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AgentOps Basic Monitoring

This is an example of how to use the AgentOps library for basic Agent monitoring with OpenAI’s GPT

First let’s install the required packages

%pip install -U openai
%pip install -U agentops
%pip install -U python-dotenv

Then import them

from openai import OpenAI
import agentops
import os
from dotenv import load_dotenv

Next, we’ll set our API keys. There are several ways to do this, the code below is just the most foolproof way for the purposes of this notebook. It accounts for both users who use environment variables and those who just want to set the API Key here in this notebook.

Get an AgentOps API key

  1. Create an environment variable in a .env file or other method. By default, the AgentOps init() function will look for an environment variable named AGENTOPS_API_KEY. Or…

  2. Replace <your_agentops_key> below and pass in the optional api_key parameter to the AgentOps init(api_key=...) function. Remember not to commit your API key to a public repo!

load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") or "<your_openai_key>"
AGENTOPS_API_KEY = os.getenv("AGENTOPS_API_KEY") or "<your_agentops_key>"

The AgentOps library is designed to be a plug-and-play replacement for the OpenAI Client, maximizing use with minimal install effort.

openai = OpenAI(api_key=OPENAI_API_KEY)
agentops.init(AGENTOPS_API_KEY, default_tags=["openai-gpt-notebook"])

Now just use OpenAI as you would normally!

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Single Session with ChatCompletion

message = [{"role": "user", "content": "Write a 12 word poem about secret agents."}]
response = openai.chat.completions.create(
    model="gpt-3.5-turbo", messages=message, temperature=0.5, stream=False
)
print(response.choices[0].message.content)

Make sure to end your session with a Result (Success|Fail|Indeterminate) for better tracking

agentops.end_session("Success")

Now if you check the AgentOps dashboard, you should see information related to this run!

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Events

Additionally, you can track custom events via AgentOps. Let’s start a new session and record some events

# Create new session
agentops.start_session(tags=["openai-gpt-notebook-events"])

The easiest way to record actions is through the use of AgentOps’ decorators

from agentops import record_action


@record_action("add numbers")
def add(x, y):
    return x + y


add(2, 4)

We can also manually craft an event exactly the way we want

from agentops import ActionEvent

message = ({"role": "user", "content": "Hello"},)
response = openai.chat.completions.create(
    model="gpt-3.5-turbo", messages=message, temperature=0.5
)

if "hello" in str(response.choices[0].message.content).lower():
    agentops.record(
        ActionEvent(
            action_type="Agent says hello",
            logs=str(message),
            returns=str(response.choices[0].message.content),
        )
    )

agentops.end_session("Success")