In this tutorial, we build an end-to-end accounts-payable extraction pipeline with lift-pdf, using synthetic invoice PDFs as controlled test documents and a structured JSON schema as the target output format. Instead of treating invoice parsing as a simple OCR task, we frame it as schema-guided document understanding: we generate realistic invoices, define fields such as […]
The post Designing a Schema-Guided Invoice Intelligence Pipeline with lift-pdf for Accounts-Payable Extraction, Validation, and Ledger Generation appeared first on MarkTechPost.
The post New Zealand’s RBNZ expected to hike rates in another uncertain, close-call vote appeared on BitcoinEthereumNews.com.
The Reserve Bank of New Zealand (RBNZ) is widely expected to raise the Official Cash Rate (OCR) by 25 basis points (bps) from 2.25% to 2.50% on Wednesday, snapping a three-consecutive-meeting pause. Economists are deeply divided about how the Kiwi central bank will proceed this time after the last decision to hold the cash rate steady was a very close call, increasing the chances of higher volatility around the decision. The RBNZ interest rate announcement is due at 02:00 GMT, accompanied by the Monetary Policy Review (MPR) and the Minutes of the meeting, followed by Governor Dr. Anna Breman’s press conference at 03:00 GMT. The New Zealand Dollar (NZD) faces a key test this week as the RBNZ looks to hike the OCR against a backdrop of still-elevated inflation concerns, soft domestic economic activity, and sharply lower global Oil prices. What to expect from t
Most enterprise data still sits inside PDFs, scans, and slide decks. Large language models and agents cannot use that data until it becomes structured JSON. Open-source document extraction has become the standard way to do that conversion on your own hardware. Two different problems hide under the phrase ‘PDF to JSON.’ The first is schema-driven […]
The post Structured PDF-to-JSON: A Guide to Open-Source Extraction Models in 2026 appeared first on MarkTechPost.
We build a practical GLM-5.2 workflow using its hosted, OpenAI-compatible API instead of running the model locally. We set up multiple providers, load the API key securely, and create a reusable chat wrapper. We then test thinking-effort control, streamed reasoning, function calling, a tool-using agent, structured JSON output, and long-context retrieval. We close with token and cost accounting so every demo stays measurable.
The post GLM-5.2 OpenAI-Compatible API: A Hands-On Guide to Reasoning Effort, Function Calling, and Long-Context Retrieval appeared first on MarkTechPost.
In this tutorial, we build a complete Crawlee for Python workflow from setup to AI-ready output. We generate a local demo website, then crawl it with BeautifulSoupCrawler, ParselCrawler, and PlaywrightCrawler. We extract titles, metadata, product fields, and JavaScript-rendered cards, and capture full-page screenshots. We then normalize the data, build a link graph, and export JSON, CSV, and RAG-ready JSONL chunks.
The post Crawlee for Python: Build a Web Crawling Pipeline with Robots Handling, Link Graphs, and RAG Chunk Export appeared first on MarkTechPost.
In this tutorial, we build a workflow that uses Docling Parse to analyze PDF documents at a detailed structural level. We prepare a stable Python environment, handle common Colab dependency issues, and generate a custom multi-page PDF with text, columns, table-like content, vector shapes, and an embedded image. We then extract words, characters, and lines with page-level coordinates, render visual overlays, and save results into structured JSON and CSV. We see how low-level parsing supports layout analysis, reading-order reconstruction, and retrieval-ready document preparation.
The post How to Build a Parsing Pipeline with Docling Parse for Layout-Aware Document Intelligence appeared first on MarkTechPost.
Enterprise Document Intelligence [Vol.1 #5ter] - Table cells, OCR, captions, headings: cloud-grade structure, running on your own machine. No key, no per-page bill, nothing leaves the building
The post Parse PDFs for RAG Locally with Docling: Rich Tables, No Cloud Upload appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #5bis] - The same relational tables. Native table cells. OCR for scanned pages and images. Captions and headings without regex.
The post When PyMuPDF Can’t See the Table: Parse PDFs for RAG with Azure Layout appeared first on Towards Data Science.
Testing fourteen engines on ninety-three human documents
The post I Spent May Evaluating Different Engines for OCR appeared first on Towards Data Science.
