Update app.py

app.py

@@ -1,11 +1,11 @@
 import os
-import json
+import pandas as pd
 import gradio as gr
 from huggingface_hub import InferenceClient
 from transformers import pipeline
 
 # Install necessary dependencies
-os.system('pip install transformers gradio requests')
+os.system('pip install transformers gradio requests pandas')
 
 # Inference client for chat completion
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
@@ -50,28 +50,16 @@ def evaluate_pci_compliance(audit_data):
     compliance_analysis = respond(audit_data, system_message, max_tokens=1024, temperature=0.7, top_p=0.95)
     return compliance_analysis
 
-# Analyze JSON file input
-def analyze_json_file(file_obj):
-    # Handle both file-like objects and strings properly
-    if isinstance(file_obj, bytes):
-        file_str = file_obj.decode("utf-8")
-    elif isinstance(file_obj, str):
-        file_str = file_obj
-    else:
-        # Assuming it's a file-like object, read the content as a string
-        file_str = file_obj.read().decode("utf-8")
-    
-    # Check if the file content is empty
-    if not file_str.strip():
-        raise ValueError("Uploaded file is empty or not in JSON format.")
-    
+# Analyze CSV file input
+def analyze_csv_file(file_obj):
+    # Read the CSV file into a pandas DataFrame
     try:
-        # Attempt to parse JSON
-        json_data = json.loads(file_str)
-    except json.JSONDecodeError as e:
-        raise ValueError(f"Error decoding JSON: {str(e)}")
+        df = pd.read_csv(file_obj)
+    except Exception as e:
+        raise ValueError(f"Error reading CSV file: {str(e)}")
     
-    audit_data = json.dumps(json_data, indent=2)  # Convert JSON to a formatted string
+    # Convert DataFrame to dictionary for processing
+    audit_data = df.to_dict(orient='records')
     return audit_data
 
 # Custom CSS for the specified theme
@@ -147,22 +135,22 @@ footer {
 # Gradio Interface
 with gr.Blocks(css=custom_css) as demo:
     with gr.Column():
-        gr.Markdown("# GDPR and PCI Compliance Evaluation\n### Upload Audit Data in JSON Format")
-        json_file = gr.File(label="Upload JSON file")
+        gr.Markdown("# GDPR and PCI Compliance Evaluation\n### Upload Audit Data in CSV Format")
+        csv_file = gr.File(label="Upload CSV file")
         
         gdpr_compliance = gr.Textbox(lines=10, placeholder="GDPR Compliance Analysis...", label="GDPR Compliance Analysis", elem_classes="label-hidden")
         pci_compliance = gr.Textbox(lines=10, placeholder="PCI Compliance Analysis...", label="PCI Compliance Analysis", elem_classes="label-hidden")
         
-        def run_compliance_checks(json_file):
-            if json_file is None:
+        def run_compliance_checks(csv_file):
+            if csv_file is None:
                 return "No file uploaded", "No file uploaded"
-            audit_data = analyze_json_file(json_file)
+            audit_data = analyze_csv_file(csv_file)
             gdpr_analysis = evaluate_gdpr_compliance(audit_data)
             pci_analysis = evaluate_pci_compliance(audit_data)
             return gdpr_analysis, pci_analysis
         
         check_compliance_btn = gr.Button("Run Compliance Checks")
-        check_compliance_btn.click(run_compliance_checks, inputs=[json_file], outputs=[gdpr_compliance, pci_compliance])
+        check_compliance_btn.click(run_compliance_checks, inputs=[csv_file], outputs=[gdpr_compliance, pci_compliance])
         
         clear_btn = gr.Button("Clear")
         clear_btn.click(lambda: ("", ""), None, [gdpr_compliance, pci_compliance])