Ross ROSS = Recommend OSS · open-source software intelligence for agents

Rasa Open Source

Some data may be outdated — see provenance labels.

💬 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 observed · 2026-09-26

github.com/RasaHQ/rasa · homepage · Python · Apache-2.0 (permissive) observed · 2026-09-26

Health v2 · maintenance only

62/100

  • Activity 86
  • Release rhythm 8
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3658
  • days_rel: 644
  • days_push: 88
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

21330 stars · 4913 forks observed · 2026-09-26

What it is AI-extracted, prompt v1, taxonomy v1, 2026-10-19, confidence 0.97

Rasa Open Source is a Python-based framework for building text and voice conversational agents. It provides NLU, dialogue management, and integrations with messaging platforms.

Use cases

  • build a custom chatbot for a website or app
  • create a voice assistant that integrates with Alexa or Google Assistant
  • train an NLU model to understand user intents from text
  • manage multi‑turn dialogues with custom actions and slots
  • connect a conversational agent to Slack, Facebook Messenger, or other channels
  • run automated tests for conversation flows
  • deploy an on‑premise AI assistant for privacy‑sensitive use cases

When to choose

  • You need full control over the conversational pipeline and want an open‑source solution.
  • Your project requires custom actions, integrations, or on‑premise deployment.
  • You want to leverage Python’s ML ecosystem for NLU and dialogue management.

When to avoid

  • You need enterprise‑grade scalability, analytics, and built‑in observability (use Rasa Pro instead).
  • You prefer a low‑code, drag‑and‑drop interface without writing code.
  • You require out‑of‑the‑box LLM‑only handling without training your own models.

Facets

library · maturity maintenance

nlp api-framework cli chatbots python windows cross-platform open-source conversational-ai voice-assistants dialogue-management rasa-sdk rasa-core natural-language-processing devops linux macos

10 sources

Member repositories

RepositoryRoleHealth v2
RasaHQ/rasamain62
RasaHQ/rasa_coremirror10
RasaHQ/rasa-sdksdk97

For agents

markdown · JSON · MCP: product_card(name="RasaHQ/rasa")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem