switch to gpt2

app.py

@@ -1,12 +1,28 @@
 import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load pre-trained model and tokenizer from Hugging Face
+model_name = "gpt2"  # You can use other models like "gpt-neo", "gpt-3", etc.
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 # Title of the app
-st.title("Simple Streamlit App")
+st.title("LLM Chatbot")
+
+# User input for chatbot
+user_input = st.text_input("You: ", "")
 
-# User input for text
-user_input = st.text_input("Enter some text:")
+# Function to generate the response using the model
+def generate_response(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs.input_ids, max_length=150, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
 
-# Display the input text
 if user_input:
-    st.write(f"You entered: {user_input}")
+    # Generate a response from the model
+    response = generate_response(user_input)
+    
+    # Display only the bot's response
+    st.write(f"Bot: {response}")