Broadcast Mode for Parallel Research Sweep

Demonstrates broadcast mode for gathering information from multiple sources simultaneously.

Demonstrates broadcast mode for gathering information from multiple sources simultaneously. Each agent specializes in a different source, and the leader merges findings into a comprehensive report.

"""
Broadcast Mode for Parallel Research Sweep

Demonstrates broadcast mode for gathering information from multiple sources
simultaneously. Each agent specializes in a different source, and the leader
merges findings into a comprehensive report.

"""

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.team.mode import TeamMode
from agno.team.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.hackernews import HackerNewsTools

# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------

web_researcher = Agent(
    name="Web Researcher",
    role="Searches the general web for information",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[DuckDuckGoTools()],
    instructions=[
        "Search the web for the given topic.",
        "Focus on recent, authoritative sources.",
        "Provide a concise summary of key findings.",
    ],
)

hn_researcher = Agent(
    name="HackerNews Researcher",
    role="Searches Hacker News for community discussions and stories",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[HackerNewsTools()],
    instructions=[
        "Search Hacker News for stories and discussions on the topic.",
        "Highlight top-voted stories and notable community opinions.",
        "Provide story titles, scores, and key takeaways.",
    ],
)

trend_analyst = Agent(
    name="Trend Analyst",
    role="Analyzes broader trends and implications from available data",
    model=OpenAIResponses(id="gpt-5.2"),
    instructions=[
        "Analyze the topic from a trends perspective.",
        "Identify patterns: is interest growing, plateauing, or declining?",
        "Consider industry, academic, and public interest angles.",
    ],
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------

team = Team(
    name="Research Sweep Team",
    mode=TeamMode.broadcast,
    model=OpenAIResponses(id="gpt-5.2"),
    members=[web_researcher, hn_researcher, trend_analyst],
    instructions=[
        "You lead a research sweep team.",
        "All researchers investigate the same topic from different angles.",
        "Merge their findings into a comprehensive report covering:",
        "1. Key facts and recent developments",
        "2. Community sentiment and notable discussions",
        "3. Overall trend analysis and outlook",
    ],
    show_members_responses=True,
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    team.print_response(
        "Research the current state of WebAssembly adoption in 2025.",
        stream=True,
    )

Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/03_teams/modes/broadcast

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python 03_research_sweep.py