Create app.py

app.py

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+import gradio as gr
+import os
+from fastai.text.all import *
+import warnings
+warnings.filterwarnings('ignore')
+
+print("Current directory files:", os.listdir('.'))
+
+# Try to load model
+try:
+    learn = load_learner('js_concept_tagger_simple_numbers.pkl')
+    print("✅ Model loaded successfully!")
+except Exception as e:
+    print(f"❌ Model loading failed: {e}")
+    learn = None
+
+def predict_js_concept(code_snippet):
+    if learn is None:
+        return "❌ Model not available - check logs", 0.0, "Model loading failed"
+    
+    try:
+        pred, pred_idx, probs = learn.predict(code_snippet)
+        predicted_concept = str(pred)
+        confidence = float(probs.max())
+        return predicted_concept, confidence, f"Success! Predicted: {predicted_concept}"
+    except Exception as e:
+        return f"Prediction error: {str(e)}", 0.0, "Prediction failed"
+
+# Simple interface
+demo = gr.Interface(
+    fn=predict_js_concept,
+    inputs=gr.Textbox(label="JavaScript Code", lines=3),
+    outputs=[
+        gr.Textbox(label="Prediction"),
+        gr.Number(label="Confidence"),
+        gr.Textbox(label="Status")
+    ],
+    title="JS Concept Classifier",
+    examples=[["const age = 25;"]]
+)
+
+if __name__ == "__main__":
+    demo.launch()