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app.py

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+"""
+HuggingFace Space - ESS Variable Classification Demo
+Interactive Gradio interface for the XLM-RoBERTa ESS classifier.
+"""
+import gradio as gr
+from transformers import pipeline
+
+# Load the model
+MODEL_NAME = "benjaminBeuster/xlm-roberta-base-ess-classification"
+classifier = pipeline("text-classification", model=MODEL_NAME)
+
+# Category descriptions
+CATEGORY_INFO = {
+    "DEMOGRAPHY (POPULATION, VITAL STATISTICS, AND CENSUSES)": "Demographics, population statistics, age, gender",
+    "ECONOMICS": "Economic issues, finance, income",
+    "EDUCATION": "Education, schooling, qualifications",
+    "HEALTH": "Healthcare, medical services, health satisfaction",
+    "POLITICS": "Political systems, trust in government, parliament",
+    "SOCIETY AND CULTURE": "Social issues, cultural topics, religion",
+    "LABOUR AND EMPLOYMENT": "Work, occupation, employment status",
+    "PSYCHOLOGY": "Mental health, psychological wellbeing",
+    "OTHER": "General or uncategorized topics"
+}
+
+def classify_text(text):
+    """Classify survey question/variable."""
+    if not text.strip():
+        return "Please enter some text to classify."
+
+    result = classifier(text)[0]
+    label = result['label']
+    score = result['score']
+
+    # Format output
+    output = f"**Category:** {label}\n\n"
+    output += f"**Confidence:** {score:.2%}\n\n"
+
+    if label in CATEGORY_INFO:
+        output += f"**Description:** {CATEGORY_INFO[label]}"
+
+    return output
+
+# Example questions
+examples = [
+    ["What is your age?"],
+    ["How satisfied are you with the healthcare system?"],
+    ["Trust in country's parliament"],
+    ["What is your highest level of education?"],
+    ["How often do you pray?"],
+    ["What is your occupation?"],
+    ["Do you feel safe walking alone at night?"],
+]
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=classify_text,
+    inputs=gr.Textbox(
+        lines=3,
+        placeholder="Enter a survey question or variable description...",
+        label="Input Text"
+    ),
+    outputs=gr.Markdown(label="Classification Result"),
+    title="ESS Variable Classification",
+    description="""
+    Classify European Social Survey (ESS) variables into 19 subject categories.
+
+    This model is fine-tuned from XLM-RoBERTa-Base and achieves 83.8% accuracy on the test set.
+    """,
+    examples=examples,
+    article="""
+    ### About
+
+    This classifier helps organize survey variables by automatically categorizing them into subject areas.
+    Built on [XLM-RoBERTa-Base](https://huggingface.co/FacebookAI/xlm-roberta-base),
+    trained on European Social Survey metadata.
+
+    **Model:** [benjaminBeuster/xlm-roberta-base-ess-classification](https://huggingface.co/benjaminBeuster/xlm-roberta-base-ess-classification)
+
+    **Performance:** 83.8% accuracy | F1: 0.796 (weighted)
+    """,
+    theme=gr.themes.Soft(),
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    demo.launch()