feat: add receipt OCR pipeline (refs #69)

Implement receipt-specific OCR extraction for fuel receipts:

- Pattern matching modules for date, currency, and fuel data extraction
- Receipt-optimized image preprocessing for thermal receipts
- POST /extract/receipt endpoint with field extraction
- Confidence scoring per extracted field
- Cross-validation of fuel receipt data
- Unit tests for all pattern matchers

Extracted fields: merchantName, transactionDate, totalAmount,
fuelQuantity, pricePerUnit, fuelGrade

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

ocr/app/models/schemas.py

@@ -93,3 +93,25 @@ class JobSubmitRequest(BaseModel):
     callback_url: Optional[str] = Field(default=None, alias="callbackUrl")
 
     model_config = {"populate_by_name": True}
+
+
+class ReceiptExtractedField(BaseModel):
+    """A single extracted field from a receipt with confidence."""
+
+    value: str | float
+    confidence: float = Field(ge=0.0, le=1.0)
+
+
+class ReceiptExtractionResponse(BaseModel):
+    """Response from receipt extraction endpoint."""
+
+    success: bool
+    receipt_type: str = Field(alias="receiptType")
+    extracted_fields: dict[str, ReceiptExtractedField] = Field(
+        default_factory=dict, alias="extractedFields"
+    )
+    raw_text: str = Field(alias="rawText")
+    processing_time_ms: int = Field(alias="processingTimeMs")
+    error: Optional[str] = None
+
+    model_config = {"populate_by_name": True}