Update app.py

app.py

@@ -35,6 +35,22 @@ dataset = load_dataset("squad")  # you can replace "squad" with any dataset you'
 
 # Print the first few entries to verify that it’s loaded
 print(dataset["train"][0])  # Prints the first example from the training set
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+# Load pre-trained GPT-2 model and tokenizer from Hugging Face
+model_name = "gpt2"  # You can use other models such as 'distilgpt2' for faster responses
+
+# Initialize tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Create a pipeline for text generation
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+def chatbot_response(user_input):
+    # Generate a response using the model
+    response = generator(user_input, max_length=100, num_return_sequences=1)
+    
+    # Extract and return the generated text
+    return response[0]['generated_text']