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| 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.") | |
| with gr.Row(): | |
| # First column for input components | |
| with gr.Column(): | |
| code_input = gr.Textbox(lines=10, label="Code Snippet", placeholder="Enter your code here", elem_id="full_width") | |
| compliance_standard = gr.Dropdown( | |
| choices=["GDPR", "HIPAA", "PCI-DSS", "SOC 2", "ISO 27001"], | |
| label="Compliance Standard", | |
| value="GDPR" | |
| ) | |
| analyze_button = gr.Button("Analyze Compliance") | |
| # Second column for output | |
| with gr.Column(): | |
| gr.Markdown("### Compliance Suggestions") # This acts as the label for the output | |
| output_markdown = gr.Markdown() | |
| # Link button to function with inputs and outputs | |
| analyze_button.click(fn=analyze_compliance_stream, inputs=[code_input, compliance_standard], outputs=output_markdown) | |
| # Run the Gradio app | |
| app.launch() |