It can store the content of your documents in a format that can be easily compared to the user’s prompt. Vector database: A vector database is designed to store and retrieve embeddings. The SentenceTransformers library contains a rich variety of pre-trained embedding models.ģ. These embeddings can be used to find documents that are related to the user’s prompt. This is typically done using a technique called word or sentence embeddings, which represent text as dense vectors in a high-dimensional space. Embedding model: An embedding model is used to transform text data into a numerical format that can be easily compared to other text data. These models are trained on large amounts of text and can generate high-quality responses to user prompts.Ģ. Some popular examples include Dolly, Vicuna, GPT4All, and llama.cpp. Open-source LLM: These are small open-source alternatives to ChatGPT that can be run on your local machine. Your local LLM will have a similar structure, but everything will be stored and run on your own computer:ġ. In a previous article, I did a deep dive into customizing ChatGPT with your own data and documents. Let’s start with a zoomed-out view of the components you need to create a local language model that can interact with your documents. We will also look at PrivateGPT, a project that simplifies the process of creating a private LLM.
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In this article, we will explore how to create a private ChatGPT that interacts with your local documents, giving you a powerful tool for answering questions and generating text without having to rely on OpenAI’s servers. You can run your own local large language model ( LLM), which puts you in control of your data and privacy. Additionally, it requires a constant internet connection, which can be an issue in areas with poor connectivity.įortunately, there is an alternative. The fact that it requires you to send your data over the internet can be a concern when it comes to privacy, especially if you’re using confidential documents. As much as ChatGPT is convenient, it has its tradeoffs.
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