Create feedback.py

feedback.py

@@ -0,0 +1,18 @@
+from transformers import GPT3LMHeadModel, GPT3Tokenizer
+
+# Load pre-trained model and tokenizer
+model_name = "gpt3"  # You could choose another model here
+model = GPT2LMHeadModel.from_pretrained(model_name)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+
+def generate_feedback(user_answer):
+    # Encode user input to model's input format
+    inputs = tokenizer.encode(user_answer, return_tensors='pt')
+    
+    # Generate response from the model
+    outputs = model.generate(inputs, max_length=150, num_return_sequences=1, no_repeat_ngram_size=2)
+
+    # Decode the model's output to text
+    feedback = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    return feedback