agentitest

# 🤖 AgentiTest: Agentic Test Automation

This framework uses an LLM to automate browser testing through high-level, natural language commands. It's designed to be a flexible and developer-friendly tool for creating robust and maintainable browser tests.

## 🛠️ Tech Stack

* **[`browser-use`](https://github.com/browser-use/browser-use)**: Translates natural language into browser actions with an agent.
* **[`pytest`](https://github.com/pytest-dev/pytest)**: A framework for structuring and running tests.
* **[Allure Report](https://github.com/allure-framework/allure2)**: For creating interactive and detailed test reports.

![Allure Report Overview](media/allure-report-overview.png)

## ✨ Key Features

* **Natural Language Tests**: Write tests using descriptive, natural language tasks instead of brittle selectors.
* **Adaptable Logic**: The core testing logic is designed to be easily adapted for any website.
* **Insightful Reports**: Allure reports provide screenshots, agent actions, and AI "thoughts" for each step, giving you a clear view into the test execution.
* **Environment Documentation**: Key details about the test environment—such as the OS, Python version, and browser version—are automatically included in the Allure report for better debugging and context.
* **Customizable Browser Settings**: The framework allows for detailed configuration of browser settings. For more information, see the [Browser Settings documentation](https://docs.browser-use.com/customize/browser-settings).
* **Example Implementation**: `test_community_website.py` provides a practical example of how to write a test suite.

## ⚙️ How It Works

The framework's structure is designed for clarity and scalability, separating shared logic from individual tests. It's composed of two main parts:

* **A common file (`conftest.py`)**: This central file contains `pytest` fixtures for setting up the browser and the LLM, along with a reusable `run_agent_task` helper function that executes test steps.