Evaluation Methods: Similarity Check ? about promptfoo HOT 6 CLOSED

I appreciate the feedback! Right now, evaluation is done in one of three ways:

1. Direct string comparison: this is the default behavior for anything you put in the __expected column.

2. Basic Javascript logic: using the eval: prefix, you can run string checks and keyword matches on output. For example:

   eval: output.includes('foo')
   

   The test runner expects a piece of Javascript code that returns a pass/fail boolean.

3. Self-grading with LLM: using the grade: prefix, you can ask an LLM to evaluate the output against your criteria. For example:

   grade: output contains a reference to a movie
   

   The test runner uses the provider specified in the --grader option

4. Human evaluation - the web ui helps facilitate the thumbsup/thumbsdown rating. You can aggregate these ratings and pick the "best" prompt accordingly.

In short, keyword matching and exact overlap should be handled by case 1. Semantic similarity testing is a great suggestion. I'll look into this and see if I can get it added :)

See also: https://www.promptfoo.dev/docs/configuration/expected-outputs

from promptfoo.

Support for semantic similarity is added in #7. When it lands, I'll deploy a new version of the library 0.5.0.

It works like this:

Semantic similarity: using the similar prefix, you can run compare the semantic similarity of expected vs output using OpenAI embeddings.

For example, the directive similar(0.8): hello world will test that cosine distance is >= 0.8 for test outputs

Hope this helps!

from promptfoo.

Thanks for the suggestions, @MentalGear! I've simplified the github readme and pointed users toward the docs website, which is definitely easier to navigate.

from promptfoo.

Correction: link is https://github.com/squidgyai/squidgy-testy

from promptfoo.

Thank you for the super-swift reply @typpo and planning on #7 !

With semantic similarity added, promptfoo should be among, if not the, very best open-source prompt-testing framework! (and even be on par with what commercial platforms like Vellum are offering for testing)

Just one more quick suggestion: You might want to consolidate your documentation into one place. It's excellent on https://www.promptfoo.dev/docs/intro - which is also where I found after a bit of digging the evaluation methods you mentioned. But if you also keep a version with different content in the readme.md, it can be confusing as there's no single source of truth (SSOT).

I would suggest keeping the intro and "promo gifts" along with the icon grid in the readme, and have a big link directly to the documentation at https://www.promptfoo.dev/docs/intro. :)

from promptfoo.

Thank you and darn, that was quick ! I just finished writing a blog post about open-source PT frameworks and already had to update it. 😅

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