Simon Willison’s Weblog

OpenAI released their new Jev-style Decisions API, as previously announced at last week's DevDay.

Since I already have an llm-typesafe plugin for talking to Jev, I had GPT-6 Astra read the new OpenAI API documentation and build an llm-openai-decisions plugin inspired by llm-typesafe.

Unlike Jev, the new gpt-6-luna decision model supports image input in addition to text. Both models charge for input it and not for output: OpenAI's is 10 cents per million input tokens, Jev's is 4.2 cents per million.

Otherwise the API shape is very similar to Jev, at least conceptually. Jev supports three question types for yes/no, choices, or scores. OpenAI Decisions supports the same three types.

Install the plugin like this:

llm install llm-openai-decisions

Here's an example query against an image attachment:

llm -m openai-decisions/gpt-6-luna \
  -a https://static.simonwillison.net/static/2025/two-pelicans.jpg \
  -s 'Does this image contain any mammals?'

And example output:

{"type": "predicate", "name": "evaluation", "probability": 0.0}

Consult the README for full details of how to run the other types of questions.

I built this new plugin for LLM to add support for TypeSafe AI's new Jev model. Install it like this:

llm install llm-typesafe

Then set an API key (get one here, the waitlist seems to move pretty fast):

llm keys set typesafe
# Paste key

And now you can ask yes/no "noul" questions like this:

llm -m jev 'Please refund my last payment.' \
  -s 'Does this message explicitly request a refund?'

Output:

{"type": "noul", "noul": 0.99}

Or choice questions like this:

cat message.txt | llm -m jev \
  -s 'Which team should handle this message? If billing and technical issues both occur, choose billing.' \
  -o answer_type choice \
  -o criteria '{
    "billing":"Charges, invoices, payments, or refunds",
    "technical":"Problems installing or using the product",
    "other":"Neither category fits"
  }'

Or scoring questions like this:

cat report.txt | llm -m jev \
  -s 'How reproducible is the problem described in this report?' \
  -o answer_type score \
  -o criteria '[
    "No reproduction instructions",
    "Some instructions, but important steps are missing",
    "Complete steps with expected and actual results"
  ]'

See the README for more details.