# Agent Visualization

Agent visualization allows you to generate a structured graphical representation of agents and their relationships using **Graphviz**. This is useful for understanding how agents, tools, and handoffs interact within an application.

## Installation

The visualization functionality relies on the **Graphviz** package. To use it, ensure you have Graphviz installed and add it as a dependency in `pyproject.toml`. Alternatively, install it directly via pip:

```bash
pip install openai-agents[visualization]
```

## Generating a Graph

You can generate an agent visualization using the `draw_graph` function. This function creates a directed graph where:

- **Agents** are represented as yellow boxes.
- **Tools** are represented as green ellipses.
- **Handoffs** are directed edges from one agent to another.

### Example Usage

```python
from agents import Agent, function_tool
from agents.extensions.visualization import draw_graph

@function_tool
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."

spanish_agent = Agent(
    name="Spanish agent",
    instructions="You only speak Spanish.",
)

english_agent = Agent(
    name="English agent",
    instructions="You only speak English",
)

triage_agent = Agent(
    name="Triage agent",
    instructions="Handoff to the appropriate agent based on the language of the request.",
    handoffs=[spanish_agent, english_agent],
    tools=[get_weather],
)

draw_graph(triage_agent)
```

![Agent Graph](./assets/images/graph.png)

This generates a graph that visually represents the structure of the **triage agent** and its connections to sub-agents and tools.


## Understanding the Visualization

The generated graph includes:

- A **start node** (`__start__`) indicating the entry point.
- Agents represented as **rectangles** with yellow fill.
- Tools represented as **ellipses** with green fill.
- Directed edges indicating interactions:
  - **Solid arrows** for agent-to-agent handoffs.
  - **Dotted arrows** for tool invocations.
- An **end node** (`__end__`) indicating where execution terminates.

## Customizing the Graph

### Showing the Graph
By default, `draw_graph` displays the graph inline. To show the graph in a separate window, write the following:

```python
draw_graph(triage_agent).view()
```

### Saving the Graph
By default, `draw_graph` displays the graph inline. To save it as a file, specify a filename:

```python
draw_graph(triage_agent, filename="agent_graph.png")
```

This will generate `agent_graph.png` in the working directory.

## Testing the Visualization

The visualization functionality includes test coverage to ensure correctness. Tests are located in `tests/test_visualizations.py` and verify:

- Node and edge correctness in `get_main_graph()`.
- Proper agent and tool representation in `get_all_nodes()`.
- Accurate relationship mapping in `get_all_edges()`.
- Graph rendering functionality in `draw_graph()`.

Run tests using:

```bash
pytest tests/test_visualizations.py
```

## Conclusion

Agent visualization provides a powerful way to **understand, debug, and communicate** how agents interact within an application. By leveraging **Graphviz**, you can generate intuitive visual representations of complex agent structures effortlessly.

For further details on agent functionality, see the [Agents documentation](agents.md).