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app.py

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+import gradio as gr
+import re
+
+from transformers import pipeline
+
+sp_model = "SineTheta/Spam_and_bully_detection"
+ca_model = "SineTheta/Spam_and_bully_detection"
+sp_analysis = pipeline("text-classification", model=sp_model, tokenizer=sp_model)
+ca_analysis = pipeline("text-classification", model=ca_model, tokenizer=ca_model)
+
+def bullying_analysis(language, text):
+    if language == 'English':
+        results = sp_analysis(text)
+    elif language == 'French':
+        results = ca_analysis(text)
+    return results[0]["label"], round(results[0]["score"], 5)
+
+
+gradio_ui = gr.Interface(
+    fn=bullying_analysis,
+    title="CyberBullying Detector (Spanish/Catalan)",
+    description="Enter some text and check if the model detects bullying.",
+    inputs=[
+        gr.inputs.Radio(['Spanish','Catalan'],label='Language',),
+        gr.inputs.Textbox(lines=5, label="Paste some text here"),
+    ],
+    outputs=[
+        gr.outputs.Textbox(label="Label"),
+        gr.outputs.Textbox(label="Score"),
+    ],
+    examples=[
+        ['Spanish', "Eres mas alto que un pino y mas tonto que un pepino!"],
+        ['Catalan', "Ets un barrufet!"],
+        ['Spanish', "Estas mas gordo que una foca!"],
+        ['Catalan', "Ets mes lleig que un pecat!"],
+    ],
+)
+
+gradio_ui.launch()