rasa
Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Decision gist · record as of 2026-08-14
Yes. Rasa is a mature, actively maintained framework (last commit 2026-07-24, 21297 GitHub stars) with Apache-2.0 licensing, no known security vulnerabilities, and low install friction. It is well-suited for teams building multi-channel conversational agents. The large dependency footprint and Python version cap are minor trade-offs for a production-grade ML framework.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.8,<3.11.
- Full functionality may require optional dependencies like tokenizers, which on macOS may need a Rust compiler.
- Low install friction with a pure Python wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for proprietary applications and internal deployment.
last release 2025-01-14 (577 days) · last repo commit 2026-07-24 · 21,297 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 258,673 downloads/mo, #8,425 on PyPI
Alternatives
Verify before relying
pip install rasa
import rasa
from rasa.nlu.model import Interpreter
# Load a trained NLU model to parse user intent
interpreter = Interpreter.load('path/to/model')
result = interpreter.parse('hello')- Whether the 81 runtime dependencies are all required at install time or if many are optional/conditional
- Current state of the Jira migration for issue tracking and community support responsiveness
- Performance characteristics and scalability limits for production dialogue systems
- Whether pre-trained models or training datasets are included or must be sourced separately
What it is and what it does
Rasa is a machine learning framework for building conversational agents that understand natural language and manage multi-turn dialogue. It provides NLU (intent and entity recognition), dialogue policy learning, and connectors to major messaging platforms (Slack, Facebook, Telegram, Mattermost, Rocket.Chat, Webex Teams, Microsoft Bot Framework) and voice assistants (Alexa, Google Home). The framework handles contextual conversations where the assistant builds on previous exchanges.
The package brings together 81 dependencies spanning machine learning (numpy, dask, matplotlib), async messaging (aiohttp, aio-pika, aiogram), cloud integration (boto3, google-auth), and scheduling (apscheduler). It is actively maintained and marked Production/Stable. Installation is low-friction for standard use, though some optional features may require additional system dependencies.
Use it for
- Build a customer support chatbot that remembers context across multiple turns and routes to human agents.
- Deploy a voice assistant skill for Alexa or Google Home that understands user intent and manages stateful conversations.
- Create a Slack or Mattermost bot that integrates with internal systems and learns conversation patterns.
- Prototype and train a dialogue system with custom NLU models and conversation policies before deploying to production.
- Connect a conversational interface to multiple messaging channels from a single codebase.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Rasa is a mature, actively maintained framework (last commit 2026-07-24, 21297 GitHub stars) with Apache-2.0 licensing, no known security vulnerabilities, and low install friction. It is well-suited for teams building multi-channel conversational agents. The large dependency footprint and Python version cap are minor trade-offs for a production-grade ML framework.
Install
rasa on PyPI
Before you install
Low install friction with a pure Python wheel distribution. The package has 81 runtime dependencies covering ML, messaging, and async infrastructure; installation is straightforward, though optional dependencies may be needed for full functionality on some systems.
Requires Python >=3.8,<3.11. Full functionality may require optional dependencies like tokenizers, which on macOS may need a Rust compiler.
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for proprietary applications and internal deployment.
Quickstart
pip install rasa
import rasa
from rasa.nlu.model import Interpreter
# Load a trained NLU model to parse user intent
interpreter = Interpreter.load('path/to/model')
result = interpreter.parse('hello')Verify before relying
- Whether the 81 runtime dependencies are all required at install time or if many are optional/conditional
- Current state of the Jira migration for issue tracking and community support responsiveness
- Performance characteristics and scalability limits for production dialogue systems
- Whether pre-trained models or training datasets are included or must be sourced separately
Package facts
| License | Apache-2.0 permissive |
| Python support | Capped below the current Python release <3.11,>=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 81 packagesCacheControlPyJWTSQLAlchemyabsl-pyaio-pikaaiogramaiohttpapschedulerattrsboto3certificoloramacolorclasscoloredlogscolorhashconfluent-kafkacryptographydaskdnspythonfbmessengergoogle-authjsonpicklejsonschemamatplotlibmattermostwrappernetworkxnumpypackagingpluggyportalocker |
| Maintenance | Actively maintained 577 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 258,673 / month, #8,425 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries |
Evidence: rasa-3.6.21-py3-none-any.whl
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See also rasa-sdk · pipecat-ai · home-assistant-intents · rocketchat-API · google-cloud-dialogflow-cx · livekit-plugins-google · chainlit · livekit-plugins-sarvam · speechmatics-voice · deepgram-sdk