docs: make Chinese README the default

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+<!-- WEHUB_ZH_README -->
+> [!NOTE]
+> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。  
+> [English](./README.en.md) · [原始项目](https://github.com/deepset-ai/haystack) · [上游 README](https://github.com/deepset-ai/haystack/blob/HEAD/README.md)  
+> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
+
 <div align="center">
-  <a href="https://haystack.deepset.ai/"><img src="https://raw.githubusercontent.com/deepset-ai/haystack/main/images/banner.png" alt="Blue banner with the Haystack logo and the text ‘haystack by deepset – The Open Source AI Framework for Production Ready RAG & Agents’ surrounded by abstract icons representing search, documents, agents, pipelines, and cloud systems."></a>
+  <a href="https://haystack.deepset.ai/"><img src="https://raw.githubusercontent.com/deepset-ai/haystack/main/images/banner.png" alt="蓝色横幅，带有 Haystack 徽标及文字「haystack by deepset – 面向生产就绪 RAG 与 Agent 的开源 AI 框架」，周围环绕代表搜索、文档、Agent、流水线与云系统的抽象图标。"></a>

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@@ -9,106 +15,105 @@
 | Meta    | [![Discord](https://img.shields.io/discord/993534733298450452?logo=discord)](https://discord.com/invite/qZxjM4bAHU) [![Twitter Follow](https://img.shields.io/twitter/follow/haystack_ai)](https://twitter.com/haystack_ai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
 </div>

-[Haystack](https://haystack.deepset.ai/) is an open-source AI orchestration framework for building production-ready LLM applications in Python.
+[Haystack](https://haystack.deepset.ai/) 是一款用于在 Python 中构建生产就绪 LLM 应用的开源 AI 编排框架。

-Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Build scalable RAG systems, multimodal applications, semantic search, question answering, and autonomous agents, all in a transparent architecture that lets you experiment, customize deeply, and deploy with confidence.
+设计模块化流水线与 Agent 工作流，对检索、路由、记忆与生成进行显式控制。构建可扩展的 RAG 系统、多模态应用、语义搜索、问答与自主 Agent，全部采用透明架构，便于你实验、深度定制并自信部署。

-## Table of Contents
+## 目录

- [Installation](#installation)
- [Documentation](#documentation)
- [Features](#features)
- [Haystack Enterprise: Support & Platform](#haystack-enterprise-support--platform)
- [Telemetry](#telemetry)
- [🖖 Community](#-community)
- [Contributing to Haystack](#contributing-to-haystack)
- [Organizations using Haystack](#organizations-using-haystack)
+- [安装](#installation)
+- [文档](#documentation)
+- [特性](#features)
+- [Haystack Enterprise：支持与平台](#haystack-enterprise-support--platform)
+- [遥测](#telemetry)
+- [🖖 社区](#-community)
+- [为 Haystack 做贡献](#contributing-to-haystack)
+- [使用 Haystack 的组织](#organizations-using-haystack)


-## Installation
+## 安装

-The simplest way to get Haystack is via pip:
+获取 Haystack 最简单的方式是通过 pip：

 ```sh
 pip install haystack-ai
 ```

-Install nightly pre-releases to try the newest features:
+安装每夜预发布版本以试用最新功能：
 ```sh
 pip install --pre haystack-ai
 ```

-Haystack supports multiple installation methods, including Docker images. For a comprehensive guide, please refer
-to the [documentation](https://docs.haystack.deepset.ai/docs/installation).
+Haystack 支持多种安装方式，包括 Docker 镜像。如需完整指南，请参阅
+[文档](https://docs.haystack.deepset.ai/docs/installation).

-## Documentation
+## 文档

-If you're new to the project, check out ["What is Haystack?"](https://haystack.deepset.ai/overview/intro) then go
-through the ["Get Started Guide"](https://haystack.deepset.ai/overview/quick-start) and build your first LLM application
-in a matter of minutes. Keep learning with the [tutorials](https://haystack.deepset.ai/tutorials). For more advanced
-use cases, or just to get some inspiration, you can browse our Haystack recipes in the
-[Cookbook](https://haystack.deepset.ai/cookbook).
+如果你是项目新手，请查看 ["什么是 Haystack？"](https://haystack.deepset.ai/overview/intro)，然后阅读
+["入门指南"](https://haystack.deepset.ai/overview/quick-start)，在几分钟内构建你的第一个 LLM 应用。
+继续通过 [教程](https://haystack.deepset.ai/tutorials). 学习。如需更高级的用例，或只是想获取一些灵感，可以浏览我们在
+[Cookbook](https://haystack.deepset.ai/cookbook). 中的 Haystack 示例。

-At any given point, hit the [documentation](https://docs.haystack.deepset.ai/docs/intro) to learn more about Haystack, what it can do for you, and the technology behind.
+任何时候，都可以查阅 [文档](https://docs.haystack.deepset.ai/docs/intro)，进一步了解 Haystack、它能为你做什么，以及背后的技术。

-## Features
+## 特性

-**Built for context engineering**  
-Design flexible systems with explicit control over how information is retrieved, ranked, filtered, combined, structured, and routed before it reaches the model. Define pipelines and agent workflows where retrieval, memory, tools, and generation are transparent and traceable.
+**面向上下文工程（Context Engineering）构建**  
+设计灵活的系统，对信息在到达模型之前如何被检索、排序、过滤、组合、结构化与路由进行显式控制。定义流水线与 Agent 工作流，使检索、记忆、工具与生成透明且可追溯。

-**Model- and vendor-agnostic**  
-Integrate with OpenAI, Mistral, Anthropic, Cohere, Hugging Face, Azure OpenAI, AWS Bedrock, local models, and many others. Swap models or infrastructure components without rewriting your system.
+**模型与供应商无关（Model- and vendor-agnostic）**  
+可与 OpenAI、Mistral、Anthropic、Cohere、Hugging Face、Azure OpenAI、AWS Bedrock、本地模型等众多平台集成。无需重写系统即可更换模型或基础设施组件。

-**Modular and customizable**  
-Use built-in components for retrieval, indexing, tool calling, memory, and evaluation, or create your own. Add loops, branches, and conditional logic to precisely control how context moves through your pipelines and agent workflows.
+**模块化且可定制**  
+使用内置组件完成检索、索引、工具调用、记忆与评估，或创建你自己的组件。添加循环、分支与条件逻辑，精确控制上下文在流水线与 Agent 工作流中的流转方式。

-**Extensible ecosystem**  
-Build and share custom components through a consistent interface that makes it easy for the community and third parties to extend Haystack and contribute to an open ecosystem.
+**可扩展生态**  
+通过一致的接口构建并分享自定义组件，便于社区与第三方扩展 Haystack，并为开放生态做出贡献。

 > [!TIP]
 >
-> Would you like to deploy and serve Haystack pipelines as **REST APIs** or **MCP servers**? [Hayhooks](https://github.com/deepset-ai/hayhooks) provides a simple way for you to wrap pipelines and agents with custom logic and expose them through HTTP endpoints or MCP. It also supports OpenAI-compatible chat completion endpoints and works with chat UIs like [open-webui](https://openwebui.com/).
+> 你是否希望将 Haystack 流水线部署并提供为 **REST API** 或 **MCP 服务器**？[Hayhooks](https://github.com/deepset-ai/hayhooks) 提供了一种简单方式，让你用自定义逻辑封装流水线与 Agent，并通过 HTTP 端点或 MCP 对外暴露。它还支持 OpenAI 兼容的聊天补全端点，并可与 [open-webui](https://openwebui.com/). 等聊天 UI 配合使用。

-## Haystack Enterprise: Support & Platform
+## Haystack Enterprise：支持与平台

-Get expert support from the Haystack team, build faster with enterprise-grade templates, and scale securely with deployment guides for cloud and on-prem environments with **Haystack Enterprise Starter**. Read more about it in the [announcement post](https://haystack.deepset.ai/blog/announcing-haystack-enterprise).
+获取 Haystack 团队的专业支持，借助企业级模板更快构建，并通过面向云端与本地（on-prem）环境的部署指南安全扩展，一切尽在 **Haystack Enterprise Starter**。详情请参阅[公告博文](https://haystack.deepset.ai/blog/announcing-haystack-enterprise).

-👉 [Get Haystack Enterprise Starter](https://www.deepset.ai/products-and-services/haystack-enterprise-starter?utm_source=github.com&utm_medium=referral&utm_campaign=haystack_enterprise)
+👉 [获取 Haystack Enterprise Starter](https://www.deepset.ai/products-and-services/haystack-enterprise-starter?utm_source=github.com&utm_medium=referral&utm_campaign=haystack_enterprise)

-Need a managed production setup for Haystack? The **Haystack Enterprise Platform** helps you build, test, deploy and operate Haystack pipelines with built-in observability, collaboration, governance, and access controls. It’s available as a managed cloud service or as a self-hosted solution.
+需要为 Haystack 配置托管式生产环境吗？**Haystack Enterprise Platform** 可帮助您构建、测试、部署和运维 Haystack 流水线（pipeline），内置可观测性（observability）、协作、治理与访问控制。可作为托管云服务或自托管方案使用。

-👉 Learn more about [Haystack Enterprise Platform](https://www.deepset.ai/products-and-services/haystack-enterprise-platform?utm_campaign=developer-relations&utm_source=haystack&utm_medium=readme) or [try it free](https://www.deepset.ai/haystack-enterprise-platform-trial?utm_campaign=developer-relations&utm_source=haystack&utm_medium=readme)
+👉 了解更多 [Haystack Enterprise Platform](https://www.deepset.ai/products-and-services/haystack-enterprise-platform?utm_campaign=developer-relations&utm_source=haystack&utm_medium=readme) 相关信息，或[免费试用](https://www.deepset.ai/haystack-enterprise-platform-trial?utm_campaign=developer-relations&utm_source=haystack&utm_medium=readme)

-## Telemetry
+## 遥测（Telemetry）

-Haystack collects **anonymous** usage statistics of pipeline components. We receive an event every time these components are initialized. This way, we know which components are most relevant to our community.
+Haystack 会收集流水线组件的**匿名**使用统计信息。每当这些组件被初始化时，我们都会收到一条事件。借此，我们能够了解哪些组件对社区最为重要。

-Read more about telemetry in Haystack or how you can opt out in [Haystack docs](https://docs.haystack.deepset.ai/docs/telemetry).
+有关 Haystack 遥测或如何选择退出的更多信息，请参阅 [Haystack 文档](https://docs.haystack.deepset.ai/docs/telemetry).

-## 🖖 Community
+## 🖖 社区

-If you have a feature request or a bug report, feel free to open an [issue in GitHub](https://github.com/deepset-ai/haystack/issues). We regularly check these, so you can expect a quick response. If you'd like to discuss a topic or get more general advice on how to make Haystack work for your project, you can start a thread in [Github Discussions](https://github.com/deepset-ai/haystack/discussions) or our [Discord channel](https://discord.com/invite/VBpFzsgRVF). We also check [𝕏 (Twitter)](https://twitter.com/haystack_ai) and [Stack Overflow](https://stackoverflow.com/questions/tagged/haystack).
+如有功能请求或错误报告，欢迎在 GitHub 上提交 [issue](https://github.com/deepset-ai/haystack/issues).。我们会定期查看，通常能较快回复。如需讨论某个话题，或获取如何让 Haystack 更好地服务于您项目的通用建议，可在 [Github Discussions](https://github.com/deepset-ai/haystack/discussions) 发起话题，或前往我们的 [Discord 频道](https://discord.com/invite/VBpFzsgRVF).。我们也会关注 [𝕏 (Twitter)](https://twitter.com/haystack_ai) 和 [Stack Overflow](https://stackoverflow.com/questions/tagged/haystack).

-## Contributing to Haystack
+## 为 Haystack 做贡献

-We are very open to the community's contributions - be it a quick fix of a typo, or a completely new feature! You don't need to be a Haystack expert to provide meaningful improvements. To learn how to get started, check out our [Contributor Guidelines](https://github.com/deepset-ai/haystack/blob/main/CONTRIBUTING.md) first.
+我们非常欢迎社区贡献——无论是修正一处笔误，还是提交全新功能！您无需成为 Haystack 专家也能做出有意义的改进。请先查阅我们的[贡献者指南](https://github.com/deepset-ai/haystack/blob/main/CONTRIBUTING.md)，了解如何开始。

-There are several ways you can contribute to Haystack:
- Contribute to the main Haystack project
- Contribute an integration on [haystack-core-integrations](https://github.com/deepset-ai/haystack-core-integrations)
- Contribute to the documentation in [haystack/docs-website](https://github.com/deepset-ai/haystack/tree/main/docs-website)
+您可以通过以下方式为 Haystack 做贡献：
+- 为主 Haystack 项目做贡献
+- 在 [haystack-core-integrations](https://github.com/deepset-ai/haystack-core-integrations) 上贡献集成
+- 在 [haystack/docs-website](https://github.com/deepset-ai/haystack/tree/main/docs-website) 中为文档做贡献

 > [!TIP]
->👉 **[Check out the full list of issues that are open to contributions](https://github.com/orgs/deepset-ai/projects/14)**
+>👉 **[查看完整列表：欢迎贡献的 issue](https://github.com/orgs/deepset-ai/projects/14)**

-## Organizations using Haystack
+## 使用 Haystack 的组织

-Haystack is used by thousands of teams building production AI systems across industries, including:
+数以千计的团队正在使用 Haystack 构建跨行业的生产级 AI 系统，其中包括：

- **Technology & AI Infrastructure**: [Apple](https://www.apple.com/), [Meta](https://www.meta.com/about), [Databricks](https://www.databricks.com/), [NVIDIA](https://developer.nvidia.com/blog/reducing-development-time-for-intelligent-virtual-assistants-in-contact-centers/), [Intel](https://github.com/intel/open-domain-question-and-answer#readme)
- **Public Sector AI Initiatives**: [European Commission](https://commission.europa.eu/index_en), [German Federal Ministry of Research, Technology, and Space (BMFTR)](https://www.deepset.ai/case-studies/german-federal-ministry-research-technology-space-bmftr), [PD, Baden-Württemberg State](https://www.pd-g.de/)
- **Enterprise & Industrial AI Applications**: [Airbus](https://www.deepset.ai/case-studies/airbus), [Lufthansa Industry Solutions](https://haystack.deepset.ai/blog/lufthansa-user-story), [Infineon](https://www.infineon.com/), [LEGO](https://github.com/larsbaunwall/bricky#readme), [Comcast](https://arxiv.org/html/2405.00801v2), [Accenture](https://www.accenture.com/), [TELUS Agriculture & Consumer Goods](https://www.telus.com/agcg/en)
- **Knowledge & Content Platforms**: [Netflix](https://netflix.com), [ZEIT Online](https://www.deepset.ai/case-studies/zeit-online), [Rakuten](https://www.rakuten.com/), [Oxford University Press](https://corp.oup.com/), [Manz](https://www.deepset.ai/case-studies/manz), [YPulse](https://www.deepset.ai/case-studies/ypulse)
+- **科技与 AI 基础设施**：[Apple](https://www.apple.com/), [Meta](https://www.meta.com/about), [Databricks](https://www.databricks.com/), [NVIDIA](https://developer.nvidia.com/blog/reducing-development-time-for-intelligent-virtual-assistants-in-contact-centers/), [Intel](https://github.com/intel/open-domain-question-and-answer#readme)
+- **公共部门 AI 倡议**：[European Commission](https://commission.europa.eu/index_en), [German Federal Ministry of Research, Technology, and Space (BMFTR)](https://www.deepset.ai/case-studies/german-federal-ministry-research-technology-space-bmftr), [PD, Baden-Württemberg State](https://www.pd-g.de/)
+- **企业与工业 AI 应用**：[Airbus](https://www.deepset.ai/case-studies/airbus), [Lufthansa Industry Solutions](https://haystack.deepset.ai/blog/lufthansa-user-story), [Infineon](https://www.infineon.com/), [LEGO](https://github.com/larsbaunwall/bricky#readme), [Comcast](https://arxiv.org/html/2405.00801v2), [Accenture](https://www.accenture.com/), [TELUS Agriculture & Consumer Goods](https://www.telus.com/agcg/en)
+- **知识与内容平台**：[Netflix](https://netflix.com), [ZEIT Online](https://www.deepset.ai/case-studies/zeit-online), [Rakuten](https://www.rakuten.com/), [Oxford University Press](https://corp.oup.com/), [Manz](https://www.deepset.ai/case-studies/manz), [YPulse](https://www.deepset.ai/case-studies/ypulse)


-Are you also using Haystack? Open a PR or [tell us your story](https://forms.gle/Mm3G1aEST3GAH2rn8)
+您也在使用 Haystack 吗？欢迎提交 PR，或[与我们分享您的故事](https://forms.gle/Mm3G1aEST3GAH2rn8)