Add our model and interface

app.py

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+import spacy
+import gradio as gr
+from textacy import preprocessing
+
+import en_ethicalads_topics
+
+
+ea_nlp = en_ethicalads_topics.load()
+
+preprocessor = preprocessing.make_pipeline(
+    preprocessing.normalize.unicode,
+    preprocessing.remove.punctuation,
+    preprocessing.normalize.whitespace,
+)
+
+
+def classify(input_text):
+    processed_input = preprocessor(input_text)
+    ea_output = ea_nlp(processed_input)
+    return str(sorted(ea_output.cats.items(), key=lambda x: x[1], reverse=True))
+
+
+iface = gr.Interface(
+    fn=classify,
+    inputs=gr.Textbox(lines=5, placeholder="Input text to detect the topic classification..."),
+    outputs="text",
+)
+iface.launch()

requirements.txt

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+spacy
+textacy
+gradio
+
+https://huggingface.co/davidfischer/en_ethicalads_topics