vlense 0.1.2

A Python package to extract text from images and PDFs using Vision Language Model (VLM).

Vlense

A Python package to extract text from images and PDFs using Vision Language Models (VLM).

Features

• Extract text from images and PDFs
• Supports JSON, HTML, and Markdown formats
• Easy integration with Vision Language Models
• Asynchronous processing with batch support
• Custom JSON schema for structured output

Installation

pip install vlense

Usage

import os
import asyncio
from vlense import Vlense
from pydantic import BaseModel

path = ["./images/image1.jpg", "test.pdf"]
output_dir = "./output"
model = "gemini/gemini-1.5-flash"
temp_dir = "./temp_images"
os.environ["GEMINI_API_KEY"] = "YOUR_API_KEY"


async def main():
    vlense = Vlense()
    responses = await vlense.ocr(
        file_path=path,
        model=model,
        output_dir=output_dir,
        temp_dir=temp_dir,
        batch_size=3,
        clean_temp_files=False,
    )

if __name__ == "__main__":
    asyncio.run(main())

API

Vlense.ocr()

Performs OCR on the provided files.

Parameters:

• file_path : (Union[str, List[str]]): Path or list of paths to PDF/image files.

• model : (str, optional): Model name for generating completions. Defaults to "gemini-1.5-flash".

• output_dir : (Optional[str], optional): Directory to save output. Defaults to None.

• temp_dir : (Optional[str], optional): Directory for temporary files. Defaults to system temp.

• batch_size : (int, optional): Number of concurrent processes. Defaults to 3.

• format : (str, optional): Output format ('markdown', 'html', 'json'). Defaults to 'markdown'.

• json_schema : (Optional[Type[BaseModel]], optional): Pydantic model for JSON output. Required if format is 'json'.

• clean_temp_files : (Optional[bool], optional): Cleanup temporary files after processing. Defaults to True.

Returns:

• Dict[str, VlenseResponse] : Generated content.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

Author: Aditya Miskin
Email: [e-mail]
Repository: https://github.com/adityamiskin/vlense