react-native-devtools-frontend/scripts/ai_assistance

AI Assistance Evaluation

This directory contains scripts for the prompt iteration & evaluation process for AI Assistance.

Mainly, auto-run.js script takes example URLs, runs the examples and outputs the results to the data/ directory. Then, the HTML page in eval/ folder takes these results and presents them in a UI for evaluation.

Running

Prerequisites

• You need to have at least Node v20 to run Auto AI Assistance.
• You need to have a version of Chrome that contains the AI Assistance feature. (i.e. you also need to be logged in & have sync enabled)

Steps

1. Run a AI Assistance enabled Chrome executable with --remote-debugging-port 9222 and --auto-open-devtools-for-tabs targeting about:blank. For example:

/Applications/Google\ Chrome\ Canary.app/Contents/MacOS/Google\ Chrome\ Canary --remote-debugging-port=9222 --auto-open-devtools-for-tabs about:blank

2. Make sure you use en-US locale in DevTools.

3. Close the DevTools window for the initial about:blank page but keep the tab open.

4. Run the following command. See below for the list of values --test-target supports. This flag is used to determine which AI experience is evaluated.

node scripts/ai_assistance/auto-run.js --test-target elements --example-urls <example-url-1> <example-url-2>

At the end of these steps, the examples in the urls <example-url-1> and <example-url-2> should be run and the results must be saved to the data/ folder.

Tip: You can add a --label <label> argument to the run to label the dataset. For example:

node scripts/ai_assistance/auto-run.js --label title-change --example-urls <example-url-1> <example-url-2>

--test-target values

• elements: tests the entrypoint via right clicking on an element in the Elements panel.
• performance-main-thread: tests the entrypoint via right clicking on an event in the Performance panel main thread.
• performance-insights: tests the entrypoint via the "Ask AI" button shown on an individual Insight in the Performance panel sidebar.

Evaluating the results

Steps

1. Serve the scripts/ai_assistance folder by using a simple file server. For example:

python3 -m http.server

2. Visit http://localhost:8000/eval URL to see the UI.
3. Select the dataset you want to evaluate in the UI. (Dataset: selector)
4. Evaluate the examples one by one.

Tip: You can navigate the questions with Tab key and move between examples with ArrowLeft and ArrowRight.