Installation & Setup

# Install CrewAI
pip install crewai

# Install with tools support
pip install "crewai[tools]"

# Set your API key
export OPENAI_API_KEY="sk-..."

# Or use the CrewAI CLI to create a project
crewai create crew my_crew
cd my_crew

from crewai import Agent, Task, Crew, Process

# Define agents
researcher = Agent(
    role="Senior Research Analyst",
    goal="Find comprehensive information about AI trends in 2026",
    backstory="""You are an experienced research analyst with a talent
    for finding and synthesizing information from multiple sources.
    You are thorough, accurate, and always cite your findings.""",
    verbose=True
)

writer = Agent(
    role="Content Writer",
    goal="Write an engaging article based on research findings",
    backstory="""You are a skilled content writer who transforms
    complex research into clear, engaging articles. You write in
    a professional yet approachable tone.""",
    verbose=True
)

# Define tasks
research_task = Task(
    description="""Research the top 5 AI trends for 2026.
    Include specific examples, statistics, and expert opinions.
    Focus on practical applications, not hype.""",
    expected_output="A detailed research report with 5 AI trends",
    agent=researcher
)

writing_task = Task(
    description="""Write a 500-word article about AI trends in 2026
    based on the research findings. Make it engaging and informative.
    Include an introduction, body, and conclusion.""",
    expected_output="A polished 500-word article",
    agent=writer
)

# Create and run the crew
crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, writing_task],
    process=Process.sequential,  # Tasks run in order
    verbose=True
)

result = crew.kickoff()
print(result)

from crewai import Agent, LLM

# Use a specific OpenAI model
agent = Agent(
    role="Analyst",
    goal="Analyze data",
    backstory="You are a data analyst.",
    llm="gpt-4o"
)

# Use Anthropic Claude
agent = Agent(
    role="Analyst",
    goal="Analyze data",
    backstory="You are a data analyst.",
    llm=LLM(model="anthropic/claude-sonnet-4-20250514")
)

# Use local Ollama model
agent = Agent(
    role="Analyst",
    goal="Analyze data",
    backstory="You are a data analyst.",
    llm=LLM(model="ollama/llama3", base_url="http://localhost:11434")
)