Parallel Workflow

Execute independent tasks simultaneously to reduce total execution time.

Use Parallel to run independent steps at the same time. When steps don’t depend on each other’s output, running them in parallel reduces total execution time.

When to use: When you have independent tasks that don’t depend on each other’s output but can contribute to the same final goal. Ideal for research from multiple sources, parallel data processing, or any scenario where tasks can run simultaneously.

Install dependencies:

uv pip install agno openai yfinance

parallel_steps_workflow.py

from agno.agent import Agent
from agno.tools.hackernews import HackerNewsTools
from agno.tools.yfinance import YFinanceTools
from agno.workflow import Step, Workflow
from agno.workflow.parallel import Parallel

# Create agents
news_researcher = Agent(name="News Researcher", tools=[HackerNewsTools()])
finance_researcher = Agent(name="Finance Researcher", tools=[YFinanceTools()])
writer = Agent(name="Writer")
reviewer = Agent(name="Reviewer")

# Create individual steps
research_news_step = Step(name="Research News", agent=news_researcher)
research_finance_step = Step(name="Research Finance", agent=finance_researcher)
write_step = Step(name="Write Article", agent=writer)
review_step = Step(name="Review Article", agent=reviewer)

# Create workflow with parallel research
workflow = Workflow(
    name="Content Creation Pipeline",
    steps=[
        Parallel(research_news_step, research_finance_step, name="Research Phase"),
        write_step,
        review_step,
    ],
)

workflow.print_response("Write about the latest AI developments and stock trends")