> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.privategpt.dev/llms.txt.
> For full documentation content, see https://docs.privategpt.dev/llms-full.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.privategpt.dev/_mcp/server.

# API Reference

The API is divided in two logical blocks:

1. 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.
   * Chat & Completions using context from ingested documents: abstracting the retrieval of context, the prompt
     engineering and the response generation.

2. Low-level API, allowing advanced users to implement their own complex pipelines:
   * Embeddings generation: based on a piece of text.
   * Contextual chunks retrieval: given a query, returns the most relevant chunks of text from the ingested
     documents.