Azure OpenAI Reasoning Model GPT 4 1

Adapt the archived GPT-4.1 stage to a native Azure OpenAI reasoning deployment.

reasoning_model_gpt_4_1.py
"""
Reasoning Model Gpt 4 1
=======================

Demonstrates this reasoning cookbook example.
"""

from agno.agent import Agent
from agno.models.azure.openai_chat import AzureOpenAI


# ---------------------------------------------------------------------------
# Create Example
# ---------------------------------------------------------------------------
def run_example() -> None:
    agent = Agent(
        model=AzureOpenAI(id="gpt-5.6-luna"), reasoning_model=AzureOpenAI(id="gpt-4.1")
    )
    agent.print_response(
        "Solve the trolley problem. Evaluate multiple ethical frameworks. "
        "Include an ASCII diagram of your solution.",
        stream=True,
    )


# ---------------------------------------------------------------------------
# Run Example
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    run_example()

Select a native reasoning deployment

The archived AzureOpenAI(id="gpt-4.1") is not recognized as a native reasoning model. Agno can skip that stage and still produce a final answer. Deploy GPT-5.2 in your Azure resource, then replace the reasoning_model value with:

AzureOpenAI(id="gpt-5.2", azure_deployment="your-reasoning-deployment")

Replace the deployment placeholder with the name from your resource. Keep the underlying model ID in id so Agno can recognize its reasoning capability. AZURE_OPENAI_API_KEY and AZURE_OPENAI_ENDPOINT identify the resource; they do not create the deployment.

An explicit reasoning_model runs as a separate, tool-free reasoning stage before the main model response. show_full_reasoning=True displays the reasoning data Agno receives; it cannot reveal a provider's private internal trace. Some adapters use the reasoning stage's answer text when separate reasoning content is unavailable. A failed reasoning stage can still be followed by a main-model answer, so a completed run alone does not prove the reasoning stage succeeded.

Also deploy the final GPT-5.6 Luna model and replace its constructor with AzureOpenAI(id="gpt-5.6-luna", azure_deployment="your-answer-deployment"). Use explicit per-model deployment names so the two calls cannot accidentally share one AZURE_OPENAI_DEPLOYMENT setting.

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Install dependencies

uv pip install -U agno openai

Export environment variables

export AZURE_OPENAI_API_KEY="your_azure_openai_api_key_here"
export AZURE_OPENAI_ENDPOINT="your_azure_openai_endpoint_here"

Run the example

Save the code above as reasoning_model_gpt_4_1.py, then run:

python reasoning_model_gpt_4_1.py

Full source: cookbook/10_reasoning/models/azure_openai/reasoning_model_gpt_4_1.py