pitching fix

policy_analyser/analyse.py

@@ -115,11 +115,19 @@ class Health(LOB):
             bad_factor_names = [factor['Factor'] for factor in bad_factors]
             avg_factors = markdown_table_to_json(analysis.split(f'<AVERAGE>')[-1].split(f'</AVERAGE>')[0].replace('## Average Factors', ''))
             avg_factor_names = [factor['Factor'] for factor in bad_factors]
-            if len(bad_factors) < 3 and any(['sum insured' in factor.lower() for factor in bad_factor_names]) \
-                or len(avg_factors) < 3 and any(['sum insured' in factor.lower() for factor in avg_factor_names]):
-                prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Policy : " + self.acko_super_topup
-            else:
+            if len(bad_factors) > 3:
+                prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Super Top up Policy : " + self.acko_policy + '\nNote : Super Top up is an additional policy the customer can buy to enhance the benefits along with their current policy'
+            elif len(avg_factors) > 3:
                 prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Super Top up Policy : " + self.acko_policy + '\nNote : Super Top up is an additional policy the customer can buy to enhance the benefits along with their current policy'
+            elif len(bad_factors) < 3 and any(['sum insured' in factor.lower() for factor in bad_factor_names]):
+                prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Policy : " + self.acko_super_topup
+            elif len(avg_factors) < 3 and any(['sum insured' in factor.lower() for factor in avg_factor_names]):
+                prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Policy : " + self.acko_super_topup
+            # if len(bad_factors) < 3 and any(['sum insured' in factor.lower() for factor in bad_factor_names]) \
+            #     or len(avg_factors) < 3 and any(['sum insured' in factor.lower() for factor in avg_factor_names]):
+            #     prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Policy : " + self.acko_super_topup
+            # else:
+            #     prompt = self.suggest_prompt + "\nCustomer Policy Analysis : " + analysis + "\nAcko's Super Top up Policy : " + self.acko_policy + '\nNote : Super Top up is an additional policy the customer can buy to enhance the benefits along with their current policy'
             response = call_openai(prompt)
             if len(response) > 0:
                 return response