fix: merge main branch and renumber migration 037→040

Resolve all merge conflicts between our automation feature branch and current main (v0.163.0, 920 commits ahead). Conflicts resolved: - app/api/__init__.py: add automation_router alongside main's new routers (classification_rules, qr_auth, sessions, system_reset) - app/config.py: add main's new settings (dropbox_use_global_credentials, factory_reset_on_startup, enable_factory_reset) - app/models.py: add main's new models (ClassificationRuleModel, UserSession, QRLoginChallenge, SharePoint integration type) - app/utils/settings_service.py: merge automation_hooks_enabled with main's new metadata entries - docs/API.md: merge automation API docs with main's classification rules docs - docs/ConfigurationGuide.md: add factory reset settings - tests/conftest.py: import both AutomationHook and new main models Migration renumbered: - 037_add_automation_hooks → 040_add_automation_hooks - down_revision: 039_add_classification_rules (was 036_add_document_translation_fields) - Chain: 036 → 037 → 038 → 039 → 040 (automation hooks) For all non-automation files with conflicts, main's version was taken since our branch did not modify those files (conflicts were from a stale prior merge). Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com> Agent-Logs-Url: https://github.com/christianlouis/DocuElevate/sessions/cb62f012-3b69-4415-835e-3857ce3e9f45
2026-03-20 23:54:04 +00:00
parent d1ebac74a1
commit e518bce922
153 changed files with 16306 additions and 922 deletions
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+"""
+Rule-based document classification engine.
+
+Provides pre-built categories and a rule matcher that classifies documents
+using filename patterns, content keywords, and metadata fields.  Custom
+rules stored in the database are evaluated alongside the built-in defaults.
+
+Usage::
+
+    from app.utils.classification_rules import classify_document
+
+    result = classify_document(
+        filename="2024-03-01_Invoice_Acme.pdf",
+        text="Invoice total: $1,234.56",
+        metadata={"absender": "Acme Corp"},
+        custom_rules=custom_rules_from_db,
+    )
+    # result -> ClassificationResult(category="invoice", confidence=85, matched_rules=[...])
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+from dataclasses import dataclass, field
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+# ---------------------------------------------------------------------------
+# Pre-built categories
+# ---------------------------------------------------------------------------
+
+#: Canonical category names recognized by the system.  Users may also define
+#: their own categories via custom rules.
+BUILTIN_CATEGORIES: dict[str, str] = {
+    "invoice": "Invoice",
+    "contract": "Contract",
+    "receipt": "Receipt",
+    "letter": "Letter",
+    "report": "Report",
+    "bank_statement": "Bank Statement",
+    "tax_document": "Tax Document",
+    "insurance": "Insurance Document",
+    "payslip": "Payslip",
+    "unknown": "Unknown",
+}
+
+# ---------------------------------------------------------------------------
+# Rule type constants
+# ---------------------------------------------------------------------------
+
+RULE_TYPE_FILENAME = "filename_pattern"
+RULE_TYPE_CONTENT = "content_keyword"
+RULE_TYPE_METADATA = "metadata_match"
+
+
+# ---------------------------------------------------------------------------
+# Data classes
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class ClassificationRule:
+    """A single classification rule."""
+
+    name: str
+    category: str
+    rule_type: str  # filename_pattern | content_keyword | metadata_match
+    pattern: str  # regex for filename, keyword(s) for content, "field=value" for metadata
+    priority: int = 0  # higher = evaluated first
+    case_sensitive: bool = False
+
+    def __post_init__(self) -> None:
+        if self.rule_type not in (RULE_TYPE_FILENAME, RULE_TYPE_CONTENT, RULE_TYPE_METADATA):
+            raise ValueError(f"Invalid rule_type: {self.rule_type!r}")
+
+
+@dataclass
+class MatchedRule:
+    """Records which rule matched and why."""
+
+    rule_name: str
+    rule_type: str
+    category: str
+    confidence: int
+
+
+@dataclass
+class ClassificationResult:
+    """The outcome of running the classification engine on a document."""
+
+    category: str
+    confidence: int  # 0 – 100
+    matched_rules: list[MatchedRule] = field(default_factory=list)
+
+
+# ---------------------------------------------------------------------------
+# Built-in rules
+# ---------------------------------------------------------------------------
+
+BUILTIN_RULES: list[ClassificationRule] = [
+    # ── Invoice ───────────────────────────────────────────────────────────
+    ClassificationRule("builtin_invoice_filename", "invoice", RULE_TYPE_FILENAME, r"(?i)invoice|rechnung|facture"),
+    ClassificationRule(
+        "builtin_invoice_content",
+        "invoice",
+        RULE_TYPE_CONTENT,
+        "invoice number|invoice total|amount due|rechnung|rechnungsnummer|total amount|bill to",
+    ),
+    ClassificationRule("builtin_invoice_metadata", "invoice", RULE_TYPE_METADATA, "document_type=Invoice"),
+    ClassificationRule(
+        "builtin_invoice_kommunikationsart", "invoice", RULE_TYPE_METADATA, "kommunikationsart=Rechnung"
+    ),
+    # ── Contract ──────────────────────────────────────────────────────────
+    ClassificationRule("builtin_contract_filename", "contract", RULE_TYPE_FILENAME, r"(?i)contract|vertrag|agreement"),
+    ClassificationRule(
+        "builtin_contract_content",
+        "contract",
+        RULE_TYPE_CONTENT,
+        "hereby agrees|terms and conditions|vertrag|agreement between|party agrees|effective date",
+    ),
+    ClassificationRule("builtin_contract_metadata", "contract", RULE_TYPE_METADATA, "document_type=Contract"),
+    ClassificationRule(
+        "builtin_contract_kommunikationsart", "contract", RULE_TYPE_METADATA, "kommunikationsart=Vertrag"
+    ),
+    # ── Receipt ───────────────────────────────────────────────────────────
+    ClassificationRule("builtin_receipt_filename", "receipt", RULE_TYPE_FILENAME, r"(?i)receipt|quittung|beleg"),
+    ClassificationRule(
+        "builtin_receipt_content",
+        "receipt",
+        RULE_TYPE_CONTENT,
+        "receipt|quittung|payment received|thank you for your purchase|transaction id",
+    ),
+    ClassificationRule("builtin_receipt_metadata", "receipt", RULE_TYPE_METADATA, "document_type=Receipt"),
+    ClassificationRule(
+        "builtin_receipt_kommunikationsart", "receipt", RULE_TYPE_METADATA, "kommunikationsart=Quittung"
+    ),
+    # ── Letter ────────────────────────────────────────────────────────────
+    ClassificationRule("builtin_letter_filename", "letter", RULE_TYPE_FILENAME, r"(?i)letter|brief|schreiben"),
+    ClassificationRule(
+        "builtin_letter_content",
+        "letter",
+        RULE_TYPE_CONTENT,
+        "dear sir|dear madam|sehr geehrte|to whom it may concern|sincerely|mit freundlichen",
+    ),
+    # ── Report ────────────────────────────────────────────────────────────
+    ClassificationRule("builtin_report_filename", "report", RULE_TYPE_FILENAME, r"(?i)report|bericht"),
+    ClassificationRule(
+        "builtin_report_content",
+        "report",
+        RULE_TYPE_CONTENT,
+        "executive summary|table of contents|annual report|quarterly report|findings",
+    ),
+    # ── Bank statement ────────────────────────────────────────────────────
+    ClassificationRule(
+        "builtin_bank_filename",
+        "bank_statement",
+        RULE_TYPE_FILENAME,
+        r"(?i)bank.?statement|kontoauszug",
+    ),
+    ClassificationRule(
+        "builtin_bank_content",
+        "bank_statement",
+        RULE_TYPE_CONTENT,
+        "account statement|kontoauszug|opening balance|closing balance|account number",
+    ),
+    ClassificationRule(
+        "builtin_bank_kommunikationsart", "bank_statement", RULE_TYPE_METADATA, "kommunikationsart=Kontoauszug"
+    ),
+    # ── Tax document ──────────────────────────────────────────────────────
+    ClassificationRule("builtin_tax_filename", "tax_document", RULE_TYPE_FILENAME, r"(?i)tax|steuer|steuerbescheid"),
+    ClassificationRule(
+        "builtin_tax_content",
+        "tax_document",
+        RULE_TYPE_CONTENT,
+        "tax return|steuerbescheid|taxable income|finanzamt|tax assessment",
+    ),
+    # ── Insurance ─────────────────────────────────────────────────────────
+    ClassificationRule(
+        "builtin_insurance_filename", "insurance", RULE_TYPE_FILENAME, r"(?i)insurance|versicherung|police"
+    ),
+    ClassificationRule(
+        "builtin_insurance_content",
+        "insurance",
+        RULE_TYPE_CONTENT,
+        "insurance policy|versicherung|policennummer|coverage|premium|deductible",
+    ),
+    # ── Payslip ───────────────────────────────────────────────────────────
+    ClassificationRule(
+        "builtin_payslip_filename", "payslip", RULE_TYPE_FILENAME, r"(?i)payslip|gehaltsabrechnung|lohnabrechnung"
+    ),
+    ClassificationRule(
+        "builtin_payslip_content",
+        "payslip",
+        RULE_TYPE_CONTENT,
+        "gross salary|net salary|gehaltsabrechnung|lohnabrechnung|bruttolohn|nettolohn",
+    ),
+]
+
+
+# ---------------------------------------------------------------------------
+# Confidence scoring
+# ---------------------------------------------------------------------------
+
+#: Base confidence for each rule type when it matches.
+_CONFIDENCE_MAP: dict[str, int] = {
+    RULE_TYPE_FILENAME: 60,
+    RULE_TYPE_CONTENT: 70,
+    RULE_TYPE_METADATA: 90,
+}
+
+#: Extra confidence per additional matching rule of the same category (capped).
+_CONFIDENCE_BONUS_PER_EXTRA_RULE = 10
+
+
+# ---------------------------------------------------------------------------
+# Matching helpers
+# ---------------------------------------------------------------------------
+
+
+def _match_filename(rule: ClassificationRule, filename: str) -> bool:
+    """Return True if *rule.pattern* (regex) matches anywhere in *filename*."""
+    if not filename:
+        return False
+    flags = 0 if rule.case_sensitive else re.IGNORECASE
+    return bool(re.search(rule.pattern, filename, flags))
+
+
+def _match_content(rule: ClassificationRule, text: str) -> bool:
+    """Return True if any keyword in *rule.pattern* appears in *text*.
+
+    Keywords are separated by ``|`` (pipe).
+    """
+    if not text:
+        return False
+    keywords = [kw.strip() for kw in rule.pattern.split("|") if kw.strip()]
+    text_lower = text if rule.case_sensitive else text.lower()
+    return any((kw if rule.case_sensitive else kw.lower()) in text_lower for kw in keywords)
+
+
+def _match_metadata(rule: ClassificationRule, metadata: dict[str, Any] | None) -> bool:
+    """Return True if *rule.pattern* (``field=value``) matches *metadata*.
+
+    Pattern format: ``field_name=expected_value``.
+    """
+    if not metadata:
+        return False
+    if "=" not in rule.pattern:
+        return False
+    field_name, expected_value = rule.pattern.split("=", 1)
+    actual = metadata.get(field_name.strip())
+    if actual is None:
+        return False
+    if rule.case_sensitive:
+        return str(actual) == expected_value.strip()
+    return str(actual).lower() == expected_value.strip().lower()
+
+
+_MATCHERS: dict[str, tuple] = {
+    RULE_TYPE_FILENAME: (_match_filename, "filename"),
+    RULE_TYPE_CONTENT: (_match_content, "text"),
+    RULE_TYPE_METADATA: (_match_metadata, "metadata"),
+}
+
+
+def _evaluate_rule(
+    rule: ClassificationRule,
+    filename: str,
+    text: str,
+    metadata: dict[str, Any] | None,
+) -> MatchedRule | None:
+    """Evaluate a single rule against the document.  Return a :class:`MatchedRule` on match."""
+    entry = _MATCHERS.get(rule.rule_type)
+    if entry is None:
+        return None
+
+    matcher, arg_key = entry
+    arg_map = {"filename": filename, "text": text, "metadata": metadata}
+    matched = matcher(rule, arg_map[arg_key])
+
+    if matched:
+        return MatchedRule(
+            rule_name=rule.name,
+            rule_type=rule.rule_type,
+            category=rule.category,
+            confidence=_CONFIDENCE_MAP.get(rule.rule_type, 50),
+        )
+    return None
+
+
+# ---------------------------------------------------------------------------
+# Public API
+# ---------------------------------------------------------------------------
+
+
+def classify_document(
+    filename: str = "",
+    text: str = "",
+    metadata: dict[str, Any] | None = None,
+    custom_rules: list[ClassificationRule] | None = None,
+) -> ClassificationResult:
+    """Classify a document by evaluating built-in and custom rules.
+
+    Rules are evaluated in priority order (highest first, then built-in before
+    custom for the same priority).  The category with the most rule matches
+    wins; ties are broken by cumulative confidence.
+
+    Args:
+        filename: Original filename of the document.
+        text: Extracted / OCR text of the document.
+        metadata: Previously-extracted AI metadata dict (e.g. from ``ai_metadata``).
+        custom_rules: Optional list of user-defined :class:`ClassificationRule` objects.
+
+    Returns:
+        A :class:`ClassificationResult` with the best matching category,
+        overall confidence score, and the list of rules that fired.
+    """
+    all_rules = list(BUILTIN_RULES)
+    if custom_rules:
+        all_rules.extend(custom_rules)
+
+    # Sort by priority descending (higher priority first)
+    all_rules.sort(key=lambda r: r.priority, reverse=True)
+
+    matches: list[MatchedRule] = []
+    for rule in all_rules:
+        result = _evaluate_rule(rule, filename, text, metadata)
+        if result is not None:
+            matches.append(result)
+
+    if not matches:
+        return ClassificationResult(category="unknown", confidence=0, matched_rules=[])
+
+    # Aggregate by category: pick the one with the most matches, then highest
+    # cumulative confidence as tiebreaker.
+    category_scores: dict[str, list[MatchedRule]] = {}
+    for m in matches:
+        category_scores.setdefault(m.category, []).append(m)
+
+    best_category = max(
+        category_scores,
+        key=lambda cat: (len(category_scores[cat]), sum(m.confidence for m in category_scores[cat])),
+    )
+
+    best_matches = category_scores[best_category]
+    base_confidence = max(m.confidence for m in best_matches)
+    bonus = min(
+        (len(best_matches) - 1) * _CONFIDENCE_BONUS_PER_EXTRA_RULE,
+        100 - base_confidence,
+    )
+    final_confidence = min(base_confidence + bonus, 100)
+
+    return ClassificationResult(
+        category=best_category,
+        confidence=final_confidence,
+        matched_rules=best_matches,
+    )
+
+
+def db_rule_to_engine_rule(db_rule: Any) -> ClassificationRule:
+    """Convert a database ``ClassificationRuleModel`` row to an engine :class:`ClassificationRule`.
+
+    Args:
+        db_rule: A SQLAlchemy model instance with ``name``, ``category``,
+            ``rule_type``, ``pattern``, ``priority``, and ``case_sensitive`` attributes.
+
+    Returns:
+        A :class:`ClassificationRule` dataclass instance.
+    """
+    return ClassificationRule(
+        name=db_rule.name,
+        category=db_rule.category,
+        rule_type=db_rule.rule_type,
+        pattern=db_rule.pattern,
+        priority=db_rule.priority,
+        case_sensitive=getattr(db_rule, "case_sensitive", False),
+    )