mobile-use – Open-source mobile AI agents that enable natural language control of smartphones

What is mobile-use？

mobile-use is a mobile AI agents tool that supports natural language control of Android and iOS devices, helping users operate their phones. Users can issue commands in everyday language, and the tool will automatically complete tasks such as opening apps, filling out forms, or extracting information. mobile-use can perceive UI interfaces, navigate intelligently, and supports data extraction and structuring. The tool is highly extensible, allowing configuration with different language models. It has been open-sourced on GitHub with detailed user guides and developer documentation for quick adoption by developers and users.

Key Features of mobile-use

• Natural language interaction: Control your phone using natural language commands without complex operations.

• Cross-platform support: Compatible with both Android and iOS devices, covering a broad user base.

• UI awareness and automation: Automatically recognizes and interacts with mobile UI elements, enabling intelligent navigation.

• Data extraction and structuring: Extracts information from apps and converts it into structured data for further processing.

• Task automation: Executes complex tasks such as filling out forms or searching for information, improving efficiency.

• Extensibility: Supports configuration with different language models to suit various scenarios and requirements.

Technical Principles of mobile-use

• Natural Language Processing (NLP): Uses NLP techniques to parse user commands and understand intent.

• UI automation framework: Leverages tools like ADB (Android Debug Bridge) and XCUITest (iOS) to identify and interact with UI elements.

• Model-driven architecture: Supports multiple language models (e.g., GPT-4), enabling intelligent interactions via API calls.

• Data collection and processing: Extracts information through screenshots and OCR technology, then structures it for processing.

• Multimodal fusion: Combines text, images, and other data types to enhance accuracy and efficiency in task execution.

Project Repository

• GitHub: https://github.com/minitap-ai/mobile-use

Application Scenarios of mobile-use

• Cross-app information retrieval and sharing: Extract a friend’s address from WeChat and open it in Amap for navigation.

• Social media interaction: Search for the trending topic #ArtificialIntelligence# on Weibo, follow relevant bloggers, and comment on their latest posts.

• Video platform operations: Search for the latest video from a creator on Bilibili, play it, and leave a comment.

• Daily task automation: Open Alipay, go to “My Bills,” and check the total expenses for the current month.

• Chinese app operations: Search for “Shanghai Disneyland guide” on Xiaohongshu, view the most-liked post, and save it to favorites.