LangGraph

LangGraph is a framework for building reactive, multi-agent systems.

Quickstart

Confident AI provides a CallbackHandler that can be used to trace LangGraph agent’s execution.

Install the following packages:


pip install -U deepeval langgraph langchain langchain-openai

main.py


import os
import time
from langgraph.prebuilt import create_react_agent
 
from deepeval.integrations.langchain.callback import CallbackHandler
import deepeval
 
os.environ["OPENAI_API_KEY"] = "<your-openai-api-key>"
deepeval.login_with_confident_api_key("<your-confident-api-key>")
 
def get_weather(city: str) -> str:  
    return f"It's always sunny in {city}!"
agent = create_react_agent(
    model="openai:gpt-4o-mini",  
    tools=[get_weather],  
    prompt="You are a helpful assistant"  
)
 
result = agent.invoke(
    input = {"messages": [{"role": "user", "content": "what is the weather in sf"}]}, 
    config = {"callbacks": [CallbackHandler()]}
)
 
time.sleep(5) # Wait for the trace to be published

Run your agent by executing the script:


python main.py

You can directly view the traces in the Observatory by clicking on the link in the output printed in the console.

💡

DeepEval’s CallbackHandler is an implementation of LangChain’s BaseCallbackHandler.