deep_research_streaming.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
deep_research_streaming.py, then run:Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Stream real-time progress (thought summaries, text, generated images) from a Deep Research task instead of waiting for the final report.
"""
Gemini Interactions - Deep Research streaming
==============================================
Stream real-time progress (thought summaries, text, generated images) from
a Deep Research task instead of waiting for the final report.
`thinking_summaries="auto"` is required to receive intermediate reasoning
during streaming; without it the stream may only deliver the final result.
Background execution is required for agents and is enabled automatically.
"""
import asyncio
from agno.agent import Agent
from agno.models.google import GeminiInteractions
agent = Agent(
model=GeminiInteractions(
agent="deep-research-preview-04-2026",
thinking_summaries="auto",
),
markdown=True,
)
if __name__ == "__main__":
# --- Sync streaming ---
agent.print_response(
"Research the history and impact of Google TPUs.",
stream=True,
)
# --- Async streaming ---
asyncio.run(
agent.aprint_response(
"Research the current state of open-source LLM inference engines.",
stream=True,
)
)
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
deep_research_streaming.py, then run:python deep_research_streaming.py
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