┌───────────┐    ┌───────────┐    ┌───────────┐    ┌───────────┐
│ Research  │ ─► │  Analyze  │ ─► │   Write   │ ─► │   Edit    │
└───────────┘    └───────────┘    └───────────┘    └───────────┘

from praisonaiagents import Agent, Task, PraisonAIAgents

# Create agents for each step
researcher = Agent(
    name="Researcher",
    instructions="Research the given topic thoroughly."
)

analyst = Agent(
    name="Analyst",
    instructions="Analyze the research and extract key insights."
)

writer = Agent(
    name="Writer",
    instructions="Write content based on the analysis."
)

editor = Agent(
    name="Editor",
    instructions="Edit and polish the written content."
)

# Create sequential tasks
tasks = [
    Task(description="Research AI trends", agent=researcher),
    Task(description="Analyze the research", agent=analyst),
    Task(description="Write a report", agent=writer),
    Task(description="Edit the report", agent=editor)
]

# Run sequentially (default)
agents = PraisonAIAgents(
    agents=[researcher, analyst, writer, editor],
    tasks=tasks,
    process="sequential"
)

result = agents.start()

from praisonaiagents.workflows import SequentialWorkflow

workflow = SequentialWorkflow(
    agents=[researcher, analyst, writer, editor]
)

result = workflow.run("Create a report on AI trends")

from praisonaiagents import Task

research_task = Task(
    description="Research the topic",
    agent=researcher,
    expected_output="Research findings"
)

analysis_task = Task(
    description="Analyze the research findings",
    agent=analyst,
    context=[research_task],  # Receives research output
    expected_output="Analysis report"
)

writing_task = Task(
    description="Write based on analysis",
    agent=writer,
    context=[analysis_task],  # Receives analysis output
    expected_output="Draft content"
)

editing_task = Task(
    description="Edit the draft",
    agent=editor,
    context=[writing_task],  # Receives draft
    expected_output="Final content"
)

from praisonaiagents import Agent

def pipeline(input_text: str) -> str:
    """Run agents in a pipeline."""
    
    # Step 1: Research
    researcher = Agent(name="Researcher")
    research = researcher.start(f"Research: {input_text}")
    
    # Step 2: Analyze
    analyst = Agent(name="Analyst")
    analysis = analyst.start(f"Analyze this research: {research}")
    
    # Step 3: Write
    writer = Agent(name="Writer")
    content = writer.start(f"Write based on: {analysis}")
    
    # Step 4: Edit
    editor = Agent(name="Editor")
    final = editor.start(f"Edit this: {content}")
    
    return final

result = pipeline("AI trends in 2024")