gradio_pdf / src /README.md
freddyaboulton's picture
Upload folder using huggingface_hub
3311c9f verified
|
raw
history blame
4.86 kB

gradio_pdf

PyPI - Version

Python library for easily interacting with trained machine learning models

Installation

pip install gradio_pdf

Usage


import gradio as gr
from gradio_pdf import PDF
from pdf2image import convert_from_path
from transformers import pipeline
from pathlib import Path

dir_ = Path(__file__).parent

p = pipeline(
    "document-question-answering",
    model="impira/layoutlm-document-qa",
)

def qa(question: str, doc: str) -> str:
    img = convert_from_path(doc)[0]
    output = p(img, question)
    return sorted(output, key=lambda x: x["score"], reverse=True)[0]['answer']


demo = gr.Interface(
    qa,
    [gr.Textbox(label="Question"), PDF(label="Document")],
    gr.Textbox(),
    examples=[["What is the total gross worth?", str(dir_ / "invoice_2.pdf")],
              ["Whos is being invoiced?", str(dir_ / "sample_invoice.pdf")]]
)

if __name__ == "__main__":
    demo.launch()

PDF

Initialization

name type default description
value
Any
None None
height
int | None
None None
label
str | None
None None
info
str | None
None None
show_label
bool | None
None None
container
bool
True None
scale
int | None
None None
min_width
int | None
None None
interactive
bool | None
None None
visible
bool
True None
elem_id
str | None
None None
elem_classes
list[str] | str | None
None None
render
bool
True None
load_fn
Callable[Ellipsis, Any] | None
None None
every
float | None
None None

Events

name description
change
upload

User function

The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).

  • When used as an Input, the component only impacts the input signature of the user function.
  • When used as an output, the component only impacts the return signature of the user function.

The code snippet below is accurate in cases where the component is used as both an input and an output.

def predict(
    value: str
) -> str | None:
    return value