用大模型打造农村智能服务元搜索平台，让村民轻松找解决方案。
FUTURAL: A Metasearch Platform for Empowering Rural Areas with Smart Solutions
- 用开源数据+大模型构建自然语言搜索界面。
- 原型测试显示检索准确率高，可快速扩展功能。
- 适合关注数字普惠与乡村智慧化的研究者和开发者。
FUTURAL项目旨在通过五大关键领域的一系列数字智能解决方案（SS），应对紧迫的社会与环境问题。该项目的核心是一个强大的元搜索平台，不仅作为FUTURAL解决方案的主要访问入口，还支持检索其他项目的智能解决方案。本文详细介绍了元搜索平台的最小可行产品（MVP）实现，聚焦于单一开源数据服务，并利用大语言模型（LLMs）的生成能力构建用户友好的自然语言接口。文中详述了MVP设计、用于适配特定应用的LLM工具，以及全面的评估方法。评估结果表明，该方法高效且易于在未来的MVP迭代中部署。这一基础工作为平台扩展至更多服务和多样数据集铺平道路，从而提升其应对更广泛查询与数据集的能力。
原文摘要 · Abstract (English)
The FUTURAL project aims to provide a comprehensive suite of digital Smart Solutions (SS) across five critical domains to address pressing social and environmental issues. Central to this initiative is a robust Metasearch platform, which will not only serve as the primary access point to FUTURAL's solutions but also facilitate the search and retrieval of SS developed by other initiatives. This paper elaborates on the MVP implementation for the MetaSearch platform. It focuses on a single, open-source data service and harnesses the generative capabilities of Large Language Models (LLMs) to create a user-friendly natural language interface. The design of the Minimum Viable Product (MVP), the tools used for adapting LLMs to our specific application, and our comprehensive set of evaluation techniques are thoroughly detailed. The results from our evaluations demonstrate that our approach is highly effective and can be efficiently implemented in future iterations of the MVP. This groundwork paves the way for extending the platform to include additional services and diverse data sets from the FUTURAL project, enhancing its capacity to address a broader array of queries and datasets.
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