Xiangyun Invoice OCR

Problem

Invoice data often sits in email threads, chat logs, and drive folders, while manual review of invoice type, format, and readability is easy to miss. This skill turns PDF, OFD, and common image invoices into a callable recognition workflow for extracting basic invoice fields in batch engineering scenarios.

How It Works

The skill relies on Xiangyun OCR and uses netocr_key and netocr_secret for authentication. After input files are provided, it requests recognition through the Xiangyun API and parses invoice type and key fields, covering 40+ invoice types such as VAT special invoices, digital invoices, train tickets, toll invoices, and bank receipts. Typical steps include:
- Prepare readable files, each under 10MB
- Support .pdf, .ofd, .jpg, .png, and .bmp
- Call the recognition API and parse the response
- Feed the structured result into archiving, reconciliation, or reimbursement flows

Boundaries

Accuracy depends on image clarity, file format, and external API quota. Images should be at least 500px on the relevant side; small or blurry files may miss fields. Xiangyun OCR is billed per call, so estimate file volume and cost before running large batches. The config file is stored as config.json under the skill directory, and credentials should not be committed to repositories.