Documentation IndexFetch the complete documentation index at: /llms.txtUse this file to discover all available pages before exploring further.
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Analyze an IMDB movie dataset by attaching a CSV file to a Gemini agent.
""" Google Csv Input ================ Cookbook example for `google/gemini/csv_input.py`. """ from pathlib import Path from agno.agent import Agent from agno.media import File from agno.models.google import Gemini from agno.utils.media import download_file # --------------------------------------------------------------------------- # Create Agent # --------------------------------------------------------------------------- csv_path = Path(__file__).parent.joinpath("IMDB-Movie-Data.csv") download_file( "https://agno-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv", str(csv_path) ) agent = Agent( model=Gemini(id="gemini-2.5-flash"), markdown=True, ) agent.print_response( "Analyze the top 10 highest-grossing movies in this dataset. Which genres perform best at the box office?", files=[ File( filepath=csv_path, mime_type="text/csv", ), ], ) # --------------------------------------------------------------------------- # Run Agent # --------------------------------------------------------------------------- if __name__ == "__main__": pass
Set up your virtual environment
uv venv --python 3.12 source .venv/bin/activate
uv venv --python 3.12 .venv\Scripts\activate
Install dependencies
uv pip install -U agno google-genai
Export your Google API key
export GOOGLE_API_KEY="your_google_api_key_here"
$Env:GOOGLE_API_KEY="your_google_api_key_here"
Run the example
csv_input.py
python csv_input.py
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