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

# Streaming Response Handling

> Handle streaming responses in Python and JavaScript for real-time AI output

Streaming responses allow users to see AI replies in real-time as they are generated, rather than waiting for the complete response. This is ideal for chat applications and interactive UIs.

## Python Streaming with OpenAI SDK

```python theme={null}
from openai import OpenAI

client = OpenAI(
    api_key="your-api-key",
    base_url="https://gateway.iotex.ai/v1"
)

def stream_with_callback(prompt, on_content=None):
    """Stream response handling with callback function support"""
    stream = client.chat.completions.create(
        model="gemini-2.5-flash",
        messages=[{"role": "user", "content": prompt}],
        stream=True
    )

    full_content = ""
    for chunk in stream:
        if chunk.choices[0].delta.content is not None:
            content = chunk.choices[0].delta.content
            full_content += content

            if on_content:
                on_content(content)

    return full_content

# Usage example
def print_content(content):
    print(content, end="", flush=True)

result = stream_with_callback("Write a Python quicksort algorithm", print_content)
```

## JavaScript Streaming with OpenAI SDK

```javascript theme={null}
import OpenAI from "openai";

const client = new OpenAI({
    apiKey: "your-api-key",
    baseURL: "https://gateway.iotex.ai/v1"
});

async function streamChat(prompt) {
    const stream = await client.chat.completions.create({
        model: "gemini-2.5-flash",
        messages: [{ role: "user", content: prompt }],
        stream: true,
    });

    for await (const chunk of stream) {
        const content = chunk.choices[0]?.delta?.content;
        if (content) {
            process.stdout.write(content);
        }
    }
}

await streamChat("Explain what machine learning is");
```

<Note>
  For a browser-based streaming example using the Fetch API, see [JavaScript/Node.js Examples](/code-examples/javascript-nodejs#browser-usage-with-fetch-api).
</Note>

## Benefits of Streaming

* **Faster perceived response time** — users see content immediately as it's generated
* **Better user experience** — reduces waiting time and provides real-time feedback
* **Interruptible** — you can stop generation early if needed
* **Ideal for chat applications** — perfect for conversational interfaces

## Implementation Tips

1. **Error handling**: Wrap streaming code in try/catch to handle network interruptions
2. **Cancellation**: Implement the ability to cancel ongoing streams (e.g., using `AbortController` in JavaScript)
3. **Buffering**: For UI rendering, consider batching small chunks to avoid excessive DOM updates
4. **Memory**: For very long responses, process chunks as they arrive instead of accumulating the full string