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Crew AI is an open source agentic framework. Crew AI docs

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Prerequisites

  1. Create an API key to authorize requests to Nebius Token Factory.
  2. Save the API key into a NEBIUS_API_KEY environment variable: 
    export NEBIUS_API_KEY="<API_key>"
  3. Install the crewai package: 
    pip install crewai

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Quickstart

from crewai import Agent, Task, LLM, Crew, Process
import os

llm=LLM(
        model="nebius/Qwen/Qwen3-30B-A3B",
        api_key=os.getenv("NEBIUS_API_KEY")
)

# Create a researcher agent
## see documentation : https://docs.crewai.com/en/concepts/agents#direct-code-definition
researcher = Agent(
  role='Senior Researcher',
  goal='Discover groundbreaking technologies',
  verbose=True,
  llm=llm,
  backstory='A curious mind fascinated by cutting-edge innovation and the potential to change the world, you know everything about tech.'
)

# Task for the researcher
research_task = Task(
  description='Identify the next big trend in AI',
  expected_output='5 paragraphs on the next big AI trend',
  agent=researcher  # Assigning the task to the researcher
)

# Instantiate your crew
tech_crew = Crew(
  agents=[researcher],
  tasks=[research_task],
  process=Process.sequential  # Tasks will be executed one after the other
)

# Begin the task execution
result = tech_crew.kickoff()

## see raw response
print("=== CREW OUTPUT ===")
print(result.raw)
## Look at `token_usage` output
print("\n=== TOKEN USAGE ===")
print(f"Total tokens: {result.token_usage.total_tokens}")
print(f"Prompt tokens: {result.token_usage.prompt_tokens}")
print(f"Completion tokens: {result.token_usage.completion_tokens}")
print(f"Successful requests: {result.token_usage.successful_requests}")

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More Examples

View more examples in our cookbook.