Document OCR & Extraction for RAG - UnstructuredIO Tutorial

In this video you will learn step by step how to use the Unstructured.io Serverless API for document OCR and extraction with a FREE api key.

If you're wondering how to extract text from pdf files (or any other file type such as excel sheets word or PowerPoint slides) through advanced layout analysis and optical character recognition, and specifically how to also extract tables, images, formulas and all kinds of artefacts present in complex documents in a clean way, Unstructured.io is the solution for you.

Unstructured allows you to process even the most complex documents and immediately get them LLM ready through partitioning with layout analysis and ocr models.

Additionally, you can extract all images and tables from the document encoded in base64 format which allows you to send them as is to multi-modal LLMs to generate descriptions or answer questions about them.

Integration into a RAG pipeline is pretty straightforward as unstructured takes care of the ingestion step (with all kinds of documents not only pdf) and produce typed elements (text, image, table, title) as well as chunks with target token sizes. The next step is naturally to connect it with your vectorstore by embedding the elements and storing their medata along with their vector forms.

Unstructured is supported by Langchain which had a specific class for it and can thus easily be integrated into your stack.

00:00 Intro
01:31 Package Installation
01:59 Api Key
03:46 Client Setup
04:32 Basic Request
06:33 Layout-Aware Chunking
08:25 Image/Table Extraction
10:01 Outro

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unstructured documentation : docs.unstructured.io/api-reference/api-services/ov…

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