second update app.py

changed variable name "somme" to "similarities" to be more explicit. Better formatted the description. Added more explicative input and audio labels.

app.py

@@ -2,27 +2,31 @@ import pandas as pd
 from sentence_transformers import SentenceTransformer, util
 import gradio
 
-PATH_TO_FILE = 'cabot_dataset_def_csv.csv'
+PATH_TO_FILE = 'cabot_qa.csv'
 df = pd.read_csv(PATH_TO_FILE, sep=';')
 df.drop_duplicates(inplace=True, ignore_index=True)
 
 model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
 
 def run_question(Question):
-    somme = []
+    similarities = []
     for jdx, j in enumerate(list(df.Question)):
-        somme.append(float(util.pytorch_cos_sim(
+        similarities.append(float(util.pytorch_cos_sim(
             model.encode(list(df.Question)[jdx], convert_to_tensor=True),
             model.encode(Question, convert_to_tensor=True))))
-    if round(max(somme)*100) < 70:
+    if round(max(similarities)*100) < 70:
         return 'I\'m sorry, I\'m not sure I understood your question. Could you try again?'
     else:
-        return df.loc[somme.index(max(somme)), 'Answer']
+        return df.loc[similarities.index(max(similarities)), 'Answer']
 
-gradio.Interface(run_question, "text", "text",
-                 title='Introducing C.A.BOT',
-                 description='Hi! This is Cabot, the Consular Affairs bot.\nI will help you answer your questions about the Citizen Services that you can request at the Consular Sections within U.S. Embassy Rome.').launch()
+description = """Hi! I'm is Cabot, the Consular Affairs bot.<br>
+I will answer your questions about the Citizen Services that you can request at the Consular Sections within U.S. Embassy Rome."""
 
+gradio.Interface(run_question,
+                 title='Introducing C.A.BOT',
+                 description=description,
+                 inputs=gradio.Textbox(label="Type your question here!"),
+                 outputs=gradio.Textbox(label="Answer")).launch()