Update app.py

app.py

@@ -1,26 +1,27 @@
-
-
 import gradio as gr
 
-# 1. Define your title and description
-title = "Spanish Songs Toxicity Classification"
-description = "Pretrained models: ES-EN Translation (Opus MT) + Roberta Toxicity Classifier"
+# 1. Load the models using the Inference API
+# We use gr.load to get the 'functions' for these models
+translator = gr.load("models/Helsinki-NLP/opus-mt-es-en")
+classifier = gr.load("models/SkolkovoInstitute/roberta_toxicity_classifier")
 
-# 2. Load the models using the modern gr.load syntax
-# Note: Adding "models/" prefix is the standard for the Hub
-translator_es = gr.load("models/Helsinki-NLP/opus-mt-es-en")
-toxicity_classifier = gr.load("models/SkolkovoInstitute/roberta_toxicity_classifier")
+# 2. Define a wrapper function to chain them
+def Spanish_Toxicity_Check(text):
+    # Step 1: Translate Spanish to English
+    english_text = translator(text)
+    # Step 2: Pass English result to Toxicity classifier
+    results = classifier(english_text)
+    return results
 
-# 3. Use gr.Series to chain them together
-# This passes the output of the translator directly into the classifier
-interface = gr.Series(
-    translator_es, 
-    toxicity_classifier, 
-    description=description,
-    title=title
+# 3. Create the Interface
+demo = gr.Interface(
+    fn=Spanish_Toxicity_Check,
+    inputs=gr.Textbox(label="Input Spanish Song Lyric", placeholder="Escribe aquí..."),
+    outputs=gr.Label(label="Toxicity Analysis"),
+    title="Spanish Songs Toxicity Classification",
+    description="Pretrained models: ES-EN Translation (Opus MT) + Roberta Toxicity Classifier"
 )
 
-# 4. Launch the app
+# 4. Launch
 if __name__ == "__main__":
-    interface.launch()
-
+    demo.launch()