updated gradio

app.py

@@ -4,45 +4,39 @@ from blindbox.requests import SecureSession
 DEMO_SERVER = "4.208.9.167:80"
 
 def run_query( server, prompt):
-    if prompt == None or server == None:
-        return("⛔ Error: please select an option for stages 1 and 2")
-    if len(prompt) == 0 or len(server) == 0:
-        return("⛔ Error: please select an option for stages 1-3")
-    if server != "Authentic and verified confidential VM server":
+    if server == "Non-confidential VM server":
         return ("⛔ Error: you can only connect to an application running on a Confidential VM")
     POLICY = "./cce_policy.txt"
+    if prompt == None:
+        return ("⛔ Error: please provide input code")
     try:
         with SecureSession(f"http://{DEMO_SERVER}", POLICY) as secure_session:
             res = secure_session.post(endpoint="/generate", json={"input_text": prompt})
             cleaned = res.text.replace('\\n', '\n').split('\n\n')[0].split(':"')[1]
-            return("✅ Query successful\n" + cleaned)
+            cleaned = cleaned.replace('\\', '')
+            return(cleaned + "\n\n✅ Input is end-to-end protected\nUser data is protected by a highly isolated and secure environment during runtime, meaning we, as the service providers, cannot access your input!")
     except Exception as err:
         return(f"⛔ Query failed!\n{err}")
 
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("<h1><center>🔒Confidential code generation with BlindBox and Santacoder</center></h1>")
-    gr.Markdown("<p>This is the demo for our article on deploying code generation LLM models with BlindBox: <b>AI-assisted code generation with privacy guarantees: Securely deploy SantaCoder with BlindBox</b><br>You can view the article  <a href='https://blog-mithril-security.ghost.io/ai-assisted-code-generation-with-privacy-guarantees-securely-deploy-santacoder-with-blindbox'>here!</a></p>")
-    gr.Markdown("<p>You can use this demo to send a function definition to BigCode's open-source Santacoder model and get back an auto-completed function.</p>")
-    gr.Markdown("<p>The model is deployed within a highly-isolated Trusted Execution Environment, meaning that we, as the service provider, have no access to the data sent to this model!</p>")
-    gr.Markdown("<p>You can see how we deployed the model by checking out the integration section of our <a href='https://blindbox.mithrilsecurity.io/en/latest/docs/how-to-guides/santacoder/'>documentation!</p>")
-    gr.Markdown("><h3>Step 1: Check that we are connecting to an authentic confidential VM")
-    gr.Markdown("<p>This first option allows you to choose whether to connect to the Santacoder application deployed with BlindBox on a verified confidential VM or the same application deployed on a dummy server which is not within a confidential VM. This demonstrates how BlindBox blocks requests to non-authentic confidential VMs!</p>")
-    with gr.Column():
-        server = gr.Radio(
-        ["Authentic and verified confidential VM server", "Unauthentic dummy server"], label="Select the server you want to connect to"
-        )
-    gr.Markdown("><h3>Step 2: Select your prompt</h3>")
-    gr.Markdown("<p>Select between the following prompt examples we provide.</p>")
-    with gr.Column():
-        prompt = gr.Radio(
-        ["def sum(x, y):", "def print_name(name):", "def hello_world():", "def square_root(nbr):"], label="Select your user prompt"
+with gr.Blocks(css=".gradio-container {background-color: #20233fff}") as demo:
+    gr.Markdown("<h1 style='text-align: center; color: white;'>🎅 SantaCoder with <span style='color: #f0ba2d;'>BlindBox:</span> Private Code Generation </h1>")
+    
+    gr.Markdown("<p style='text-align: center; color: white;'>This is our demo for our <a style='color: #f0ba2d;', href='https://blog-mithril-security.ghost.io/ai-assisted-code-generation-with-privacy-guarantees-securely-deploy-santacoder-with-blindbox'>article</a> on deploying code generation LLM models with BlindBox")
+    gr.Markdown("<p style='text-align: center; color: white;'>The user input is <span style='color: #f0ba2d;'>end-to-end protected</span> with the user prompt processed in a highly isolated and secure environment</p>")
+    gr.Markdown("<p style='text-align: center; color: white;'>You can see how we deployed the model in the integration section of our <a style='color:  #f0ba2d;', href='https://blindbox.mithrilsecurity.io/en/latest/docs/how-to-guides/santacoder/'>documentation!</p>")
+    _, colum_2, _ = gr.Column(scale=1), gr.Column(scale=6), gr.Column(scale=1)
+    with colum_2:
+        prompt = gr.Code(lines=3, language="python", label="Input code", value="def hello_name(name):")
+        
+        with gr.Accordion("Advanced settings", open=False):
+            server = gr.Radio(
+        ["Authentic confidential VM server", "Non-confidential VM server"], label="Test connections to secure and insecure servers"
         )
-    gr.Markdown("><h3>Step 3: Query the Santacoder model</h3>")
-    with gr.Column():
-        trigger = gr.Button("Test query")
+        trigger = gr.Button(label="Run query")
     with gr.Column():
-        output = gr.Textbox(placeholder="Output", label="See the output of your query here")
+        output = gr.Textbox(placeholder="Output", label="Output")
     trigger.click(fn=run_query, inputs=[server, prompt], outputs=output)
+    gr.HTML(label="Contact", value="<img src='https://github.com/mithril-security/blindbox/blob/main/docs/assets/logo.png?raw=true.png' alt='contact' style='display: block; margin: auto; max-width: 200px;'>")
 
 if __name__ == "__main__":
     demo.launch()