Prompto: An open source library for asynchronous querying of LLM endpoints
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Abstract (arXiv)
Recent surge in Large Language Model (LLM) availability has opened exciting avenues for research. However, efficiently interacting with these models presents a significant hurdle since LLMs often reside on proprietary or self-hosted API endpoints, each requiring custom code for interaction. Conducting comparative studies between different models can therefore be time-consuming and necessitate significant engineering effort, hindering research efficiency and reproducibility. To address these challenges, we present prompto, an open source Python library which facilitates asynchronous querying of LLM endpoints enabling researchers to interact with multiple LLMs concurrently, while maximising efficiency and utilising individual rate limits. Our library empowers researchers and developers to interact with LLMs more effectively and allowing faster experimentation, data generation and evaluation. prompto is released with an introductory video (https://youtu.be/lWN9hXBOLyQ) under MIT License and is available via GitHub (https://github.com/alan-turing-institute/prompto).
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 22 references that are in the map. First posted on arXiv 12 Aug 2024.
Builds on
13 of 22 references.
References · 13
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- 2024Aya 23: Open Weight Releases to Further Multilingual Progresscited by 123
1 more
- 2024On the Societal Impact of Open Foundation Modelscited by 65
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Citing papers per year: 2024: 1; 2025: 0; 2026: 1.
2 papers.