Convert string lists into LlamaIndex document objects

The StringIterable Reader converts an iterable of strings into a list of LlamaIndex documents. It is a simple utility for quickly creating documents directly from a list of text strings already in memory, without reading from a file or an external source first.

StringIterableReader is instantiated with no configuration, and load_data takes a texts argument - any iterable of strings, such as a Python list - and returns each string wrapped as a document, ready to be indexed like documents loaded from any other source.

Use it when you already have text content as Python strings - generated programmatically, pulled from an API response, or assembled from some other in-memory source - and want to get it into LlamaIndex's document format without writing the text to a file first just to read it back in. Do not use it when your source is a file, database, or external API with its own dedicated LlamaIndex reader; those readers handle fetching and parsing directly, while this one only wraps strings you already have on hand.

load_data takes any iterable of strings and returns each one as a LlamaIndex document, with no parsing or transformation beyond the wrapping itself.

from llama_index.readers.string_iterable import StringIterableReader

reader = StringIterableReader()

documents = reader.load_data(
    texts=["I went to the store", "I bought an apple"]
)

Developers who already have text content as in-memory Python strings and need the fastest path to turning it into LlamaIndex documents, without an intermediate file or a dedicated source-specific reader.