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README.md

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+---
+language: en
+tags:
+- playwright
+- test-automation
+- qa
+- e2e-testing
+- rag
+license: apache-2.0
+datasets:
+- web-test-examples
+---
+
+# Playwright Test Automator
+
+A specialized model for automated generation of Playwright E2E test scripts based on web application crawl data.
+
+## Overview
+
+Playwright Test Automator is built on a RAG-based architecture that combines AI-powered test generation with Playwright's robust browser automation capabilities. The model is designed to generate reliable, maintainable, and efficient end-to-end tests with minimal human intervention.
+
+## Features
+
+- **Automated Crawling**: Intelligently crawls web applications to discover interactive elements and page structures
+- **Smart Login Detection**: Automatically identifies login forms and credentials fields
+- **Robust Selector Generation**: Creates resilient selectors that withstand minor UI changes
+- **Error Handling**: Implements comprehensive error handling for reliable test execution
+- **Validation Framework**: Integrated with Giskard for model validation and continuous improvement
+
+## Use Cases
+
+- Generating regression test suites for web applications
+- Automating QA workflows for small to large web projects
+- Creating test scripts for complex user journeys
+- Validating forms and interactive elements across browsers
+
+## Requirements
+
+- Python 3.11+
+- Playwright
+- OpenAI API access
+- Supabase for knowledge retrieval (optional)
+
+## Example Usage
+
+```python
+from services.crawler_service import crawler_service
+
+# Crawl a website and generate tests
+test_result = await crawler_service.crawl_with_login(
+    url="https://example.com/login",
+    username="test_user",
+    password="password123"
+)
+
+# Generate a Playwright test from the crawl data
+test_code = await crawler_service.generate_test_from_crawl_data(test_result)
+
+# Write the test to a file
+with open("example_test.spec.js", "w") as f:
+    f.write(test_code["code"])
+```
+
+## Sample Generated Test
+
+```javascript
+// Example E2E Test
+// Automated test for Example Application
+// Auto-generated by Playwright Test Automator
+
+import { test, expect } from '@playwright/test';
+
+test('Example E2E Test', async ({ page }) => {
+  // Configure viewport for better element visibility
+  await page.setViewportSize({ width: 1280, height: 800 });
+  
+  // Helper function for safer element interactions
+  async function safeClick(selector, description) {
+    // Implementation details...
+  }
+
+  // Navigate to the application
+  await page.goto('https://example.com/login');
+  
+  // Login process
+  await page.fill("input[type='text'][name='username']", "test_user");
+  await page.fill("input[type='password']", "password123");
+  await safeClick("button[type='submit']", "login button");
+  
+  // Verify successful login
+  await expect(page).toHaveURL(/dashboard/);
+});
+```
+
+## Limitations
+
+- Best performance on standard web forms and common UI patterns
+- May require adjustments for highly dynamic or custom UI frameworks
+- Requires valid credentials for protected areas of applications
+
+## Training Methodology
+
+This model was trained on a diverse set of web applications using a specialized dataset of high-quality test scripts. The training process included:
+
+1. Web crawling of various application types
+2. Test generation with OpenAI integration
+3. Validation using Giskard framework
+4. Iterative improvements based on execution results
+
+## Citation
+
+```
+@misc{playwright-test-automator,
+  author = {QA RAG App Team},
+  title = {Playwright Test Automator},
+  year = {2025},
+  publisher = {Hugging Face},
+  journal = {HuggingFace Hub},
+  howpublished = {\url{https://huggingface.co/playwright-test-automator}}
+}
+```