> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentops.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# CrewAI
> AgentOps and CrewAI teamed up to make monitoring Crew agents dead simple.
## Video Tutorial
[CrewAI](https://www.crewai.com/) is a framework for easily building multi-agent applications. AgentOps integrates with CrewAI to provide observability into your agent workflows. Crew has comprehensive [documentation](https://docs.crewai.com) available as well as a great [quickstart](https://docs.crewai.com/how-to/Creating-a-Crew-and-kick-it-off/) guide.
## Installation
Install AgentOps and CrewAI, along with `python-dotenv` for managing API keys:
```bash pip theme={null}
pip install agentops crewai python-dotenv
```
```bash poetry theme={null}
poetry add agentops crewai python-dotenv
```
```bash uv theme={null}
uv pip install agentops crewai python-dotenv
```
## Setting Up API Keys
You'll need API keys for AgentOps and OpenAI (since CrewAI's built-in `LLM` uses OpenAI models by default):
* **OPENAI\_API\_KEY**: From the [OpenAI Platform](https://platform.openai.com/api-keys)
* **AGENTOPS\_API\_KEY**: From your [AgentOps Dashboard](https://app.agentops.ai/)
Set these as environment variables or in a `.env` file.
```bash Export to CLI theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
export AGENTOPS_API_KEY="your_agentops_api_key_here"
```
```txt Set in .env file theme={null}
OPENAI_API_KEY="your_openai_api_key_here"
AGENTOPS_API_KEY="your_agentops_api_key_here"
```
Then load them in your Python code:
```python theme={null}
from dotenv import load_dotenv
import os
load_dotenv()
AGENTOPS_API_KEY = os.getenv("AGENTOPS_API_KEY")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
```
## Usage
Simply initialize AgentOps at the beginning of your CrewAI application. AgentOps automatically instruments CrewAI components—including its `LLM`—to track your agent interactions.
Here's how to set up a basic CrewAI application with AgentOps:
```python theme={null}
import agentops
from crewai import Agent, Task, Crew, LLM
# Initialize AgentOps client
agentops.init()
# Define the LLM to use with CrewAI
llm = LLM(
model="openai/gpt-4o", # Or your preferred model
temperature=0.7,
)
# Create an agent
researcher = Agent(
role='Researcher',
goal='Research and provide accurate information about cities and their history',
backstory='You are an expert researcher with vast knowledge of world geography and history.',
llm=llm,
verbose=True
)
# Create a task
research_task = Task(
description='What is the capital of France? Provide a detailed answer about its history, culture, and significance.',
expected_output='A comprehensive response about Paris, including its status as the capital of France, historical significance, cultural importance, and key landmarks.',
agent=researcher
)
# Create a crew with the researcher
crew = Crew(
agents=[researcher],
tasks=[research_task],
verbose=True
)
# Execute the task
result = crew.kickoff()
print("\nCrew Research Results:")
print(result)
```
## Examples
Create job postings with a crew of specialized agents
Validate and improve markdown content using CrewAI agents