update

README.md

@@ -15,7 +15,7 @@ tags:
   - data anonymization
   - homomorphic encryption
   - security
-python_version: 3.8.16
+python_version: 3.10
 ---
 
 # Data Anonymization using FHE

app.py

@@ -84,9 +84,10 @@ with open("files/original_document.txt", "r") as file:
 with open("files/anonymized_document.txt", "r") as file:
     anonymized_document = file.read()
 
-demo = gr.Blocks()
+demo = gr.Blocks(css=".markdown-body { font-size: 18px; }")
 
 with demo:
+
     gr.Markdown(
         """
         <p align="center">
@@ -112,11 +113,12 @@ with demo:
             """
         )
 
-    with gr.Accordion("Original Document", open=False):
-        gr.Markdown(original_document)
+    with gr.Row():
+        with gr.Accordion("Original Document", open=True):
+            gr.Markdown(original_document)
 
-    with gr.Accordion("Anonymized Document", open=False):
-        gr.Markdown(anonymized_document)
+        with gr.Accordion("Anonymized Document", open=True):
+            gr.Markdown(anonymized_document)
 
     # gr.Markdown(
     #     """
@@ -129,14 +131,20 @@ with demo:
     with gr.Row():
         input_text = gr.Textbox(
             value=default_demo_text,
-            lines=13,
+            lines=1,
             placeholder="Input text here...",
             label="Input",
         )
 
-        anonymized_text_output = gr.Textbox(label="Anonymized Text with FHE", lines=13)
+        # List of example queries for easy access
+        example_queries = ["Example Query 1", "Example Query 2", "Example Query 3"]
+        examples_radio = gr.Radio(choices=example_queries, label="Example Queries")
+
+        examples_radio.change(lambda example_query: example_query, inputs=[examples_radio], outputs=[input_text])
+
+    anonymized_text_output = gr.Textbox(label="Anonymized Text with FHE", lines=1)
 
-    identified_words_output = gr.Dataframe(label="Identified Words", visible=True)
+    identified_words_output = gr.Dataframe(label="Identified Words", visible=False)
 
     submit_button = gr.Button("Anonymize with FHE")
 

fhe_anonymizer.py

@@ -56,6 +56,7 @@ class FHEAnonymizer:
 
             if probability >= 0.5:
                 identified_words_with_prob.append((token, probability))
+
                 # Use the existing UUID if available, otherwise generate a new one
                 tmp_uuid = self.uuid_map.get(token, str(uuid.uuid4())[:8])
                 processed_tokens.append(tmp_uuid)