Floating LLM Function Buttons for Context-Aware Browser Workflows
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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, which persist across webpages, dynamically modify based on content, and include custom buttons for specific tasks, enabling efficient, flexible, and accurate interactions with AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional systems provide localized access to AI models within a singular webpage, then the system structure is simple, but navigation efficiency deteriorates requiring excessive device interactions
Solution Approach 1:
The floating widget serves multiple functions: it provides AI model access, displays contextual information, and remains visible across different webpages simultaneously. This multi-functionality eliminates the need for users to navigate between separate pages for AI interaction and information display, reducing navigation time while maintaining relatively simple system architecture.
Solution Approach 2:
The system transitions from a localized two-dimensional webpage-based AI access model to a three-dimensional floating widget that overlays content across the webpage surface. This dimensional change allows the AI interface to persist and adapt across different webpage contexts without requiring users to leave the current page, thereby reducing navigation interactions.
2Ease of manufacture
If conventional systems use rigid localized access to AI models, then implementation is straightforward, but operational flexibility deteriorates limiting functionality
Solution Approach 1:
The floating widget dynamically adapts its content and functionality based on the current webpage context. It automatically adjusts which AI functions are displayed and how information is presented according to the detected webpage content, maintaining operational flexibility while preserving the simplicity of the floating interface architecture.
Solution Approach 2:
The system applies different AI functions and interface characteristics to different webpage contexts. By analyzing the local webpage content and applying appropriate AI capabilities accordingly, the system achieves operational flexibility without requiring complex centralized control, thus maintaining implementation ease.
3Device complexity
If conventional systems rely on user prompts for AI responses, then the system is simple, but response accuracy deteriorates due to incomplete data
Solution Approach 1:
The floating widget performs preliminary actions by automatically detecting and extracting relevant information from the current webpage before the user needs to query the AI model. This pre-processing of contextual data ensures that the AI receives complete and accurate information, improving response accuracy without significantly increasing system complexity.
Solution Approach 2:
The floating widget acts as an intermediary between the webpage content and the AI model. It extracts, processes, and prepares relevant information from the webpage, then presents it to the AI model in a structured format. This intermediary function ensures accurate data transmission and improves response accuracy while maintaining relatively simple system architecture.
4Device complexity
If conventional systems require separate navigation to access AI models, then the interface is simple, but productivity deteriorates due to excessive interactions
Solution Approach 1:
The system merges the AI model interface with the webpage viewing experience by placing the floating widget directly on the webpage. This combination allows users to access AI functions while viewing content, eliminating the need to switch between separate pages and significantly improving productivity while maintaining interface simplicity.
Solution Approach 2:
The floating widget maintains continuous visibility and accessibility of AI functions throughout the webpage viewing process. Unlike conventional systems where AI access is interrupted by navigation requirements, the floating widget ensures continuous interaction capability, improving productivity by eliminating broken interaction flows.
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.