added app.py

app.py

@@ -0,0 +1,45 @@
+import streamlit as st
+from simpletransformers.classification import MultiLabelClassificationModel
+import torch
+
+# Function to make predictions
+def predict(model, text):
+    raw_outputs, _ = model.predict([text])
+    return raw_outputs
+
+# Streamlit App
+def main():
+    st.title("Dravidian-English Code Mixed TextSentiment Prediction App")
+
+    # Language model selection
+    selected_language = st.selectbox("Select Language Model", ["Kannada", "Malayalam", "Tamil"])
+
+    # Load the pre-trained model based on the selected language
+    model_paths = {
+        "Kannada": "KanModel1",
+        "Malayalam": "MalModel1",  
+        "Tamil": "TamModel1",  
+    }
+
+    if selected_language in model_paths:
+        model_path = model_paths[selected_language]
+        model = MultiLabelClassificationModel('xlm', model_path, use_cuda=False)
+
+        # User input for text
+        text_input = st.text_area("Enter text for prediction", "")
+
+        # Make predictions when the user clicks the button
+        if st.button("Predict"):
+            if text_input:
+                predictions = predict(model, text_input)
+
+                # Display the predictions
+                if predictions == [[1, 0, 0]]:
+                    st.success('Positive Sentiment')
+                elif predictions == [[0, 1, 0]]:
+                    st.error('Negative Sentiment')
+                else:
+                    st.warning('Mixed Sentiment')
+
+if __name__ == "__main__":
+    main()