> For the complete documentation index, see [llms.txt](https://docs.flowiseai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.flowiseai.com/using-flowise/streaming.md).

# Streaming

If streaming is set when making prediction, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available.

### Using Python/TS Library

Flowise provides 2 libraries:

* [Python](https://pypi.org/project/flowise/): `pip install flowise`
* [Typescript](https://www.npmjs.com/package/flowise-sdk): `npm install flowise-sdk`

{% tabs %}
{% tab title="Python" %}

```python
from flowise import Flowise, PredictionData

def test_streaming():
    client = Flowise()

    # Test streaming prediction
    completion = client.create_prediction(
        PredictionData(
            chatflowId="<flow-id>",
            question="Tell me a joke!",
            streaming=True
        )
    )

    # Process and print each streamed chunk
    print("Streaming response:")
    for chunk in completion:
        # {event: "token", data: "hello"}
        print(chunk)


if __name__ == "__main__":
    test_streaming()
```

{% endtab %}

{% tab title="Typescript" %}

```javascript
import { FlowiseClient } from 'flowise-sdk'

async function test_streaming() {
  const client = new FlowiseClient({ baseUrl: 'http://localhost:3000' });

  try {
    // For streaming prediction
    const prediction = await client.createPrediction({
      chatflowId: '<flow-id>',
      question: 'What is the capital of France?',
      streaming: true,
    });

    for await (const chunk of prediction) {
        // {event: "token", data: "hello"}
        console.log(chunk);
    }
    
  } catch (error) {
    console.error('Error:', error);
  }
}

// Run streaming test
test_streaming()
```

{% endtab %}

{% tab title="cURL" %}

```bash
curl https://localhost:3000/api/v1/predictions/{flow-id} \
  -H "Content-Type: application/json" \
  -d '{
    "question": "Hello world!",
    "streaming": true
  }'
```

{% endtab %}
{% endtabs %}

```html
event: token
data: Once upon a time...
```

A prediction's event stream consists of the following event types:

| Event           | Description                                                                                                                         |
| --------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| start           | The start of streaming                                                                                                              |
| token           | Emitted when the prediction is streaming new token output                                                                           |
| error           | Emitted when the prediction returns an error                                                                                        |
| end             | Emitted when the prediction finishes                                                                                                |
| metadata        | All metadata such as chatId, messageId, of the related flow. Emitted after all tokens have finished streaming, and before end event |
| sourceDocuments | Emitted when the flow returns sources from vector store                                                                             |
| usedTools       | Emitted when the flow used tools                                                                                                    |

### Streamlit App

<https://github.com/HenryHengZJ/flowise-streamlit>