Skip to main content
This example demonstrates using reasoning models through LiteLLM. The reasoning_content from the model response is extracted and displayed. 
"""
LiteLLM Reasoning Agent Example

This example demonstrates using reasoning models through LiteLLM.
The reasoning_content from the model response is extracted and displayed.

Supported reasoning models through LiteLLM:
- deepseek/deepseek-reasoner (DeepSeek R1)
"""

from agno.agent import Agent
from agno.models.litellm import LiteLLM

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

task = "9.11 and 9.9 -- which is bigger?"

# Using DeepSeek R1 through LiteLLM
agent = Agent(
    model=LiteLLM(
        id="deepseek/deepseek-reasoner",
    ),
    markdown=True,
)

agent.print_response(task, stream=True, stream_events=True, show_reasoning=True)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/90_models/litellm

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python reasoning_agent.py