Add application file

app.py

@@ -0,0 +1,22 @@
+import streamlit as st
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import torch
+
+
+# Load the model for inference
+model = AutoModelForSeq2SeqLM.from_pretrained('SantiagoPG/chatbot_customer_service')
+tokenizer = AutoTokenizer.from_pretrained("Kaludi/Customer-Support-Assistant-V2")
+
+def get_chatbot_response(message):
+    inputs = tokenizer.encode(message, return_tensors='pt')
+    reply_ids = model.generate(inputs)
+    return tokenizer.decode(reply_ids[0], skip_special_tokens=True)
+
+# Streamlit interface
+st.title("Customer Service Chatbot")
+
+user_input = st.text_input("Type your question here:")
+
+if user_input:
+    response = get_chatbot_response(user_input)
+    st.text_area("Response", value=response, height=100, max_chars=None, key=None)