Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import joblib
+import numpy as np
+from sentence_transformers import SentenceTransformer
+import lightgbm as lgb
+
+# Load models
+ridge = joblib.load("model/ridge_model.pkl")
+lgbm = lgb.Booster(model_file="model/lgb_model.txt")
+sbert = SentenceTransformer('paraphrase-mpnet-base-v2')
+
+def predict_score(essay_text):
+    embedding = sbert.encode([essay_text])
+    ridge_score = ridge.predict(embedding)[0]
+    lgbm_score = lgbm.predict(embedding)[0]
+    final_score = 0.5 * ridge_score + 0.5 * lgbm_score
+    return round(final_score, 2)
+
+gr.Interface(
+    fn=predict_score,
+    inputs="text",
+    outputs="number",
+    title="Automated Essay Scorer",
+    description="Paste your essay below and get a predicted score."
+).launch()