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141 lines
5.7 KiB
Markdown
141 lines
5.7 KiB
Markdown
<!-- WEHUB_ZH_README -->
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> [!NOTE]
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> 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。
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> [English](./README.en.md) · [原始项目](https://github.com/RasaHQ/rasa) · [上游 README](https://github.com/RasaHQ/rasa/blob/HEAD/README.md)
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> 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。
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<h1 align="center">Rasa Open Source</h1>
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<div align="center">
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[](https://info.rasa.com/community?utm_source=github&utm_medium=website&utm_campaign=)
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[](https://hello.rasa.ai/?utm_source=github&utm_medium=website&utm_campaign=)
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[](https://badge.fury.io/py/rasa)
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[](https://pypi.python.org/pypi/rasa)
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[](https://github.com/RasaHQ/rasa/actions)
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[](https://rasa.com/docs)
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</div>
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<br />
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<div align="center">
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<h3>🚧 <b>注意:维护模式</b> 🚧</h3>
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<p>
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Rasa Open Source 目前处于维护模式。
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<br />
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使用 Rasa 构建 AI agent 的未来方向是 <b>Hello Rasa</b> 与 <b>CALM</b>。
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</p>
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</div>
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<hr />
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## 🚀 Rasa 的未来:Hello Rasa
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**构建可靠的 AI agent 变得更容易了。**
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[**Hello Rasa**](https://hello.rasa.ai/?utm_source=github&utm_medium=website&utm_campaign=) 是我们全新的交互式 playground,用于原型化 AI agent。它将 LLM 的流畅表达能力与我们 **CALM**(Conversational AI with Language Models,基于语言模型的对话式 AI)引擎的可靠性相结合。
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### 为什么切换到 Hello Rasa?
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* **无需设置:** 打开 playground,选择一个模板(Banking、Telecom、Support),即可在浏览器中开始构建。
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* **无需 NLU 训练:** 我们已超越 intents。LLM 负责理解对话,而你定义业务流。
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* **内置 copilot:** 专用 AI 助手可帮助你生成代码、调试流程,并即时扩展 agent。
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* **可用于生产:** Hello Rasa 不只是玩具。准备扩展时,可将 agent 导出到 Rasa Platform。
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### 核心概念
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* **CALM:** 将 LLM 的灵活性与其严格的业务逻辑相结合。LLM 理解用户;代码强制执行规则。
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* **Flows(流程):** 描述逻辑步骤(例如收款、转账),而非僵化的对话树。
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* **Inspector(检查器):** 查看实时决策过程。没有黑箱。
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👉 **[在 Hello Rasa 免费开始构建](https://hello.rasa.ai/?utm_source=github&utm_medium=website&utm_campaign=)**
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---
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## 🧠 加入 Agent Engineering 社区
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我们正在为交付真实世界 AI agent 的人们打造一个家园。
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Agent Engineering 的演进速度超过任何单一框架。这是一个厂商中立的场所,可与行业内的构建者一起讨论架构、记忆、编排与安全。
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### 你能获得什么:
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* **人脉:** 结识正在构建生产级 agent 的工程师
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* **学习:** 讨论实用模式,而不仅是理论
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* **权限:** 直接影响 Hello Rasa 路线图,并抢先体验新功能
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| 频道 | 用途 |
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| :--- | :--- |
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| **#agent-design** | 架构、推理、记忆、测试 |
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| **#showcase** | 展示你的构建成果、演示与仓库 |
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| **#ask-anything** | 调试与工作流问题 |
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👉 **[加入社区](https://info.rasa.com/community?utm_source=github&utm_medium=website&utm_campaign=)**
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---
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<br>
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<br>
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# Rasa Open Source(旧版)
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> **注意:** 以下文档与安装说明适用于经典 Rasa Open Source 框架。如需最新的基于 CALM 的体验,请参阅上方的 [Hello Rasa](#-the-future-of-rasa-hello-rasa) 章节。
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Rasa 是一个用于自动化文本与语音对话的开源机器学习框架。借助 Rasa,你可以在以下渠道上构建上下文助手:
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- Facebook Messenger
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- Slack
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- Google Hangouts
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- Webex Teams
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- Microsoft Bot Framework
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- Rocket.Chat
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- Mattermost
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- Telegram
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- Twilio
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- 你自己的自定义对话渠道
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Rasa 帮助你构建能够处理大量来回交互、具备多层上下文的助手。
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### 📚 资源
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- 🤓 [阅读文档](https://rasa.com/docs/rasa/)
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- 😁 [安装 Rasa](https://rasa.com/docs/rasa/installation/environment-set-up)
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- 🚀 [全面了解 Conversational AI](https://learning.rasa.com/)
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- 🏢 [探索企业平台](https://rasa.com/product/rasa-platform/)
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## 开发内部机制与贡献
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我们欢迎贡献。开始前请先阅读我们的 [贡献指南](CONTRIBUTING.md)。
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### 开发环境安装
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Rasa 使用 **Poetry** 进行打包与依赖管理。
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1. **安装 Poetry**:请遵循[官方指南](https://python-poetry.org/docs/#installation).
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2. **从源码构建**:
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```bash
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make install
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```
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*macOS 用户注意*:若遇到编译器问题,请在安装前尝试 `export SYSTEM_VERSION_COMPAT=1`。
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### 运行测试
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请确保已安装开发依赖:
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```bash
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make prepare-tests-ubuntu # Ubuntu/Debian
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make prepare-tests-macos # macOS
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make test # Run tests
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```
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### 发布版本
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Rasa 遵循语义化版本(Semantic Versioning)。
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* **Major(主版本)**:不兼容的 API 变更
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* **Minor(次版本)**:向后兼容的功能新增
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* **Patch(补丁版本)**:向后兼容的缺陷修复
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有关发布节奏与维护政策的完整详情,请访问我们的 [产品发布与维护政策](https://rasa.com/rasa-product-release-and-maintenance-policy/).
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## 许可证
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根据 Apache License, Version 2.0 授权。Copyright 2022 Rasa Technologies GmbH。[许可证副本](https://www.google.com/search?q=LICENSE.txt).
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