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Pixeltable’s OpenAI integration enables you to access OpenAI models via the OpenAI API.

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Prerequisites

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Important notes

  • OpenAI usage may incur costs based on your OpenAI plan.
  • Be mindful of sensitive data and consider security measures when integrating with external services.
First you’ll need to install required libraries and enter your OpenAI API key. 
%pip install -qU pixeltable openai

import os
import getpass
if 'OPENAI_API_KEY' not in os.environ:
    os.environ['OPENAI_API_KEY'] = getpass.getpass('Enter your OpenAI API key:')
Now let’s create a Pixeltable directory to hold the tables for our demo. 
import pixeltable as pxt

# Remove the 'openai_demo' directory and its contents, if it exists
pxt.drop_dir('openai_demo', force=True)
pxt.create_dir('openai_demo')

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Chat completions

Create a Table: In Pixeltable, create a table with columns to represent your input data and the columns where you want to store the results from OpenAI. 
from pixeltable.functions import openai

# Create a table in Pixeltable and add a computed column that calls OpenAI

t = pxt.create_table('openai_demo.chat', {'input': pxt.String})

messages = [{'role': 'user', 'content': t.input}]
t.add_computed_column(output=openai.chat_completions(
    messages=messages,
    model='gpt-4o-mini',
    model_kwargs={
        # Optional dict with parameters for the OpenAI API
        'max_tokens': 300,
        'top_p': 0.9,
        'temperature': 0.7
    }
))

# Parse the response into a new column
t.add_computed_column(response=t.output.choices[0].message.content)

# Start a conversation
t.insert([{'input': 'How many islands are in the Aleutian island chain?'}])
t.select(t.input, t.response).head()

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Embeddings

Note: OpenAI Embeddings API is not available with free tier API keys 
emb_t = pxt.create_table('openai_demo.embeddings', {'input': pxt.String})
emb_t.add_computed_column(embedding=openai.embeddings(
    input=emb_t.input,
    model='text-embedding-3-small'
))

emb_t.insert([{'input': 'OpenAI provides a variety of embeddings models.'}])

emb_t.head()

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Image generations

image_t = pxt.create_table('openai_demo.images', {'input': pxt.String})
image_t.add_computed_column(img=openai.image_generations(
    image_t.input,
    model='dall-e-2',
))

image_t.insert([
    {'input': 'A giant Pixel floating in the open ocean in a sea of data'}
])

image_t

image_t.head()

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Audio Transcription

audio_t = pxt.create_table('openai_demo.audio', {'input': pxt.Audio})
audio_t.add_computed_column(result=openai.transcriptions(
    audio_t.input,
    model='whisper-1',
    model_kwargs={
        'language': 'en',
        'prompt': 'Transcribe the contents of this recording.'
    },
))

url = (
    'https://github.com/pixeltable/pixeltable/raw/release/tests/data/audio/'
    'jfk_1961_0109_cityuponahill-excerpt.flac'
)
audio_t.insert([{'input': url}])

audio_t.head()

audio_t.head()[0]['result']['text']

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Learn more

To learn more about advanced techniques like RAG operations in Pixeltable, check out the RAG Operations in Pixeltable tutorial. If you have any questions, don’t hesitate to reach out.
Last modified on December 13, 2025