Gemini Interactions - Deep Research with multimodal input
Deep Research accepts images and documents (PDFs) as input, then conducts web-based research grounded in that content.
Deep Research accepts images and documents (PDFs) as input, then conducts web-based research grounded in that content. Pass them as Agno Image / File objects with a URL (GCS / Gemini URIs pass through; regular HTTP URLs are downloaded and base64-encoded automatically).
"""
Gemini Interactions - Deep Research with multimodal input
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Deep Research accepts images and documents (PDFs) as input, then conducts
web-based research grounded in that content. Pass them as Agno `Image` /
`File` objects with a URL (GCS / Gemini URIs pass through; regular HTTP
URLs are downloaded and base64-encoded automatically).
"""
from agno.agent import Agent
from agno.media import File, Image
from agno.models.google import GeminiInteractions
agent = Agent(
model=GeminiInteractions(
agent="deep-research-preview-04-2026",
thinking_summaries="auto",
),
markdown=True,
)
if __name__ == "__main__":
# --- Image-grounded research ---
agent.print_response(
"Analyze the interspecies dynamics in this image and research the "
"symbiotic relationships shown.",
images=[
Image(
url="https://storage.googleapis.com/generativeai-downloads/images/generated_elephants_giraffes_zebras_sunset.jpg"
)
],
)
# --- Document-grounded research ---
agent.print_response(
"What is this document about, and how does it relate to current "
"research trends?",
files=[File(url="https://arxiv.org/pdf/1706.03762")],
)Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno google-genaiExport your Google API key
export GOOGLE_API_KEY="your_google_api_key_here"Run the example
Save the code above as deep_research_multimodal.py, then run:
python deep_research_multimodal.pyFull source: cookbook/90_models/google/gemini_interactions/deep_research_multimodal.py