For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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Overview

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.
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