llm-pdf-to-images
LLM fragment plugin to load a PDF as a sequence of images
Installation
Install this plugin in the same environment as LLM.
llm install llm-pdf-to-images
The llm-pdf-to-images plugin provides a fragment loader that converts each page of a PDF document into an image attachment.
You can use the pdf-to-images: fragment prefix to convert a PDF file into a series of image attachments which can be sent to a model.
Example usage:
llm -f pdf-to-images:path/to/document.pdf 'Summarize this document'
Fragment syntax
pdf-to-images:<path>?dpi=N&format=jpg|png&quality=Q
<path>: Path to the PDF file accessible to the environment where LLM runs.dpi=N: (optional) Dots per inch to use when rendering the PDF pages, which affects the resolution of the output images. Defaults to300if omitted.format=jpg|png: (optional) Image format to use for the output. Can be eitherjpg(default) orpng.quality=Q: (optional) JPEG quality factor between 1 and 100. Only applies when using JPG format. Defaults to30if omitted. Higher values produce better quality but larger file sizes.
More examples
Convert a PDF file to images with default settings (300 DPI, JPG format, quality 30):
llm -f pdf-to-images:document.pdf 'summarize this document'
Convert a PDF with higher resolution (600 DPI):
llm -f 'pdf-to-images:document.pdf?dpi=600' 'summarize'
Convert a PDF to PNG format:
llm -f 'pdf-to-images:document.pdf?format=png' 'describe all figures'
Convert a PDF with high-quality JPG images:
llm -f 'pdf-to-images:document.pdf?quality=90' 'extract all visible text'
Combine multiple parameters:
llm -f 'pdf-to-images:document.pdf?dpi=450&format=jpg&quality=75' 'OCR'
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-pdf-to-images
python -m venv venv
source venv/bin/activate
Now install the dependencies and test dependencies:
python -m pip install -e '.[test]'
To run the tests:
python -m pytest
Release files for llm-pdf-to-images 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| llm_pdf_to_images-0.1.tar.gz | 7.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llm_pdf_to_images-0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.3 kB
Release files / llm_pdf_to_images-0.1.tar.gz
| Download URL | llm_pdf_to_images-0.1.tar.gz |
|---|---|
| Size | 7.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Transparency logRelease files / llm_pdf_to_images-0.1-py3-none-any.whl
| Download URL | llm_pdf_to_images-0.1-py3-none-any.whl |
|---|---|
| Size | 7.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0e477b6f6eade17c79b613d234faf3681fd1864942eb3062fec870609a93cc72
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BLAKE2b-256 checksum How to use checksums |
6dd06f5fe2da16461bebbe1f2a43a44cedcccab0c535daaa5f5e77570fcc831e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 18, 2025.
Transparency log