📄 ocrbase is a lightweight, model-agnostic API that standardizes document parsing across visual language models (VLMs).

Key Features of ocrbase

🪶 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.

🧩 Core

• /v1/parse — turn a document into text
• /v1/parse/async — enqueue a parse job
• /v1/extract — extract structured JSON from a document
• /v1/extract/async — enqueue an extract job
• /v1/job/:jobId — inspect parse or extract job status

🧠 Models

Both models are state of the art:

• paddleocr — 94.5 on OmniDocBench v1.5
• glmocr — 94.6 on OmniDocBench v1.5

📋 Requirements

• paddleocr — set up PaddleOCR-VL
• glmocr — self-host GLM-OCR with vLLM

🚀 Quick Start

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

☁️ Optional S3 Input Staging

If S3_ACCESS_KEY_ID, S3_SECRET_ACCESS_KEY, S3_BUCKET, and S3_ENDPOINT are set, /v1/parse will:

• upload incoming File inputs to S3
• fetch remote document URLs and upload the contents to S3
• upload base64 or data URL payloads to S3
• pass a presigned GET URL into the selected document model

If those env vars are not set, ocrbase keeps the current direct behavior and sends the original input to the model.

📬 Optional BullMQ Parse Queue

If REDIS_URL and the S3 env vars above are set, queue mode is enabled:

• POST /v1/parse uploads or normalizes the input to S3, enqueues a parse job, waits for completion, and returns the normal parse response
• POST /v1/parse/async returns 202 { jobId }
• GET /v1/job/:jobId returns the job state plus result or error

If Redis is missing, or Redis is present but S3 is not fully configured, POST /v1/parse keeps the existing direct behavior and the async/status endpoints return 503.

When queue mode is enabled, Bull Board is also available at /v1/admin/queues.