Context-Aware LLM Function Buttons for Browser Workflow Access
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Solution Overview
Problem
Conventional systems for accessing artificial intelligence models are inefficient, operationally inflexible, and inaccurate due to localized access, excessive navigation, and reliance on incomplete user prompts.
Innovation Solution
A floating widget approach that generates adaptable large language model (LLM) function buttons within a web browser, dynamically modifying based on webpage content, allowing for customizable and autonomous workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional systems provide localized access to AI models within a specific webpage, then the system structure is simple, but navigation efficiency deteriorates requiring excessive device interactions
Solution Approach 1:
The patent applies the dynamics principle by transforming the static localized AI access system into a dynamic floating widget that adapts its position and functionality based on user needs. The widget moves freely across different webpages, allowing users to access AI models without navigating away from their current context, thus reducing navigation time while maintaining system flexibility
Solution Approach 2:
The floating AI widget serves multiple functions across different webpages, combining search, analysis, and interaction capabilities in a single universal interface. This multi-functionality eliminates the need for separate localized AI access points on each webpage, reducing the number of device interactions required while maintaining access to AI models throughout the browsing experience
2Ease of manufacture
If conventional systems use rigid localized access to AI models, then implementation is straightforward, but operational flexibility deteriorates limiting task capabilities
Solution Approach 1:
The system transitions from rigid localized access to a dynamic floating widget that automatically adapts to different webpage contents and user actions. The widget modifies its behavior based on the detected webpage context, enabling flexible task execution across diverse websites while maintaining a unified access interface that was relatively easy to implement
Solution Approach 2:
The floating AI widget performs self-service by automatically detecting webpage content, determining relevant AI functions, and presenting appropriate interaction options without requiring manual configuration. This self-adaptive behavior provides operational flexibility across different tasks while keeping the implementation straightforward through automated context-aware functionality
3Device complexity
If conventional systems rely on user prompts for AI responses, then system simplicity is maintained, but response accuracy deteriorates due to incomplete information
Solution Approach 1:
The system performs preliminary action by automatically analyzing webpage content before the user needs to interact with the AI model. It extracts relevant information, identifies key concepts, and prepares contextual data that will enhance the accuracy of subsequent AI responses. This preliminary content processing occurs in the background, maintaining system simplicity while significantly improving response accuracy through pre-computed contextual understanding
Solution Approach 2:
The floating AI widget acts as an intermediary between the user and the AI model, automatically enriching user prompts with contextual information extracted from the webpage. This intermediary function bridges the gap between simple user input and accurate AI responses by injecting relevant background information, thereby improving response accuracy without requiring complex user-side modifications
Data Source
AI summary
This disclosure describes systems that generate a selection of large language model (LLM) function buttons in a floating widget within a web browser of a client device. The disclosed systems can generate or otherwise select the LLM function buttons to include based on context of a webpage within the web browser. Responsive to detecting an indication of an interaction with an LLM function button, the disclosed systems can generate a side panel within the web browser according to the LLM function button. In some embodiments, the disclosed systems can display and utilize a customized LLM function button responsive to detecting a certain webpage or content within the webpage. Further, in some embodiments, the disclosed systems can generate an LLM function button to perform a customized workflow responsive to detecting a certain webpage or content within the webpage.