Update app.py

app.py

@@ -1,8 +1,11 @@
 import gradio as gr
 from Recommender import Recommender
 from Preprocess import ModelUtils, Preprocess
+import numpy as np
+import pandas as pd
 
-data_path = "data"
+
+data_path = "result.csv"
 model_path = "model_root"
 
 data = pd.read_csv(data_path)
@@ -14,16 +17,17 @@ p = Preprocess(model_path)
 
 data = pd.read_csv(data_path)
 
-rec = Recommender (4, 3, 0)
+rec = Recommender (0, 1, 2, 3, 4)
 k = 3
 
 table = [tuple(row) for row in data.to_numpy()]
 
 def recom (title) :
-    rec.recommend_k(table, k, title)
+    indices, scores, title_scores = rec.recommend_k(table, k, title)
+    out = list(data[indices]['title'])
+    return "\n".join(out)
 
 demo = gr.Interface(fn=recom, 
-             inputs=[gr.Dropdown(choices = list(desc['title'][:20]), multiselect=True, max_choices=3, label="Movies"), 
-                     gr.Radio(["bert", "scibert", "nltk" , "none"], value="none", label="Tokenization and text preprocess")], 
-             outputs=gr.Textbox(label="Recommended"))
+             inputs=[gr.Dropdown(choices = list(data['title'][:20]), multiselect=False, label="Titles")], 
+             outputs=gr.Textbox(label="Titles of recommended items"), type='multiline')
 demo.launch()