Async Sqlite for Team

Agno supports using Sqlite asynchronously as a storage backend for Teams, with the AsyncSqliteDb class.

Usage

Provide db_url, db_file or db_engine. If none is provided, a new database is created in the current directory. The following example uses db_file.

Install the sqlalchemy, aiosqlite, openai, and ddgs packages:

uv pip install sqlalchemy aiosqlite openai ddgs

async_sqlite_for_team.py

import asyncio
from typing import List

from agno.agent import Agent
from agno.db.sqlite import AsyncSqliteDb
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

# Initialize AsyncSqliteDb with a database file
db = AsyncSqliteDb(db_file="team_storage.db")

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, provide a thoughtful and engaging summary.",
    ],
    output_schema=Article,
    markdown=True,
    show_members_responses=True,
)

asyncio.run(
    hn_team.aprint_response("Write an article about the top 2 stories on hackernews")
)

Params

Parameter	Type	Default	Description
id	Optional[str]	-	The ID of the database instance. UUID by default.
db_engine	Optional[AsyncEngine]	-	The SQLAlchemy async database engine to use.
db_url	Optional[str]	-	The database URL to connect to.
db_file	Optional[str]	-	The database file to connect to.
session_table	Optional[str]	-	Name of the table to store Agent, Team and Workflow sessions.
memory_table	Optional[str]	-	Name of the table to store user memories.
metrics_table	Optional[str]	-	Name of the table to store metrics.
eval_table	Optional[str]	-	Name of the table to store evaluation runs data.
knowledge_table	Optional[str]	-	Name of the table to store knowledge documents data.
culture_table	Optional[str]	-	Name of the table to store cultural knowledge.
traces_table	Optional[str]	-	Name of the table to store traces.
spans_table	Optional[str]	-	Name of the table to store spans.
versions_table	Optional[str]	-	Name of the table to store schema versions.
learnings_table	Optional[str]	-	Name of the table to store learnings.
schedules_table	Optional[str]	-	Name of the table to store cron schedules.
schedule_runs_table	Optional[str]	-	Name of the table to store schedule run history.
approvals_table	Optional[str]	-	Name of the table to store human approval requests.
auth_tokens_table	Optional[str]	-	Name of the table to store OAuth tokens for external services.
service_accounts_table	Optional[str]	-	Name of the table to store service accounts.