Changes committed

backend/llm_service.py

@@ -2,24 +2,86 @@ import ollama
 import json
 import base64
 
+INVOICE_SCHEMA = {
+    "document_type": None,
+    "invoice_number": None,
+    "invoice_date": None,
+    "due_date": None,
+    "purchase_order_number": None,
+    "vendor": {
+        "name": None,
+        "address": None,
+        "email": None,
+        "phone": None,
+        "gstin": None,
+        "tax_id": None,
+        "website": None
+    },
+    "customer": {
+        "name": None,
+        "address": None,
+        "gstin": None
+    },
+    "amounts": {
+        "subtotal": None,
+        "tax": None,
+        "discount": None,
+        "shipping": None,
+        "round_off": None,
+        "total": None,
+        "amount_paid": None,
+        "balance_due": None,
+        "currency": None
+    },
+    "tax_breakdown": [
+        {
+            "type": None,
+            "rate": None,
+            "amount": None
+        }
+    ],
+    "line_items": [
+        {
+            "line_no": None,
+            "description": None,
+            "product_code": None,
+            "hsn_sac": None,
+            "quantity": None,
+            "unit": None,
+            "unit_price": None,
+            "discount": None,
+            "tax_rate": None,
+            "tax_amount": None,
+            "total": None
+        }
+    ],
+    "payment_information": {
+        "bank_name": None,
+        "account_number": None,
+        "ifsc": None,
+        "upi_id": None
+    },
+    "metadata": {
+        "pages": None,
+        "ocr_confidence": None,
+        "language": None
+    }
+}
+
 def extract_data(text: str = None, image_path: str = None, model_type: str = "text") -> dict:
     """
     Extracts structured data using either Text (Gemma) or Vision (Qwen) models.
     """
     
-    prompt = """
+    prompt = f"""
     You are an expert data extraction assistant. 
-    Extract the following fields from the provided document and return them as a SINGLE VALID JSON OBJECT:
-    - invoice_number (string)
-    - date (string)
-    - vendor_name (string)
-    - total_amount (string)
-    - currency (string)
-    - line_items (list of objects with: description, quantity, unit_price, total)
+    Extract every possible detail from the provided document and return it strictly as a SINGLE VALID JSON OBJECT matching the following schema structure:
+    
+    {json.dumps(INVOICE_SCHEMA, indent=4)}
 
     IMPORTANT: 
-    - Return ONLY the JSON. No markdown formatting, no explanations. 
-    - If a field is not found, use null.
+    - Return ONLY the JSON. No markdown formatting, no explanations, no prefix.
+    - If a field is not found or data is not available, use null.
     """
     
     messages = [{'role': 'user', 'content': prompt}]