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Run the same AI prompt against multiple images automatically, without writing loops or managing API calls.

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Problem

You have a collection of images that all need the same analysis—like “Describe this image”, “Is this product damaged?”, or “What objects are visible?”. Writing a loop to call an API for each image is tedious and error-prone. You need to handle rate limits, retries, and track which images succeeded or failed.

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Solution

What’s in this recipe:
  • Analyze multiple images with a single prompt using openai.vision()
  • Get all results at once, stored in your table
  • No loops or manual API calls
You add a computed column that applies openai.vision() to every image in your table. Pixeltable handles the API calls, retries, and result storage automatically. When you insert new images, the analysis runs automatically—no extra code needed.

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Setup

%pip install -qU pixeltable openai

import os
import getpass

if 'OPENAI_API_KEY' not in os.environ:
    os.environ['OPENAI_API_KEY'] = getpass.getpass('OpenAI API Key: ')

import pixeltable as pxt
from pixeltable.functions import openai

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Load images

# Create a fresh directory
pxt.drop_dir('vision_demo', force=True)
pxt.create_dir('vision_demo')

Connected to Pixeltable database at: postgresql+psycopg://postgres:@/pixeltable?host=/Users/pjlb/.pixeltable/pgdata
Created directory ‘vision_demo’.
<pixeltable.catalog.dir.Dir at 0x13d30b550>
t = pxt.create_table('vision_demo.images', {'image': pxt.Image})

Created table ‘images’.
# Insert sample images
t.insert([
    {'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000036.jpg'},
    {'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000090.jpg'},
    {'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000106.jpg'},
])

Inserting rows into `images`: 3 rows [00:00, 646.84 rows/s]
Inserted 3 rows with 0 errors.
3 rows inserted, 6 values computed.
# View loaded images
t.collect()

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Analyze images with AI

Add a computed column using openai.vision(). The prompt runs automatically on all images: 
# Define the prompt
PROMPT = "Describe this image in one sentence."

# Add computed column for AI analysis using openai.vision
t.add_computed_column(
    description=openai.vision(
        prompt=PROMPT,
        image=t.image,
        model='gpt-4o-mini'
    )
)

Added 3 column values with 0 errors.
3 rows updated, 6 values computed.

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View results

openai.vision() returns the text content directly: 
# View results: image alongside its AI-generated description
t.select(t.image, t.description).collect()

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New images are analyzed automatically

When you insert more images, the analysis runs without any extra code: 
# Insert a new image - analysis happens automatically
t.insert([{'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000139.jpg'}])

# View all results including the new image
t.select(t.image, t.description).collect()

Inserting rows into `images`: 1 rows [00:00, 684.00 rows/s]
Inserted 1 row with 0 errors.

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Explanation

How it works:
  1. Add images to your table
  2. Define a computed column with openai.vision()
  3. Pixeltable executes the API call for each row automatically
  4. Results are cached—rerunning won’t re-call the API
  5. New rows trigger automatic computation
Changing the prompt: To use a different prompt, add a new computed column with if_exists='replace': 
t.add_computed_column(
    description=openai.vision(prompt="New prompt", image=t.image, model='gpt-4o'),
    if_exists='replace'
)
Using other providers: Replace openai.vision with:
  • anthropic.messages for Claude
  • google.generate_content for Gemini
  • together.chat_completions for Together AI

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See also

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New images are analyzed automatically

When you insert more images, the analysis runs without any extra code: