Refactoring task cache to be a tool (#50)

* Refactoring task cache to be a tool

The previous implementation of the task caching system was early exiting
the agent executor due to the fact it was returning an AgentFinish object.

This now refactors it to use a cache specific tool that is dynamically
added and forced into the agent in case of a task execution that was
already executed with the same input.

crewai/agent.py

@@ -1,7 +1,6 @@
 import uuid
 from typing import Any, List, Optional
 
-from langchain.agents import AgentExecutor
 from langchain.agents.format_scratchpad import format_log_to_str
 from langchain.chat_models import ChatOpenAI
 from langchain.memory import ConversationSummaryMemory
@@ -18,7 +17,12 @@ from pydantic import (
 )
 from pydantic_core import PydanticCustomError
 
-from crewai.agents import CacheHandler, CrewAgentOutputParser, ToolsHandler
+from crewai.agents import (
+    CacheHandler,
+    CrewAgentExecutor,
+    CrewAgentOutputParser,
+    ToolsHandler,
+)
 from crewai.prompts import Prompts
 
 
@@ -29,7 +33,7 @@ class Agent(BaseModel):
     The agent can also have memory, can operate in verbose mode, and can delegate tasks to other agents.
 
     Attributes:
-            agent_executor: An instance of the AgentExecutor class.
+            agent_executor: An instance of the CrewAgentExecutor class.
             role: The role of the agent.
             goal: The objective of the agent.
             backstory: The backstory of the agent.
@@ -68,8 +72,8 @@ class Agent(BaseModel):
     tools: List[Any] = Field(
         default_factory=list, description="Tools at agents disposal"
     )
-    agent_executor: Optional[InstanceOf[AgentExecutor]] = Field(
-        default=None, description="An instance of the AgentExecutor class."
+    agent_executor: Optional[InstanceOf[CrewAgentExecutor]] = Field(
+        default=None, description="An instance of the CrewAgentExecutor class."
     )
     tools_handler: Optional[InstanceOf[ToolsHandler]] = Field(
         default=None, description="An instance of the ToolsHandler class."
@@ -127,11 +131,11 @@ class Agent(BaseModel):
         self.tools_handler = ToolsHandler(cache=self.cache_handler)
         self.__create_agent_executor()
 
-    def __create_agent_executor(self) -> AgentExecutor:
+    def __create_agent_executor(self) -> CrewAgentExecutor:
         """Create an agent executor for the agent.
 
         Returns:
-            An instance of the AgentExecutor class.
+            An instance of the CrewAgentExecutor class.
         """
         agent_args = {
             "input": lambda x: x["input"],
@@ -170,7 +174,7 @@ class Agent(BaseModel):
                 tools_handler=self.tools_handler, cache=self.cache_handler
             )
         )
-        self.agent_executor = AgentExecutor(agent=inner_agent, **executor_args)
+        self.agent_executor = CrewAgentExecutor(agent=inner_agent, **executor_args)
 
     @staticmethod
     def __tools_names(tools) -> str: