Update backend.py

backend.py

@@ -4,7 +4,7 @@ import requests
 import html  # For escaping HTML characters
 from bs4 import BeautifulSoup
 import pandas as pd  # Added pandas for Excel export
-from openai import OpenAI 
+from openai import OpenAI
 
 # Initialize OpenAI API with Nvidia's Llama model
 client = OpenAI(
@@ -87,13 +87,59 @@ def generate_testcases(user_story):
         return []
 
 def export_test_cases(test_cases):
+    """
+    Exports the test cases to an Excel file with specific columns:
+    - Test Case
+    - Preconditions
+    - Steps
+    - Expected Result
+    
+    :param test_cases: A list of test case dictionaries or raw text.
+    :return: Bytes of the Excel file.
+    """
     if not test_cases:
         return "No test cases to export."
 
-    # Use pandas to export the test cases to Excel
+    # Define the structure of the Excel file
+    formatted_test_cases = []
+    
+    for case in test_cases:
+        # Assuming each test case is a dictionary with 'test_case' content or similar
+        test_case_content = case.get('test_case', '')
+        
+        # Split the content into separate sections (you might need to adjust based on actual output structure)
+        lines = test_case_content.split('\n')
+        test_case = ""
+        preconditions = ""
+        steps = ""
+        expected_result = ""
+        
+        for line in lines:
+            if "Preconditions" in line:
+                preconditions = line.replace("Preconditions:", "").strip()
+            elif "Steps" in line:
+                steps = line.replace("Steps:", "").strip()
+            elif "Expected Result" in line:
+                expected_result = line.replace("Expected Result:", "").strip()
+            else:
+                # Default to putting the first part as the "Test Case"
+                if not test_case:
+                    test_case = line.strip()
+        
+        # Append to formatted test cases list
+        formatted_test_cases.append({
+            'Test Case': test_case,
+            'Preconditions': preconditions,
+            'Steps': steps,
+            'Expected Result': expected_result
+        })
+    
+    # Convert the list of dictionaries into a DataFrame
+    df = pd.DataFrame(formatted_test_cases)
+    
+    # Create an Excel file using pandas
     output = io.BytesIO()
-    df = pd.DataFrame(test_cases)
-    df.to_excel(output, index=False, engine='openpyxl')  # Use 'openpyxl' engine
-    output.seek(0)  # Rewind the buffer
-
-    return output.getvalue()
+    df.to_excel(output, index=False, engine='openpyxl')  # Export to Excel without index
+    output.seek(0)  # Rewind the buffer to the beginning
+    
+    return output.getvalue()