Merge branch 'version_three' of http://23.29.118.76:3000/bolade/Anton_wireframe into version_three

app/services/report_gen.py

@@ -1,11 +1,11 @@
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
+# Import database models and compatibility score service
+from db.models import InvestorTable, ProjectTable
 from jinja2 import Environment, FileSystemLoader
 from playwright.async_api import async_playwright
 
-# Import database models and compatibility score service
-from db.models import InvestorTable, ProjectTable
 from services.compatibility_score import calculate_project_investor_compatibility
 
 
@@ -80,7 +80,7 @@ class ReportGenerator:
                 context["compatibility_score"] = self._calculate_compatibility_score(
                     investor_data, project_data
                 )
-            
+
             context["match_criteria"] = self._generate_match_criteria(
                 investor_data, project_data
             )
@@ -99,8 +99,7 @@ class ReportGenerator:
             "sector": 30,
             "stage": 30,
             "geography": 20,
-            "check_size": 15,
-            "thesis": 5,
+            "check_size": 20,
         }
 
         # Aggregate data from all funds
@@ -169,9 +168,6 @@ class ReportGenerator:
         if check_match:
             score += weights["check_size"]
 
-        # Thesis alignment (simplified)
-        score += weights["thesis"]
-
         return min(score, 100)
 
     def _generate_match_criteria(
@@ -297,8 +293,6 @@ class ReportGenerator:
                 cr["lower"] <= project_val <= cr["upper"] for cr in check_ranges
             )
             check_match = "Perfect" if match_found else "Mismatch"
-        elif project_val > 0:
-            check_match = "Strong"
 
         criteria.append(
             {
@@ -308,19 +302,7 @@ class ReportGenerator:
                 else "N/A",
                 "evidence": check_evidence,
                 "match": check_match,
-                "weight": "15%",
-            }
-        )
-
-        # Thesis criterion
-        thesis = investor_data.get("investment_thesis", [])
-        criteria.append(
-            {
-                "name": "Thesis",
-                "requirement": "Founder-led, ESG focus",
-                "evidence": ", ".join(thesis[:2]) if thesis else "Entrepreneur-led",
-                "match": "Strong",
-                "weight": "5%",
+                "weight": "20%",
             }
         )