add annotated text, and compare original text and the corrected text

app.py

@@ -1,9 +1,42 @@
 import streamlit as st
 from happytransformer import HappyTextToText, TTSettings
+from annotated_text import annotated_text
+import difflib
 
 checkpoint = "team-writing-assistant/t5-base-c4jfleg"
 
 
+def diff_strings(a, b):
+    result = []
+    diff = difflib.Differ().compare(a.split(), b.split())
+    replacement = ""
+    for line in diff:
+        if line.startswith("  "):
+            if len(replacement) == 0:
+                result.append(" ")
+                result.append(line[2:])
+            else:
+                result.append(" ")
+                result.append(("", replacement, "#ffd"))
+                replacement = ""
+                result.append(line[2:])
+        elif line.startswith("- "):
+            if len(replacement) == 0:
+                replacement = line[2:]
+            else:
+                result.append(" ")
+                result.append(("", replacement, "#fdd"))
+                replacement = ""
+        elif line.startswith("+ "):
+            if len(replacement) == 0:
+                result.append(("", line[2:], "#dfd"))
+            else:
+                result.append(" ")
+                result.append((line[2:], replacement, "#ddf"))
+                replacement = ""
+    return result
+
+
 @st.cache(suppress_st_warning=True, allow_output_mutation=True)
 def get_happy_text(model_name):
     st.write(f"Loading the HappyTextToText model {model_name}, please wait...")
@@ -31,7 +64,9 @@ def output(input_text):
     with st.spinner('Detecting 🔍..'):
         input_text = "grammar: " + input_text
         result = happy_tt.generate_text(input_text, args=args)
-        st.markdown("## " + result.text)
+        # st.markdown("## " + result.text)
+        diff = diff_strings(input_text[9:], result.text)
+        annotated_text(*diff)
 
 
 if example_1:

requirements.txt

@@ -1 +1,2 @@
-happytransformer
+happytransformer
+st-annotated-text