PrivateGPT is a software that allows users to ask questions to their documents without an internet connection, using the power of LLMs. The software is 100% private, and no data leaves the execution environment at any point. Users can ingest documents and ask questions without an internet connection. PrivateGPT is built with LangChain, GPT4All, LlamaCpp, Chroma, and SentenceTransformers. The software requires Python 3.10 or later and supports various file extensions, such as CSV, Word Document, EverNote, Email, EPub, PDF, PowerPoint Document, Text file (UTF-8), and more. Users can ingest multiple documents, and all will be accumulated in the local embeddings database. PrivateGPT uses a local LLM based on GPT4All-J or LlamaCpp to understand questions and create answers, and the context for the answers is extracted from the local vector store using a similarity search to locate the right piece of context from the docs. This is a test project, and it is not production-ready.