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
pythonimport 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:
pythonasync 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:
pythonfrom 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
