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Conversational AI Made Easy: Developing an ML FAQ Model Demo from Scratch U
In today’s fast-paced digital era, conversational AI chatbots have emerged as a game-changer in delivering efficient and personalized user interactions. FAQs form a significant portion of user queries in various domains, such as customer support, e-commerce, and information retrieval.
With Rasa, you can build chatbots that understand user intents, extract relevant information, and provide contextual responses based on the conversation flow. https://github.com/RasaHQ/rasa allows developers to build and deploy conversational AI chatbots and provides a flexible architecture and powerful NLU capabilities (Figure 1).
This configuration file defines several intents, which represent different types of user inputs that the chatbot can recognize.
With Rasa, you can build chatbots that understand user intents, extract relevant information, and provide contextual responses based on the conversation flow. https://github.com/RasaHQ/rasa allows developers to build and deploy conversational AI chatbots and provides a flexible architecture and powerful NLU capabilities (Figure 1).
This configuration file defines several intents, which represent different types of user inputs that the chatbot can recognize.
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