fix: reduce hallucination in receipt extraction — conservative prompts + date injection

Two sources of hallucinated values in receipt parsing:

1. The LLM extraction prompt had no explicit "don't guess" constraint, so
   when Tesseract produced garbled OCR text the LLM substituted plausible-
   looking values (wrong vendor names, wrong totals) instead of returning
   safe defaults.

2. The date field asked the LLM to extract the date from the OCR text even
   when date_hint (from the filename timestamp, e.g. 20260509_180857.jpg)
   was already available — a reliable signal that was being ignored.

expenses_agent._parse_receipt_text:
- LLM path: new prompt leads with "copy values EXACTLY, do NOT guess or
  infer"; adds "if OCR looks corrupted, return safe default rather than
  a more logical value"; injects date_hint directly as an authoritative
  value when available so the LLM never needs to extract the date.
- Vision fast path: normalise "null" string for date the same way as time;
  prefer date_hint over a null date returned by the vision model.

receipt_parser._ocr_image_vision:
- Vision prompt now leads with the same "copy exactly, do not guess"
  constraint and explicitly accepts null for date/time when not clearly
  visible, matching the conservative tone of the LLM extraction prompt.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

agent_service/agents/expenses_agent.py

@@ -360,13 +360,17 @@ class ExpensesAgent(BaseAgent):
                     # Map the vision category label → expense product name
                     product_name = self._match_category(
                         data.get('category', ''), expense_products or [])
-                    # Vision model sometimes returns the string "null" instead of JSON null
+                    # Vision model sometimes returns the string "null" instead
+                    # of JSON null — normalise both fields.
+                    _NULL = (None, 'null', 'None', '')
                     raw_time = data.get('time')
-                    time_val = None if raw_time in (None, 'null', 'None', '') else str(raw_time)
+                    time_val = None if raw_time in _NULL else str(raw_time)
+                    raw_date = data.get('date')
+                    date_val = None if raw_date in _NULL else str(raw_date)
                     return {
                         'vendor': str(data.get('vendor') or filename),
                         'amount': float(data.get('amount', 0.0)),
-                        'date': str(data.get('date') or date_hint or today),
+                        'date': date_val or date_hint or today,
                         'time': time_val,
                         'product_name': product_name,
                     }
@@ -398,19 +402,38 @@ class ExpensesAgent(BaseAgent):
                 receipt_text = stripped[:1500] + '\n[...]\n' + stripped[-1500:]
             else:
                 receipt_text = stripped
+
+            # When the filename carries a reliable timestamp, inject it directly
+            # so the LLM doesn't try to read (and potentially misread) the date
+            # from garbled OCR text.
+            if date_hint:
+                date_instruction = (
+                    f'Use exactly "{date_hint}" — this date was read from the file '
+                    f'timestamp and is more reliable than the OCR text.'
+                )
+            else:
+                date_instruction = (
+                    f'Extract from the receipt text in YYYY-MM-DD format; '
+                    f'use {today} only if no date is visible.'
+                )
+
             prompt = (
-                'Extract expense details from the following receipt text. '
+                'You are a receipt data extractor. '
+                'Copy values EXACTLY as they appear in the text — '
+                'do NOT guess, infer, "correct" OCR errors, or invent plausible values.\n\n'
                 'Return ONLY valid JSON with these keys:\n'
-                '"vendor" (string, merchant or restaurant name),\n'
+                f'"vendor": merchant name exactly as printed; '
-                '"amount" (number — the FINAL total the customer paid; '
+                f'empty string "" if you cannot find it clearly,\n'
-                'look for a line explicitly labeled "Total", "Grand Total", "Amount Due", or "Balance Due"; '
+                f'"amount": the FINAL total — find a line labeled "Total", "Grand Total", '
-                'do NOT use subtotal, tax, tip, or individual line items; '
+                f'"Amount Due", or "Balance Due"; copy the number exactly as written; '
-                'if the label is ambiguous choose the bottom-most total on the receipt; '
+                f'never use subtotal, tax, or tip lines; '
-                'return 0 if no clear total is found),\n'
+                f'return 0 if no clearly labeled final total is present,\n'
-                f'"date" (string YYYY-MM-DD, use {date_hint or today} if not found in text),\n'
+                f'"date": {date_instruction}\n'
-                '"time" (string HH:MM in 24-hour format — the transaction time printed on the receipt; '
+                f'"time": transaction time HH:MM (24-hour) exactly as printed, or null,\n'
-                'null if not present),\n'
+                f'"product_name": best match from [{product_list}] or "".\n\n'
-                f'"product_name" (string, pick the best match from [{product_list}] or empty string).\n\n'
+                f'IMPORTANT: This text came from OCR and may contain garbled characters. '
+                f'If a value looks corrupted, return the safe default (0 / "" / null) '
+                f'rather than substituting a "more logical" value.\n\n'
                 f'Receipt text:\n{receipt_text}\n\nJSON only:'
             )
         try:

agent_service/tools/receipt_parser.py

@@ -113,18 +113,24 @@ def _ocr_image_vision(data: bytes, filename: str, ollama_url: str, model: str) -
             messages=[{
                 'role': 'user',
                 'content': (
-                    'This is a photo of a receipt. Extract these fields:\n'
+                    'You are a receipt data extractor. '
-                    '- vendor: the store or restaurant name\n'
+                    'Read this receipt image and extract the following fields. '
-                    '- amount: the FINAL total the customer paid. Look for a line '
+                    'Copy values EXACTLY as printed — do NOT guess, infer, or '
-                    'labeled "Total", "Grand Total", "Amount Due", or "Balance Due". '
+                    'invent values you cannot clearly see.\n\n'
-                    'Do NOT use subtotal, tax, or tip. Return 0 if you cannot find '
+                    'Fields to extract:\n'
-                    'a clear final total.\n'
+                    '- vendor: the store or restaurant name exactly as printed; '
-                    '- date: transaction date in YYYY-MM-DD format\n'
+                    'empty string if not clearly visible\n'
-                    '- time: transaction time in HH:MM 24-hour format, or null\n'
+                    '- amount: the FINAL total the customer paid; find a line '
-                    '- category: one word describing the expense type — one of: '
+                    'labeled "Total", "Grand Total", "Amount Due", or "Balance Due"; '
-                    'meals, fuel, hotel, office, transport, other\n\n'
+                    'copy the number exactly; do NOT use subtotal, tax, or tip; '
+                    'return 0 if no clearly labeled final total is visible\n'
+                    '- date: transaction date in YYYY-MM-DD format; '
+                    'null if not clearly visible\n'
+                    '- time: transaction time in HH:MM 24-hour format; '
+                    'null if not clearly visible\n'
+                    '- category: one of: meals, fuel, hotel, office, transport, other\n\n'
                     'Return ONLY a valid JSON object, no commentary, no markdown:\n'
-                    '{"vendor":"...","amount":0.00,"date":"YYYY-MM-DD",'
+                    '{"vendor":"...","amount":0.00,"date":"YYYY-MM-DD or null",'
                     '"time":"HH:MM or null","category":"..."}'
                 ),
                 'images': [data],