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aliyun-qwen-ocr

aliyun-qwen-ocr

github.com/cinienceDocuments39667 installsUpdated 11w ago
Repository

About aliyun-qwen-ocr

aliyun-qwen-ocr is a skill for extracting text and parsing document structure with Model Studio Qwen OCR. It offers built-in tasks for common formats such as tables and formulas, as well as custom extraction prompts.

Key features

  1. 01Text extraction and document parsing
  2. 02Built-in table and formula tasks
  3. 03Key information extraction
  4. 04Custom extraction prompts
  5. 05URL, local path, and data URL input

Use cases

  1. 01Extracting fields from invoices
  2. 02Parsing tables in images
  3. 03Recognizing formulas in documents

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/cinience/alicloud-skills --skill aliyun-qwen-ocr

After installing, type/aliyun-qwen-ocrin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
api_reference.md
sources.md
scripts/
prepare_ocr_request.py

Details

From the project README

Category: provider

Model Studio Qwen OCR

Validation

mkdir -p output/aliyun-qwen-ocr
python -m py_compile skills/ai/multimodal/aliyun-qwen-ocr/scripts/prepare_ocr_request.py && echo "py_compile_ok" > output/aliyun-qwen-ocr/validate.txt

Pass criteria: command exits 0 and output/aliyun-qwen-ocr/validate.txt is generated.

Output And Evidence

  • Save request payloads, selected OCR task name, and normalized output expectations under output/aliyun-qwen-ocr/.
  • Keep the exact model, image source, and task configuration with each saved run.

Use Qwen OCR when the task is primarily text extraction or document structure parsing rather than broad visual reasoning.

Critical model names

Use one of these exact model strings:

  • qwen-vl-ocr
  • qwen-vl-ocr-latest
  • qwen-vl-ocr-2025-11-20
  • qwen-vl-ocr-2025-08-28
  • qwen-vl-ocr-2025-04-13
  • qwen-vl-ocr-2024-10-28

Selection guidance:

  • Use qwen-vl-ocr for the stable channel.
  • Use qwen-vl-ocr-latest only when you explicitly want the newest OCR behavior.
  • Pin qwen-vl-ocr-2025-11-20 when you need reproducible document parsing based on the Qwen3-VL OCR upgrade.

Prerequisites

  • Install dependencies (recommended in a venv):
python3 -m venv .venv
. .venv/bin/activate
python -m pip install requests
  • Set DASHSCOPE_API_KEY in environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Normalized interface (ocr.extract)

Request
  • image (string, required): HTTPS URL, local path, or data: URL.
  • model (string, optional): default qwen-vl-ocr.
  • prompt (string, optional): use when you want custom extraction instructions.
  • task (string, optional): built-in OCR task.
  • task_config (object, optional): configuration for built-in task such as extraction fields.
  • enable_rotate (bool, optional): default false.
  • min_pixels (int, optional)
  • max_pixels (int, optional)
  • max_tokens (int, optional)
  • temperature (float, optional): recommended to keep near default/low values.
Response
  • text (string): extracted text or structured markdown/html-style output.
  • model (string)
  • usage (object, optional)

Built-in OCR tasks

Use one of these values in task:

  • text_recognition
  • key_information_extraction
  • document_parsing
  • table_parsing
  • formula_recognition
  • multi_lan
  • advanced_recognition

Quick start

Custom prompt:

python skills/ai/multimodal/aliyun-qwen-ocr/scripts/prepare_ocr_request.py \
  --image "https://example.com/invoice.png" \
  --prompt "Extract seller name, invoice date, amount, and tax number in JSON."

Built-in task:

python skills/ai/multimodal/aliyun-qwen-ocr/scripts/prepare_ocr_request.py \
  --image "https://example.com/table.png" \
  --task table_parsing \
  --model qwen-vl-ocr-2025-11-20

Operational guidance

  • Prefer built-in OCR tasks for standard parsing jobs because they use official task prompts.
  • For critical business fields, add downstream validation rules after OCR.
  • qwen-vl-ocr and older snapshots default to 4096 max output tokens unless higher limits are approved by Alibaba Cloud; qwen-vl-ocr-2025-11-20 follows the model maximum.
  • Increase max_pixels only when small text is missed; this raises token cost.

Output location

  • Default output: output/aliyun-qwen-ocr/request.json
  • Override base dir with OUTPUT_DIR.

References

  • references/api_reference.md
  • references/sources.md

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