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

# LogSpanModelStreamContent

> Span content type for streaming LLM inference operations with raw chunks and aggregated output.

# LogSpanModelStreamContent

Span content for streaming LLM inference calls. Unlike [LogSpanModelContent](/docs/reference/sdk/v2/typescript/types/LogSpanModelContent), this type captures both the raw stream chunks and an aggregated final output, giving you full visibility into the streaming lifecycle.

## Import

```typescript theme={null}
import type { LogSpanModelStreamContent } from '@adaline/api';
import { LogSpanModelStreamContentTypeEnum } from '@adaline/api';
```

## Type Definition

```typescript theme={null}
interface LogSpanModelStreamContent {
  type: 'ModelStream';
  provider: string;                // 1-512 chars
  model: string;                   // 1-512 chars
  input: string;                   // JSON string (must be valid JSON)
  output: string;                  // Raw stream chunks concatenated
  aggregateOutput: string;         // JSON string (must be valid JSON)
  variables?: LogSpanVariable | null;
  cost?: number | null;            // USD, minimum: 0
}
```

## Properties

* `type` - Discriminator field, always `'ModelStream'` for this content type
* `provider` - Provider name (e.g. `'openai'`, `'anthropic'`, `'google'`)
* `model` - Model identifier (e.g. `'gpt-4o'`, `'claude-sonnet-4-20250514'`)
* `input` - The request payload as a JSON string (`JSON.stringify()` of the request object)
* `output` - Raw stream chunks concatenated into a single string (does not need to be valid JSON)
* `aggregateOutput` - The final assembled response as a JSON string (`JSON.stringify()` of the complete response)
* `variables` - Variable attached for evaluation tracking ([LogSpanVariable](/docs/reference/sdk/v2/typescript/types/LogSpanVariable))
* `cost` - Inference cost in USD

<Note>
  All fields except `variables` and `cost` are required. This differs from `LogSpanModelContent` where every field is optional.
</Note>

***

## Example

```typescript theme={null}
import OpenAI from 'openai';

const openai = new OpenAI();

const params = {
  model: 'gpt-4o',
  messages: [
    { role: 'system' as const, content: 'You are a helpful assistant.' },
    { role: 'user' as const, content: 'Write a haiku about observability.' },
  ],
  stream: true,
};

const stream = await openai.chat.completions.create(params);

let chunks = '';
let fullContent = '';
for await (const chunk of stream) {
  const raw = JSON.stringify(chunk);
  chunks += raw + '\n';
  fullContent += chunk.choices[0]?.delta?.content ?? '';
}

span.update({
  content: {
    type: 'ModelStream',
    provider: 'openai',
    model: 'gpt-4o',
    input: JSON.stringify(params),
    output: chunks,
    aggregateOutput: JSON.stringify({ role: 'assistant', content: fullContent }),
    cost: 0.0018,
  },
});
```

***

## Related

* [LogSpanContent](/docs/reference/sdk/v2/typescript/types/LogSpanContent) — union type that includes `LogSpanModelStreamContent`
* [LogSpanModelContent](/docs/reference/sdk/v2/typescript/types/LogSpanModelContent) — non-streaming variant for single LLM calls
* [LogSpanVariable](/docs/reference/sdk/v2/typescript/types/LogSpanVariable) — variable type used in the `variables` field
* [Span](/docs/reference/sdk/v2/typescript/classes/span) — class that accepts `LogSpanContent` via `span.update()`