Orcheo: 一个用于对话式搜索的模块化全栈平台
Orcheo: A Modular Full-Stack Platform for Conversational Search
AI总结：
提出Orcheo开源平台，通过模块化架构、生产级基础设施和45+即用组件，解决对话式搜索研究中框架统一与原型部署的难题。
摘要：
对话式搜索（CS）需要一个复杂的软件工程流水线，集成了查询重构、排序和响应生成。CS研究人员目前面临两个障碍：缺乏一个统一的框架来有效地与社区共享贡献，以及难以部署用于用户评估的端到端原型。我们介绍了Orcheo，一个旨在弥合这一差距的开源平台。Orcheo提供三个关键优势：（i）模块化架构通过单文件节点模块促进组件复用，便于CS研究中的共享和可重复性；（ii）生产级基础设施通过双执行模式、安全凭证管理和执行遥测弥合原型到系统的差距，内置AI编码支持降低学习曲线；（iii）入门工具包包括45多个现成组件，用于查询理解、排序和响应生成，能够快速启动完整的CS流水线。我们描述了框架架构，并通过强调模块化和易用性的案例研究验证了Orcheo的实用性。Orcheo在MIT许可下以开源形式发布于此https URL。
英文摘要：
Conversational search (CS) requires a complex software engineering pipeline that integrates query reformulation, ranking, and response generation. CS researchers currently face two barriers: the lack of a unified framework for efficiently sharing contributions with the community, and the difficulty of deploying end-to-end prototypes needed for user evaluation. We introduce Orcheo, an open-source platform designed to bridge this gap. Orcheo offers three key advantages: (i) A modular architecture promotes component reuse through single-file node modules, facilitating sharing and reproducibility in CS research; (ii) Production-ready infrastructure bridges the prototype-to-system gap via dual execution modes, secure credential management, and execution telemetry, with built-in AI coding support that lowers the learning curve; (iii) Starter-kit assets include 45+ off-the-shelf components for query understanding, ranking, and response generation, enabling the rapid bootstrapping of complete CS pipelines. We describe the framework architecture and validate Orcheo's utility through case studies that highlight modularity and ease of use. Orcheo is released as open source under the MIT License at https://github.com/AI-Colleagues/orcheo.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
