Update app.py

app.py

@@ -20,43 +20,28 @@ st.set_page_config(
 
 # Turkish 
 sentiment_pipeline_tr = pipeline(task = "text-classification", model = "SoDehghan/BERTurk-hate-speech")  # "gritli/bert-sentiment-analyses-imdb"
-header_tr = r"$\textsf{\scriptsize HSD in Turkish}$"
-st.subheader(header_tr)
+label_dict = {'LABEL_1': 'Hate ❌', 'LABEL_0': 'Non-hate ✅'}
+
+def hsd_turkish:
 
-tr_input = st.text_area("Enter your text here:", height=50, key="tr_input")  #height=30
-if st.button("Click for predictions!", key="tr_predict"):
-    with st.spinner('Generating predictions...'):
         result_tr = sentiment_pipeline_tr(tr_input)
         sentiment_tr = result_tr[0]["label"]
         label_dict = {'LABEL_1': 'Hate ❌', 'LABEL_0': 'Non-hate ✅'}  #🚫
         sentiment_tr = label_dict[sentiment_tr]
-        st.write(f"Detection: {sentiment_tr}")
-
+        return sentiment_tr
 
-# Arabic
-sentiment_pipeline_ar = pipeline(task = "text-classification", model = "SoDehghan/BERTurk-hate-speech")
-header_ar = r"$\textsf{\scriptsize HSD in Arabic}$"
-st.subheader(header_ar)
 
-ar_input = st.text_area("Enter your text here:", height=50 , key="ar_input")
-if st.button("Click for predictions!", key="ar_predict"):
-    with st.spinner('Generating predictions...'):
-        result_ar = sentiment_pipeline_ar(ar_input)
-        sentiment_ar = result_ar[0]["label"]
-        label_dict = {'LABEL_1': 'Hate ❌', 'LABEL_0': 'Non-hate ✅'}
-        sentiment_ar = label_dict[sentiment_ar]
-        st.write(f"Detection: {sentiment_ar}") 
 
 
 st.sidebar.title("Hate Speech Detection")
 #st.sidebar.write("In this HuggingFace space you can use Hate Speech Detection model built at [VERİM - Center of Excellence in Data Analytics - Sabanci University](https://github.com/verimsu).")
 st.sidebar.write('This tool is developed in the context of the EU project "Utilizing Digital Technology for Social Cohesion, Positive Messaging and Peace by Boosting Collaboration, Exchange and Solidarity" (EuropeAid/170389/DD/ACT/Multi) by [Sabanci University Center of Excellence in Data Analytics](https://github.com/verimsu).')
 
-iface = gr.Interface(fn=[translator_fn_baseline, translator_fn_roberta],
-                     inputs=gr.inputs.Textbox(lines=2, placeholder=None, label="Your Danish text goes here."),
+iface = gr.Interface(fn=[hsd_turkish],
+                     inputs=gr.inputs.Textbox(lines=2, placeholder=None, label="Enter text here:"),
                      outputs=['text'],   # a list should match the number of values returned by fn to have one input and 2 putputs.
-                     description = "This App translates text from Danish to the English language.",
-                     title = "Danish to English Translator App",
+                     #description = "This App translates text from Danish to the English language.",
+                     title = "HSD in Turkish",
                      theme = "peach")
 
 iface.launch(share=False, enable_queue=True)