Agent with Storage

Code

db.py

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.ibm import WatsonX
from agno.tools.websearch import WebSearchTools

# Setup the database
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url=db_url)

agent = Agent(
    model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"),
    db=db,
    tools=[WebSearchTools()],
    add_history_to_context=True,
)
agent.print_response("How many people live in Canada?")
agent.print_response("What is their national anthem called?")

Usage

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

uv venv --python 3.12
.venv\Scripts\activate

Set your API key

export IBM_WATSONX_API_KEY=xxx
export IBM_WATSONX_PROJECT_ID=xxx

Install dependencies

uv pip install -U ddgs psycopg sqlalchemy ibm-watsonx-ai agno

Set up PostgreSQL

Make sure you have a PostgreSQL database running. You can adjust the db_url in the code to match your database configuration.

Run Agent

Save the code above as db.py, then run:

python db.py

PostgreSQL storage maintains conversation state across multiple interactions. The example creates an IBM WatsonX agent with a PostgreSQL storage backend and sends multiple messages, preserving the conversation history between them.

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Agent with Storage

Code

Usage

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Code

Usage