Open Source TypeScript QA Automation Software

ai-wright adds AI steps to any Playwright test. ai.act carries out UI actions from a plain-language objective, ai.verify makes vision-driven assertions that fail the step when the model is not confident enough, and ai.extract pulls structured data from the page. Screenshots are annotated with Set-of-Marks overlays and combined with DOM element maps, so the model can work through complex UIs. Keep most of each test as deterministic Playwright code and use AI only on the brittle steps. It is for teams writing Playwright end-to-end tests who want AI help on dynamic interfaces such as chat widgets, canvas dashboards and multi-step wizards, without vendor lock-in. Bring your own OpenAI, Google Gemini or Anthropic Claude key, or use a TestChimp key. Install with npm install ai-wright, then import { ai } from 'ai-wright' in your tests. Maintained by TestChimp (https://testchimp.io), the QA platform for coding agents.

semantic-graph finds duplicate and related tests in your test suite. It scans Playwright-style test files written with test() and test.describe(), embeds each test, groups similar tests with DBSCAN clustering and names each cluster with an LLM. The results open in a local web UI with a folder tree and a 2D similarity graph laid out with UMAP, so overlapping tests are easy to spot. It is for developers and QA engineers who want to keep a growing suite lean and find tests that cover the same ground. Run it with npx @testchimp/semantic-graph visualize --tests-dir ./tests and an OpenAI API key, or use Anthropic Claude together with Voyage embeddings. No database is needed, since embeddings are computed in memory on each run. Maintained by TestChimp (https://testchimp.io), the QA platform for coding agents.

Your Apollo GraphQL development companion for doing quality, faster. Chimp helps you write high-quality code from the get-go. No more putting tests and quality as an after-thought. Quality first, speed for free. Boilerplate is time-consuming, error-prone and boring! Chimp reduces that through its various generators and smart defaults. Modularity leads to maintainable and testable code, and this is a key feature of all Chimp's domain-driven and data-driven generators. Chimp encourages a test-driven workflow by creating tests based on your schema, and helping you stay on the straight and narrow. Chimp's GQL scaffolding will generate and wire up types, resolvers, and tests, ready for you to write use-cases for your app. Per the single responsibility principle, every query, mutation and field resolver are isolated making them easy to maintain long-term. Use Chimp on new or existing projects, and walk away any time. There are no runtime dependencies as it uses a pure Apollo stack.