Ollama OCR Skill#

Use this skill when you need to recognize text from images using Ollama's local vision/OCR models. No internet required - fully offline OCR.

When to Use#

• User sends an image and wants text extraction
• User asks to recognize text from a screenshot or picture
• Need local offline OCR without cloud API dependency
• Processing sensitive images that shouldn't be sent to third parties

Models Available#

ModelBest ForSizeglm-ocr:latestChinese text OCR2.2GBllava:7bGeneral image understanding4.7GBmoondreamLightweight vision model1.5GBllama3.2-vision:latestLarge vision model7GB+

Ollama Endpoint#

Default: http://172.17.0.2:11434 (Docker container to host gateway)

Note: Endpoint is pre-configured for OpenClaw running in Docker accessing host Ollama. Adjust OLLAMA_HOST in ollama_ocr.py if your setup differs.

Usage#

Command Line#

bash

python3 ollama_ocr.py /path/to/image.jpg [model_name]

Examples:

bash

python3 ollama_ocr.py receipt.png glm-ocr:latest
python3 ollama_ocr.py screenshot.jpg llava:7b

Python API#

python

from ollama_ocr import ollama_ocr

# Basic OCR with default model (glm-ocr)
result = ollama_ocr('/path/to/image.jpg')

# Specify model
result = ollama_ocr('/path/to/image.jpg', 'glm-ocr:latest')

print(result)

Example Prompts to Activate This Skill#

• "识别这张图片里的文字"
• "帮我 OCR 一下这个截图"
• "Extract text from this image"
• "What text is in this screenshot?"

Notes#

• Image path must be absolute or relative to script location
• For large images, consider resizing first to avoid timeout
• glm-ocr works best for Chinese text
• Some models may have output quirks (e.g., glm-ocr occasionally repeats)
• First call may be slow if model isn't cached in memory

Requirements#

• Ollama installed and running
• At least one vision/OCR model downloaded (e.g., ollama pull glm-ocr:latest)