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

# Streaming

> Token-by-token output over Server-Sent Events.

Set `"stream": true` to receive tokens incrementally. Tera streams responses as Server-Sent Events on the same `/v1/chat/completions` endpoint.

## Wire format

Each event is a single line prefixed with `data:` carrying a JSON delta. The stream terminates with `data: [DONE]`.

```text theme={null}
data: {"id":"...","object":"chat.completion.chunk","created":1700000000,"model":"Qwen/Qwen2.5-7B-Instruct","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"...","object":"chat.completion.chunk","created":1700000000,"model":"Qwen/Qwen2.5-7B-Instruct","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"...","object":"chat.completion.chunk","created":1700000000,"model":"Qwen/Qwen2.5-7B-Instruct","choices":[{"index":0,"delta":{"content":" there"},"finish_reason":null}]}

data: {"id":"...","object":"chat.completion.chunk","created":1700000000,"model":"Qwen/Qwen2.5-7B-Instruct","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]
```

## Reading the stream

<CodeGroup>
  ```python python theme={null}
  from openai import OpenAI

  client = OpenAI(base_url="https://api.tera.gw/v1", api_key="sk-tera-...")

  stream = client.chat.completions.create(
      model="Qwen/Qwen2.5-7B-Instruct",
      messages=[{"role": "user", "content": "Count to five."}],
      stream=True,
  )

  for chunk in stream:
      delta = chunk.choices[0].delta.content or ""
      print(delta, end="", flush=True)
  ```

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

  const client = new OpenAI({
    baseURL: "https://api.tera.gw/v1",
    apiKey: process.env.TERA_API_KEY,
  });

  const stream = await client.chat.completions.create({
    model: "Qwen/Qwen2.5-7B-Instruct",
    messages: [{ role: "user", content: "Count to five." }],
    stream: true,
  });

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

  ```bash curl theme={null}
  curl -N https://api.tera.gw/v1/chat/completions \
    -H "Authorization: Bearer $TERA_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "model": "Qwen/Qwen2.5-7B-Instruct",
      "messages": [{"role": "user", "content": "Count to five."}],
      "stream": true
    }'
  ```
</CodeGroup>

## Finish reasons

The final non-`[DONE]` event has a non-null `finish_reason`:

* `stop` — natural end of generation
* `length` — hit `max_tokens` or the model's max context
* `tool_calls` — the model emitted a tool call (see [Tool calling](/concepts/tool-calling))

## Streaming with reasoning models

Reasoning models (e.g. `Qwen/Qwen3.5-27B`) stream `reasoning_content` deltas before the visible content. See [Reasoning](/concepts/reasoning).

## Operational notes

* **Heartbeats** — we do not currently send keep-alive comments. Configure client read timeouts above your expected longest generation (server-side default: 120s).
* **Disconnects** — if the client disconnects mid-stream, generation is cancelled on the backend.
* **HTTP/2** — Tera supports HTTP/2; SDK defaults are fine.