Programming a chatbot yourself is a good solution if you want customized functionalities. Most chatbots use Python, Javascript, node.js, Java, and other languages. The best programming language for a chatbot will depend on the specific chatbot you want to build and the features you want it to have. Software development frameworks and libraries are a great place to start your development journey. Coding, deploying, and testing the bot will take at least six months and requires a high skill level. The cost can also be significantly higher than using out-of-the-box solutions.

One of the most popular frameworks is Tensorflow. TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across various tasks but focuses on training deep neural networks. The Google team developed TensorFlow for internal Google use in research and production and later released it to the public. Tensorflow uses node.js for web applications. Try out this exercise to find out how it works.

Chatbots built with Microsoft Bot Framework can understand people’s communication through text, SMS, video, and speech. The frameworks deploy active learning and include pre-existing, pre-built models that allow chatbots to interact with users on chat programs they already use. The open-source SDK allows businesses to test chatbot products before being deployed into a channel.

Rasa is an open-source machine learning framework for building conversational AI assistants. It is written in Python and uses various machine-learning techniques to understand and respond to natural language.

Rasa consists of two main components:

• Rasa NLU: Rasa NLU is a natural language understanding engine that can be used to extract entities, intents, and other information from text.
• Rasa Core: Rasa Core is a dialogue management engine that can be used to build conversational flows.

Rasa can be used to build various conversational AI applications, such as chatbots, virtual assistants, and voice assistants.