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

# Streaming

> Streaming API — StreamEvent, StreamEventType, and async iterators for real-time response output.

# Streaming

cascadeflow supports streaming responses via `stream_events()` for custom UI integration and `run_streaming()` for terminal output with visual feedback.

## stream\_events()

Returns an async iterator of `StreamEvent` objects.

```python theme={null}
async for event in agent.stream_events("Explain TypeScript"):
    if event.type == StreamEventType.CHUNK:
        print(event.content, end="", flush=True)
    elif event.type == StreamEventType.COMPLETE:
        print(f"\nDone — model: {event.data.get('model')}")
```

## StreamEvent

| Field     | Type              | Description                                   |
| --------- | ----------------- | --------------------------------------------- |
| `type`    | `StreamEventType` | Event type                                    |
| `content` | `str`             | Content chunk (for `CHUNK` events)            |
| `data`    | `dict[str, Any]`  | Event metadata (model, phase, strategy, etc.) |

## StreamEventType

| Value       | Description            |
| ----------- | ---------------------- |
| `START`     | Stream started         |
| `CHUNK`     | Content chunk received |
| `TOOL_CALL` | Tool call detected     |
| `COMPLETE`  | Stream complete        |
| `ERROR`     | Error occurred         |

## run\_streaming()

Higher-level method with built-in visual feedback (pulsing dot indicator).

```python theme={null}
result = await agent.run_streaming(
    "Explain quantum mechanics",
    enable_visual=True,
    max_tokens=500,
)
print(f"\nCost: ${result.total_cost:.6f}")
```

## Tool Streaming

When tools are involved, cascadeflow uses a tool-aware streaming manager:

```python theme={null}
async for event in agent.stream_events(
    "Search and summarize",
    tools=tools,
    tool_executor=executor,
    max_steps=5,
):
    if event.type == StreamEventType.TOOL_CALL:
        print(f"Calling tool: {event.data['tool_name']}")
    elif event.type == StreamEventType.CHUNK:
        print(event.content, end="")
```

## ToolStreamEvent

Tool-specific streaming event with additional fields.

| Field         | Type                  | Description           |
| ------------- | --------------------- | --------------------- |
| `type`        | `ToolStreamEventType` | Tool event type       |
| `tool_call`   | `dict[str, Any]`      | Tool call details     |
| `tool_result` | `Any`                 | Tool execution result |
| `content`     | `str`                 | Content chunk         |