Doctor Appointment using Chatbot(using rasa open source)

   

                                            

                                          What is Rasa Open Source?

Rasa Open Source provides building blocks to create visual assistants. Use Rasa to automatically create human-to-computer interactions anywhere from websites to social media.

Rasa Open Source offers three main functions. Together, they provide everything you need to build a visible helper.

Rasa is an open-source machine learning framework for automated text and voice-based conversations. Understand messages, hold conversations, and connect to message channels with APIs.

                                     Natural Language Understanding

Convert human language into organized data. Rasa Open Source provides an open source natural language processing  to convert messages from your users into entities and intents understood by chatbots. Based on low-level machine learning libraries such as Tensor Flow and spaCy, Rasa Open Source provides customizable and customizable natural language processing software. Get up and running fast with easy-to-use default settings, or change custom sections and fine-tune the parameters to get the best performance for your dataset .Rasa Open Source is the most flexible and transparent solution for chat AI — and open source means you have complete control over building an NLP chatbot that really helps your users.

                                                 Dialogue Management

In contextual conversation, something beyond the previous step plays a role in what should happen next. For example, when a user asks "How many?", It is not clear in the message alone what the user is asking. In the context of the helper, "You have mail!", The answer may be "You have five letters in your mailbox". In the case of a debt negotiation, the answer may be, "You have three outstanding debts". The assistant needs to know the previous action in order to select the next action.

 

                                                       Entities

Entities are organized pieces of information within a user's message. For entities outsourcing to work, you need to specify training data to train the ML model or you need to define common terms to exclude entities using RegexEntityExtractor based on alphabetical pattern.

When deciding which entities to pursue, consider what information your assistant needs about his or her user policies. The user may provide additional pieces of information that you do not need in any user policy; you do not need to exclude these as entities.next action.

 

                                                       Intents

Intent represents the things the user wants to do during the conversation. Rasa uses the concept of Intents to explain how user messages should be categorized. Rasa NLU will split user messages into one or more user intents.

 

                                                         Stories

Stories is a type of training data used to train your chat dialogue management model. Stories can be used to train models that are able to generalize to unseen conversation paths . A story is a representation of a conversation between a user and an AI assistant, which is translated into a specific format where the user input is displayed as objectives (and entities if required), while the responses and actions of the assistant are displayed as action words.

 

Rules

Rules are a type of training data used to train your assistant’s chat management model. Rules define short pieces of conversation that should always follow the same path.  Rules for dealing with certain small chat patterns, but unlike stories, the rules do not have the power to generalize to unseen conversation paths. Combine rules and stories to make your assistant stronger and more capable of managing real user behavior

Integrations

Integration points are built into more than 10 messaging channels, as well as storage points to connect to websites, APIs, and other data sources.

                                     

KEY FEATURES:-

àBook Appointment

àSchedule Meeting

TOOLS AND TECHNOLOGY:-

àRasa , Mongo dB , Vscode .

SCREENSHOT OF OUR PROJECT:-

REFERENCES:-

àhttps://rasa.com/

àhttps://www.youtube.com/playlist?list=PL75e0qA87dlEjGAc9j9v3a5h1mxI2