Upload app.py

app.py

@@ -2,22 +2,41 @@ import gradio as gr
 import random
 import pandas as pd
 
-opo = pd.read_csv('oportunidades.csv')
-simulation = pd.read_csv('simulation1.csv')
+opo = pd.read_csv('oportunidades_results.csv', lineterminator='\n')
+simulation = pd.read_csv('simulation2.csv')
 userID = max(simulation['userID']) + 1
 
-opo_n = random.randrange(len(opo))
-evaluated = [opo_n]
+def build_display_text(opo_n):
+    
+    title = opo.loc[opo_n]['opo_titulo']
+    link = opo.loc[opo_n]['link']
+    summary = opo.loc[opo_n]['facebook-bart-large-cnn_results']
+
+    display_text = f"**{title}**\n\nURL:\n{link}\n\nSUMMARY:\n{summary}"
+
+    return display_text
+
+opo_n_one = random.randrange(len(opo))
+opo_n_two = random.randrange(len(opo))
+opo_n_three = random.randrange(len(opo))
+opo_n_four = random.randrange(len(opo))
 
-def predict_next(inp):
+evaluated = []
+
+def predict_next(option, nota):
     global userID
-    global opo_n
+    global opo_n_one
+    global opo_n_two
+    global opo_n_three
+    global opo_n_four
     global evaluated
     global opo
     global simulation
 
-    simulation = simulation.append({'userID': userID, 'itemID': opo_n, 'rating': inp}, ignore_index=True)
-    evaluated.append(opo_n)
+    selected = [opo_n_one, opo_n_two, opo_n_three, opo_n_four][int(option)-1]
+
+    simulation = simulation.append({'userID': userID, 'itemID': selected, 'rating': nota}, ignore_index=True)
+    evaluated.append(selected)
     
     from surprise import Reader
     reader = Reader(rating_scale=(1, 5))
@@ -37,19 +56,36 @@ def predict_next(inp):
         if i not in evaluated:
             items.append(i)
             est.append(svdpp.predict(userID, i).est)
-    
-    opo_n = items[est.index(max(est))]
-    return opo.loc[opo_n]['opo_texto']
+
+    opo_n_one = items[est.index(sorted(est)[-1])]
+    opo_n_two = items[est.index(sorted(est)[-2])]
+    opo_n_three = items[est.index(sorted(est)[-3])]
+    opo_n_four = items[est.index(sorted(est)[-4])]
+
+    return build_display_text(opo_n_one), build_display_text(opo_n_two), build_display_text(opo_n_three), build_display_text(opo_n_four)
+
 
 with gr.Blocks() as demo:
-    gr.Markdown("# MCTI Recommender System")
-    
-    current_opo = gr.Textbox(opo.loc[opo_n]['opo_texto'], label='Oportunidade')
-    nota = gr.Slider(1,5,step=1,label="Nota")
-    confirm = gr.Button("Confirmar")
+    with gr.Row():
+        one_opo = gr.Textbox(build_display_text(opo_n_one), label='Oportunidade 1')
+        two_opo = gr.Textbox(build_display_text(opo_n_two), label='Oportunidade 2')
+
+    with gr.Row():
+        three_opo = gr.Textbox(build_display_text(opo_n_three), label='Oportunidade 3')
+        four_opo = gr.Textbox(build_display_text(opo_n_four), label='Oportunidade 4')
+
+    with gr.Row():
+        option = gr.Radio(['1', '2', '3', '4'], label='Opção', value = '1')
+
+    with gr.Row():
+        nota = gr.Slider(1,5,step=1,label="Nota 1")
+
+    with gr.Row():
+        confirm = gr.Button("Confirmar")
 
-    confirm.click(fn=predict_next,
-               inputs=nota,
-               outputs=current_opo)
+        confirm.click(fn=predict_next,
+               inputs=[option, nota],
+               outputs=[one_opo, two_opo, three_opo, four_opo])
 
-demo.launch() 
+if __name__ == "__main__":
+    demo.launch()