Awesome AI AgentsWeb Automation Systems

theredsix/cerebellum

⭐ 864 Python repository created 2024-09-16

Cerebellum is a lightweight browser automation system designed to accomplish user-defined goals on web pages by simulating keyboard and mouse actions. It operates by simplifying web browsing into navigating a directed graph where each webpage represents a node containing visible elements and data, and user actions such as clicking or typing represent edges that transition between these nodes. The system starts at an initial webpage and aims to reach a target node that signifies the completion of the user's goal. It leverages a large language model (LLM), specifically Claude 3.5 Sonnet, to analyze page content and interactive elements to discover new nodes and decide the next action based on the current state and past actions. This decision-making process is iterative, with Cerebellum executing the LLM's planned actions and feeding the resulting new state back into the LLM until the goal is achieved or deemed unachievable. Cerebellum is compatible with any Selenium-supported browser and supports form filling using user-provided JSON data. It also accepts runtime instructions to dynamically adjust browsing strategies and actions. The project is actively being developed with a roadmap that includes handling tabbed browsing, improving scrolling behaviors, adding data extraction capabilities, supporting additional LLMs, and creating training datasets from browsing sessions. Known issues include limitations with the current LLM's refusal to solve CAPTCHAs and navigate pages with political content. The project is open for contributions and is maintained by Han Wang along with several collaborators. It is licensed under the MIT License. Cerebellum offers a novel approach to browser automation by integrating AI-driven planning to navigate complex web interactions, making it a powerful tool for automating web-based tasks that require goal-oriented browsing and interaction.

https://github.com/theredsix/cerebellum

agentsaiai-driven-planningautomation-frameworkautomation-uibrowserbrowser-automationbrowsing-strategiesclaude-3.5-sonnetdata-extractiondirected-graphfine-tuningform-fillingkeyboard-and-mouse-actionslarge-language-modelllmmit-licenseopen-sourceruntime-instructionsscrolling-behaviorseleniumtabbed-browsingtraining-datasetsuser-defined-goalsweb-navigationwebpage-nodes

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