Update app.py

app.py

@@ -6,17 +6,18 @@ from sentence_transformers.util import cos_sim
 from sentence_transformers import SentenceTransformer
 import gradio as gr
 #%%
-etalon = pd.read_csv("etalon_prod.csv")
+# etalon = pd.read_csv("etalon_prod.csv")
 df = pd.read_csv("preprocessed_complaints.csv")
 
 model = SentenceTransformer('sentence-transformers/multi-qa-distilbert-cos-v1')
 
 
-unique_complaints = df['Жалобы'].values.tolist()
+unique_complaints = df['Жалобы'].unique()
 
 with open("embeddings.npy", 'rb') as f:
     embeddings = np.load(f)
 
+#%%
 def get_recommend(user_input, 
                   top_k_spec = 3,
                   top_k_services = 5,
@@ -69,7 +70,7 @@ def get_recommend(user_input,
     result['Рекомендации по обследованию'] = top_k_services_lst
     result['Рекомендации по обследованию по МКБ'] = top_k_services_lst_by_mkb
 
-    return result
+    return result, sorted_df
 #%%
 gradio_app = gr.Interface(
     get_recommend,