url_context.py
Run the Example
1
Set up your virtual environment
2
Install dependencies
3
Export your Google API key
4
Run the example
Save the code above as
url_context.py, then run:Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Compare two recipe pages by enabling Gemini’s url_context to fetch page content.
google-generativeai package. Agno v2.7.2 uses the Google Gen AI SDK from google-genai. Use the generated install step below."""Run `uv pip install google-generativeai` to install dependencies."""
from agno.agent import Agent
from agno.models.google import Gemini
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
model=Gemini(id="gemini-2.5-flash", url_context=True),
markdown=True,
)
url1 = "https://www.foodnetwork.com/recipes/ina-garten/perfect-roast-chicken-recipe-1940592"
url2 = "https://www.allrecipes.com/recipe/83557/juicy-roasted-chicken/"
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# --- Sync ---
agent.print_response(
f"Compare the ingredients and cooking times from the recipes at {url1} and {url2}"
)
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
url_context.py, then run:python url_context.py
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