LLM OCR

Turn PDFs and images into clean Markdown with vision LLMs:
Gemini, OpenAI, Claude, or a local model through Ollama.

pip install ocr-llm
export GEMINI_API_KEY="..."   # or OPENAI_API_KEY / ANTHROPIC_API_KEY
ocr-llm document.pdf -o document.md

Or from Python:

from llm_ocr import LLMOCR, Gemini

markdown = LLMOCR(Gemini()).convert_sync("document.pdf")

It handles multi-page PDFs concurrently, keeps pages in order, retries failed requests, and works with any OpenAI-compatible server.

Installation

pip install ocr-llm

Gemini and OpenAI work out of the box. Claude needs an extra:

pip install "ocr-llm[anthropic]"

PDF input needs poppler: brew install poppler on macOS, sudo apt-get install poppler-utils on Debian/Ubuntu. Images work without it.

Providers

Keys are read from the environment, or passed as api_key=. Choose a model with model=: either a constant such as Gemini.PRO_2_5 or any model name as a string, so new models work without a library update.

from llm_ocr import Anthropic, Gemini, OpenAI

Gemini(model=Gemini.PRO_2_5)
Anthropic(model="claude-haiku-5-5")

# Ollama, vLLM, LM Studio, OpenRouter: anything that speaks the OpenAI API
OpenAI(base_url="http://localhost:11434/v1", model="llava")

Usage

convert_sync is the simplest entry point and also works in notebooks:

from llm_ocr import LLMOCR, OpenAI

ocr = LLMOCR(OpenAI())
markdown = ocr.convert_sync("document.pdf", output_path="document.md")

In async code, use convert and its siblings:

import asyncio

from llm_ocr import LLMOCR, Gemini


async def main():
    async with LLMOCR(Gemini()) as ocr:
        report = await ocr.convert("report.pdf")
        receipt = await ocr.convert("receipt.png")  # images work too

        # bytes from an upload or object store; PDF or image is detected
        with open("report.pdf", "rb") as f:
            from_bytes = await ocr.convert_bytes(f.read())


asyncio.run(main())

convert_image also accepts raw bytes or a PIL.Image.Image.

Command line

# Uses whichever of GEMINI_API_KEY / OPENAI_API_KEY / ANTHROPIC_API_KEY is set
ocr-llm document.pdf -o document.md

ocr-llm scan.png --provider anthropic --instructions "Tables only"

ocr-llm document.pdf --base-url http://localhost:11434/v1 --model llava

Without -o, the Markdown goes to stdout. ocr-llm --help lists every option.

Configuration

from llm_ocr import LLMOCR, OCRConfig, OpenAI

config = OCRConfig(
    dpi=300,
    max_concurrency=8,
    additional_instructions="Write formulas in LaTeX.",
)
ocr = LLMOCR(OpenAI(), config=config)

Logging

Progress is reported through the standard logging module (it was print() before 1.1.0). To see it:

import logging

logging.basicConfig(level=logging.INFO)

Project

Changelog · Contributing · Roadmap · MIT License