Update AI matcher to return only the best match with confidence score

ai_matcher.py

@@ -13,27 +13,30 @@ class AIMatcher:
         matches = []
         
         for receipt in receipts:
-            # Get ALL potential matches for this receipt, not just the best one
-            receipt_matches = self._find_all_matches(receipt, transactions)
-            matches.extend(receipt_matches)
+            # Get the BEST match for this receipt (highest confidence score)
+            best_match = self._find_best_match(receipt, transactions)
+            if best_match:
+                matches.append(best_match)
         
         return sorted(matches, key=lambda x: x.confidence_score, reverse=True)
     
-    def _find_all_matches(self, receipt: Receipt, transactions: List[Transaction]) -> List[Match]:
-        """Find ALL potential matches for a receipt, not just the best one"""
+    def _find_best_match(self, receipt: Receipt, transactions: List[Transaction]) -> Match:
+        """Find the BEST match for a receipt (highest confidence score)"""
         candidates = self._filter_candidates(receipt, transactions)
         if not candidates:
-            return []
+            return None
             
-        matches = []
+        best_match = None
+        highest_score = 0
         
         for transaction in candidates:
             score, reason = self._calculate_match_score(receipt, transaction)
-            # Include ALL matches regardless of score - let the user decide
-            match = Match(receipt, transaction, score, reason)
-            matches.append(match)
+            # Keep the match with the highest score, regardless of how low it is
+            if score > highest_score:
+                highest_score = score
+                best_match = Match(receipt, transaction, score, reason)
         
-        return matches
+        return best_match
     
     def _filter_candidates(self, receipt: Receipt, transactions: List[Transaction]) -> List[Transaction]:
         # Return MOST transactions - let the AI decide on scoring
@@ -68,22 +71,24 @@ class AIMatcher:
         - Amount difference: ${amount_diff} ({amount_percent_diff:.1f}%)
         - Vendor comparison: "{receipt.vendor}" vs "{transaction.vendor}"
         
-        IMPORTANT: Score ALL potential matches, even imperfect ones. The score should reflect how likely this is a match:
+        Score this potential match based on how likely it is the correct match:
         
         - Perfect matches (same vendor, amount, date): 0.95-1.0
         - High confidence (minor differences): 0.8-0.94
         - Medium confidence (moderate differences): 0.6-0.79
         - Low confidence (significant differences): 0.4-0.59
         - Very low confidence (major differences): 0.2-0.39
-        - No meaningful similarity: 0.0-0.19
+        - Minimal similarity: 0.1-0.19
+        - No meaningful similarity: 0.0-0.09
         
         Examples:
         - Same vendor, same amount, 11 days apart: 0.7-0.8
         - Similar vendor name, same amount, same date: 0.8-0.9
         - Same vendor, 10% amount difference, same date: 0.6-0.7
         - Different vendor, same amount, same date: 0.3-0.4
+        - Completely different vendor, amount, date: 0.1-0.2
         
-        Consider vendor name similarity, amount accuracy, and date proximity. Even imperfect matches should get reasonable scores if there's any meaningful similarity.
+        Consider vendor name similarity, amount accuracy, and date proximity. Score based on overall likelihood this is the correct match.
         
         Return only: score|reason
         """