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This example demonstrates how to create an asynchronous data analyst agent that can analyze movie data using DuckDB tools and provide insights about movie ratings.

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Code

data_analyst.py
"""Run `pip install duckdb` to install dependencies."""

import asyncio
from textwrap import dedent

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckdb import DuckDbTools

duckdb_tools = DuckDbTools(
    create_tables=False, export_tables=False, summarize_tables=False
)
duckdb_tools.create_table_from_path(
    path="https://agno-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv",
    table="movies",
)

agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[duckdb_tools],
    markdown=True,
    additional_context=dedent("""\
    You have access to the following tables:
    - movies: contains information about movies from IMDB.
    """),
)
asyncio.run(agent.aprint_response("What is the average rating of movies?"))

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Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Install libraries

pip install -U agno openai duckdb
3

Export your OpenAI API key

  export OPENAI_API_KEY="your_openai_api_key_here"
4

Create a Python file

Create a Python file and add the above code.
touch data_analyst.py
5

Run Agent

python data_analyst.py
6

Find All Cookbooks

Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:Agno Cookbooks on GitHub
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