AssistantGPT: Enhancing User Interaction with LLM Integration

As user interface technologies evolve, integrating voice and text commands becomes crucial for enhancing interaction with operating systems. AssistantGPT leverages OpenAI's GPT API to enable natural language-driven system functionalities, improving productivity through precise task interpretation and execution. The application supports a diverse range of operations, including web searches, API interactions via OpenAPI schemas, voice conversations, and command execution through the shell, demonstrating adaptability and scalability across various use cases and environments. Implemented using Electron.js, React, Python, and FastAPI, AssistantGPT demonstrates high efficiency, reliability, and user-friendliness. By bridging complex system functionalities and intuitive user interfaces, AssistantGPT significantly advances human-computer interaction, offering practical solutions for both professional and personal applications.

Authors

Publication Details

Published
2024-09-19
DOI
https://doi.org/10.1109/sisy62279.2024.10737548
Citations
6
Primary Topic
Service-Oriented Architecture and Web Services
Type
article
Field-Weighted Citation Impact
4.67
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article

AssistantGPT: Enhancing User Interaction with LLM Integration

Attila Kiss, Kálmán Balázs Neszlényi, Alex Milos
6 citations
Service-Oriented Architecture and Web Services
4.67
article

AssistantGPT: Enhancing User Interaction with LLM Integration

Attila Kiss, Kálmán Balázs Neszlényi, Alex Milos
article en
6 citations

Abstract

As user interface technologies evolve, integrating voice and text commands becomes crucial for enhancing interaction with operating systems. AssistantGPT leverages OpenAI's GPT API to enable natural language-driven system functionalities, improving productivity through precise task interpretation and execution. The application supports a diverse range of operations, including web searches, API interactions via OpenAPI schemas, voice conversations, and command execution through the shell, demonstrating adaptability and scalability across various use cases and environments. Implemented using Electron.js, React, Python, and FastAPI, AssistantGPT demonstrates high efficiency, reliability, and user-friendliness. By bridging complex system functionalities and intuitive user interfaces, AssistantGPT significantly advances human-computer interaction, offering practical solutions for both professional and personal applications.

Openalex Percentile: Top 5%
Service-Oriented Architecture and Web Services
4.67
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