```python from langchain.agents import load_tools from langchain.agents import initialize_agent from langchain.agents import AgentType from langchain.llms import OpenAI ``` First, let's load the language model we're going to use to control the agent. ```python llm = OpenAI(temperature=0) ``` Next, let's load some tools to use. Note that the `llm-math` tool uses an LLM, so we need to pass that in. ```python tools = load_tools(["serpapi", "llm-math"], llm=llm) ``` Finally, let's initialize an agent with the tools, the language model, and the type of agent we want to use. ```python agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True) ``` Now let's test it out! ```python agent.run("Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?") ``` ``` > Entering new AgentExecutor chain... I need to find out who Leo DiCaprio's girlfriend is and then calculate her age raised to the 0.43 power. Action: Search Action Input: "Leo DiCaprio girlfriend" Observation: Camila Morrone Thought: I need to find out Camila Morrone's age Action: Search Action Input: "Camila Morrone age" Observation: 25 years Thought: I need to calculate 25 raised to the 0.43 power Action: Calculator Action Input: 25^0.43 Observation: Answer: 3.991298452658078 Thought: I now know the final answer Final Answer: Camila Morrone is Leo DiCaprio's girlfriend and her current age raised to the 0.43 power is 3.991298452658078. > Finished chain. "Camila Morrone is Leo DiCaprio's girlfriend and her current age raised to the 0.43 power is 3.991298452658078." ```