"""
Basic Coordinate Mode Example
Demonstrates the default `mode=coordinate` where the team leader:
1. Analyzes the user's request
2. Selects the most appropriate member agent(s)
3. Crafts specific tasks for each selected member
4. Synthesizes member responses into a final answer
"""
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.team.mode import TeamMode
from agno.team.team import Team
# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
researcher = Agent(
name="Researcher",
role="Research specialist who finds and summarizes information",
model=OpenAIResponses(id="gpt-5.2"),
instructions=[
"You are a research specialist.",
"Provide clear, factual summaries on any topic.",
"Organize findings with structure and cite limitations.",
],
)
writer = Agent(
name="Writer",
role="Content writer who crafts polished, engaging text",
model=OpenAIResponses(id="gpt-5.2"),
instructions=[
"You are a skilled content writer.",
"Transform raw information into well-structured, readable text.",
"Use headers, bullet points, and clear prose.",
],
)
# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
team = Team(
name="Research & Writing Team",
mode=TeamMode.coordinate,
model=OpenAIResponses(id="gpt-5.2"),
members=[researcher, writer],
instructions=[
"You lead a research and writing team.",
"For informational requests, ask the Researcher to gather facts first,",
"then ask the Writer to polish the findings into a final piece.",
"Synthesize everything into a cohesive response.",
],
show_members_responses=True,
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
team.print_response(
"Write a brief overview of how large language models are trained, "
"covering pre-training, fine-tuning, and RLHF.",
stream=True,
)
