Update app.py

app.py

@@ -1,23 +1,26 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load a question-answering model instead of a text generator
-qa_pipeline = pipeline("question-answering", model="deepset/roberta-base-squad2")
+# Use a different LLM (GPT-Neo instead of GPT-2)
+generator = pipeline('text-generation', model='EleutherAI/gpt-neo-125M')
 
-def get_answer(question):
-    context = """
-    London is the capital of the United Kingdom. The UK consists of England, Scotland, Wales, and Northern Ireland.
-    """
-    answer = qa_pipeline(question=question, context=context)
-    return answer["answer"]
+def generate_text(prompt):
+    generated = generator(
+        prompt,
+        max_length=20,          # Limit response length
+        do_sample=False,        # Make output deterministic
+        temperature=0.1,        # Reduce randomness
+        repetition_penalty=2.0  # Prevent repeating words
+    )
+    return generated[0]['generated_text']
 
-# Create Gradio Interface
+# Create the Gradio interface
 iface = gr.Interface(
-    fn=get_answer,
+    fn=generate_text,
     inputs="text",
     outputs="text",
     title="Ask Any Question",
-    description="Ask factual questions and get precise answers."
+    description="Ask a question and get an answer using GPT-Neo."
 )
 
 iface.launch()