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 50+ 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/ShaojieJiang/orcheo.

翻译：对话式搜索（CS）需要集成查询重构、排序和响应生成的复杂软件工程流水线。当前CS研究者面临两大障碍：缺乏用于高效共享社区贡献的统一框架，以及部署用户评估所需的端到端原型系统存在困难。本文介绍Orcheo——一个旨在弥合此鸿沟的开源平台。Orcheo具备三大核心优势：（i）模块化架构通过单文件节点模块促进组件复用，推动CS研究的共享与可复现性；（ii）生产就绪的基础设施通过双执行模式、安全凭证管理和执行遥测技术弥合原型与系统间的差距，内置的AI编程支持降低了学习门槛；（iii）入门套件资源包含50余个开箱即用的查询理解、排序和响应生成组件，支持快速构建完整的CS流水线。我们阐述了框架架构，并通过突显模块化与易用性的案例研究验证了Orcheo的实用性。Orcheo已基于MIT许可证在https://github.com/ShaojieJiang/orcheo开源发布。