01_basic_team_factory.py
"""Basic Team Factory -- per-tenant team with role-based members.
Demonstrates a TeamFactory that builds a team with different members
depending on the caller's context. The team mode and member composition
vary per request.
Run:
.venvs/demo/bin/python cookbook/05_agent_os/factories/team/01_basic_team_factory.py
Test:
curl -X POST http://localhost:7777/teams/support-team/runs \
-F 'message=I need help with billing and a technical issue' \
-F 'user_id=tenant_42' \
-F 'stream=false'
"""
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.factory import RequestContext
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.team.factory import TeamFactory
from agno.team.team import Team
# ---------------------------------------------------------------------------
# Database
# ---------------------------------------------------------------------------
db = PostgresDb(
id="team-factory-db",
db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
)
# ---------------------------------------------------------------------------
# Factory
# ---------------------------------------------------------------------------
def build_support_team(ctx: RequestContext) -> Team:
"""Build a support team tailored to the calling tenant."""
user_id = ctx.user_id or "anonymous"
billing_agent = Agent(
name="Billing Agent",
role="Handle billing inquiries",
model=OpenAIResponses(id="gpt-5.4"),
instructions=f"You handle billing questions for tenant {user_id}. Be concise.",
)
tech_agent = Agent(
name="Tech Support Agent",
role="Handle technical issues",
model=OpenAIResponses(id="gpt-5.4"),
instructions=f"You handle technical support for tenant {user_id}. Be concise.",
)
return Team(
name="Support Team",
model=OpenAIResponses(id="gpt-5.4"),
members=[billing_agent, tech_agent],
db=db,
instructions=[
f"You are the support team leader for tenant {user_id}.",
"Route billing questions to the Billing Agent and technical issues to the Tech Support Agent.",
],
markdown=True,
)
support_team_factory = TeamFactory(
db=db,
id="support-team",
name="Per-tenant Support Team",
description="Builds a support team with billing and tech agents per tenant",
factory=build_support_team,
)
# ---------------------------------------------------------------------------
# AgentOS
# ---------------------------------------------------------------------------
agent_os = AgentOS(
id="team-factory-demo",
description="Demo: basic team factory",
teams=[support_team_factory],
)
app = agent_os.get_app()
# ---------------------------------------------------------------------------
# Run
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent_os.serve(app="01_basic_team_factory:app", port=7777, reload=True)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U "agno[os]" openai psycopg-binary
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run PgVector
docker run -d \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-e PGDATA=/var/lib/postgresql \
-v pgvolume:/var/lib/postgresql \
-p 5532:5432 \
--name pgvector \
agnohq/pgvector:18
5
Run the example
Save the code above as
01_basic_team_factory.py, then run:python 01_basic_team_factory.py