DataChad: an AI App with LangChain & Deep Lake to Chat with Any Data

- DataChad is a web application that enables users to interactively query and generate insights from their data using large language models (LLMs) like OpenAI's GPT-3.5 or GPT-4. - It supports various data sources, including CSV files, GitHub repositories, PDF documents, text files, web URLs, and local directories. - DataChad uses LangChain to build a conversational interface that allows users to ask natural language questions and receive relevant answers in seconds. - The application is built using Hugging Face's Transformers library for LLMs, LangChain for building the chat interface, and Activeloop's Deep Lake vector database for storing embeddings of data documents. - Users can customize various parameters like k (number of context documents), fetch_k (maximum number of documents to search), temperature (creativity level), max_tokens (maximum tokens per response), and more. - DataChad is open source, and users can contribute to the project by adding new data loaders or improving existing ones.