import gradio as gr import ast import requests #Using Gradio Demos as API - This is Hot! 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" #Define inference function #First: Get initial images for the grid display def get_initial_images(): response = requests.post(API_URL_INITIAL, json={ "data": [] }).json() response_dict = response['data'][0] return response_dict #Second: Process response dictionary to get imges as hyperlinked image tags 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 = '
\n' + "\n".join(initial[:-1]) #Third: Load more images for the grid def get_next10_images(response_dict, row_count): row_count = int(row_count) #Convert the string to a dictionary 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 ] #len(initial)-1 }).json() row_count+=10 response_dict = response['data'][0] next_set = [resp[0][:-1] for resp in response_dict["data"]] next_set_images = '
\n' + "\n".join(next_set[:-1]) return response_dict, row_count, next_set_images #response['data'][0] #Defining the Blocks layout 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("""

Streaming PlaygroundAI Images in a grid


Based on PlaygroundAI Image dataset


""") with gr.Accordion(label="Details about the working:", open=False, elem_id='accordion'): gr.HTML("""


▶️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.
▶️In this demo, I am making such an API request to the Playground_AI_Exploration Space.
▶️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.

""") with gr.Column(): #(elem_id = "col-container"): 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 ) #initial[:-1] ) gr.HTML('''
Duplicate Space

''') b1.click(get_next10_images, [df, row_count], [df, row_count, img_search], api_name = "load_playgroundai_images" ) demo.launch(debug=True)