<h1 align="center">Rasa Open Source</h1> <div align="center">

</div> <div align="center"> <h3>🚧 <b>Note: Maintenance Mode</b> 🚧</h3> <p> Rasa Open Source is currently in maintenance mode.

The future of building AI agents with Rasa is <b>Hello Rasa</b> and <b>CALM</b>.

</p> </div> <hr />

🚀 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?

No setup required: Open the playground, pick a template (Banking, Telecom, Support), and start building in your browser.
No NLU training: We have moved beyond intents. The LLM handles dialogue understanding while you define the business flows.
Built-in copilot: A specialized AI assistant helps you generate code, debug flows, and expand your agent instantly.
Production ready: Hello Rasa is not just a toy. Export your agent to the Rasa Platform when you are ready to scale.

Core concepts

CALM: Combines LLM flexibility with strict business logic. The LLM understands the user; the code enforces the rules.
Flows: Describe logical steps (e.g., collect money, transfer funds) rather than rigid dialogue trees.
Inspector: See real-time decision-making. No black boxes.

👉 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:

Network: Meet engineers building production agents
Learn: Discuss practical patterns, not just theory
Access: Direct influence on the Hello Rasa roadmap and early access to features

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:

Facebook Messenger
Slack
Google Hangouts
Webex Teams
Microsoft Bot Framework
Rocket.Chat
Mattermost
Telegram
Twilio
Your own custom conversational channels

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.

Install Poetry: Follow the official guide.
Build from source:
bash
```
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:

bash

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

Releases

Rasa follows Semantic Versioning.

Major: Incompatible API changes
Minor: Backward-compatible functionality
Patch: Backward-compatible bug fixes

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

README