Simple Team Memory Performance Evaluation

"""
Simple Team Memory Performance Evaluation
=========================================

Demonstrates team response performance with memory enabled.
"""

import asyncio
import random

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIChat
from agno.team.team import Team

# ---------------------------------------------------------------------------
# Create Sample Inputs
# ---------------------------------------------------------------------------
cities = [
    "New York",
    "Los Angeles",
    "Chicago",
    "Houston",
    "Miami",
    "San Francisco",
    "Seattle",
    "Boston",
    "Washington D.C.",
    "Atlanta",
    "Denver",
    "Las Vegas",
]

# ---------------------------------------------------------------------------
# Create Database
# ---------------------------------------------------------------------------
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url=db_url)


# ---------------------------------------------------------------------------
# Create Tool
# ---------------------------------------------------------------------------
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."


# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
weather_agent = Agent(
    id="weather_agent",
    model=OpenAIChat(id="gpt-5.2"),
    role="Weather Agent",
    description="You are a helpful assistant that can answer questions about the weather.",
    instructions="Be concise, reply with one sentence.",
    tools=[get_weather],
    db=db,
    update_memory_on_run=True,
    add_history_to_context=True,
)

team = Team(
    members=[weather_agent],
    model=OpenAIChat(id="gpt-5.2"),
    instructions="Be concise, reply with one sentence.",
    db=db,
    markdown=True,
    update_memory_on_run=True,
    add_history_to_context=True,
)


# ---------------------------------------------------------------------------
# Create Benchmark Function
# ---------------------------------------------------------------------------
async def run_team():
    random_city = random.choice(cities)
    _ = team.arun(
        input=f"I love {random_city}! What weather can I expect in {random_city}?",
        stream=True,
        stream_events=True,
    )

    return "Successfully ran team"


# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
team_response_with_memory_impact = PerformanceEval(
    name="Team Memory Impact",
    func=run_team,
    num_iterations=5,
    warmup_runs=0,
    measure_runtime=False,
    memory_growth_tracking=True,
)

# ---------------------------------------------------------------------------
# Run Evaluation
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    asyncio.run(
        team_response_with_memory_impact.arun(print_results=True, print_summary=True)
    )