Upload app.py

app.py

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+# app.py
+
+import gradio as gr
+import joblib
+import numpy as np
+from feature_extraction.pipeline import text_to_features
+
+# Load pretrained Random Forest model for Openness
+model = joblib.load("models/openness_rf.pkl")
+
+def predict_openness(text):
+    try:
+        vec = text_to_features(text)  # shape: (1, dim)
+        pred = model.predict(vec)[0]  # already "low", "medium", or "high"
+        return f"Predicted Openness: **{pred.upper()}**"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio UI
+demo = gr.Interface(
+    fn=predict_openness,
+    inputs=gr.Textbox(lines=6, placeholder="Enter your thoughts here..."),
+    outputs=gr.Markdown(),
+    title="Big Five Personality Prediction",
+    description="This model predicts **Openness** based on your text using BERT + LIWC features.",
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    demo.launch()