Update agent.py

agent.py

@@ -2,7 +2,7 @@ import os
 from dotenv import load_dotenv
 from typing import TypedDict, List, Dict, Any, Optional
 from langgraph.graph import StateGraph, START, END, MessagesState
-from langchain.agents import create_tool_calling_agent, AgentExecutor, initialize_agent
+from langchain.agents import create_tool_calling_agent, AgentExecutor, initialize_agent, create_react_agent
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_groq import ChatGroq
 from langchain_core.tools import tool
@@ -292,14 +292,20 @@ class BasicAgent:
             ("system", self.sys_prompt),
             ("human", "{input}")
         ])
-        self.agent = initialize_agent(
-            tools=self.tools,
+        # self.agent = initialize_agent(
+        #     tools=self.tools,
+        #     llm=self.model,
+        #     agent="zero-shot-react-description",  # ReAct agent type
+        #     verbose=True,
+        #     system_prompt=self.prompt,
+        #     handle_parsing_errors="Check your output and make sure it conforms, use the Action/Action Input syntax"
+        # )
+        self.agent = create_react_agent(
             llm=self.model,
-            agent="zero-shot-react-description",  # ReAct agent type
-            verbose=True,
-            system_prompt=self.prompt,
-            handle_parsing_errors="Check your output and make sure it conforms, use the Action/Action Input syntax"
+            tools=self.tools,
+            prompt=self.prompt
         )
+        self.agent_exe = AgentExecutor(agent=self.agent, tools=self.tools, verbose=True)
         # self.graph = self.__graph_compile__()
         print("BasicAgent initialized.")
     
@@ -313,7 +319,8 @@ class BasicAgent:
             question = f"{question} with TASK-ID: {task_id}"
             # fixed_answer = self.agent.run(f'{question} with TASK-ID: {task_id}')
         # fixed_answer = "This is a default answer."
-        fixed_answer = self.agent.run(question)
+        # fixed_answer = self.agent.run(question)
+        fixed_answer = self.agent_exe.invoke({"input": question})
         # human_message = [HumanMessage(content=question)]
         # messages = self.graph.invoke({"messages": human_message})
         # fixed_answer = messages['messages'][-1].content