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Agno supports using MySQL asynchronously, with the AsyncMySQLDb class.

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Usage

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Run MySQL

Install docker desktop and run MySQL on port 3306 using: 
docker run -d \
  --name mysql \
  -e MYSQL_ROOT_PASSWORD=ai \
  -e MYSQL_DATABASE=ai \
  -e MYSQL_USER=ai \
  -e MYSQL_PASSWORD=ai \
  -p 3306:3306 \
  -d mysql:8
async_mysql_for_agent.py
import asyncio
import uuid

from agno.agent import Agent
from agno.db.base import SessionType
from agno.db.mysql import AsyncMySQLDb
from agno.tools.duckduckgo import DuckDuckGoTools

db_url = "mysql+asyncmy://ai:ai@localhost:3306/ai"
db = AsyncMySQLDb(db_url=db_url)

agent = Agent(
    db=db,
    tools=[DuckDuckGoTools()],
    add_history_to_context=True,
    add_datetime_to_context=True,
)


async def main():
    """Run the agent queries in the same event loop"""
    session_id = str(uuid.uuid4())
    await agent.aprint_response(
        "How many people live in Canada?", session_id=session_id
    )
    await agent.aprint_response(
        "What is their national anthem called?", session_id=session_id
    )
    session_data = await db.get_session(
        session_id=session_id, session_type=SessionType.AGENT
    )
    print("\n=== SESSION DATA ===")
    print(session_data.to_dict())


if __name__ == "__main__":
    asyncio.run(main())

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Params

ParameterTypeDefaultDescription
idOptional[str]-The ID of the database instance. UUID by default.
db_urlOptional[str]-The database URL to connect to.
db_engineOptional[AsyncEngine]-The SQLAlchemy async database engine to use.
db_schemaOptional[str]-The database schema to use.
session_tableOptional[str]-Name of the table to store Agent, Team and Workflow sessions.
memory_tableOptional[str]-Name of the table to store memories.
metrics_tableOptional[str]-Name of the table to store metrics.
eval_tableOptional[str]-Name of the table to store evaluation runs data.
knowledge_tableOptional[str]-Name of the table to store knowledge content.

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Developer Resources