@inproceedings{al-shaibani-etal-2026-promptlab,
title = "{P}rompt{L}ab: A Collaborative Platform for Prompt Engineering and Dataset Curation",
author = "Al-shaibani, Maged S. and
Alyafeai, Zaid and
Refai, Dania and
Alomari, Nawaf and
Ashraf, Ahmed and
Alheraki, Mais and
Alturki, Mustafa and
Luqman, Hamzah and
Ahmad, Irfan",
editor = "Croce, Danilo and
Leidner, Jochen and
Moosavi, Nafise Sadat",
booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
month = mar,
year = "2026",
address = "Rabat, Marocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eacl-demo.18/",
pages = "225--260",
ISBN = "979-8-89176-382-1",
abstract = "PromptLab is a web-based platform for collaborative prompt engineering across diverse natural language processing tasks and datasets. The platform addresses primary challenges in prompt development, including template creation, collaborative review, and quality assurance through a comprehensive workflow that supports both individual researchers and team-based projects. PromptLab integrates with HuggingFace and provides AI-assisted prompt generation via OpenRouter[{\ensuremath{<}}https://openrouter.ai/{\ensuremath{>}}], and supporting real-time validation with multiple Large Language Models (LLMs). The platform features a flexible templating system using Jinja2, role-based project management, peer review processes, and supports programmatic access through RESTful APIs. To ensure data privacy and support sensitive research environments, PromptLab includes an easy CI/CD pipeline for self-hosted deployments and institutional control. We demonstrate the platform{'}s effectiveness through two evaluations: a controlled comparison study with six researchers across five benchmark datasets and 13 models with 90 prompts; and a comprehensive case study in instruction tuning research, where over 350 prompts across 80+ datasets have been developed and validated by multiple team members. The platform is available at \url{https://promptlab.up.railway.app} and the source code is available on GitHub at \url{https://github.com/KFUPM-JRCAI/PromptLab}."
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<abstract>PromptLab is a web-based platform for collaborative prompt engineering across diverse natural language processing tasks and datasets. The platform addresses primary challenges in prompt development, including template creation, collaborative review, and quality assurance through a comprehensive workflow that supports both individual researchers and team-based projects. PromptLab integrates with HuggingFace and provides AI-assisted prompt generation via OpenRouter[\ensuremath<https://openrouter.ai/\ensuremath>], and supporting real-time validation with multiple Large Language Models (LLMs). The platform features a flexible templating system using Jinja2, role-based project management, peer review processes, and supports programmatic access through RESTful APIs. To ensure data privacy and support sensitive research environments, PromptLab includes an easy CI/CD pipeline for self-hosted deployments and institutional control. We demonstrate the platform’s effectiveness through two evaluations: a controlled comparison study with six researchers across five benchmark datasets and 13 models with 90 prompts; and a comprehensive case study in instruction tuning research, where over 350 prompts across 80+ datasets have been developed and validated by multiple team members. The platform is available at https://promptlab.up.railway.app and the source code is available on GitHub at https://github.com/KFUPM-JRCAI/PromptLab.</abstract>
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%0 Conference Proceedings
%T PromptLab: A Collaborative Platform for Prompt Engineering and Dataset Curation
%A Al-shaibani, Maged S.
%A Alyafeai, Zaid
%A Refai, Dania
%A Alomari, Nawaf
%A Ashraf, Ahmed
%A Alheraki, Mais
%A Alturki, Mustafa
%A Luqman, Hamzah
%A Ahmad, Irfan
%Y Croce, Danilo
%Y Leidner, Jochen
%Y Moosavi, Nafise Sadat
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Marocco
%@ 979-8-89176-382-1
%F al-shaibani-etal-2026-promptlab
%X PromptLab is a web-based platform for collaborative prompt engineering across diverse natural language processing tasks and datasets. The platform addresses primary challenges in prompt development, including template creation, collaborative review, and quality assurance through a comprehensive workflow that supports both individual researchers and team-based projects. PromptLab integrates with HuggingFace and provides AI-assisted prompt generation via OpenRouter[\ensuremath<https://openrouter.ai/\ensuremath>], and supporting real-time validation with multiple Large Language Models (LLMs). The platform features a flexible templating system using Jinja2, role-based project management, peer review processes, and supports programmatic access through RESTful APIs. To ensure data privacy and support sensitive research environments, PromptLab includes an easy CI/CD pipeline for self-hosted deployments and institutional control. We demonstrate the platform’s effectiveness through two evaluations: a controlled comparison study with six researchers across five benchmark datasets and 13 models with 90 prompts; and a comprehensive case study in instruction tuning research, where over 350 prompts across 80+ datasets have been developed and validated by multiple team members. The platform is available at https://promptlab.up.railway.app and the source code is available on GitHub at https://github.com/KFUPM-JRCAI/PromptLab.
%U https://aclanthology.org/2026.eacl-demo.18/
%P 225-260
Markdown (Informal)
[PromptLab: A Collaborative Platform for Prompt Engineering and Dataset Curation](https://aclanthology.org/2026.eacl-demo.18/) (Al-shaibani et al., EACL 2026)
ACL
- Maged S. Al-shaibani, Zaid Alyafeai, Dania Refai, Nawaf Alomari, Ahmed Ashraf, Mais Alheraki, Mustafa Alturki, Hamzah Luqman, and Irfan Ahmad. 2026. PromptLab: A Collaborative Platform for Prompt Engineering and Dataset Curation. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 225–260, Rabat, Marocco. Association for Computational Linguistics.