Privategpt api. API Reference. Reduce bias in ChatGPT's responses and inquire about enterprise deployment. The guide is centred around handling personally identifiable data: you'll deidentify user prompts, send them to OpenAI's ChatGPT, and then re API Reference. The guide is centred around handling personally identifiable data: you'll deidentify user prompts, send them to OpenAI's ChatGPT, and then re . Discover the basic functionality, entity-linking capabilities, and best practices for prompt engineering to achieve optimal performance. Learn how to use PrivateGPT, the ChatGPT integration designed for privacy. 100% private, no data leaves your execution environment at In this guide, you'll learn how to use the API version of PrivateGPT via the Private AI Docker container. The returned information can be used to generate prompts that can be passed to /completions or /chat/completions APIs. PrivateGPT is a production-ready AI project that allows you to ask questions about your documents using the power of Large Language Models (LLMs), even in scenarios without an Internet connection. PrivateGPT provides an API containing all the building blocks required to build private, context-aware AI applications. 100% private, no data leaves your execution environment at Given a text, returns the most relevant chunks from the ingested documents. Note: it is usually a very fast API, because only the Embeddings model is involved, not the LLM. If you are looking for an enterprise-ready, fully private AI workspace check out Zylon’s website or request a demo. The API is divided in two logical blocks: High-level API, abstracting all the complexity of a RAG (Retrieval Augmented Generation) pipeline implementation: Ingestion of documents: internally managing document parsing, splitting, metadata extraction, embedding generation and storage. tcuqbluczpiyvzptdwusdboecorxfpwdokiwihqntbzyvmxln