Update main.py

main.py

@@ -70,7 +70,7 @@ def receipt_radar_prompt(raw_text:str)->str:
     system_prompt = f"""Extract information from the following receipt OCR text 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"]
     3. Format Date as dd-mm-yyyy.Strictly return the date in the format dd-mm-yyyy.
     4. metadata: For insurance receipts extract the data points given in the JSON and return the JSON with structure: \n """ + insurance_response_structure + """
     5.metadata : For travel receipts(flight ,bus,train) extract these data points as a JSON object exactly""" + travel_response_structure + """