starting to write the display function

app.py

@@ -1,15 +1,14 @@
 import gradio as gr
 import numpy as np
 import pandas as pd
-import json
 
 pd.options.plotting.backend = "plotly"
 
 
 TITLE = "Diffusion Faces Cluster Explorer"
-clusters_12 = json.load(open("clusters/professions_to_clusters_12.json"))
-clusters_24 = json.load(open("clusters/professions_to_clusters_24.json"))
-clusters_48 = json.load(open("clusters/professions_to_clusters_48.json"))
+clusters_12 = pd.read_json("clusters/professions_to_clusters_12.json")
+clusters_24 = pd.read_json("clusters/professions_to_clusters_24.json")
+clusters_48 =  pd.read_json("clusters/professions_to_clusters_48.json")
 
 clusters_by_size = {
     12: clusters_12,
@@ -26,6 +25,10 @@ adjectives.insert(0, '')
 professions = sorted([p.lower() for p in prompts['Occupation-Noun'].tolist()])
 models = ["Dall-E 2", "Stable Diffusion 1.4", "Stable Diffusion 2"]
 
+def gen_df(num_clusters,model,profs):
+    if num_clusters == 12:
+        print(clusters_12.head())
+    
 
 with gr.Blocks() as demo:
     gr.Markdown("# 🤗 Diffusion Cluster Explorer")
@@ -33,14 +36,15 @@ with gr.Blocks() as demo:
     with gr.Tab("Exploring all professions together"):
         gr.Markdown("TODO")
         with gr.Row():
-            with gr.Column():
-                gr.Markdown("Select your settings below:")
-                num_clusters = gr.Radio([12,24,48], value=12, label="How many clusters do you want to make from the data?")
-                professions = gr.Dropdown
-            with gr.Column():
-                gr.Markdown("")
-                order = gr.Dropdown(["entropy", "cluster/sum of clusters"], value="entryopy", label="Order rows by:", interactive=True)
-#        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown("Select the parameters here:")
+                num_clusters = gr.Radio([12,24,48], value=12, label="How many clusters do you want to make from the data?", interactive=True)
+                model_choices = gr.Dropdown(models, value= ["Dall-E 2", "Stable Diffusion 1.4", "Stable Diffusion 2"], label="Which models do you want to compare?", multiselect=True, interactive= True)
+                profession_choices = gr.Dropdown(professions, value=["CEO", "social worker"], label= "Which professions do you want to compare?", multiselect=True, interactive=True)
+            with gr.Column(scale=3):
+                gr.Markdown("Select the ordering here:")
+                order = gr.Dropdown(["entropy", "cluster/sum of clusters"], value="entropy", label="Order rows by:", interactive=True)
+    num_clusters.change(fn=gen_df, inputs=[num_clusters,model_choices,profession_choices], outputs=None)
             
 #        with gr.Accordion("Tag Frequencies", open=False):