name: image version: "1.0" description: Extract text from images using a vision LLM entry: script: scripts/main.py class: ImageSkill triggers: extensions:

• ".png"
• ".jpg"
• ".jpeg"
• ".webp"
• ".gif"
• ".tiff"

intents:

• "image"
• "screenshot"
• "diagram"
• "photo"

requires: [] # no pip packages; a vision LLM provider must be passed at construction time author: axoviq.com license: AGPL-3.0-or-later

Image Skill

Base64-encodes the image and passes it to a vision-capable LLM that extracts all text and key information. Returns the LLM's response as result.text.

Setup

No pip dependency — the skill uses only the Python standard library plus a LLM provider you supply at construction time. The provider can be any object that implements the complete() interface (see below).

Standalone usage

import asyncio
from synthadoc.skills.image.scripts.main import ImageSkill
# ImageSkill REQUIRES a vision-capable provider — calling extract() without
# one raises ValueError immediately.
skill = ImageSkill(provider=my_provider)
async def main():
    result = await skill.extract("/path/to/screenshot.png")
    print(result.text)          # extracted text from the image
    print(result.metadata)      # {"tokens_input": N, "tokens_output": N}
asyncio.run(main())

Provider interface — any object with this async method:

async def complete(
    messages: list,             # list of Message objects from synthadoc.skills.base
    system: str | None = None,
    temperature: float = 0.0,
    max_tokens: int = 4096,
) -> object                     # must have .text (str), .input_tokens (int), .output_tokens (int)

Build the provider with any vision-capable model. Message is importable from synthadoc.skills.base — no dependency on synthadoc.providers:

from synthadoc.skills.base import Message

Supported image formats: .png, .jpg/.jpeg, .webp, .gif, .tiff

When this skill is used

• Source path ends with .png, .jpg, .jpeg, .webp, .gif, or .tiff
• User intent contains: image, screenshot, diagram, photo