Easily display PDFs in Gradio
Project description
gradio_pdf
Easily display PDFs in Gradio
Installation
pip install gradio_pdf
Usage
import gradio as gr
from _app import demo as app
import os
_docs = {'PDF': {'description': 'A base class for defining methods that all input/output components should have.', 'members': {'__init__': {'value': {'type': 'Any', 'default': 'None', 'description': None}, 'height': {'type': 'int | None', 'default': 'None', 'description': None}, 'label': {'type': 'str | None', 'default': 'None', 'description': None}, 'info': {'type': 'str | None', 'default': 'None', 'description': None}, 'show_label': {'type': 'bool | None', 'default': 'None', 'description': None}, 'container': {'type': 'bool', 'default': 'True', 'description': None}, 'scale': {'type': 'int | None', 'default': 'None', 'description': None}, 'min_width': {'type': 'int | None', 'default': 'None', 'description': None}, 'interactive': {'type': 'bool | None', 'default': 'None', 'description': None}, 'visible': {'type': 'bool', 'default': 'True', 'description': None}, 'elem_id': {'type': 'str | None', 'default': 'None', 'description': None}, 'elem_classes': {'type': 'list[str] | str | None', 'default': 'None', 'description': None}, 'render': {'type': 'bool', 'default': 'True', 'description': None}, 'load_fn': {'type': 'Callable[..., Any] | None', 'default': 'None', 'description': None}, 'every': {'type': 'float | None', 'default': 'None', 'description': None}}, 'postprocess': {'value': {'type': 'str | None', 'description': None}}, 'preprocess': {'return': {'type': 'str', 'description': None}, 'value': None}}, 'events': {'change': {'type': None, 'default': None, 'description': ''}, 'upload': {'type': None, 'default': None, 'description': ''}}}, '__meta__': {'additional_interfaces': {}, 'user_fn_refs': {'PDF': []}}}
abs_path = os.path.join(os.path.dirname(__file__), "css.css")
with gr.Blocks(
css=abs_path,
theme=gr.themes.Default(
font_mono=[
gr.themes.GoogleFont("Inconsolata"),
"monospace",
],
),
) as demo:
gr.Markdown(
"""
# `gradio_pdf`
<div style="display: flex; gap: 7px;">
<a href="https://pypi.org/project/gradio_pdf/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/gradio_pdf"></a> <a href="https://github.com/freddyaboulton/gradio-pdf/issues" target="_blank"><img alt="Static Badge" src="https://img.shields.io/badge/Issues-white?logo=github&logoColor=black"></a> <a href="https://huggingface.co/spaces/freddyaboulton/gradio_pdf/discussions" target="_blank"><img alt="Static Badge" src="https://img.shields.io/badge/%F0%9F%A4%97%20Discuss-%23097EFF?style=flat&logoColor=black"></a>
</div>
Easily display PDFs in Gradio
""", elem_classes=["md-custom"], header_links=True)
app.render()
gr.Markdown(
"""
## Installation
```bash
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()
""", elem_classes=["md-custom"], header_links=True)
gr.Markdown("""
PDF
Initialization
""", elem_classes=["md-custom"], header_links=True)
gr.ParamViewer(value=_docs["PDF"]["members"]["__init__"], linkify=[])
gr.Markdown("### Events")
gr.ParamViewer(value=_docs["PDF"]["events"], linkify=['Event'])
gr.Markdown("""
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
""", elem_classes=["md-custom", "PDF-user-fn"], header_links=True)
demo.load(None, js=r"""function() {
const refs = {};
const user_fn_refs = {
PDF: [], };
requestAnimationFrame(() => {
Object.entries(user_fn_refs).forEach(([key, refs]) => {
if (refs.length > 0) {
const el = document.querySelector(`.${key}-user-fn`);
if (!el) return;
refs.forEach(ref => {
el.innerHTML = el.innerHTML.replace(
new RegExp("\\b"+ref+"\\b", "g"),
`<a href="#h-${ref.toLowerCase()}">${ref}</a>`
);
})
}
})
Object.entries(refs).forEach(([key, refs]) => {
if (refs.length > 0) {
const el = document.querySelector(`.${key}`);
if (!el) return;
refs.forEach(ref => {
el.innerHTML = el.innerHTML.replace(
new RegExp("\\b"+ref+"\\b", "g"),
`<a href="#h-${ref.toLowerCase()}">${ref}</a>`
);
})
}
})
})
}
""")
demo.launch()
## `PDF`
### Initialization
<table>
<thead>
<tr>
<th align="left">name</th>
<th align="left" style="width: 25%;">type</th>
<th align="left">default</th>
<th align="left">description</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><code>value</code></td>
<td align="left" style="width: 25%;">
```python
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.
- As output: Is passed, the preprocessed input data sent to the user's function in the backend.
- As input: Should return, the output data received by the component from the user's function in the backend.
def predict(
value: str
) -> str | None:
return value
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