chore: update

app.py

@@ -96,6 +96,10 @@ def run_fhe_fn(query_box):
     anonymizer.run_server_and_decrypt_output(query_box)
 
     anonymized_text = read_pickle(KEYS_DIR / "reconstructed_sentence")
+    
+    # Removing Spaces Before Punctuation:
+    anonymized_text = re.sub(r"\s([,.!?;:])", r"\1", anonymized_text)
+
     identified_words_with_prob = read_pickle(KEYS_DIR / "identified_words_with_prob")
 
     # Convert the list of identified words and probabilities into a DataFrame
@@ -203,12 +207,8 @@ with demo:
 
     with gr.Accordion("What is encrypted anonymization?", open=False):
         gr.Markdown(
-<<<<<<< HEAD
         """
         Anonymization is the process of removing personally identifiable information (PII) 
-=======
-            """Anonymization is the process of removing personally identifiable information (PII) 
->>>>>>> 053bec9 (chore: update with marketing remarks)
         from data to protect individual privacy.
     
         To resolve trust issues when deploying anonymization as a cloud service, Fully Homomorphic 
@@ -224,13 +224,15 @@ with demo:
     ########################## Key Gen Part ##########################
 
     gr.Markdown(
-        "### Key generation\n\n"
-        """In FHE schemes, two sets of keys are generated. First, secret keys are used for 
-        encrypting and decrypting data owned by the client. Second, evaluation keys allow a server 
-        to blindly process the encrypted data. """
+        "## Step 1: Key generation\n\n"
+
+        """In FHE schemes, two sets of keys are generated. First, the secret keys which are used for 
+        encrypting and decrypting data owned by the client. Second, the evaluation keys that allow 
+        a server to blindly process the encrypted data.
+        """
     )
 
-    gen_key_btn = gr.Button("Generate the private and evaluation keys")
+    gen_key_btn = gr.Button("Generate the secret and evaluation keys")
 
     gen_key_btn.click(
         key_gen_fn,
@@ -240,33 +242,38 @@ with demo:
 
     ########################## Main document Part ##########################
 
-    gr.Markdown("## Private document")
+    gr.Markdown("## Step 2: Private document")
+
+
 
     with gr.Row():
         with gr.Column():
+            gr.Markdown("**Original document:**")
             gr.Markdown(
                 """This document was retrieved from the [Microsoft Presidio](https://huggingface.co/spaces/presidio/presidio_demo) demo.\n\n     
                 You can select and deselect sentences to customize the document that will be used 
-                as the initial prompt for ChatGPT in this space's final stage.\n\n
+                as the initial prompt for ChatGPT in step 5.
                 """
             )
         with gr.Column():
+            gr.Markdown("**Anonymized document:**")        
             gr.Markdown(
-                """You can see the anonymized document that is sent to ChatGPT here. 
-                ChatGPT will answer any queries that you have about the document below. 
-                The anonymized information is replaced with hexadecimal strings. 
+                """You can see below the anonymized text, replaced with hexademical strings, that 
+                will be sent to ChatGPT. 
+                
+                ChatGPT will then be able to answer any queries about the document.
                 """
             )
 
     with gr.Row():
         with gr.Column():
             original_sentences_box = gr.CheckboxGroup(
-                ORIGINAL_DOCUMENT, value=ORIGINAL_DOCUMENT, label="Original document:"
+                 ORIGINAL_DOCUMENT, value=ORIGINAL_DOCUMENT, show_label=False,
             )
 
         with gr.Column():
-            anonymized_doc_box = gr.Textbox(
-                label="Anonymized document:", value=ANONYMIZED_DOCUMENT, interactive=False, lines=11
+            anonymized_doc_box = gr.Textbox(show_label=False, 
+                value=ANONYMIZED_DOCUMENT, interactive=False, lines=11
             )
 
     original_sentences_box.change(
@@ -278,15 +285,14 @@ with demo:
     ########################## User Query Part ##########################
 
     gr.Markdown("<hr />")
-    gr.Markdown("## Private query")
+    gr.Markdown("## Step 3: Private query")
 
     gr.Markdown(
-        """Now, formulate a query regarding the selected document.\n\n
+        """Now, you can formulate a query. Please choose from the predefined options in 
+        “Queries examples” or craft a custom question in the “Customized query” text box.
 
-                Choose from predefined options in 'Example Queries' or craft a custom query 
-                in the 'User Query' box. Keep your question concise and relevant to the text's 
-                context. Any off-topic question will not be processed.
-                """
+        Remain concise and relevant to the context. Any off-topic query will not be processed.
+        """
     )
 
     with gr.Row():
@@ -294,11 +300,13 @@ with demo:
 
             with gr.Column(scale=5):
                 default_query_box = gr.Dropdown(
-                    list(DEFAULT_QUERIES.values()), label="Example queries"
+                    list(DEFAULT_QUERIES.values()), label="Queries examples:"
                 )
 
+            gr.Markdown("Or")
+
             query_box = gr.Textbox(
-                value="Who lives in Maine?", label="User query", interactive=True
+                value="Who lives in Maine?", label="Customized query:", interactive=True
             )
 
             default_query_box.change(
@@ -313,40 +321,40 @@ with demo:
             gr.Markdown(
                 """
                 <p align="center">
-                Encrypt data locally with FHE 💻 ⚙️
+                Encrypt the query locally with FHE
                 </p>
                 """
             )
-            encrypt_btn = gr.Button("Encrypt data")
+            encrypt_btn = gr.Button("Encrypt query”")
             gr.HTML("<div style='height: 25px;'></div>")
 
         with gr.Column(scale=5):
             output_encrypted_box = gr.Textbox(
-                label="Encrypted anonymized query that is sent to the anonymization server", lines=6
+                label="Encrypted anonymized query that will be sent to the anonymization server:", lines=8
             )
 
     encrypt_btn.click(
         fn=encrypt_query_fn, inputs=[query_box], outputs=[query_box, output_encrypted_box]
     )
 
+    ########################## FHE processing Part ##########################
+
     gr.Markdown("<hr />")
-    gr.Markdown("## Secure anonymization with FHE")
+    gr.Markdown("## Step 4: Secure anonymization with FHE")
     gr.Markdown(
-        """
-        Once the client encrypts the private query locally, 
-        the client transmits it to a remote server to perform the 
-        anonymization on encrypted data. When the computation is finished, the server returns 
-        the result to the client for decryption.
+        """ Once the client encrypts the private query locally, it will be sent to a remote server 
+        to perform the anonymization on encrypted data. When the computation is done, the server 
+        will return the result to the client for decryption.
         """
     )
 
     run_fhe_btn = gr.Button("Anonymize with FHE")
 
     anonymized_text_output = gr.Textbox(
-        label="Decrypted anonymized query that will be sent to ChatGPT", lines=1, interactive=True
+        label="Decrypted anonymized query that will be sent to ChatGPT:", lines=1, interactive=True
     )
 
-    identified_words_output = gr.Dataframe(label="Identified words", visible=False)
+    identified_words_output = gr.Dataframe(label="Identified words:", visible=False)
 
     run_fhe_btn.click(
         run_fhe_fn,
@@ -354,20 +362,21 @@ with demo:
         outputs=[anonymized_text_output, identified_words_output],
     )
 
-    gr.Markdown("<hr />")
+    ########################## ChatGpt Part ##########################
 
-    gr.Markdown("## Secure your communication on ChatGPT with anonymized queries")
+    gr.Markdown("<hr />")
+    gr.Markdown("## Spet 5: Secure your communication on ChatGPT with anonymized queries")
     gr.Markdown(
         """After securely anonymizing the query with FHE, 
-                you can forward it to ChatGPT without any concern for information leakage."""
+        you can forward it to ChatGPT without having any concern about information leakage."""
     )
 
     chatgpt_button = gr.Button("Query ChatGPT")
 
     with gr.Row():
-        chatgpt_response_anonymized = gr.Textbox(label="ChatGPT anonymized response", lines=13)
+        chatgpt_response_anonymized = gr.Textbox(label="ChatGPT's anonymized response:", lines=13)
         chatgpt_response_deanonymized = gr.Textbox(
-            label="ChatGPT non-anonymized response", lines=13
+            label="ChatGPT's non-anonymized response:", lines=13
         )
 
     chatgpt_button.click(
@@ -377,13 +386,9 @@ with demo:
     )
 
     gr.Markdown(
-        """**Please Note**: As this space is intended solely for demonstration purposes, some 
-        private information may be missed the the anonymization algorithm. Please validate the 
+        """**Please note**: As this space is intended solely for demonstration purposes, some 
+        private information may be missed during by the anonymization algorithm. Please validate the 
         following query before sending it to ChatGPT."""
     )
-<<<<<<< HEAD
-=======
-
->>>>>>> 053bec9 (chore: update with marketing remarks)
 # Launch the app
 demo.launch(share=False)