QA GPT

One of the most painful and ignored parts of software development is thorough testing. Sure, great engineers will write unit tests & integration tests. Some might even write UI tests. But if you're lazy like me, you tend to be a little lackadaisical when it comes to testing your product with the user in mind. A quote I've frequently heard is "That's the QA team's job" when it comes to functionality testing.

I made QA GPT to help engineers & QA teams test the functionality of their products without writing any code and without spending already constrained human time doing functionality tests.

Here's a short demo video showing how it works:

Running QA GPT

Running QA GPT is remarkably simple, as it's just a simple python project. Note that you must have access to GPT-4-Vision in order to be able to run QA GPT. To run the project:

1. Get your GPT-4-Vision enabled API key from OpenAI
2. Drop the key into the OPENAI_API_KEY environment variable
3. Open main.py and change the task and url in the initial driver.navigate to match your test case
4. Activate a python virtual environment if you are using one and install requirements: pip install -r requirements.txt.
5. Run python main.py

I've included an example testing task in main.py that logs into a website with the given credentials, makes a change to an input field, saves it, and verifies that it was successfully saved. Feel free to modify the task and url as you wish to fit your test case.

Roadmap

• Use GPT-4 Vision to automate browser actions
• Basic actions like click + fill in an input field
• Prompt engineering to make it recognize when things go wrong
• Log stack traces and record sessions
• Drag and drop action
• Map stack traces to timestamps in video recordings
• A clean UI to view the video recordings + see stack traces
• Plug into CI tools for continuous runs on every commit to the master branch
• Chain prompts for deeper understanding of failures
• Alerting into Slack when errors come up
• Plugin LlaVa and CogVLM to make the AI cheaper + faster
• Write better comments + make a Youtube explainer.
• Introduce a hosted solution

Acknowledgements

• https://github.com/ishan0102/vimGPT. The entire vision module + usage of Vimium is basically copied from Ishan's repo.
• https://github.com/nat/natbot. This gave me inspiration in the first place to use Generative AI for testing automation