Create app.py

app.py

@@ -0,0 +1,35 @@
+import streamlit as st
+import torch
+import transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+def load_data():
+  tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+  model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+  return tokenizer, model
+
+tokenizer, model = load_data()
+
+st.title("Chatbot -- Microsoft DialoGPT Medium")
+st.write("Write or paste text as if sending a text message to a person. The machine will attempt to respond appropriately.")
+input = st.text_input('Your text message:')
+
+if 'count' not in st.session_state or st.session_state.count == 6:
+  st.session_state.count = 0 
+  st.session_state.chat_history_ids = None
+  st.session_state.old_response = ''
+else:
+  st.session_state.count += 1
+  
+new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
+bot_input_ids = torch.cat([st.session_state.chat_history_ids, new_user_input_ids], dim=-1) if st.session_state.count > 1 else new_user_input_ids
+st.session_state.chat_history_ids = model.generate(bot_input_ids, max_length=500, pad_token_id=tokenizer.eos_token_id)
+response = tokenizer.decode(st.session_state.chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
+
+if st.session_state.old_response == response:
+  bot_input_ids = new_user_input_ids
+  st.session_state.chat_history_ids = model.generate(bot_input_ids, max_length=5000, pad_token_id=tokenizer.eos_token_id)
+  response = tokenizer.decode(st.session_state.chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
+  
+st.write(f"Machine text message: {response}")
+st.session_state.old_response = response