[2f988f42] fix(company-explorer): Implement robust quantitative potential and atomic opener generation\n\n- Refactored ClassificationService for two-stage metric extraction (direct area and proxy).- Enhanced MetricParser for targeted value matching and robust number parsing.- Implemented persona-specific 'Atomic Opener' generation using segmented pains.- Fixed logging configuration and Pydantic response models.- Added dedicated debugging script and updated documentation (GEMINI.md, MIGRATION_PLAN.md).

2026-02-21 08:01:07 +00:00
parent 62a924a168
commit 45acbeefb9
13 changed files with 666 additions and 534 deletions
--- a/company-explorer/backend/tests/test_metric_extraction_hospital.py
+++ b/company-explorer/backend/tests/test_metric_extraction_hospital.py
@@ -0,0 +1,82 @@
+import unittest
+import os
+import sys
+from unittest.mock import MagicMock, patch
+
+# Adjust path to allow importing from backend
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+from backend.services.classification import ClassificationService
+from backend.database import Company, Industry, RoboticsCategory, Session
+
+class TestHospitalMetricFinal(unittest.TestCase):
+
+    def setUp(self):
+        self.service = ClassificationService()
+        self.mock_db = MagicMock(spec=Session)
+        
+        self.mock_company = Company(id=8, name="Klinikum Landkreis Erding")
+        self.mock_industry_hospital = Industry(
+            id=1,
+            name="Healthcare - Hospital",
+            scraper_search_term="Anzahl Betten",
+            standardization_logic="wert * 100",
+            primary_category=RoboticsCategory(name="Reinigungsroboter"),
+            secondary_category=RoboticsCategory(name="Serviceroboter"),
+        )
+        self.mock_website_content = "Ein langer Text, der die 100-Zeichen-Prüfung besteht."
+
+    @patch('backend.services.classification.ClassificationService._generate_marketing_opener')
+    @patch('backend.services.classification.ClassificationService._extract_and_calculate_metric_cascade')
+    @patch('backend.services.classification.ClassificationService._find_direct_area')
+    @patch('backend.services.classification.ClassificationService._run_llm_classification_prompt')
+    @patch('backend.services.classification.ClassificationService._get_website_content_and_url')
+    @patch('backend.services.classification.ClassificationService._load_industry_definitions')
+    def test_final_hospital_logic(
+        self, 
+        mock_load_industries, 
+        mock_get_website, 
+        mock_classify, 
+        mock_find_direct_area, 
+        mock_extract_cascade, 
+        mock_generate_opener
+    ):
+        print("\n--- Running Final Hospital Logic Test ---")
+
+        # --- MOCK SETUP ---
+        mock_load_industries.return_value = [self.mock_industry_hospital]
+        mock_get_website.return_value = (self.mock_website_content, "http://mock.com")
+        mock_classify.return_value = "Healthcare - Hospital"
+        mock_find_direct_area.return_value = None # STAGE 1 MUST FAIL
+        
+        proxy_metric_result = {
+            "calculated_metric_name": "Anzahl Betten",
+            "calculated_metric_value": 352.0,
+            "calculated_metric_unit": "Betten",
+            "standardized_metric_value": 35200.0,
+            "standardized_metric_unit": "m²",
+            "metric_source": "wikipedia",
+        }
+        mock_extract_cascade.return_value = proxy_metric_result
+        mock_generate_opener.side_effect = ["Primary Opener", "Secondary Opener"]
+
+        # --- EXECUTION ---
+        updated_company = self.service.classify_company_potential(self.mock_company, self.mock_db)
+
+        # --- ASSERTIONS ---
+        mock_find_direct_area.assert_called_once()
+        mock_extract_cascade.assert_called_once()
+
+        self.assertEqual(updated_company.calculated_metric_name, "Anzahl Betten")
+        self.assertEqual(updated_company.calculated_metric_value, 352.0)
+        self.assertEqual(updated_company.standardized_metric_value, 35200.0)
+        print("   ✅ Metrics from Stage 2 correctly applied.")
+
+        self.assertEqual(updated_company.ai_opener, "Primary Opener")
+        self.assertEqual(updated_company.ai_opener_secondary, "Secondary Opener")
+        print("   ✅ Openers correctly applied.")
+
+        print("\n--- ✅ PASSED: Final Hospital Logic Test. ---")
+
+if __name__ == '__main__':
+    unittest.main()