RealVoiceGPT is a web application that lets you have voice conversations with ChatGPT. The project uses ElevenLabs AI text to speech to give the chatbot a realistic voice, Flask and React to build the web interface, OpenAI’s Whisper to convert your speech to text in realtime, and GPT3.5 and ElevenLabs Prime Voice AI.

This project is a Python-based Telegram chatbot that uses Google's Generative AI (Gemini) for responses. It utilizes Flask for the web server and Vercel Functions for serverless computing. The bot can be interacted with via Telegram and includes a plugin system for extending its functionality.

Conversational AI chatbot with consistent persona. Implementation of Seq2Seq, Transformer and Multiple Encoders in Python. Backend using Flask.

A modern, responsive AI chatbot web application built with Flask and Together API. Experience seamless conversations with an intelligent AI assistant.

Scalable AI Chatbot API built with Flask, OpenAI, and vector memory — designed for modular full-stack integration.

A Banking chatbot solution built with RASA using four languages: Arabic, English, French and Tunisian dialect This solution aims to provide users with response to commonly asked questions about bank services as well as taking actions such as: User sign-up User sign-in (Flask interface) Currency convertor Money Transfer Email notifications Id card verification through camera using AI The chat bot was deployed on Messanger and on a Flask web site

This is the main repository for the final MyTherapyPal application. It consists of a flutter mobile & web user interface application with account registration & login functionality, chat functionality and an AI mental health assistant chatbot, which is implemented using a REST API web service powered by Python Flask.

Overview Virtual Assistant is an application program that understands natural language voice commands or text commands and completes the tasks for users. Virtual Assistants features a human interface system, they can understand the language and meaning of what the user is saying and have built in replies. Learn from different instances so that they can have a long term human interaction. It uses artificial intelligence to learn things from different situations. Using AI they can recognize, predict and classify based on analysis. Purpose Virtual Assistant provides various services. It is ready to help wherever you are and can be deployed in your devices. Wider scope and perform users to get answers to their questions and perform tasks using voice or text commands, all in an interactive form. Precise voice and text recognition with the ability to have conversation with the users. In case of Google assistant, they recognize the voice of the user and perform the specific task. Use case Customer support: Rather of customers waiting for a long to solve an issue, the can get instant support from chatbot, Banking Chatbots: Personalized banking with an aim to improve customer satisfaction and engagement. Project support: Can send notifications for various tasks. Reminder to follow up with an action. HR assistants: Can help employees register time off, retrieve company policies, and find answers to repetitive employment questions. Teaching: Can helps teachers to create more detailed learning plans and materials. Being full-blown health assistants: Virtual assistants can do so much more than giving tips, they can often help patients apply simple treatments, remind them to take medicine, and monitor their health. Automating FAQs and administrative tasks: If there's a scenario where the customers have dozens of repetitive questions, virtual assistant is there 24/7 to answer questions from people who may be anxious to get answers. Technical support: The customer has a product technical error, in this case, asks the customer to type the error they encounter, then it generates a dynamic link to search the customer input words in the technical knowledge repositories and guide the customer through his search. Efficient Processes: Make processes more streamlined and transparent by synchronizing between functions, roles, and departments. Booking: A virtual assistant can respond to a consumer through messages, web, SMS or email and update them on the status of their existing reservation, make changes to the reservation, process related payments or refunds, send proactive notifications and provide detailed information on their itinerary. Features a. NLP Text Search : Virtual assistant concentrates on NLP and NLU. Understands the slang that is used in everyday conversation and analyses the sentiments to enhance a better set of communication. b. FAQ voice assistant : FAQ voice assistant is a voice assistant that provides a list of questions and answers relating to a particular subject. c. Conversations voice assistant : Conversations voice assistant is a voice assistant that provides conversational services based on a subject. d. Speech conversations (STT,TTS) : It provides conversational services such as speech to text and text to speech. e. Integration with Enterprise Systems : It provides administrative service to clients. Such as scheduling appointments, making phone calls, making travel arrangements, managing email accounts etc. f. Rich Conversations : Rich conversation is a conversation that can use different features such as images, videos, buttons, forms etc. a) Images:Imagescanbesentorreceivedduringconversations. b) Buttons:Buttonscanprovidedifferentfunctionalitiesasperthefeatureofthebutton. c) Videos:Videoscanbesentorreceivedduringconversations d) Forms: Forms help to give visible shape or configuration of something. Technical Requirement g. HTML5 h. JavaScript i. Python (Flask API, NLP Packages) j. MySQL k. Docker l. Git

AI-powered chatbot built with Python, NLP, and Flask — automate customer support queries with intent recognition and dynamic responses.

Learn how to use database with Rasa Chat bot. This Chatbot with Database will store the user details in Database. I have created this Chat Bot Using Rasa NLU and Rasa Core, Database used is SQlite3, and this is a Flask App. For Understanding the basics of Rasa Chatbot , please check this link: https://youtu.be/sofMxJF4CZ4 If you have any questions with what we covered in this video then feel free to ask in the comment section below & I'll do my best to answer your queries. Please consider clicking the SUBSCRIBE button to be notified for future videos & thank you all for watching. Channel: https://www.youtube.com/channel/UCgHDngFV50KmbqF_6-K8XhA Support my channel 🙏 by LIKE ,SHARE & SUBSCRIBE Check the complete Machine Learning Playlist : https://www.youtube.com/playlist?list=PLv8Cp2NvcY8CoxylKNIYBd9ZVQ1SlFWQ3 Check the complete Deep Learning Playlist : https://www.youtube.com/playlist?list=PLv8Cp2NvcY8CaSVfCIyg5mvek8JvaD7tE Subscribe my channel: https://www.youtube.com/channel/UCgHDngFV50KmbqF_6-K8XhA Support my channel 🙏 by LIKE ,SHARE & SUBSCRIBE Contact: aarohisingla1987@gmail.com #chatbot #rasa #rasanlu #rasacore #AI #ArtificialIntelligence #DeepLearning #conersationalchatbot #Chatbotwithdatabase #spacy

This project is a Flask-based AI chatbot that uses the Groq API for real-time conversation generation. It features conversation history, code block formatting with a copy option, and a full-screen user-friendly interface with Markdown and syntax highlighting support.

Purpose : Major Project Team Size : 4 Duration : 10 Months [ Oct. 1, 2021 - June 31, 2022 ] Key Skills : Rasa AI , Python , NLP , Flask , HTML , CSS , JavaScript It is a Web-based Chatbot to automate healthcare management with audio assistance. Users can get immediate medication for their symptoms and book appointments via an audio feature. In addition to text assistance, this chatbot has an audio assistance feature. This feature eliminates the restrictions that visually impaired patients face with currently available text-enabled healthcare chatbots. This voice-enabled chatbot was designed and developed using the Rasa interface for the backend, the Web Speech API, and the Talkify API for voice input and output, respectively. Title: ' TaBiB: Chatbot for Healthcare Automation with Audio Assistance using Artificial Intelligence '. The project was presented and was approved at the 6th National Conference of Science and Engineering (NCSEM), 2022. Tools used : Rasa AI, Python, NLP, Flask, Web Speech API, Talkify API, HTML, CSS in Atom Editor.

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

AI clinical diagnostics platform with 5 ML models and Mistral-7B medical Q&A chatbot. Provides diagnostic support and medical assistance using scikit-learn and Flask.

This repository contains a Flask-based user interface for building and interacting with chatbots powered by Andrew Ng's aisuite library. The project provides a seamless and intuitive way to create, configure, and deploy AI chatbots for various applications.

ChatGPT Voice Chatbot Telegram is a Python and Flask-based GitHub repository that enables users to communicate with an AI chatbot using voice-to-text and text-to-voice technologies powered by OpenAI. The repository provides a flexible and customizable solution for building advanced voice-enabled chatbots using natural language processing.

LegalEase is an AI-powered legal assistance platform built with Flutter and Flask. It integrates Google Generative AI (Gemini) to provide dynamic chatbot interactions and PDF document parsing. Key features include personalized legal guidance, multi-language support, case-specific insights, and secure API integration for scalable solutions.

Career Compass is an AI-powered chatbot system that offers personality-based career recommendations using MBTI, Big Five, and real-time job market data. Built with Flask, React.js, SpaCy, and PostgreSQL/MongoDB, it delivers dynamic, personalized career insights

A self-hosted AI RAG chatbot built with Flask, Ollama, PostgreSQL (pgvector), and Docker. Upload your own documents and chat with them locally

AI-powered retrieval-based chatbot built with Python and Flask, featuring modern animated UI and intelligent intent matching for commercial website integration.

This repository contains a Personal AI Chatbot project built with Hugging Face’s DialoGPT-medium model, Flask for the backend, and ReactJS (using Vite) for the frontend. The chatbot allows users to interact with an AI in real-time, offering context-aware and human-like responses.

A chatbot built with React and Flask, featuring preset prompts, bold-styled responses, and Firebase integration. Includes setup for Google Generative AI and a responsive TailwindCSS UI.

🚀 Excited to share a new project I just completed — a Simple AI Chatbot built with Python, NLTK, and Flask! This chatbot can: Understand basic user intents like greetings, thanks, and farewells Respond intelligently with randomized replies Work both in a command-line environment and via a web interface (built using Flask)

This project is a simple chatbot deployed with HTML, CSS, JavaScript, Python (Flask), and the Gemini AI API. It allows users to interact with a chatbot interface via a webpage. User messages are processed by the Gemini API, which generates responses displayed on the web page.

This is a simple and interactive AI chatbot web application that utilizes the Google Gemini API to provide conversational capabilities. Users can chat with an AI model and receive responses in real-time. The application is built using Flask for the backend and HTML/CSS for the frontend.

This project shows how to create a simple chatbot using Flask and OpenAI. The project receives messages from users and generates responses using OpenAI's GPT-3.5 model.

A chill, mental-health–focused AI chatbot built with Flask, Deepseek API, and NLP-powered emotion detection.

Phone Finder – AI-powered Mobile Search (MERN + Flask) A mobile phone comparison and recommendation platform for users in Pakistan. Built with the MERN stack and a Flask-based AI chatbot to suggest phones based on user needs.

🎮 An AI-powered chatbot that provides real-time strategy suggestions for gamers using Google's Gemini API. Built with Flask, HTML, JS, and Python-dotenv.

AI Chatbot Project is a multi-persona chatbot web application built with Flask. It features three distinct chatbots: a Clothing Store Assistant, a Tech Support Assistant, and a Travel Agency Assistant. The chatbots leverage OpenAI's GPT model for dynamic conversation, store user data in SQLite databases, and feature smooth, responsive UI animation