Summary

Auto Inspector is an open-source AI agent designed to automate web testing by translating user stories into executable test reports. It targets engineers and researchers seeking to streamline testing workflows, allowing them to focus on test planning while the AI handles execution.

How It Works

The agent interprets natural language user stories to perform web interactions and generate test results. It operates as both a Docker-based GUI application and a Node.js CLI utility, offering flexibility for different user needs. This AI-driven approach aims to simplify test creation by abstracting complex scripting.

Quick Start & Requirements

The GUI version requires Docker and Docker Compose. After cloning the repository and adding an OPENAI_API_KEY to a .env file, the application can be started with make up. The CLI version requires Node.js v20+ and an OPENAI_API_KEY. Installation involves cloning, navigating to the backend, running npm install, and then executing tests via npm run example:voyager or npm run scenario. Note: The GUI version is currently not ready for self-hosting.

Highlighted Details

• Open-source under the Apache 2.0 license.
• Dual interface: Dockerized GUI for ease of use and Node.js CLI for development.
• Roadmap indicates planned features such as variable/secret management, multi-case execution, real-time UI updates, and improved action/page stabilization.

Maintenance & Community

The project is actively under development, with a roadmap detailing planned features for a stable release. Contributors are encouraged to open issues for suggestions or feedback. No specific community channels or notable contributors are listed.

Licensing & Compatibility

Licensed under Apache 2.0, generally permissive for commercial use and integration with closed-source projects.

Limitations & Caveats

The GUI version is explicitly stated as not ready for self-hosting. Many features are still in progress (marked with 🏗️ in the roadmap), indicating the project is in an alpha or beta stage. Operation relies on an external OpenAI API key, introducing potential costs and service dependencies.