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-Open source machine learning tools for developers to build, improve, and deploy text-and voice-based chatbots and assistants. (cit. RASA github home).
+"''Open source machine learning tools for developers to build, improve, and deploy text-and voice-based chatbots and assistants''". (cit. [https://github.com/RasaHQ/ RASA github home page]).
-RASA is probably the most important tool to develop "task-oriented" conversational application. Despite the RASA official statement, is not originally developed to manage voice interaction, but chatbots. RASA consist in two main components:
+RASA is probably the most important open-source tool to develop "task-oriented" conversational applications. Despite the RASA official statement, the original project has not  conceived to manage voice interactions, but just [[chatbots]] with some support to GUI/buttons.
-* ''RASA NLU'' is based upon DIET, a a refined state of the art  intent/entities classifier
+RASA architecture consist in two main components:
-* ''RASA Core'' (now called ''RASA Dialog Manager''), based on TED, a machine learning algorithm, to manage multi-turn dialogs, escaping the traditional state-machine based way, but instead allowing conversation developers to insert "''stories",'' set of sequences of intents-actions examples. In a sense, developers define the conversational agent dialog manager giving examples (the stories).
-RASA own a huge open community of developers and researchers. It's probably the biggest open source project to develop on-premise "production-ready" complex dialog systems. All the development ecosystem is around the Python programming language.
+* ''RASA NLU'' is based upon [https://rasa.com/blog/introducing-dual-intent-and-entity-transformer-diet-state-of-the-art-performance-on-a-lightweight-architecture/ DIET algorithm], a a refined state of the art  intent/entities "classifier
+* ''RASA Core'' (now called ''RASA Dialog Manager''), based on [https://rasa.com/blog/unpacking-the-ted-policy-in-rasa-open-source/ TED policy], a machine learning algorithm, to manage multi-turn dialogs, escaping the traditional state-machine based way, but instead allowing conversation developers to insert "''stories",'' set of of intents-actions sequences (conversation examples). With [https://rasa.com/blog/were-a-step-closer-to-getting-rid-of-intents/ end-to-end training], developers program the conversational agent [[dialog manager]] giving end-to-end turn-taking examples (the stories).
+RASA owned in few years now, a huge open community of developers and researchers. It's probably the biggest open source project to develop on-premise "production-ready" complex dialog systems. All the development ecosystem is around the [[Python]] programming language.
 == References ==
-home page: https://rasa.com/
-github: https://github.com/RasaHQ/
+* Home page: https://rasa.com/
+* Github: https://github.com/RasaHQ/
-community forum: https://forum.rasa.com/
+* Community forum: https://forum.rasa.com/