The hard part of RAG isn't finding the right chunk!
When you chunk a document for RAG, each chunk lands in the index on its own, disconnected from the section it came from. So two chunks with identical text, but from completely different parts of the document, look exactly the same to a flat index.
That becomes a problem the moment a question needs context from more than one section. The chunks come back, but how they relate to each other gets lost.
ADE Section fixes this. It reads the parsed document, builds the actual hierarchy, and figures out where every chunk falls within it. That gets attached to the chunk before it's embedded.
Once that's in place, a broad question can stay at the section level. A specific one can drop into a sub-chunk. You can scope a search to one part of a document instead of the whole thing.
Citations get more accurate too. The model knows exactly which section a fact came from.
Run ADE Parse, then run ADE Section.
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She Had Everyone Hooked from the First Note: Young Chinese Student Sings #
Adele# A Cappella
@Adele
Queremos que sigas adelante, Bella!
Turn Claude Code into a document processing agent!
Traditional OCR extracts text but loses critical information. Table structures with merged cells disappear. Relationships between charts and captions break. Multi-column reading order gets scrambled.
That's why most document pipelines need manual templates per document type, and break the moment a vendor changes their invoice format.
Agentic Document Extraction (ADE) takes a different approach. It's vision-first, understanding layout the way a person reading the page would. Handles complex tables, dense forms, multi-column pages, and scanned documents.
LandingAI now released the ADE skills for AI coding agents. Instead of calling the API directly, your agent writes Python scripts that parse, extract, classify, and chain these steps into full pipelines.
Every extracted value comes with bounding boxes, page coordinates, and confidence scores traceable back to the source document.
Two skills make up the system:
1. Document-extraction - parsing into structured Markdown, extracting fields with JSON schemas or Pydantic models, splitting and classifying multi-document batches.
2. Document-workflows - batch processing in parallel, classify-then-extract pipelines, RAG preparation with chunking and embeddings, exporting to DataFrames or Snowflake, building Streamlit UIs.
Once installed, you describe what you need in plain English. Ask your agent to extract line items from a folder of invoices, pull every figure from a scientific paper as PNGs, or read account statements across pages into a single CSV.
Key capabilities:
• Parses 20+ file formats with layout-aware structured output
• Vision-first model, no templates required
• Bounding boxes, page coordinates, and confidence scores per extraction
• Classify-then-extract pipelines for mixed document batches
• Works with Claude Code, Cursor, Roo Code, or any Agent Skills-compatible Agent
I've shared the link in the replies!
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If Andy Burnham becomes Britain’s next prime minister, what should he tackle first? Lucy Fisher, Miranda Green and Robert Shrimsley discuss the policy areas that could shape his government.
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La diferencia entre Kendall Jenner y Justin Bieber. Esta es la diferencia entre nacer rico y hacerse rico más adelante en la vida. Te hace ser más humilde.
*En clases de español para extranjeros.*
YO: Y díganme, ¿por qué quieren aprender español?
ALUMNA JAPONESA 🇯🇵: Mi empresa requiere que lo aprenda para poder trabajar en las sucursales que tenemos aquí.
YO: Oh, eso suena muy interesante.
ALUMNA ESTADOUNIDENSE 🇺🇸: Porque quiero aprender más de mis raíces. Mis padres son mexicanos que residen en Estados Unidos, pero nunca me enseñaron español para que no sufriera bullying en mi barrio.
YO: Lamento que fuera así, pero al aprender español verás que tus raíces son mucho más interesantes de lo que aparentan.
ALUMNO FRANCÉS 🇫🇷: Porque quiero darle una sorpresa a mi esposa mexicana. No se esperará que un día llegue yo hablándole en español. Creo que sería una bonita sorpresa.
YO: Ow, eso es muy tierno de tu parte.
ALUMNO ALEMÁN 🇩🇪: Porque me encantaría aprender más sobre las culturas latinoamericanas. Desde niño me sentí atraído hacia ellas por su manera tan alegre de vivir la vida. Me gustaría convertirme en parte de ellas.
YO: Y no te arrepentirás.
ALUMNO INGLÉS 🏴: Porque quiero ver "Shrek" en español.
*Todos lo miran confundidos.*
ALUMNO INGLÉS 🏴: Dicen que es mucho más chistosa en español latino, y yo soy muy fan de esa película, así que...
*El alumno inglés se encoge de hombros.*
YO: Pero... Debe haber alguna otra razón, ¿no?
ALUMNO 🏴: No. Sólo Shrek.
*Doy un paso hacia adelante y le tiendo mi mano para que la estreche.*
YO: Ese es el propósito más noble que he escuchado en todos mis años de enseñanza de la lengua española. Me comprometo a que aprendas español perfectamente para que puedas cumplir tan puro objetivo.
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ÖLÜ INTERNET TEORİSİ GERÇEK OLDU..
World of Warcraft’ta insan oyuncuların olmadığı bir sunucu ortaya çıktı. onun yerine 1.800 adet DeepSeek destekli yapay zeka botu oynuyor.
botlar sıradan oyuncular gibi davranıyor. sohbet ediyor, karakter kasıyor, dungeon dönüyor, grup kuruyor ve birbirleriyle PvP atıyor.
internetin ne kadarının artık insanlar tarafından kullanıldığından emin miyiz?
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