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):
    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")
    message = "\n\n✅ Secure query succesful"
    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]
            cleaned = cleaned.replace('\\', '')
            return(cleaned + message)
    except Exception as err:
        return(f"⛔ Query failed!\n{err}")

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):")
        
        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"
        )
        trigger = gr.Button(label="Run query")
    with gr.Column():
        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/laura-images/docs/assets/contact-us.png?raw=true.png' alt='contact' style='display: block; margin: auto; max-width: 600px;'>")
if __name__ == "__main__":
    demo.launch()