Towards Data Science
Jun 13
Parse PDFs for RAG Locally with Docling: Rich Tables, No Cloud Upload
Enterprise Document Intelligence [Vol. 1 #5ter] - Table cells, OCR, captions, headings: cloud-grade structure, running on your own machine.
When PyMuPDF Can’t See the Table: Parse PDFs for RAG with Azure Layout
Enterprise Document Intelligence [Vol. 1 #5bis] - The same relational tables.
Related stories
Towards Data Science
Jun 11
Stop Returning Flat Text from a PDF: The Relational Tables RAG Needs
Enterprise Document Intelligence [Vol. 1 #5B] - One PDF in, a relational set of DataFrames out: lines, pages, TOC, images, cross-references, captions, spans, and a parsing summary The post Stop Returning Flat Text from a PDF: The Relational Tables RAG Needs appeared first on Towards Data Science .
Towards Data Science
Sep 3
Tables in PDFs for RAG: Don’t Flatten the Grid
The article titled "Tables in PDFs for RAG: Don’t Flatten the Grid" discusses Enterprise Document Intelligence, presenting a diagnostic and five composable operations rather than a decision tree. It appears in the Vol.1 #B4 issue of the publication and was first posted on Towards Data Science.
Towards Data Science
Jun 11
Stop Returning Flat Text from a PDF: The Relational Shape RAG Needs
Enterprise Document Intelligence [Vol. 1 #5B] - One PDF in, a relational set of DataFrames out: lines, pages, TOC, images, cross-references, captions, spans, and a parsing summary The post Stop Returning Flat Text from a PDF: The Relational Shape RAG Needs appeared first on Towards Data Science .
Towards Data Science
Jun 10
Beyond extract_text: The Two Layers of a PDF That Drive RAG Quality
Enterprise Document Intelligence [Vol. 1 #5A] - Document signals (metadata, native TOC, source software) and page-level content (text vs scans, tables, images, columns, page profile) The post Beyond extract_text: The Two Layers of a PDF That Drive RAG Quality appeared first on Towards Data Science .
Towards Data Science
Aug 23
Parse the Folder, Not Just the PDFs: The Relational Tables RAG Needs on a Case File
The article discusses how Enterprise Document Intelligence should begin by parsing the folder structure rather than just PDFs, emphasizing that the index must reflect the case type’s requirements before any folder is accessed. It highlights that the two key questions to develop are not retrieval questions but rather focus on the relational tables needed for Retrieval-Augmented Generation (RAG) in a case file context.
Towards Data Science
Jul 7
A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers
Enterprise Document Intelligence [Vol. 1 #9A] - Same paper, same question as Article 1.
Towards Data Science
Aug 21
Retrieve One Row from a Table, Not the Whole Table: Row-Level Chunks for RAG
Enterprise Document Intelligence [Vol. 1 #7sexies] - The unit of retrieval doesn’t have to be a page or a paragraph.
Towards Data Science
Jul 17
One RAG Pipeline, Four Very Different PDFs: Same Four Bricks, Every Answer Typed and Cited
Enterprise Document Intelligence [Vol. 1 #9B] - One call wires the four upgraded bricks together, run on a paper, a NIST standard, and a report with a broken TOC The post One RAG Pipeline, Four Very Different PDFs: Same Four Bricks, Every Answer Typed and Cited appeared first on Towards Data Science .
Towards Data Science
Jun 21
Reconstructing the Table of Contents a PDF Forgot to Ship, So RAG Can Scope by Section
Enterprise Document Intelligence [Vol. 1 #5septies] - When a PDF prints a contents page but exposes no outline, two ways to turn it back into structure, plus the page-alignment step everyone forgets The post Reconstructing the Table of Contents a PDF Forgot to Ship, So RAG Can Scope by Section appeared first on Towards Data Science .
Towards Data Science
Jun 14
Vision LLMs are PDF Parsers Too: Reading Charts and Diagrams for RAG
Enterprise Document Intelligence [Vol. 1 #5quater] - The other parsers read the words on a page.
Towards Data Science
Jun 20
Making a PDF’s Images Searchable for RAG, Without Paying to Read Them All
Enterprise Document Intelligence [Vol. 1 #5sexies] - image_df tells you where every picture is.