C
Integration
CrewAI
End-to-end tracing for CrewAI crews, tasks, and agent delegation. See how your role-based agents collaborate.
Prerequisites
- CrewAI installed
- Lanternfish SDK installed
1
Install the SDK
bash
pip install "lanternfish[crewai]"2
Initialize with auto-instrument
python
import os
import lanternfish
from crewai import Crew, Agent, Task
# Simply call instrument() and CrewAI crew execution is auto-traced!
lanternfish.instrument(
api_key=os.environ["LANTERNFISH_API_KEY"],
endpoint=os.environ["LANTERNFISH_ENDPOINT"],
)
researcher = Agent(
role="Senior Research Analyst",
goal="Uncover cutting-edge AI developments",
backstory="Expert in AI research...",
)
writer = Agent(
role="Tech Content Strategist",
goal="Craft compelling content on tech advancements",
backstory="Seasoned content creator...",
)3
Use as normal — tracing is automatic
python
# Define tasks
research_task = Task(
description="Research the latest AI agent frameworks",
agent=researcher,
expected_output="A 4-paragraph report",
)
write_task = Task(
description="Write an engaging article based on the research",
agent=writer,
expected_output="A 500-word article",
)
# Create and run the crew — all traced automatically
crew = Crew(
agents=[researcher, writer],
tasks=[research_task, write_task],
)
result = crew.kickoff()
# Lanternfish captures: crew structure, task execution,
# agent delegation, tool usage, token costsWhat Lanternfish captures
- Complete trace timeline
- Token usage and cost
- Latency metrics
- Tool and function calls
- Error tracking
- Model information