update

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from blindbox.requests import SecureSession
 
 DEMO_SERVER = "4.208.9.167:80"
+text = "<h1 style='text-align: center; color: white;'>🎅 SantaCoder with <span style='color: #f0ba2d;'>BlindBox:</span> Private Code Generation </h1><p style='text-align: left; 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. The user input is <a style='color:  #f0ba2d;', href='https://blindbox.mithrilsecurity.io/en/latest/docs/getting-started/confidential_computing/'>protected during computation</a> by leveraging state-of-the-art <a style='color:  #f0ba2d;', href='https://www.ibm.com/topics/confidential-computing'> Confidental Computing technologies.</a> This means that data sent to Santacoder model is never accessible to the service provider during computation- private code remains private!</p><p style='text-align: left; 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!</a></p><p style='text-align: left; color: white;'>⚠️ BlindBox is still under development. Do not test with production data!</p>"
 bullets = "<ul><li style='color: white;'>✅ Connection verified by attestation</li><li style='color: white;'>✅ Application deployed on Confidential VM</li></ul><p style='color: white;'>Features coming soon:</p><ul><li style='color: white;'>⌛ TLS</li><li style='color: white;'>⌛ Network isolation</li></ul>"
 
 def run_query( server, prompt):
@@ -20,13 +21,10 @@ def run_query( server, prompt):
     except Exception as err:
         return(f"⛔ Query failed!\n{err}")
 
-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: left; 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. The user input is <a style='color:  #f0ba2d;', href='https://blindbox.mithrilsecurity.io/en/latest/docs/getting-started/confidential_computing/'>protected during computation.</a></p>")
-    gr.Markdown("<p style='text-align: left; 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!</a></p>")
-    gr.Markdown("<p style='text-align: left; color: white;'>⚠️ BlindBox is still under development. Do not test with production data!</p>")
+demo = gr.Blocks(css=".gradio-container { background-color: #20233fff;} .app.svelte-1mya07g.svelte-1mya07g {max-width: 1100px !important;}")
+with demo:
+    gr.Markdown(value=text)
     gr.Markdown(value=bullets)
-
     _, 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):")