app.py

import gradio as gr
from huggingface_hub import InferenceClient

# Initialize the Hugging Face Inference Client
client = InferenceClient()

# Function to stream the compliance suggestions as they are generated
def analyze_compliance_stream(code, compliance_standard):
    prompt = f"Analyze the following code for {compliance_standard} compliance and suggest modifications or refactoring to meet the guidelines:\n\n{code}"
    
    messages = [
        {"role": "user", "content": prompt}
    ]

    # Create a stream to receive generated content
    stream = client.chat.completions.create(
        model="Qwen/Qwen2.5-Coder-32B-Instruct",
        messages=messages,
        temperature=0.5,
        max_tokens=1024,
        top_p=0.7,
        stream=True
    )

    # Stream content as it is generated
    compliance_suggestions = ""
    for chunk in stream:
        compliance_suggestions += chunk.choices[0].delta.content
        yield compliance_suggestions  # Yield incremental content to display immediately

# Create Gradio interface with the modified layout
with gr.Blocks() as app:
    gr.Markdown("## Code Compliance Advisor")
    gr.Markdown("Analyze your code for legal compliance and security standards (e.g., GDPR, HIPAA) and receive actionable suggestions.")

    # Full-width text area for code input
    code_input = gr.Textbox(lines=10, label="Code Snippet", placeholder="Enter your code here", elem_id="full_width")

    # Dropdown for selecting compliance standard
    compliance_standard = gr.Dropdown(
        choices=["GDPR", "HIPAA", "PCI-DSS", "SOC 2", "ISO 27001"],
        label="Compliance Standard",
        value="GDPR"
    )

    # Button to trigger analysis
    analyze_button = gr.Button("Analyze Compliance")

    # Result display in Markdown to HTML
    output_html = gr.HTML(label="Compliance Suggestions")

    # Link button to function with inputs and outputs
    analyze_button.click(fn=analyze_compliance_stream, inputs=[code_input, compliance_standard], outputs=output_html, every=0.1)

# Run the Gradio app
app.launch()