All 124 Dependencies
Every package Rasa Open Source depends on, ranked by repo health score.
Rasa Open Source is a production-grade Python framework for building AI-powered conversational assistants that handle complex, multi-turn dialogues. Unlike simple FAQ bots or rule-based systems, Rasa trains custom NLU models to recognize user intents and extract entities from free-form text, then applies learned dialogue policies to determine the appropriate response at each turn — enabling assistants that handle interruptions, slot-filling, and context shifts naturally.
The framework is built around a graph-based execution engine where NLU components (tokenizers, featurizers, classifiers, entity extractors) and dialogue policies are defined as pluggable GraphComponents wired together in a directed graph. This makes the pipeline fully customizable: swap in a spaCy tokenizer, a BERT-based featurizer, or a custom action that queries an external database without touching the rest of the system.
Rasa ships with native connectors for Slack, Facebook Messenger, Telegram, Twilio, Microsoft Bot Framework, Mattermost, and Rocket.Chat, along with a REST channel for custom integrations. Tracker stores support PostgreSQL, Redis, and MongoDB for production-scale conversation history persistence. For high-throughput event processing, a Kafka broker integration enables decoupled, stream-based architectures.
Now in maintenance mode as Rasa shifts focus to their CALM (Conversational AI with Language Models) approach, Rasa Open Source 3.6.x remains the most widely deployed open source conversational AI framework with over 21,000 GitHub stars and 25 million downloads.