🤖 HealthCare ChatBot Major -1 (4th year - 7th semester) Health Care Chat-Bot is a Healthcare Domain Chatbot to simulate the predictions of a General Physician. ChatBot can be described as software that can chat with people using artificial intelligence. These software are used to perform tasks such as quickly responding to users, informing them, helping to purchase products and providing better service to customers. We have made a healthcare based chatbot. The three main areas where chatbots can be used are diagnostics, patient engagement outside medical facilities, and mental health. In our major we are working on diagnostic. 📃 Brief A chatbot is an artificially intelligent creature which can converse with humans. This could be text-based, or a spoken conversation. In our project we will be using Python as it is currently the most popular language for creating an AI chatbot. In the middle of AI chatbot, architecture is the Natural Language Processing (NLP) layer. This project aims to build an user-friendly healthcare chatbot which facilitates the job of a healthcare provider and helps improve their performance by interacting with users in a human-like way. Through chatbots one can communicate with text or voice interface and get reply through artificial intelligence Typically, a chat bot will communicate with a real person. Chat bots are used in applications such as E-commerce customer service, Call centres, Internet gaming,etc. Chatbots are programs built to automatically engage with received messages. Chatbots can be programmed to respond the same way each time, to respond differently to messages containing certain keywords and even to use machine learning to adapt their responses to fit the situation. A developing number of hospitals, nursing homes, and even private centres, presently utilize online Chatbots for human services on their sites. These bots connect with potential patients visiting the site, helping them discover specialists, booking their appointments, and getting them access to the correct treatment. In any case, the utilization of artificial intelligence in an industry where individuals’ lives could be in question, still starts misgivings in individuals. It brings up issues about whether the task mentioned above ought to be assigned to human staff. This healthcare chatbot system will help hospitals to provide healthcare support online 24 x 7, it answers deep as well as general questions. It also helps to generate leads and automatically delivers the information of leads to sales. By asking the questions in series it helps patients by guiding what exactly he/she is looking for. 📜 Problem Statement During the pandemic, it is more important than ever to get your regular check-ups and to continue to take prescription medications. The healthier you are, the more likely you are to recover quickly from an illness. In this time patients or health care workers within their practice, providers are deferring elective and preventive visits, such as annual physicals. For some, it is not possible to consult online. In this case, to avoid false information, our project can be of help. 📇 Features Register Screen. Sign-in Screen. Generates database for user login system. Offers you a GUI Based Chatbot for patients for diagnosing. [A pragmatic Approach for Diagnosis] Reccomends an appropriate doctor to you for the following symptom. 📜 Modules Used Our program uses a number of python modules to work properly: tkinter os webbrowser numpy pandas matplotlib 📃 Algorithm We have used Decision tree for our health care based chat bot. Decision Tree is a Supervised learning technique that can be used for both classification and Regression problems, but mostly it is preferred for solving Classification problems. It is a tree-structured classifier, where internal nodes represent the features of a dataset, branches represent the decision rules and each leaf node represents the outcome.It usually mimic human thinking ability while making a decision, so it is easy to understand. :suspect: Project Members Anushka Bansal - 500067844 - R164218014 Shreya Sharma - 500068573 - R164218070 Silvi - 500069092 - R164218072 Ishika Agrawal - 500071154 - R164218097

An example of a chatbot built with Microsoft Bot Framework and featuring e-commerce capabilities via Moltin, Azure Search, Recommendations API, and LUIS

AI-powered sustainable e-commerce platform with EarthScore ratings, group buying via DBSCAN clustering, and multi-agent chatbot. Gamifies eco-friendly shopping with real-time carbon tracking, achievements, and community bulk purchasing. Built for Amazon Hackathon 2025.

In this tutorial, we will build an e-commerce chatbot that can query Amazon product embeddings using Redis and generate nice responses with Langchain. Our chatbot will take user input, find relevant products, and present the information in a friendly and detailed manner.

Creating a chatbot for your e-commerce business is now easier than ever with OpenAI, bypassing complex deep learning algorithms

A comprehensive e-commerce platform featuring a multi-vendor marketplace, chatbot support, order tracking, advanced analytics, and full customer, vendor, and admin management.

RAG-based chatbot for retail e-commerce.

A chatbot (also known as a talkbot, chatterbot, Bot, IM bot, interactive agent, or Artificial Conversational Entity)The classic historic early chatbots are ELIZA (1966) and PARRY (1972).More recent notable programs include A.L.I.C.E., Jabberwacky and D.U.D.E (Agence Nationale de la Recherche and CNRS 2006). While ELIZA and PARRY were used exclusively to simulate typed conversation, many chatbots now include functional features such as games and web searching abilities. In 1984, a book called The Policeman's Beard is Half Constructed was published, allegedly written by the chatbot Racter (though the program as released would not have been capable of doing so). One pertinent field of AI research is natural language processing. Usually, weak AI fields employ specialized software or programming languages created specifically for the narrow function required. For example, A.L.I.C.E. uses a markup language called AIML, which is specific to its function as a conversational agent, and has since been adopted by various other developers of, so called, Alicebots. Nevertheless, A.L.I.C.E. is still purely based on pattern matching techniques without any reasoning capabilities, the same technique ELIZA was using back in 1966. This is not strong AI, which would require sapience and logical reasoning abilities. Jabberwacky learns new responses and context based on real-time user interactions, rather than being driven from a static database. Some more recent chatbots also combine real-time learning with evolutionary algorithms that optimise their ability to communicate based on each conversation held. Still, there is currently no general purpose conversational artificial intelligence, and some software developers focus on the practical aspect, information retrieval. Chatbot competitions focus on the Turing test or more specific goals. Two such annual contests are the Loebner Prize and The Chatterbox Challenge (offline since 2015, materials can still be found from web archives). According to Forrester (2015), AI will replace 16 percent of American jobs by the end of the decade.Chatbots have been used in applications such as customer service, sales and product education. However, a study conducted by Narrative Science in 2015 found that 80 percent of their respondents believe AI improves worker performance and creates jobs.[citation needed] is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatterbots use sophisticated natural language processing systems, but many simpler systems scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database. The term "ChatterBot" was originally coined by Michael Mauldin (creator of the first Verbot, Julia) in 1994 to describe these conversational programs.Today, most chatbots are either accessed via virtual assistants such as Google Assistant and Amazon Alexa, via messaging apps such as Facebook Messenger or WeChat, or via individual organizations' apps and websites. Chatbots can be classified into usage categories such as conversational commerce (e-commerce via chat), analytics, communication, customer support, design, developer tools, education, entertainment, finance, food, games, health, HR, marketing, news, personal, productivity, shopping, social, sports, travel and utilities. Background

In this project artificial intelligence and machine learning techniques are applied innovatively to an ecommerce website introducing a new perspective to online shopping with artificial agents. This project presents an aspect of negotiating and bargaining online and features a bargain-based e-commerce website, where chatbot act as a shopkeeper and can negotiate the price of the product with a customer and a content-based recommendation system that recommends similar products based on product attributes and description rather than on likings and ratings of customer. The chatbot is developed using deep learning algorithms combined with the natural language processing techniques and recommendation system is developed using natural language processing algorithms. This project is implemented using modern tools and technologies Python, Flask and Machine learning libraries Scikit-Learn and Keras.

An e-Commerce ChatBot based on contextual-NLP processes, developed with Rasa Open Source, written in python

A web-app to assist farmers in their agricultural practices with features such as a multilingual chatbot, fertilizer recommendations, weather prediction and price estimation of the yield. It also has an additional e-commerce platform for them to sell their produce.

Go To Market bot is an Enterprise AI Chatbot, a conversation agent that manages the on field staff (e-commerce merchandiser or vendors) of multinational companies operating from different locations and retail stores.

This project is a multi-agent customer service chatbot designed for an e-commerce platform. The chatbot employ specialized agents handle distinct tasks to ensure efficient and accurate interactions. The chatbot aims to enhance user experience by streamlining order processing, answering FAQs, and providing personalized recommendations.

A Retrieval-Augmented Generation (RAG) based chatbot system for e-commerce product search and order management. The system provides semantic search capabilities for products and handles order queries through a conversational interface.

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Full-stack e-commerce site with AI chatbot using Spring Boot, Spring Security, JWT, React.js, Redux, TypeScript and various technologies.

Repo for the e-commerce Chatbot implemented in Rasa and Python, during my 8-month internship at Deutsche Telekom.

Chatbot for E-Commerce Related Questions

Shieldtify- Fully functional e-commerce web application featuring AI chatbot

A full-stack e-commerce chatbot with FAQ, recommendations, and order tracking

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A ChatBot powered by OpenAI GPT-3.5 which can answer questions on E-commerce data

A constrained dialog agent framework that ensures LLM-powered chatbots only say what they are allowed to say. Designed for business use cases where accuracy matters: e-commerce, customer support, surveys, HR bots.

E-Commerce with AI Chat Bot is a modern Android application that provides a seamless shopping experience with the help of an AI-powered chatbot. The app retrieves data from a remote server and uses a range of cutting-edge tools and APIs

A virtual assistant is an independent contractor who provides administrative services to clients while operating outside of the client's office. A virtual assistant typically operates from a home office but can access the necessary planning documents, such as shared calendars, remotely. People employed as virtual assistants often have several years of experience as an administrative assistant or office manager. New opportunities are opening up for virtual assistants who are skilled in social media, content management, blog post writing, graphic design, and Internet marketing. As working from home has become more accepted for both workers and employers, the demand for skilled virtual assistants is expected to grow. In today’s era almost all tasks are digitalized. We have Smartphone in hands and it is nothing less than having world at your fingertips. These days we aren’t even using fingers. We just speak of the task and it is done. There exist systems where we can say Text Friend, “I will Call you Letter.” And the text is sent or any one may make call by saying “Call To Mr. Roy” That is the task of a Virtual Assistant. It also supports specialized task such as booking a flight, or finding cheapest book online from various e-commerce sites and then providing an interface to book an order are helping automate search, discovery and online order operations. An intelligent virtual assistant (IVA) or intelligent personal assistant (IPA) is a software agent that can perform tasks or services for an individual based on commands or questions. The term "chatbot" is sometimes used to refer to virtual assistants generally or specifically accessed by online chat. In some cases, online chat programs are exclusively for entertainment purposes. Some virtual assistants are able to interpret human speech and respond via synthesized voices. Users can ask their assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal (spoken?) commands. A similar concept, however with differences, lays under the dialogue systems. The project aims to develop a personal-assistant for Linux-based / Windows systems using Python, Jupitar Notebook, PyCharm. Voice Assistant using Python draws its inspiration from virtual assistants like Cortana for Windows, and Siri for iOS. It has been designed to provide a user-friendly interface for carrying out a variety of tasks by employing certain well-defined commands. Users can interact with the assistant either through voice commands or using sound or Voice input input. As a personal assistant, this system assists the end-user with day-to-day activities like general human conversation, searching queries in google, Bing or yahoo, searching for videos, retrieving images, live weather conditions, word meanings, searching for medicine details, health recommendations based on symptoms and reminding the user about the scheduled events and tasks. The user statements/commands are analyzed with the help of machine learning to give an optimal solution.

An automated FAQ chatbot for an e-commerce platform. Made using LangChain, Gemini Pro, ChromaDB & Streamlit.

Full-stack e-commerce platform with Flask backend, React frontend, and AI chatbot

E-Commerce Website with AI Chatbot

Prototype of a e-commerce messenger chatbot

RAG system for an e-commerce support chatbot.