AI2Apps: A Visual IDE for Building LLM-based AI Agent Applications
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arXiv
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| Format: | Preprint |
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2024
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| author | Pang, Xin Li, Zhucong Chen, Jiaxiang Cheng, Yuan Xu, Yinghui Qi, Yuan |
| author_facet | Pang, Xin Li, Zhucong Chen, Jiaxiang Cheng, Yuan Xu, Yinghui Qi, Yuan |
| contents | We introduce AI2Apps, a Visual Integrated Development Environment (Visual IDE) with full-cycle capabilities that accelerates developers to build deployable LLM-based AI agent Applications. This Visual IDE prioritizes both the Integrity of its development tools and the Visuality of its components, ensuring a smooth and efficient building experience.On one hand, AI2Apps integrates a comprehensive development toolkit ranging from a prototyping canvas and AI-assisted code editor to agent debugger, management system, and deployment tools all within a web-based graphical user interface. On the other hand, AI2Apps visualizes reusable front-end and back-end code as intuitive drag-and-drop components. Furthermore, a plugin system named AI2Apps Extension (AAE) is designed for Extensibility, showcasing how a new plugin with 20 components enables web agent to mimic human-like browsing behavior. Our case study demonstrates substantial efficiency improvements, with AI2Apps reducing token consumption and API calls when debugging a specific sophisticated multimodal agent by approximately 90% and 80%, respectively. The AI2Apps, including an online demo, open-source code, and a screencast video, is now publicly accessible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_04902 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AI2Apps: A Visual IDE for Building LLM-based AI Agent Applications Pang, Xin Li, Zhucong Chen, Jiaxiang Cheng, Yuan Xu, Yinghui Qi, Yuan Artificial Intelligence Software Engineering We introduce AI2Apps, a Visual Integrated Development Environment (Visual IDE) with full-cycle capabilities that accelerates developers to build deployable LLM-based AI agent Applications. This Visual IDE prioritizes both the Integrity of its development tools and the Visuality of its components, ensuring a smooth and efficient building experience.On one hand, AI2Apps integrates a comprehensive development toolkit ranging from a prototyping canvas and AI-assisted code editor to agent debugger, management system, and deployment tools all within a web-based graphical user interface. On the other hand, AI2Apps visualizes reusable front-end and back-end code as intuitive drag-and-drop components. Furthermore, a plugin system named AI2Apps Extension (AAE) is designed for Extensibility, showcasing how a new plugin with 20 components enables web agent to mimic human-like browsing behavior. Our case study demonstrates substantial efficiency improvements, with AI2Apps reducing token consumption and API calls when debugging a specific sophisticated multimodal agent by approximately 90% and 80%, respectively. The AI2Apps, including an online demo, open-source code, and a screencast video, is now publicly accessible. |
| title | AI2Apps: A Visual IDE for Building LLM-based AI Agent Applications |
| topic | Artificial Intelligence Software Engineering |
| url | https://arxiv.org/abs/2404.04902 |