> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Scientific Abstract Critique

> Critique a small-sample teaching-method abstract for bias and flawed conclusions, comparing gpt-4o built-in chain-of-thought with a deepseek-reasoner reasoning model.

Demonstrates built-in and DeepSeek-backed reasoning for methodology critique.

```python scientific_research.py theme={null}
"""
Scientific Abstract Critique
============================

Demonstrates built-in and DeepSeek-backed reasoning for methodology critique.
"""

from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat

# ---------------------------------------------------------------------------
# Create Agents
# ---------------------------------------------------------------------------
task = (
    "Read the following abstract of a scientific paper and provide a critical evaluation of its methodology,"
    "results, conclusions, and any potential biases or flaws:\n\n"
    "Abstract: This study examines the effect of a new teaching method on student performance in mathematics. "
    "A sample of 30 students was selected from a single school and taught using the new method over one semester. "
    "The results showed a 15% increase in test scores compared to the previous semester. "
    "The study concludes that the new teaching method is effective in improving mathematical performance among high school students."
)

cot_agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    reasoning=True,
    markdown=True,
)

deepseek_agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    reasoning_model=DeepSeek(id="deepseek-reasoner"),
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Agents
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    print("=== Built-in Chain Of Thought ===")
    cot_agent.print_response(task, stream=True, show_full_reasoning=True)

    print("\n=== DeepSeek Reasoning Model ===")
    deepseek_agent.print_response(task, stream=True, show_full_reasoning=True)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </Step>

  <Step title="Export your API keys">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export DEEPSEEK_API_KEY="your_deepseek_api_key_here"
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:DEEPSEEK_API_KEY="your_deepseek_api_key_here"
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `scientific_research.py`, then run:

    ```bash theme={null}
    python scientific_research.py
    ```
  </Step>
</Steps>

Full source: [cookbook/10\_reasoning/agents/scientific\_research.py](https://github.com/agno-agi/agno/blob/main/cookbook/10_reasoning/agents/scientific_research.py)