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Evaluating models and prompts

Evaluation dataset consists of 16 screenshots. A Python script for running screenshot-to-code on the dataset and a UI for rating outputs is included. With this set up, we can compare and evaluate various models and prompts.

Running evals

  • Input screenshots should be located at backend/evals_data/inputs and the outputs will be backend/evals_data/outputs. If you want to modify this, modify EVALS_DIR in backend/evals/config.py. You can download the input screenshot dataset here: TODO.
  • Set a stack (STACK var) in backend/run_evals.py
  • Run python backend/run_evals.py - this runs the screenshot-to-code on the input dataset in parallel but it will still take a few minutes to complete.
  • Once the script is done, you can find the outputs in backend/evals_data/outputs.

Rating evals

In order to view and rate the outputs, visit your front-end at /evals.

  • Rate each output on a scale of 1-4
  • You can also print the page as PDF to share your results with others.

Generally, I run three tests for each model/prompt + stack combo and take the average score out of those tests to evaluate.