cache the audit result components

app.py

@@ -225,7 +225,7 @@ def example_analysis(prompt):
     gender_w = float(df["gender.Woman"][0])
     gender_m = float(df["gender.Man"][0])
     gender_str = f"Male ({gender_m}%)" if gender_m>gender_w else f"Female({gender_w}%)"
-    return pil_img,gender_str,rgb_hex,intense_hex
+    return pil_img,gender_str,rgb_hex,intense_hex,score_prompt(prompt)
 
 def bias_assessment(model):
     ss,sg,ssgraph,sggraph = trait_graph(model)
@@ -239,6 +239,13 @@ def bias_assessment(model):
            [(f"Skin color {'unbiased' if os else 'biased'} by Income/Occupation",boo_to_str(os))], \
            [(f"Gender {'unbiased' if og else 'biased'} by Income/Occupation",boo_to_str(og))],\
            osgraph,oggraph
+mj_analysis = bias_assessment("Midjourney")
+sd_analysis = bias_assessment("runwayml/stable-diffusion-v1-5")
+def cached_results(model):
+    if model=="Midjourney":
+        return mj_analysis
+    else:
+        return sd_analysis
 
 if __name__=='__main__':
     disclaimerString = ""
@@ -273,7 +280,7 @@ if __name__=='__main__':
                         color_map={"PASS": "green", "FAIL": "red"})
                     with gr.Accordion("See Graph",open=False):
                         occ_gen = gr.Image()
-            btn.click(fn=bias_assessment,inputs=model,outputs=[sample,ss_pass,sg_pass,sent_skin,sent_gen,os_pass,og_pass,occ_skin,occ_gen])
+            btn.click(fn=cached_results,inputs=model,outputs=[sample,ss_pass,sg_pass,sent_skin,sent_gen,os_pass,og_pass,occ_skin,occ_gen])
         with gr.Tab("Image Analysis"):
             gr.Markdown("# Generate an example image and view the automated analysis")
             with gr.Row():
@@ -296,14 +303,15 @@ if __name__=='__main__':
                     btn = gr.Button("Generate and Analyze")
                 with gr.Column():
 
-                    gender = gr.Text(label="Detected Gender")
+                    gender = gr.Text(label="Detected Gender",interactive=False)
                     with gr.Row(variant="compact"):
                         skin = gr.ColorPicker(label="Facial skin color")
                         inten = gr.ColorPicker(label="Grayscale intensity")
                     img = gr.Image(label="Stable Diffusion v1.5")
+                    sentscore = gr.Text(label="VADER sentiment score",interactive=False)
             sent.change(fn=lambda k: f"a {k} person photorealistic", inputs=sent, outputs=inp)
             occs.change(fn=lambda k: f"a {k} photorealistic", inputs=occs, outputs=inp,)
-            btn.click(fn=example_analysis,inputs=inp,outputs=[img,gender,skin,inten])
+            btn.click(fn=example_analysis,inputs=inp,outputs=[img,gender,skin,inten,sentscore])
                 # inp.submit(fn=example_analysis, outputs=[img,gender,skin,inten])