Ocrbase – pdf → .md/.json document OCR and structured extraction API

In plain words

Ocrbase is an API that converts PDF documents into markdown or JSON format while extracting and structuring their content. It's designed for developers who need to programmatically process PDF files and convert them into machine-readable formats. The tool combines optical character recognition with document parsing to automatically identify and organize text elements, making it useful for workflows involving document digitization, data extraction, or content migration.

written from the facts on this page · September 2026

From the sources

📄 ocrbase is a lightweight, model-agnostic API that standardizes document parsing across visual language models (VLMs). 🪶 Lightweight : Tiny Bun + Elysia service, single container, minimal footprint. 🔌 Model-Agnostic : Point at any supported VLM — GLM-OCR, PaddleOCR-VL — via env vars. 📊 State of the Art : Backed by models scoring ≥94.5 on OmniDocBench v1.5. 💎 Easy to Deploy : One command away from a working OCR API. docker run -d -p 3000:3000 \ -e PADDLEOCR_URL=http://localhost:8190 \ -e GLM_OCR_URL=http://localhost:5002 \ --name ocrbase ghcr.io/ocrbase-hq/ocrbase 🛠️ Develop bun install bun dev ☁️ Optional S3 Input Staging If S3_ACCESS_KEY_ID , S3_SECRET_ACCESS_KEY , S3_BUCKET , and…from github.com

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  I've developed a Python API service that uses GPT-4o for OCR on PDFs. It features parallel processing and batch handling for improved performance. Not only does it convert PDF to markdown, but it also describes the images within the PDF using captions like `[Image: This picture shows 4 people waving]`. In testing with NASA's Apollo 17 flight documents, it successfully converted complex, multi-oriented pages into well-structured Markdown. The project is open-source and available on GitHub. Feedback is welcome.

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