Update the classifier function

kaanta

@@ -1 +0,0 @@
-Subproject commit 5140abe64a725e0eda4de06ba52a34e31f5ce0f1

transaction_classifier.py

@@ -26,23 +26,25 @@ class TransactionClassifier:
     Classifies bank transactions (from Mono API or manual entry) into tax categories
     """
     
-    # Nigerian bank transaction patterns
+    # Nigerian bank transaction patterns (expanded for better coverage)
     INCOME_PATTERNS = {
         'employment_income': [
             r'\bSALARY\b', r'\bWAGES\b', r'\bPAYROLL\b', r'\bSTIPEND\b',
-            r'\bEMPLOYMENT\b', r'\bMONTHLY PAY\b', r'\bNET PAY\b'
+            r'\bEMPLOYMENT\b', r'\bMONTHLY PAY\b', r'\bNET PAY\b',
+            r'\bGROSS PAY\b', r'\bEARNINGS\b', r'\bSALARY PAYMENT\b'
         ],
         'business_income': [
             r'\bSALES\b', r'\bREVENUE\b', r'\bINVOICE\b', r'\bPAYMENT RECEIVED\b',
-            r'\bCUSTOMER\b', r'\bCLIENT\b'
+            r'\bCUSTOMER\b', r'\bCLIENT\b', r'\bPROJECT\b', r'\bCONSULTING\b',
+            r'\bFREELANCE\b', r'\bCONTRACT\b'
         ],
         'rental_income': [
             r'\bRENT RECEIVED\b', r'\bTENANT\b', r'\bLEASE PAYMENT\b',
-            r'\bPROPERTY INCOME\b'
+            r'\bPROPERTY INCOME\b', r'\bRENTAL\b'
         ],
         'investment_income': [
             r'\bDIVIDEND\b', r'\bINTEREST\b', r'\bINVESTMENT\b',
-            r'\bCOUPON\b', r'\bBOND\b'
+            r'\bCOUPON\b', r'\bBOND\b', r'\bSTOCK\b', r'\bSHARE\b'
         ]
     }
     
@@ -112,11 +114,13 @@ class TransactionClassifier:
         # Classify using pattern matching
         classification = self._classify_by_patterns(narration, tx_type, amount)
         
+        # DISABLED: LLM classification to avoid rate limits
+        # Only use pattern matching for now
         # If confidence is low and RAG is available, use LLM
-        if classification.confidence < 0.7 and self.rag:
-            llm_classification = self._llm_classify(transaction)
-            if llm_classification.confidence > classification.confidence:
-                classification = llm_classification
+        # if classification.confidence < 0.7 and self.rag:
+        #     llm_classification = self._llm_classify(transaction)
+        #     if llm_classification.confidence > classification.confidence:
+        #         classification = llm_classification
         
         # Enrich original transaction
         return {