Update app.py

app.py

@@ -1,17 +1,21 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import pipeline, set_seed
 
-# Create a text2text-generation pipeline with the "google/flan-t5-base" model
-pipe = pipeline("text2text-generation", model="google/flan-t5-base")
+# Create a text generation pipeline with the "gpt2" model
+pipe = pipeline("text-generation", model="gpt2")
 
-st.title("Question-Answer Generator")
-user_question = st.text_input("Ask a question:")
+st.title("Poem Generator")
+user_word = st.text_input("Enter a word:")
 
-if st.button("Generate Answer"):
-    if user_question:
-        # Use the T5 model to generate a more precise answer
-        answer = pipe(user_question, max_length=100, do_sample=False)[0]["generated_text"]
-        st.write("Answer:")
-        st.write(answer)
+if st.button("Generate Poem"):
+    if user_word:
+        # Set a seed for reproducibility
+        set_seed(42)
+        
+        # Prompt the model to generate a poem based on the user's word
+        poem_prompt = f"Write a poem about '{user_word}':"
+        poem = pipe(poem_prompt, max_length=100, do_sample=True, num_return_sequences=1)[0]["generated_text"]
+        st.markdown("**Poem:**")
+        st.markdown(poem)
     else:
-        st.warning("Please enter a question.")
+        st.warning("Please enter a word.")