> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pixeltable.com/llms.txt
> Use this file to discover all available pages before exploring further.
# whisper
> 
# module pixeltable.functions.whisper
Pixeltable UDFs
that wraps the OpenAI Whisper library.
This UDF will cause Pixeltable to invoke the relevant model locally. In order to use it, you must
first `pip install openai-whisper`.
## udf transcribe()
```python Signature theme={"theme":{"light":"light-plus","dark":"dark-plus"}}
@pxt.udf
transcribe(
audio: pxt.Audio,
*,
model: pxt.String,
temperature: pxt.Json[(Float, ...)] | None = (0.0, 0.2, 0.4, 0.6, 0.8, 1.0),
compression_ratio_threshold: pxt.Float | None = 2.4,
logprob_threshold: pxt.Float | None = -1.0,
no_speech_threshold: pxt.Float | None = 0.6,
condition_on_previous_text: pxt.Bool = True,
initial_prompt: pxt.String | None = None,
word_timestamps: pxt.Bool = False,
prepend_punctuations: pxt.String = '"\'“¿([{-',
append_punctuations: pxt.String = '"\'.。,，!！?？:：”)]}、',
decode_options: pxt.Json | None = None
) -> pxt.Json
```
Transcribe an audio file using Whisper.
This UDF runs a transcription model *locally* using the Whisper library,
equivalent to the Whisper `transcribe` function, as described in the
[Whisper library documentation](https://github.com/openai/whisper).
**Requirements:**
* `pip install openai-whisper`
**Parameters:**
* **`audio`** (`pxt.Audio`): The audio file to transcribe.
* **`model`** (`pxt.String`): The name of the model to use for transcription.
**Returns:**
* `pxt.Json`: A dictionary containing the transcription and various other metadata.
**Examples:**
Add a computed column that applies the model `base.en` to an existing Pixeltable column `tbl.audio`
of the table `tbl`:
```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}}
tbl.add_computed_column(result=transcribe(tbl.audio, model='base.en'))
```