> ## 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.

# Ollama DeepSeek R1

> Pair a local Ollama Llama 3.2 model with DeepSeek R1 as a reasoning model to solve the trolley problem.

**1. Add the following code to your Python file**

```python ollama_reasoning.py theme={null}
from agno.agent import Agent
from agno.models.ollama.chat import Ollama

agent = Agent(
    model=Ollama(id="llama3.2:latest"),
    reasoning_model=Ollama(id="deepseek-r1:14b", options={"num_predict": 4096}),
)
agent.print_response(
    "Solve the trolley problem. Evaluate multiple ethical frameworks. "
    "Include an ASCII diagram of your solution.",
    stream=True,
)
```

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

**2. Install dependencies**

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

**3. Install Ollama**

Follow the [installation guide](https://github.com/ollama/ollama?tab=readme-ov-file#macos) and run:

```bash theme={null}
ollama pull llama3.2:latest
ollama pull deepseek-r1:14b
```

**4. Run Agent**

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


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