rasa README

The project's README from github.com/RasaHQ/rasa. As one markdown file: README.md.

Rasa Open Source

Join the Agent Engineering Community Try Hello Rasa PyPI version Supported Python Versions Build Status Documentation Status


🚧 Note: Maintenance Mode 🚧

Rasa Open Source is currently in maintenance mode.
The future of building AI agents with Rasa is Hello Rasa and CALM.


🚀 The Future of Rasa: Hello Rasa

Building reliable AI agents just got easier.

Hello Rasa is our new interactive playground for prototyping AI agents. It combines LLM fluency with the reliability of business logic using our CALM (Conversational AI with Language Models) engine.

Why switch to Hello Rasa?

Core concepts

👉 Start building for free at Hello Rasa


🧠 Join the Agent Engineering Community

We are building a home for people shipping real-world AI agents.

Agent Engineering is evolving faster than any single framework. This is a vendor-neutral space to discuss architectures, memory, orchestration, and safety with builders across the industry.

What you get:

Channel Purpose
#agent-design Architectures, reasoning, memory, testing
#showcase Show your builds, demos, and repos
#ask-anything Debugging and workflow questions

👉 Join the Community




Rasa Open Source (Legacy)

Note: The documentation and installation instructions below apply to the classic Rasa Open Source framework. For the latest CALM-based experience, see the Hello Rasa section above.

Rasa is an open source machine learning framework for automating text and voice-based conversations. With Rasa, you can build contextual assistants on:

Rasa helps you build contextual assistants that can handle layered conversations with lots of back-and-forth.

📚 Resources

Development Internals & Contributing

We are happy to receive contributions. Please review our Contribution Guidelines before getting started.

Installation for Development

Rasa uses Poetry for packaging and dependency management.

  1. Install Poetry: Follow the official guide.
  2. Build from source:
    make install
    
    Note for macOS users: If you run into compiler issues, try export SYSTEM_VERSION_COMPAT=1 before installation.

Running Tests

Make sure you have development requirements installed:

make prepare-tests-ubuntu # Ubuntu/Debian
make prepare-tests-macos  # macOS
make test                 # Run tests

Releases

Rasa follows Semantic Versioning.

For full details on our release cadence and maintenance policy, visit our Product Release and Maintenance Policy.

License

Licensed under the Apache License, Version 2.0. Copyright 2022 Rasa Technologies GmbH. Copy of the license.

rasa (RasaHQ/rasa)

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21.4K ·GitHub
这是什么?Rasa Open Source 是一个开源机器学习框架,用于自动化基于文本和语音的对话——你可以构建聊天机器人、语音助手这类有上下文理解能力的智能助手,然后把它们接入 Slack、Messenger、Telegram 等渠道。
它是我用来写代码的框架,还是更偏向托管的聊天机器人搭建平台?它是一个框架:一个 Python 代码库,你可以用它构建自己的智能助手,从 NLU(自然语言理解)到对话管理一应俱全。企业级的 Rasa Platform 是另一款独立产品——这个仓库就是开源框架本身。
要运行或折腾这个经典框架,我需要装些什么?需要一个 Python 环境——这个项目从里到外都是 Python,并用 Poetry 做打包和依赖管理。仓库里自带 Dockerfile,macOS 用户如果在从源码编译时编译器报错,可能需要设置 SYSTEMVERSIONCOMPAT=1。
现在用 Rasa 做开发还是靠这个仓库吗?不完全是——Rasa Open Source 已进入维护模式。项目的重心已经转向 Hello Rasa 和 CALM 引擎,所以这个仓库基本只会出修复,不会再有新功能。
用它构建的助手实际能部署在哪些地方?它可以接入 Facebook Messenger、Slack、Google Hangouts、Webex Teams、Microsoft Bot Framework、Rocket.Chat、Mattermost、Telegram 和 Twilio,也支持你自定义的对话渠道。
CALM 是什么?CALM(Conversational AI with Language Models,基于语言模型的对话式 AI)是 Rasa 较新的引擎:由大语言模型理解用户说的话,同时由代码来执行业务规则。你把流程描述成一个个逻辑步骤——比如收款或转账——而不是僵化的对话树。
Hello Rasa 的流程还需要意图训练数据吗?不需要。README 里说他们已经超越了意图(intents):由大语言模型负责对话理解,你只需定义业务流程,而且内置的 copilot 还能帮你生成代码、调试流程、扩展你的 agent。
Hello Rasa 是能上生产环境的,还是只是个演示?README 称它已达到生产可用级别——'not just a toy'(不只是玩具)——等你准备扩大规模时,可以把你的 agent 导出到 Rasa Platform。它还提供一个 Inspector,实时展示决策过程,完全没有黑箱。
这个项目有社区吗?有——一个厂商中立的 Agent Engineering Community,面向真正在生产环境中落地 AI agent 的开发者,里面有各种频道,比如讨论架构的 #agent-design、展示作品的 #showcase,以及提问排错的 #ask-anything。
What are similar projects?botkit, eliza, ChatterBot, botpress, NPC-Forge, leon, openclaw, pipecat
Creator
RasaHQ
Size
1.6 GB
Stars
21.4K
Age
10y
Commits · 90 Days