langchain-chat is an AI-driven Q&A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. Easy to set up and extend.

LSTM with attention for time series predictions of stock prices using own Ticker Embedding model

langchain-chat is an AI-driven Q&A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. Easy to set up and extend.

PyTorch Implementation of the paper "Semantic Compression Embedding for Generative Zero-Shot Learning" accepted to IJCAI-2022

This is a research project for movie recommendation system using RL

App that answers questions about any YouTube video using its transcript. Built using Retrieval-Augmented Generation (RAG) with LangChain, vector stores, and LLMs.