106 lines
3.3 KiB
Markdown
106 lines
3.3 KiB
Markdown
# Agent Visualization
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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.
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## Installation
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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:
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```bash
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pip install graphviz
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```
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## Generating a Graph
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You can generate an agent visualization using the `draw_graph` function. This function creates a directed graph where:
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- **Agents** are represented as yellow boxes.
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- **Tools** are represented as green ellipses.
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- **Handoffs** are directed edges from one agent to another.
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### Example Usage
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```python
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from agents import Agent, function_tool
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from agents.visualizations import draw_graph
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@function_tool
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def get_weather(city: str) -> str:
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return f"The weather in {city} is sunny."
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spanish_agent = Agent(
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name="Spanish agent",
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instructions="You only speak Spanish.",
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)
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english_agent = Agent(
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name="English agent",
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instructions="You only speak English",
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)
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triage_agent = Agent(
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name="Triage agent",
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instructions="Handoff to the appropriate agent based on the language of the request.",
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handoffs=[spanish_agent, english_agent],
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tools=[get_weather],
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)
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draw_graph(triage_agent)
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```
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This generates a graph that visually represents the structure of the **triage agent** and its connections to sub-agents and tools.
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## Understanding the Visualization
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The generated graph includes:
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- A **start node** (`__start__`) indicating the entry point.
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- Agents represented as **rectangles** with yellow fill.
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- Tools represented as **ellipses** with green fill.
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- Directed edges indicating interactions:
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- **Solid arrows** for agent-to-agent handoffs.
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- **Dotted arrows** for tool invocations.
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- An **end node** (`__end__`) indicating where execution terminates.
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## Customizing the Graph
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### Showing the Graph
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By default, `draw_graph` displays the graph inline. To show the graph in a separate window, write the following:
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```python
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draw_graph(triage_agent).view()
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```
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### Saving the Graph
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By default, `draw_graph` displays the graph inline. To save it as a file, specify a filename:
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```python
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draw_graph(triage_agent, filename="agent_graph.png")
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```
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This will generate `agent_graph.png` in the working directory.
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## Testing the Visualization
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The visualization functionality includes test coverage to ensure correctness. Tests are located in `tests/test_visualizations.py` and verify:
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- Node and edge correctness in `get_main_graph()`.
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- Proper agent and tool representation in `get_all_nodes()`.
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- Accurate relationship mapping in `get_all_edges()`.
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- Graph rendering functionality in `draw_graph()`.
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Run tests using:
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```bash
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pytest tests/test_visualizations.py
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```
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## Conclusion
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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.
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For further details on agent functionality, see the [Agents documentation](agents.md).
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