added questions generator

test.py

@@ -1,42 +1,72 @@
-from src.services.sop_generator import  SopGeneratorExecutive
-from src.utils.document_loader import load_document
-from src.services.document_parser import DocumentParser
-from src.services.sop_generator import SopGeneratorExecutive
-file_path = r"C:\Users\User\Desktop\Blessing_AI\MKD\test_erp_ai\erp_ai\test\erp_ai\data\raw\document.doc"
-docs = load_document(file_path)
+import json
+from src.services.questions_generator import QuestionsGenerator
 
-
-if __name__ == "__main__":
-    SOP = DocumentParser()
-    so = SopGeneratorExecutive()
-    referencs_roles = ["AR Director "]
-    workers_list = [
-    {
-      
-        "position": "AR dIRECTOR ",
-        "role": "Developer",
-        "department": "IT"
-    },
-    {
-        "name": "Jane Smith",
-        "position": "Project Manager",
-        "role": "Manager",
-        "department": "IT"
-    }
-]
-
-    departments_and_roles = SOP.extract_sops_for_workers_by_department(docs,workers_list)
-    # Prepare extracted roles (only managers)
-    '''extracted_managers = []
-    for department in departments_and_roles['departments']:
-        extracted_managers.extend([
+# Mocking the SOPs input as described in your example
+mock_sops_input = {
+    "sops": {
+        "departments": [
             {
-                'name': manager['name'],
-                'position': manager.get('position', 'Unknown Position'),
-                'role': manager.get('role', 'Unknown Role')  # PRP or SRP classification
+                "name": "Accounts Receivable",
+                "workers": [
+                    {
+                        "name": "Angela Lewis",
+                        "position": "AR Director",
+                        "sops": {
+                            "must": [],
+                            "shall": [],
+                            "will": []
+                        }
+                    },
+                    {
+                        "name": "Jamie Vega",
+                        "position": "AR Supervisor",
+                        "sops": {
+                            "must": [
+                                "Provide escalation information to the AR Director if additional escalations are needed."
+                            ],
+                            "shall": [],
+                            "will": []
+                        }
+                    },
+                    {
+                        "name": "Jessica Merzougui",
+                        "position": "AR Supervisor",
+                        "sops": {
+                            "must": [
+                                "Provide escalation information to the AR Director if additional escalations are needed."
+                            ],
+                            "shall": [],
+                            "will": []
+                        }
+                    },
+                    {
+                        "name": "Deniece Santos",
+                        "position": "AR Analyst",
+                        "sops": {
+                            "must": [],
+                            "shall": [],
+                            "will": []
+                        }
+                    }
+                ]
             }
-            for manager in department['managers']
-        ])'''
+        ]
+    }
+}
 
-    print(departments_and_roles)
+# Defining the full input data including additional parameters
+input_data = {
+    "sops": json.dumps(mock_sops_input),  # Convert SOPs to JSON string format
+    "assessment_type": "progress",        # Set the assessment type
+    "frequency_type": "weekly",           # Set the frequency type (daily, weekly, etc.)
+    "duration": 4                         # Set the duration (number of frequency cycles, e.g., 4 weeks)
+}
 
+# Initialize the QuestionsGenerator
+generator = QuestionsGenerator()
+
+# Invoke the generate_questions method with the mock input
+questions_response = generator.generate_questions(input_data)
+
+# Print the generated questions response
+print(json.dumps(questions_response, indent=4))