mlsanityData to 14 Oct 2026

Generative AI Toolkit -- a framework for increasing the quality of LLM-based applications over their whole life cycle

arXiv 2412.14215 ↗First posted 18 Dec 2024cs.SE cs.AIcited by 2

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Abstract (arXiv)

As LLM-based applications reach millions of customers, ensuring their scalability and continuous quality improvement is critical for success. However, the current workflows for developing, maintaining, and operating (DevOps) these applications are predominantly manual, slow, and based on trial-and-error. With this paper we introduce the Generative AI Toolkit, which automates essential workflows over the whole life cycle of LLM-based applications. The toolkit helps to configure, test, continuously monitor and optimize Generative AI applications such as agents, thus significantly improving quality while shortening release cycles. We showcase the effectiveness of our toolkit on representative use cases, share best practices, and outline future enhancements. Since we are convinced that our Generative AI Toolkit is helpful for other teams, we are open sourcing it on and hope that others will use, forward, adapt and improve

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 18 of its 61 references that are in the map. First posted on arXiv 18 Dec 2024.

Builds on

18 of 61 references.

References · 18

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6 more
  1. 2023Textbooks Are All You Needcited by 569
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.