# generation/streamers

Streamers for surfacing generated tokens as they are produced.

Pass a `TextStreamer` (or `WhisperTextStreamer` for audio transcription) via
the `streamer` argument of `generate()` to receive decoded text as tokens
are emitted — useful for chat UIs and incremental transcription.

**Example:** Stream generated text to stdout
```javascript
import { pipeline, TextStreamer } from '@huggingface/transformers';

const generator = await pipeline('text-generation', 'onnx-community/Qwen3-0.6B-ONNX');
const streamer = new TextStreamer(generator.tokenizer, {
  skip_prompt: true,
  callback_function: (text) => process.stdout.write(text),
});
await generator('Tell me a joke about JavaScript.', { max_new_tokens: 64, streamer });
```

## Classes

### BaseStreamer

Abstract base class for output streamers.

#### `BaseStreamer.put(value)`

Function that is called by `.generate()` to push new tokens

**Parameters**

- `value` (`bigint[][]`)

#### `BaseStreamer.end()`

Function that is called by `.generate()` to signal the end of generation

### TextStreamer

Simple text streamer that prints the token(s) to stdout as soon as entire words are formed.

#### `TextStreamer.constructor(tokenizer, options)`

**Parameters**

- `tokenizer` ([`PreTrainedTokenizer`](../tokenizers#module_tokenizers.PreTrainedTokenizer))
- `options` (`Object`)
  - `skip_prompt` (`boolean`) _optional_ — defaults to `false` — Whether to skip the prompt tokens
  - `skip_special_tokens` (`boolean`) _optional_ — defaults to `true` — Whether to skip special tokens when decoding
  - `callback_function` (`function(string): void`) _optional_ — defaults to `null` — Function to call when a piece of text is ready to display
  - `token_callback_function` (`function(bigint[]): void`) _optional_ — defaults to `null` — Function to call when a new token is generated
  - `decode_kwargs` (`Object`) _optional_ — defaults to `{}` — Additional keyword arguments to pass to the tokenizer's decode method

#### `TextStreamer.put(value)`

Receives tokens, decodes them, and prints them to stdout as soon as they form entire words.

**Parameters**

- `value` (`bigint[][]`)

#### `TextStreamer.end()`

Flushes any remaining cache and prints a newline to stdout.

#### `TextStreamer.on_finalized_text(text, stream_end)`

Prints the new text to stdout. If the stream is ending, also prints a newline.

**Parameters**

- `text` (`string`)
- `stream_end` (`boolean`)

### WhisperTextStreamer

Utility class to handle streaming of tokens generated by whisper speech-to-text models.
Callback functions are invoked when each of the following events occur:
 - A new chunk starts (on_chunk_start)
 - A new token is generated (callback_function)
 - A chunk ends (on_chunk_end)
 - The stream is finalized (on_finalize)

#### `WhisperTextStreamer.constructor(tokenizer, options)`

**Parameters**

- `tokenizer` (`WhisperTokenizer`)
- `options` (`Object`)
  - `skip_prompt` (`boolean`) _optional_ — defaults to `false` — Whether to skip the prompt tokens
  - `callback_function` (`function(string): void`) _optional_ — defaults to `null` — Function to call when a piece of text is ready to display
  - `token_callback_function` (`function(bigint[]): void`) _optional_ — defaults to `null` — Function to call when a new token is generated
  - `on_chunk_start` (`function(number): void`) _optional_ — defaults to `null` — Function to call when a new chunk starts
  - `on_chunk_end` (`function(number): void`) _optional_ — defaults to `null` — Function to call when a chunk ends
  - `on_finalize` (`function(): void`) _optional_ — defaults to `null` — Function to call when the stream is finalized
  - `time_precision` (`number`) _optional_ — defaults to `0.02` — Precision of the timestamps
  - `skip_special_tokens` (`boolean`) _optional_ — defaults to `true` — Whether to skip special tokens when decoding
  - `decode_kwargs` (`Object`) _optional_ — defaults to `{}` — Additional keyword arguments to pass to the tokenizer's decode method

#### `WhisperTextStreamer.put(value)`

**Parameters**

- `value` (`bigint[][]`)