Update app.py

app.py

@@ -1,18 +1,28 @@
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
 import streamlit as st
-from transformers import pipeline
 
-# Load the zero-shot classification pipeline
-theme_detection = pipeline('zero-shot-classification')
+# Load pre-trained GPT-2 model and tokenizer
+model_name = "gpt2"  # You can try other GPT-2 variants as well
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+model = GPT2LMHeadModel.from_pretrained(model_name)
 
-st.title("Theme Detection App")
+st.title("Theme Generation App")
 
 # Create a textarea for user input
 user_text = st.text_area("Enter Text:", "Type here...")
 
-if st.button("Detect Themes"):
-    # Perform theme detection
-    themes = theme_detection(user_text, ['Theme1', 'Theme2', 'Theme3'])
-    
-    # Display the result
-    st.success(f"Detected Themes: {', '.join(themes['labels'])}")
+if st.button("Generate Themes"):
+    # Construct a prompt for thematic generation
+    prompt = f"Generate themes based on the following text: {user_text}\nThemes:"
+
+    # Tokenize the prompt
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
 
+    # Generate themes using GPT-2
+    output = model.generate(input_ids, max_length=100, num_beams=5, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7)
+
+    # Decode the generated themes
+    generated_themes = tokenizer.decode(output[0], skip_special_tokens=True)
+    
+    # Display the generated themes
+    st.success(f"Generated Themes: {generated_themes}")