> ## Documentation Index
> Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# CrewAI Tracing
> Instrument multi-agent applications using CrewAI
colab.research.google.com
## Install
```bash theme={null}
pip install openinference-instrumentation-crewai crewai crewai-tools
```
CrewAI uses either Langchain or LiteLLM under the hood to call models, depending on the version.
If you're using **CrewAI\<0.63.0**, we recommend installing our `openinference-instrumentation-langchain` library to get visibility of LLM calls.
If you're using **CrewAI>= 0.63.0**, we recommend instead adding our `openinference-instrumentation-litellm` library to get visibility of LLM calls.
## Setup
Connect to your Phoenix instance using the register function.
```python theme={null}
from phoenix.otel import register
# configure the Phoenix tracer
tracer_provider = register(
project_name="my-llm-app", # Default is 'default'
auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)
```
## Run CrewAI
From here, you can run CrewAI as normal
```python expandable theme={null}
import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import SerperDevTool
os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"
os.environ["SERPER_API_KEY"] = "YOUR_SERPER_API_KEY"
search_tool = SerperDevTool()
# Define your agents with roles and goals
researcher = Agent(
role='Senior Research Analyst',
goal='Uncover cutting-edge developments in AI and data science',
backstory="""You work at a leading tech think tank.
Your expertise lies in identifying emerging trends.
You have a knack for dissecting complex data and presenting actionable insights.""",
verbose=True,
allow_delegation=False,
# You can pass an optional llm attribute specifying what model you wanna use.
# llm=ChatOpenAI(model_name="gpt-3.5", temperature=0.7),
tools=[search_tool]
)
writer = Agent(
role='Tech Content Strategist',
goal='Craft compelling content on tech advancements',
backstory="""You are a renowned Content Strategist, known for your insightful and engaging articles.
You transform complex concepts into compelling narratives.""",
verbose=True,
allow_delegation=True
)
# Create tasks for your agents
task1 = Task(
description="""Conduct a comprehensive analysis of the latest advancements in AI in 2024.
Identify key trends, breakthrough technologies, and potential industry impacts.""",
expected_output="Full analysis report in bullet points",
agent=researcher
)
task2 = Task(
description="""Using the insights provided, develop an engaging blog
post that highlights the most significant AI advancements.
Your post should be informative yet accessible, catering to a tech-savvy audience.
Make it sound cool, avoid complex words so it doesn't sound like AI.""",
expected_output="Full blog post of at least 4 paragraphs",
agent=writer
)
# Instantiate your crew with a sequential process
crew = Crew(
agents=[researcher, writer],
tasks=[task1, task2],
verbose=True, # Enable verbose logging
process = Process.sequential
)
# Get your crew to work!
result = crew.kickoff()
print("######################")
print(result)
```
## Observe
Now that you have tracing setup, all calls to your Crew will be streamed to your running Phoenix for observability and evaluation.
## Resources
* [OpenInference package](https://github.com/Arize-ai/openinference/blob/main/python/instrumentation/openinference-instrumentation-crewai)
* [Example Notebook](https://colab.research.google.com/github/Arize-ai/phoenix/blob/main/tutorials/tracing/crewai_tracing_tutorial.ipynb)