Create app.py

app.py

@@ -0,0 +1,47 @@
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import gradio as gr
+
+# Load the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("sagard21/python-code-explainer")
+model = AutoModelForSeq2SeqLM.from_pretrained("sagard21/python-code-explainer")
+
+def explain_code(python_code):
+    # Tokenize the input code
+    inputs = tokenizer(python_code, return_tensors="pt", truncation=True, max_length=512)
+    
+    # Generate explanation
+    explanation_ids = model.generate(
+        inputs["input_ids"],
+        max_length=256,
+        num_beams=5,
+        early_stopping=True
+    )
+    
+    # Decode and return the explanation
+    explanation = tokenizer.decode(explanation_ids[0], skip_special_tokens=True)
+    return explanation
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=explain_code,
+    inputs=gr.Code(
+        language="python",
+        label="Enter Python Code",
+        lines=10,
+        placeholder="def hello_world():\n    print('Hello, world!')"
+    ),
+    outputs=gr.Textbox(
+        label="Code Explanation",
+        lines=5
+    ),
+    title="Python Code Explainer",
+    description="🔍 Enter Python code and get a natural language explanation of what it does.",
+    examples=[
+        ["def add(a, b):\n    return a + b"],
+        ["for i in range(5):\n    print(i)"],
+        ["x = [i**2 for i in range(10) if i % 2 == 0]"]
+    ]
+)
+
+# Launch the app
+demo.launch()