Tool]:
+    def get_multimodal_tools(self) -> Sequence[BaseTool]:
         from crewai.tools.agent_tools.add_image_tool import AddImageTool
 
         return [AddImageTool()]
 
     def get_code_execution_tools(self):
         try:
-            from crewai_tools import CodeInterpreterTool
+            from crewai_tools import CodeInterpreterTool  # type: ignore
 
             # Set the unsafe_mode based on the code_execution_mode attribute
             unsafe_mode = self.code_execution_mode == "unsafe"

src/crewai/agents/agent_builder/base_agent.py

@@ -24,6 +24,7 @@ from crewai.tools import BaseTool
 from crewai.tools.base_tool import Tool
 from crewai.utilities import I18N, Logger, RPMController
 from crewai.utilities.config import process_config
+from crewai.utilities.converter import Converter
 
 T = TypeVar("T", bound="BaseAgent")
 
@@ -42,7 +43,7 @@ class BaseAgent(ABC, BaseModel):
         max_rpm (Optional[int]): Maximum number of requests per minute for the agent execution.
         allow_delegation (bool): Allow delegation of tasks to agents.
         tools (Optional[List[Any]]): Tools at the agent's disposal.
-        max_iter (Optional[int]): Maximum iterations for an agent to execute a task.
+        max_iter (int): Maximum iterations for an agent to execute a task.
         agent_executor (InstanceOf): An instance of the CrewAgentExecutor class.
         llm (Any): Language model that will run the agent.
         crew (Any): Crew to which the agent belongs.
@@ -114,7 +115,7 @@ class BaseAgent(ABC, BaseModel):
     tools: Optional[List[Any]] = Field(
         default_factory=list, description="Tools at agents' disposal"
     )
-    max_iter: Optional[int] = Field(
+    max_iter: int = Field(
         default=25, description="Maximum iterations for an agent to execute a task"
     )
     agent_executor: InstanceOf = Field(
@@ -125,11 +126,12 @@ class BaseAgent(ABC, BaseModel):
     )
     crew: Any = Field(default=None, description="Crew to which the agent belongs.")
     i18n: I18N = Field(default=I18N(), description="Internationalization settings.")
-    cache_handler: InstanceOf[CacheHandler] = Field(
+    cache_handler: Optional[InstanceOf[CacheHandler]] = Field(
         default=None, description="An instance of the CacheHandler class."
     )
     tools_handler: InstanceOf[ToolsHandler] = Field(
-        default=None, description="An instance of the ToolsHandler class."
+        default_factory=ToolsHandler,
+        description="An instance of the ToolsHandler class.",
     )
     max_tokens: Optional[int] = Field(
         default=None, description="Maximum number of tokens for the agent's execution."
@@ -254,7 +256,7 @@ class BaseAgent(ABC, BaseModel):
     @abstractmethod
     def get_output_converter(
         self, llm: Any, text: str, model: type[BaseModel] | None, instructions: str
-    ):
+    ) -> Converter:
         """Get the converter class for the agent to create json/pydantic outputs."""
         pass
 

src/crewai/memory/entity/entity_memory.py

@@ -11,7 +11,7 @@ class EntityMemory(Memory):
     """
 
     def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
-        if hasattr(crew, "memory_config") and crew.memory_config is not None:
+        if crew and hasattr(crew, "memory_config") and crew.memory_config is not None:
             self.memory_provider = crew.memory_config.get("provider")
         else:
             self.memory_provider = None

src/crewai/memory/memory.py

@@ -1,14 +1,16 @@
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Union
+
+from pydantic import BaseModel
 
 from crewai.memory.storage.rag_storage import RAGStorage
 
 
-class Memory:
+class Memory(BaseModel):
     """
     Base class for memory, now supporting agent tags and generic metadata.
     """
 
-    def __init__(self, storage: RAGStorage):
+    def __init__(self, storage: Union[RAGStorage, Any]):
         self.storage = storage
 
     def save(

src/crewai/tools/agent_tools/add_image_tool.py

@@ -7,11 +7,11 @@ from crewai.utilities import I18N
 
 i18n = I18N()
 
+
 class AddImageToolSchema(BaseModel):
     image_url: str = Field(..., description="The URL or path of the image to add")
     action: Optional[str] = Field(
-        default=None,
+        default=None, description="Optional context or question about the image"
-        description="Optional context or question about the image"
     )
 
 
@@ -36,10 +36,7 @@ class AddImageTool(BaseTool):
                 "image_url": {
                     "url": image_url,
                 },
-            }
+            },
         ]
 
-        return {
+        return {"role": "user", "content": content}
-            "role": "user",
-            "content": content
-        }