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This repository hosts a collection of custom web applications powered by OpenAI's GPT models (incl. o1 models, gpt-4o, gpt-4o-mini and gpt-4-turbo), Whisper model, and TTS model. These apps include an interactive chatbot ("Talk to GPT") for text or voice communication, and a coding assistant ("CodeMaxGPT") that supports various coding tasks.
This project employs emotion detection in textual data, specifically trained on Twitter data comprising tweets labeled with corresponding emotions. It seamlessly takes text inputs and provides the most fitting emotion assigned to it.
YouTube Sentiment Analysis is a web application that analyzes the sentiment of YouTube comments, providing insights into comment sentiment using VADER sentiment analysis and interactive visualizations.
Certificato is a web app developed using Streamlit to help users send certificates in large quantities when provided with an excel sheet containing the name and email address of the recipients.
An Open source version of FileQueryBot. Unleash the power of conversational AI on any document. Upload or link files in any format - PDF, TXT, PPTX, DOCX, and more - and let FileQueryBot answer your questions with precision and ease.
The Global Statistics Dashboard is a comprehensive tool designed to provide insights into various global statistics. This project includes data processing scripts, a web application interface, and modular components for loading and visualizing data.
UROP: Telegram chatbot for novice programmers to learn coding. The deployed Streamlit Web Application for the Telegram Chatbot with Chatbase custom GPT LLM model API and Firebase, using Figma for prototyping of the web application.
Salary Prediction web app is designed to assist job seekers, employees, and employers in making informed decisions about compensation and employment. The project is particularly useful for individuals who are looking to negotiate their salaries, switch careers, or explore new job opportunities.
This is a Streamlit web application for predicting Telecom Churn. The app uses a trained machine learning model to predict whether a customer is likely to churn or not based on certain input features.
This is a Streamlit app that allows users to upload an image of a PAN card and detect if there has been any tampering. The app also calculates the structural similarity index (SSIM) between the uploaded image and a reference image to validate the ID.