Rasa

Description

Rasa is an open-source (legacy Open Source) and commercial (Rasa Platform / Pro) framework for building text and voice conversational assistants. The current dialogue engine is CALM (Conversational AI with Language Models): an LLM interprets each user message and emits internal commands (start flow, set slot, correct slot, cancel flow, clarify flows, chitchat, knowledge answer, human handoff), while a deterministic dialogue manager executes those commands against business logic written as Flows. Flows are step-by-step processes built from collect (slot filling), set_slots, action (custom-action server call), and branching steps; the tracker persists slot values across turns.

Solution

Each turn the user message is fed to a CALM dialogue-understanding LLM with a structured prompt that emits a set of internal commands (start flow, set slot, correct slot, cancel flow, clarify flows, chitchat, knowledge answer, human handoff). The dialogue manager interprets those commands against the currently active Flow on the tracker, executing collect / set_slots / action / branching steps. Custom actions run in an external action server; the tracker carries slot state across turns. Conversation patterns provide reusable structured sub-flows for things like clarification, correction, and handoff.

Primary use cases

• enterprise customer-support and CX assistants over text and voice
• LLM-driven dialogue understanding with deterministic flows enforcing business logic
• custom-action-driven tool use against internal APIs
• human handoff via the built-in human_handoff command
• knowledge-grounded answers via Enterprise RAG and the knowledge_answer command