Enhancements & Best Practices

Add OCR fallback, multi-language support, compliance features, and explore advanced document intelligence patterns. Includes a comprehensive FAQ.

Enhancement 1: OCR Fallback with Tesseract

When GPT-4 Vision is too expensive for high-volume processing, use Tesseract OCR as a cost-effective fallback:

# app/extraction/ocr_fallback.py
import pytesseract
from PIL import Image
import fitz
import logging
from pathlib import Path

logger = logging.getLogger(__name__)


class OCRFallback:
    """Tesseract OCR fallback for when Vision API is too costly."""

    def __init__(self, lang: str = "eng"):
        self.lang = lang

    def ocr_image(self, image_path: str) -> str:
        """Run OCR on an image file."""
        img = Image.open(image_path)
        text = pytesseract.image_to_string(img, lang=self.lang)
        logger.info(f"OCR extracted {len(text)} chars from {Path(image_path).name}")
        return text

    def ocr_pdf_page(self, pdf_path: str, page_num: int = 0, dpi: int = 300) -> str:
        """Convert PDF page to image and run OCR."""
        doc = fitz.open(pdf_path)
        page = doc[page_num]
        mat = fitz.Matrix(dpi / 72, dpi / 72)
        pix = page.get_pixmap(matrix=mat)
        img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
        doc.close()
        return pytesseract.image_to_string(img, lang=self.lang)

    def ocr_pdf_all(self, pdf_path: str) -> str:
        """OCR all pages of a PDF."""
        doc = fitz.open(pdf_path)
        texts = []
        for i in range(len(doc)):
            texts.append(self.ocr_pdf_page(pdf_path, i))
        doc.close()
        return "\n\n".join(texts)

Enhancement 2: Multi-Language Support

# Language detection and multi-language extraction
from langdetect import detect

def detect_language(text: str) -> str:
    """Detect document language. Returns ISO 639-1 code."""
    try:
        return detect(text[:1000])
    except Exception:
        return "en"

# Update vision prompts for detected language
def get_extraction_prompt(lang: str) -> str:
    prompts = {
        "en": "Extract all text and data from this document.",
        "es": "Extrae todo el texto y datos de este documento.",
        "fr": "Extraire tout le texte et les donnees de ce document.",
        "de": "Extrahieren Sie allen Text und alle Daten aus diesem Dokument.",
        "ja": "This document contains Japanese text. Extract all text preserving the original language.",
    }
    return prompts.get(lang, prompts["en"])

Enhancement 3: Compliance and Audit Trail

# app/compliance/audit.py
import json
import hashlib
from datetime import datetime
from pathlib import Path


class AuditLogger:
    """Log all document processing for compliance."""

    def __init__(self, log_dir: str = "data/audit"):
        self.log_dir = Path(log_dir)
        self.log_dir.mkdir(parents=True, exist_ok=True)

    def log_processing(self, job_id: str, filename: str, result: dict, user: str = "system"):
        entry = {
            "timestamp": datetime.utcnow().isoformat(),
            "job_id": job_id,
            "filename": filename,
            "user": user,
            "document_type": result.get("document_type"),
            "method": result.get("method"),
            "fields_extracted": len(result.get("structured_data", {})),
            "file_hash": self._hash_file(filename),
        }
        log_file = self.log_dir / f"{datetime.utcnow().strftime('%Y-%m')}.jsonl"
        with open(log_file, "a") as f:
            f.write(json.dumps(entry) + "\n")

    def _hash_file(self, file_path: str) -> str:
        try:
            with open(file_path, "rb") as f:
                return hashlib.sha256(f.read()).hexdigest()[:16]
        except Exception:
            return "unknown"

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