SingleStore for Team

uv pip install agno openai ddgs sqlalchemy pymysql

from os import getenv
from sqlalchemy import URL
from typing import List

from agno.agent import Agent
from agno.db.singlestore import SingleStoreDb
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.websearch import WebSearchTools
from pydantic import BaseModel

db_url = URL.create(
    drivername="mysql+pymysql",
    username=getenv("SINGLESTORE_USERNAME"),
    password=getenv("SINGLESTORE_PASSWORD"),
    host=getenv("SINGLESTORE_HOST"),
    port=int(getenv("SINGLESTORE_PORT", "3306")),
    database=getenv("SINGLESTORE_DATABASE"),
    query={"charset": "utf8mb4"},
).render_as_string(hide_password=False)

db = SingleStoreDb(db_url=db_url)


class Article(BaseModel):
    title: str
    summary: str
    reference_links: List[str]


hn_researcher = Agent(
    name="HackerNews Researcher",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Gets top stories from HackerNews.",
    tools=[HackerNewsTools()],
)

web_searcher = Agent(
    name="Web Searcher",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Searches the web for information on a topic",
    tools=[WebSearchTools()],
    add_datetime_to_context=True,
)

hn_team = Team(
    name="HackerNews Team",
    model=OpenAIResponses(id="gpt-5.2"),
    members=[hn_researcher, web_searcher],
    db=db,
    instructions=[
        "First, search HackerNews for what the user is asking about.",
        "Then, ask the web searcher to search for each story to get more information.",
        "Finally, summarize each story and include its reference links.",
    ],
    output_schema=Article,
    markdown=True,
    show_members_responses=True,
)

hn_team.print_response("Write an article about the top 2 stories on HackerNews")

python singlestore_for_team.py