> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.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 DeepSeek-backed reasoning for methodology critique.

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

Demonstrates DeepSeek-backed reasoning for methodology critique.
"""

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

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
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."
)

agent = Agent(
    model=OpenAIResponses(id="gpt-5.6"),
    reasoning_model=DeepSeek(id="deepseek-reasoner"),
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    agent.print_response(task, stream=True, show_full_reasoning=True)
```

## Run the Example

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

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno openai
```

**2. Export your API keys**

```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"
```

**3. Run the example**

Save the code above as `scientific_research.py`, then run:

```bash theme={null}
python scientific_research.py
```

Full source: [cookbook/10\_reasoning/agents/scientific\_research.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/10_reasoning/agents/scientific_research.py)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.