Create app.py

app.py

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+import gradio as gr
+import streamlit as st
+import requests
+import time 
+from transformers import pipeline
+import os
+
+
+# Set the page configuration
+st.set_page_config(
+        page_title="Hate Speech Detection",
+        page_icon="📖",  #":bar_chart:"
+        layout='centered'
+    )
+
+#title = r"$\textsf{\small Hate Speech Detection}$"
+#st.title(title)
+#st.write("In this HuggingFace space you will be able to use our Hate Speech Detection model built at [VERİM - Center of Excellence in Data Analytics - Sabanci University](https://github.com/verimsu).")
+
+
+# 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)
+
+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}")
+
+
+# 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."),
+                     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",
+                     theme = "peach")
+
+iface.launch(share=False, enable_queue=True)