Create app.py

app.py

@@ -0,0 +1,50 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Initialize the Hugging Face Inference Client
+client = InferenceClient()
+
+# Function to interact with the Qwen2.5-32B model and analyze code for compliance
+def analyze_compliance(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
+    )
+
+    # Collect the output from the stream
+    compliance_suggestions = ""
+    for chunk in stream:
+        compliance_suggestions += chunk.choices[0].delta.content
+
+    return compliance_suggestions
+
+# Create Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("## Legal and Compliance Code Advisor")
+    gr.Markdown("Analyze your code for legal compliance standards (e.g., GDPR, HIPAA) and receive modification suggestions.")
+
+    with gr.Row():
+        code_input = gr.Textbox(lines=10, label="Code Snippet", placeholder="Enter your code here")
+        compliance_standard = gr.Dropdown(
+            choices=["GDPR", "HIPAA", "PCI-DSS", "SOC 2", "ISO 27001"],
+            label="Compliance Standard",
+            value="GDPR"
+        )
+        output_text = gr.Textbox(label="Compliance Suggestions", placeholder="Compliance suggestions will appear here...")
+
+    analyze_button = gr.Button("Analyze Compliance")
+    analyze_button.click(fn=analyze_compliance, inputs=[code_input, compliance_standard], outputs=output_text)
+
+# Run the Gradio app
+app.launch()