Qwen 3.0 VL Upgrade Breaks Midscene XPath Locators

Hey there, fellow developers and automation enthusiasts! Have you ever hit a snag where a seemingly simple upgrade to a new, powerful AI model causes unexpected headaches in your existing automation workflows? Well, you're not alone. We've stumbled upon a curious case where upgrading from Qwen 2.5 VL to the newer, more advanced Qwen 3.0 VL within a Midscene automation environment leads to a significant hiccup: incorrect element XPath identification. This isn't just a minor annoyance; it can entirely derail your automated tests and tasks, especially when precision is paramount. Let's dive deep into understanding this issue, why it matters for your AI automation strategies, and what we can do about it. The goal here is to unravel the complexities, share insights, and help you navigate similar challenges in your own projects. We’ll explore the underlying problem, examine the technical evidence, and discuss potential workarounds to keep your automation robust and reliable, even as cutting-edge AI models evolve.

Understanding the Core Problem: Qwen VL, Midscene, and XPath

At the heart of this issue lies a fascinating interaction between large vision language models (Qwen VL), an AI automation framework called Midscene, and the fundamental concept of XPath for element location. The core problem, as observed, is that after upgrading to Qwen 3.0 VL, Midscene begins to generate incorrect XPath expressions when attempting to locate elements on a webpage, specifically a search input field on baidu.com. This contrasts sharply with the flawless performance of Qwen 2.5 VL, which correctly identifies the same elements. To truly grasp the gravity of this situation, let's break down each component. First, Qwen VL (Vision-Language) models are incredible pieces of AI technology that combine visual understanding with natural language processing. They can 'see' and 'understand' images, making them invaluable for tasks that involve interpreting graphical user interfaces (GUIs), such as recognizing buttons, text fields, and other interactive elements. When integrated into an automation framework like Midscene, these models aim to make automation more intuitive and resilient by allowing users to interact with web pages using natural language prompts, like simply saying "click the search box" or "type into the input field." This revolutionary approach promises to democratize automation, making it accessible even to those without deep coding knowledge, and to create more robust scripts that adapt to minor UI changes without constant maintenance.

Then there's Midscene, an automation framework that leverages such AI capabilities to interact with web elements, often relying on popular browser automation libraries like Playwright. When you tell Midscene to "locate the input field," it uses its integrated AI (in this case, Qwen VL) to analyze the current webpage's visual and structural information. Based on this analysis, the AI model is supposed to identify the element and provide a precise locator, such as an XPath, that Playwright can then use to interact with it. An XPath (XML Path Language) is essentially a query language for selecting nodes from an XML document, or in the context of web automation, an HTML document. It provides a powerful way to navigate through the elements and attributes of an HTML page, allowing you to pinpoint specific elements based on their position, attributes, or content. A correct XPath is like a street address for an element; it tells the automation tool exactly where to go. An incorrect XPath, however, is like a wrong address – the tool will get lost, fail to find the element, and your automation script will inevitably crash or perform unintended actions. This is precisely what happens with Qwen 3.0 VL. Instead of generating a valid, functional XPath that points to the desired search box, it produces an XPath that leads nowhere useful, effectively breaking the automation flow. This discrepancy highlights a critical challenge in adopting new AI models: ensuring backward compatibility and consistent performance, especially when they underpin foundational operations like element identification in sophisticated automation systems.

Diving Deeper into the Technical Details and Reproduced Steps

Let's get into the nitty-gritty of why this problem is occurring and how it manifests in the Midscene framework, specifically with Playwright. The core of the issue, as detailed in the user report, lies in the differing XPath outputs generated by Qwen 2.5 VL versus Qwen 3.0 VL for the exact same prompt and web page. This suggests a change in how the newer Qwen 3.0 VL model interprets the visual layout or structural hierarchy of the baidu.com page when asked to locate a generic