chore: update concrete-ml and smooth UI

app.py

@@ -64,13 +64,12 @@ def keygen():
     # Generate a fresh key
     fhe_api.generate_private_and_evaluation_keys(force=True)
     evaluation_key = fhe_api.get_serialized_evaluation_keys()
-    size_evaluation_key = len(evaluation_key)
 
     # Save evaluation_key in a file, since too large to pass through regular Gradio
     # buttons, https://github.com/gradio-app/gradio/issues/1877
     numpy.save(f"tmp/tmp_evaluation_key_{user_id}.npy", evaluation_key)
 
-    return [list(evaluation_key)[:ENCRYPTED_DATA_BROWSER_LIMIT], size_evaluation_key, user_id]
+    return [list(evaluation_key)[:ENCRYPTED_DATA_BROWSER_LIMIT], user_id]
 
 
 def encode_quantize_encrypt(text, user_id):
@@ -88,20 +87,12 @@ def encode_quantize_encrypt(text, user_id):
     numpy.save(f"tmp/tmp_encrypted_quantized_encoding_{user_id}.npy", encrypted_quantized_encoding)
 
     # Compute size
-    text_size = len(text.encode())
-    encodings_size = len(encodings.tobytes())
-    quantized_encoding_size = len(quantized_encodings.tobytes())
-    encrypted_quantized_encoding_size = len(encrypted_quantized_encoding)
     encrypted_quantized_encoding_shorten = list(encrypted_quantized_encoding)[:ENCRYPTED_DATA_BROWSER_LIMIT]
     encrypted_quantized_encoding_shorten_hex = ''.join(f'{i:02x}' for i in encrypted_quantized_encoding_shorten)
     return (
         encodings[0],
         quantized_encodings[0],
         encrypted_quantized_encoding_shorten_hex,
-        text_size,
-        encodings_size,
-        quantized_encoding_size,
-        encrypted_quantized_encoding_size,
     )
 
 
@@ -175,7 +166,7 @@ with demo:
     <img width=200 src="https://user-images.githubusercontent.com/5758427/197816413-d9cddad3-ba38-4793-847d-120975e1da11.png">
 </p>
 
-<h2 align="center">Machine Learning, Natural Language Processing and Fully Homomorphic Encryption to do Sentiment Analysis on Encrypted data.</h2>
+<h2 align="center">Sentiment Analysis On Encrypted Data Using Homomorphic Encryption.</h2>
 
 <p align="center">
     <a href="https://github.com/zama-ai/concrete-ml"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="https://user-images.githubusercontent.com/5758427/197972109-faaaff3e-10e2-4ab6-80f5-7531f7cfb08f.png">Concrete-ML</a>
@@ -194,10 +185,6 @@ with demo:
     )
 
 
-
-    # FIXME: make it smaller and in the middle
-    # gr.Image("Zama.svg")
-
     gr.Markdown(
         """
         <p align="center">
@@ -232,10 +219,6 @@ with demo:
         visible=False
     )
 
-    size_evaluation_key = gr.Number(
-        label="Size of the evalution key (in bytes):", value=0, interactive=False
-    )
-
     gr.Markdown("# Step 2: Provide a message")
     gr.Markdown("## Client side")
     gr.Markdown(
@@ -247,7 +230,6 @@ with demo:
     b_encode_quantize_text = gr.Button(
         "Encode, quantize and encrypt the text with transformer vectorizer, and send to server"
     )
-    size_text = gr.Number(label="Size of the text (in bytes):", value="0", interactive=False)
 
     with gr.Row():
         encoding = gr.Textbox(
@@ -263,14 +245,6 @@ with demo:
             max_lines=4,
             interactive=False,
         )
-    with gr.Row():
-        size_encoding = gr.Number(label="Size (in bytes):", value=0, interactive=False)
-        size_quantized_encoding = gr.Number(label="Size (in bytes):", value=0, interactive=False)
-        size_encrypted_quantized_encoding = gr.Number(
-            label="Size (in bytes):",
-            value=0,
-            interactive=False,
-        )
 
     gr.Markdown("# Step 4: Run the FHE evaluation")
     gr.Markdown("## Server side")
@@ -295,7 +269,7 @@ with demo:
     labels_sentiment = gr.Label(label="Sentiment:")
 
     # Button for key generation
-    b_gen_key_and_install.click(keygen, inputs=[], outputs=[evaluation_key, size_evaluation_key, user_id])
+    b_gen_key_and_install.click(keygen, inputs=[], outputs=[evaluation_key, user_id])
 
     # Button to quantize and encrypt
     b_encode_quantize_text.click(
@@ -305,10 +279,6 @@ with demo:
             encoding,
             quantized_encoding,
             encrypted_quantized_encoding,
-            size_text,
-            size_encoding,
-            size_quantized_encoding,
-            size_encrypted_quantized_encoding,
         ],
     )
 

requirements.txt

@@ -1,4 +1,4 @@
-concrete-ml==0.4.0
+concrete-ml==0.6.1
 gradio==3.10.0
 pandas==1.4.3
 uvicorn==0.18.2

sentiment_fhe_model/deployment/client.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c0f9430bcbd16f40dfcd8547b7c0053be4a5692f5385206fa5ef42e9d3270242
-size 467
+oid sha256:23ed14c3533c6950f73ea2bbbaff34b7de8bc57703e49fb62da29e37ecf66b87
+size 481

sentiment_fhe_model/deployment/server.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:237a28ea8367363255d3e1324841c54938885c7e4a8fff33bc1a49844c997873
-size 10443
+oid sha256:4342713378f3fc474bc8a3fdd3149e45b94cf79c4ab0cf0c3322b435fcc8cb42
+size 10418