add textwrap and spinner

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 from speaking_probes.generate import extract_gpt_parameters, speaking_probe
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from copy import deepcopy
+import textwrap
 
 
 @st.cache
@@ -24,11 +25,12 @@ prompt = st.text_area("Prompt: ")
 submitted = st.button("Send!")
 
 if submitted:
-    model, model_params, tokenizer = map(deepcopy, (model, model_params, tokenizer))
-    decoded = speaking_probe(model, model_params, tokenizer, prompt, *neurons, 
-                             repetition_penalty=2., num_generations=3,
-                             min_length=1, do_sample=True, 
-                             max_new_tokens=100)
+    with st.spinner('Wait for it..'):
+        model, model_params, tokenizer = map(deepcopy, (model, model_params, tokenizer))
+        decoded = speaking_probe(model, model_params, tokenizer, prompt, *neurons, 
+                                 repetition_penalty=2., num_generations=3,
+                                 min_length=1, do_sample=True, 
+                                 max_new_tokens=100)
 
     for text in decoded:
-        st.text(text)
+        st.text(textwrap.wrap(text, width=70))