Create app.py

app.py

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+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer (e.g., a GPT model from Hugging Face)
+@st.cache_resource
+def load_model():
+    model_name = "microsoft/DialoGPT-small"  # Replace with your chosen model
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    return tokenizer, model
+
+# Initialize model and tokenizer
+tokenizer, model = load_model()
+
+# Streamlit app layout
+st.title("🤖 Friendly Chatbot")
+st.write("Hi! I'm your friendly chatbot. Ask me anything or just say hello! 😊")
+
+# User input
+user_input = st.text_input("You:", placeholder="Type your message here...")
+
+# Generate response
+if user_input:
+    inputs = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors="pt")
+    response = model.generate(inputs, max_length=50, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
+    bot_reply = tokenizer.decode(response[0], skip_special_tokens=True)
+    st.text_area("Chatbot:", value=bot_reply, height=100)
+