Visualise any type of files
Project description
tags: [gradio-custom-component, File] title: gradio_viewer short_description: Visualise files colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py
gradio_viewer
Visualise any type of files
Installation
pip install gradio_viewer
Usage
import gradio as gr
from gradio_viewer import Viewer
def set_interface():
view_with_ms = Viewer(
value=[
"./demo/data/Le_Petit_Chaperon_Rouge_Modifie.docx",
"./demo/data/mermaid_graph-2.html",
"./demo/data/graphique_couts_annuels.png",
"./demo/data/Le_Petit_Chaperon_Rouge.zouzou",
"./demo/data/viewer.py",
],
elem_classes=["visualisation"],
n=0,
height=300,
visible=True,
ms_files=True,
)
view_without_ms = Viewer(
value=[
"./demo/data/Le_Petit_Chaperon_Rouge_Modifie.docx",
"./demo/data/mermaid_graph-2.html",
"./demo/data/graphique_couts_annuels.png",
"./demo/data/Le_Petit_Chaperon_Rouge.zouzou",
],
elem_classes=["visualisation"],
n=1,
height=300,
visible=True,
ms_files=False,
)
empty_view1 = view_with_ms
empty_view2 = view_without_ms
return view_with_ms, view_without_ms, empty_view1, empty_view2
with gr.Blocks() as demo:
with gr.Row():
view_with_ms = Viewer(visible=False)
view_without_ms = Viewer(visible=False)
empty_view1 = Viewer(visible=False)
empty_view2 = Viewer(visible=False)
demo.load(
set_interface, outputs=[view_with_ms, view_without_ms, empty_view1, empty_view2]
).then(
fn=lambda: (
Viewer(visible=False, value=None, elem_id="empty1"),
Viewer(visible=False, value=[], elem_id="empty2"),
),
outputs=[empty_view1, empty_view2],
)
if __name__ == "__main__":
demo.launch()
Viewer
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[..., Any] | None
|
None |
None |
every |
Timer | float | None
|
None |
None |
n |
int
|
0 |
None |
max_size |
int
|
5000000 |
None |
max_pages |
int
|
100 |
None |
ms_files |
bool
|
True |
None |
libre_office |
bool
|
True |
None |
interface_language |
str
|
"fr" |
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 data after preprocessing, sent to the user's function in the backend.
- As input: Should return, expects a
str
filepath or URL, or alist[str]
of filepaths/URLs.
def predict(
value: str
) -> str | list[str] | None:
return value
Project details
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