update

app.py

@@ -10,13 +10,18 @@ st.subheader("Search for News and classify the headlines with sentiment analysis
 
 query = st.text_input("Enter Query")
 
+models = [
+          "SamLowe/roberta-base-go_emotions", 
+          # "distilbert/distilbert-base-uncased-finetuned-sst-2-english"
+        ]
+
 settings = {
   "lang": "fr",
   "region": "FR",
-  "period": "1d"
+  "period": "1d",
+  "model": models[0],
 }
 
-classifier = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None)
 
 with st.sidebar:
   st.title("Settings")
@@ -28,13 +33,15 @@ with st.sidebar:
   # add period parameter
   st.header("Period")
   settings["period"] = st.selectbox("Select Period", ["1d", "7", "30d"])
-
-
+  # Add models parameters
+  st.header("Models")
+  settings["model"] = st.selectbox("Select Model", models)
 
 
 if st.button("Search"):
+  classifier = pipeline(task="text-classification", model=settings["model"], top_k=None)
   df = wna.get_news(settings, query)
-  st.dataframe(df)
+  # st.dataframe(df)
   # get each title colums
   sentences = df["title"]
   # convert into array