|
import ast |
|
import requests |
|
|
|
|
|
API_URL_INITIAL = "https://ysharma-playground-ai-exploration.hf.space/run/initial_dataframe" |
|
API_URL_NEXT10 = "https://ysharma-playground-ai-exploration.hf.space/run/next_10_rows" |
|
|
|
|
|
|
|
def get_initial_images(): |
|
response = requests.post(API_URL_INITIAL, json={ |
|
"data": [] |
|
}).json() |
|
|
|
response_dict = response['data'][0] |
|
return response_dict |
|
|
|
|
|
def process_response(response_dict): |
|
return [resp[0][:-1] for resp in response_dict["data"]] |
|
|
|
response_dict = get_initial_images() |
|
initial = process_response(response_dict) |
|
initial_imgs = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);">\n' + "\n".join(initial[:-1]) |
|
|
|
|
|
def get_next10_images(response_dict, row_count): |
|
row_count = int(row_count) |
|
|
|
|
|
if isinstance(response_dict, dict) == False : |
|
response_dict = ast.literal_eval(response_dict) |
|
response = requests.post(API_URL_NEXT10, json={ |
|
"data": [response_dict, row_count ] |
|
}).json() |
|
row_count+=10 |
|
response_dict = response['data'][0] |
|
|
|
|
|
next_set = [resp[0][:-1] for resp in response_dict["data"]] |
|
next_set_images = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2); ">\n' + "\n".join(next_set[:-1]) |
|
return response_dict, row_count, next_set_images |
|
|
|
|
|
|
|
|
|
|
|
with gr.Blocks(css = """#img_search img {width: 100%; height: 100%; object-fit: cover;}""") as demo: |
|
gr.HTML(value="top of page", elem_id="top",visible=False) |
|
gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;"> |
|
<div |
|
style=" |
|
display: inline-flex; |
|
align-items: center; |
|
gap: 0.8rem; |
|
font-size: 1.75rem; |
|
" |
|
> |
|
<h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;"> |
|
Using Gradio Demos as API - 2 </h1><br></div> |
|
<div><h4 style="font-weight: 500; margin-bottom: 7px; margin-top: 5px;"> |
|
Stream <a href="https://github.com/playgroundai/liked_images" target="_blank">PlaygroundAI Images</a> ina beautiful grid</h4><br> |
|
</div>""") |
|
with gr.Accordion(label="Details about the working:", open=False, elem_id='accordion'): |
|
gr.HTML(""" |
|
<p style="margin-bottom: 10px; font-size: 90%"><br> |
|
▶️Do you see the "view api" link located in the footer of this application? |
|
By clicking on this link, a page will open which provides documentation on the REST API that developers can use to query the Interface function / Block events.<br> |
|
▶️In this demo, I am making such an API request to the <a href="https://huggingface.co/spaces/ysharma/Playground_AI_Exploration" target="_blank">Playground_AI_Exploration</a> Space.<br> |
|
▶️I am exposing an API endpoint of this Gradio app as well. This can easily be done by one line of code, just set the api_name parameter of the event listener. |
|
</p></div>""") |
|
|
|
with gr.Column(): |
|
b1 = gr.Button("Load More Images").style(full_width=False) |
|
df = gr.Textbox(visible=False,elem_id='dataframe', value=response_dict) |
|
row_count = gr.Number(visible=False, value=19 ) |
|
img_search = gr.HTML(label = 'Images from PlaygroundAI dataset', elem_id="img_search", |
|
value=initial_imgs ) |
|
|
|
gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/Stream_PlaygroundAI_Images?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a></center> |
|
</p></div>''') |
|
b1.click(get_next10_images, [df, row_count], [df, row_count, img_search], api_name = "load_playgroundai_images" ) |