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import os
from dotenv import load_dotenv
from importlib.metadata import version
from langchain_core.tools import tool
from langchain_openai import AzureChatOpenAI
from langgraph.checkpoint.memory import MemorySaver
from azure.ai.agentserver.langgraph import from_langgraph
load_dotenv()
memory = MemorySaver()
deployment_name = os.getenv("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", "gpt-4o")
model = AzureChatOpenAI(model=deployment_name)
@tool
def get_word_length(word: str) -> int:
"""Returns the length of a word."""
return len(word)
@tool
def calculator(expression: str) -> str:
"""Evaluates mathematical expression"""
try:
maths_result = eval(expression)
return str(maths_result)
except Exception as e:
return f"Error: {str(e)}"
def create_agent(model, tools, checkpointer):
# for different langgraph versions
langgraph_version = version("langgraph")
if langgraph_version < "1.0.0":
from langgraph.prebuilt import create_react_agent
return create_react_agent(model, tools, checkpointer=checkpointer)
else:
from langchain.agents import create_agent
return create_agent(model, tools, checkpointer=checkpointer)
tools = [get_word_length, calculator]
agent_executor = create_agent(model, tools, memory)
if __name__ == "__main__":
# host the langgraph agent
from_langgraph(agent_executor).run()
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