Update main.py

main.py

@@ -141,7 +141,7 @@ def receipt_radar_prompt(raw_text:str)->str:
     system_prompt = f"""Extract information from the following receipt OCR text,Strictly first analyse if the text actually is actually related to a purchase , insurance receipt , travel receipt , hotel receipt or a text having some coupon codes , If it is not a purchase or contains a coupon code then just return null strictly  , and return a JSON object with these exact keys: brand, total_cost, location, purchase_category, brand_category, Date, currency, filename, payment_method, metadata.
     Rules:
     1. For total_cost, use the highest monetary value in the text.
-    2. For brand_category, choose the closest match from: ["Fashion and Apparel", "Jewelry and Watches", "Beauty and Personal Care", "Automobiles", "Real Estate", "Travel(it may contain reciepts of airlines , trains , taxi ,cruise ,etc)", "Hospitality(it will include reciepts of Hotels (stays) , restaurants , cafe's , bar's , Accommodation Services , Beverages Services (don't include food delivery service in hospitality))","Food Delivery Services(like swiggy , zomato,eatsure and any other you can analyse from receipt text)", "Home and Lifestyle", "Technology and Electronics", "Sports and Leisure", "Art and Collectibles", "Health and Wellness", "Stationery and Writing Instruments", "Children and Baby", "Pet Accessories", "Financial Services", "Insurance"]
+    2. For brand_category, choose the closest match from: ["Fashion and Apparel", "Jewelry and Watches", "Beauty and Personal Care", "Automobiles", "Real Estate", "Travel(it may contain reciepts of airlines , trains , taxi ,cruise ,etc)", "Hospitality(it will include reciepts of Hotels (stays) , restaurants , cafe's , bar's , Accommodation Services , Beverages Services (don't include food delivery service in hospitality))","Food Delivery Services(like swiggy , zomato,eatsure and any other you can analyse from receipt text)", "Home and Lifestyle", "Technology and Electronics", "Sports and Leisure", "Art and Collectibles", "Health and Wellness", "Stationery and Writing Instruments", "Children and Baby", "Pet Accessories","Insurance","Coupons(This may include Discounted Offers,Promo Coupons,Coupon Codes,Voucher Deals,Exclusive Discounts,Special Offers,Couponized Receipts,Promo Receipts,Coupon Tags,Discount Emails)"]
     3. Format Date as dd-mm-yyyy.Strictly return the date in the format dd-mm-yyyy.
     4. Check if the text includes the purchaser's name, receipt or transaction ID, relevant dates, amount paid, service details (insurance, travel, or hotel), and issuer information to verify if it's a valid insurance, travel, or hotel receipt. If you find that its just a promotion email ,don't assum its a travel , insurance or hotel receipt.
     4. metadata: For insurance receipts extract the data points given in the JSON and return the JSON with structure: \n """ + insurance_response_structure + """