How to
Build a tool agent
This guide outlines how to build a tool calling agent using Langchain + LLMstudio.
1. Set up your tools
Start by defining the tools your agent is going to have access to.
from langchain.tools import tool
@tool
def buy_ticket(destination: str):
"""Use this to buy a ticket"""
return "Bought ticket number 270924"
@tool
def get_departure(ticket_number: str):
"""Use this to fetch the departure time of a train"""
return "8:25 AM"
2. Setup your .env
Create a .env file on the root of your project with the the credentials for the providers you want to use.
OPENAI_API_KEY="YOUR_API_KEY"
3. Set up your model using LLMstudio
Use LLMstudio to choose the provider and model you want to use.
model = ChatLLMstudio(model_id='openai/gpt-4o')
4. Build the agent
Set up your agent and agent executor using Langchain.
from langchain import hub
from langchain.agents import AgentExecutor, create_openai_tools_agent
prompt = hub.pull("hwchase17/openai-tools-agent")
agent = create_openai_tools_agent(model, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools)
input = "Can you buy me a ticket to madrid?"
# Using with chat history
agent_executor.invoke(
{
"input": input,
}
)