Rename test.py to app.py

test.py → app.py

@@ -48,6 +48,42 @@ def set_model(current_model_index):
     current_model = models[current_model_index]
     return gr.update(value=f"{current_model['name']}")
 
+#define inference function
+#First: Get initial images for the grid display 
+def get_initial_images():
+  response = requests.post(API_URL_INITIAL, json={
+            "data": []
+            }).json()
+  #data = response["data"][0]['data'][0][0][:-1]
+  response_dict = response['data'][0]
+  return response_dict  #, [resp[0][:-1] for resp in response["data"][0]["data"]]
+
+#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  = '<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])
+
+#Third: Load more images for the grid
+def get_next10_images(response_dict, row_count):
+    row_count = int(row_count)
+    #print("(1)",type(response_dict))
+    #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]
+    #print("(2)",type(response))
+    #print("(3)",type(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  #response['data'][0]
+
 
 with gr.Blocks(theme='pikto/theme@>=0.0.1,<0.0.3') as pan:
     gr.Markdown("AI CONTENT TOOLS.")
@@ -91,51 +127,16 @@ with gr.Blocks(theme='pikto/theme@>=0.0.1,<0.0.3') as pan:
          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()
-  #data = response["data"][0]['data'][0][0][:-1]
-  response_dict = response['data'][0]
-  return response_dict  #, [resp[0][:-1] for resp in response["data"][0]["data"]]
-
-#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  = '<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])
-
-#Third: Load more images for the grid
-def get_next10_images(response_dict, row_count):
-    row_count = int(row_count)
-    #print("(1)",type(response_dict))
-    #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]
-    #print("(2)",type(response))
-    #print("(3)",type(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  #response['data'][0]
 
 #get_next10_images(response_dict=response_dict, row_count=9)
 #position: fixed; top: 0; left: 0; width: 100%; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
 
 #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("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
-        <div
-        style="
+    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;
@@ -147,8 +148,8 @@ with gr.Blocks(css = """#img_search img {width: 100%; height: 100%; object-fit:
         <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("""
+    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>
@@ -156,16 +157,16 @@ with gr.Blocks(css = """#img_search img {width: 100%; height: 100%; object-fit:
         ▶️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(): #(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", 
+    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('''<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" ) 
+         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" ) 
             
 
     with gr.Tab("Diffuser"):