from langchain.agents import AgentType, initialize_agent, load_tools
parameters = {
"max_new_tokens": 50,
"num_return_sequences": 1,
"top_k": 250,
"top_p": 0.25,
"do_sample": False,
"temperature": 0.1,
}
llm.model_kwargs = parameters
# Next, let's load some tools to use. Note that the `llm-math` tool uses an LLM, so we need to pass that in.
tools = load_tools(["python_repl", "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.
agent = initialize_agent(
tools,
llm,
agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
verbose=True,
)
# Now let's test it out!
agent.run(
"""
Write a Python script that prints "Hello, world!"
"""
)