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c4e128a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 | """Core Pydantic v2 document models."""
from __future__ import annotations
from enum import StrEnum
from uuid import UUID, uuid4
from pydantic import BaseModel, Field, field_validator, model_validator
# ──────────────────────────────────────────────────────────────────────────────
# Enums
# ──────────────────────────────────────────────────────────────────────────────
class Language(StrEnum):
"""ISO 639-1 language codes supported by the corpus."""
km = "km"
en = "en"
mixed = "mixed"
unknown = "unknown"
class Category(StrEnum):
"""Document category taxonomy."""
government_report = "government_report"
government_form = "government_form"
law = "law"
gazette = "gazette"
book = "book"
research_paper = "research_paper"
manual = "manual"
annual_report = "annual_report"
financial_report = "financial_report"
certificate = "certificate"
contract = "contract"
invoice = "invoice"
receipt = "receipt"
newspaper = "newspaper"
magazine = "magazine"
presentation = "presentation"
other = "other"
class DeduplicationStrategy(StrEnum):
sha256 = "sha256"
simhash = "simhash"
both = "both"
# ──────────────────────────────────────────────────────────────────────────────
# Sub-models
# ──────────────────────────────────────────────────────────────────────────────
class PageMeta(BaseModel):
"""Per-page metadata extracted from a PDF."""
page_number: int = Field(..., ge=1, description="1-indexed page number")
width_pt: float = Field(..., gt=0, description="Page width in points")
height_pt: float = Field(..., gt=0, description="Page height in points")
text_char_count: int = Field(default=0, ge=0)
image_count: int = Field(default=0, ge=0)
has_text_layer: bool = False
class ValidationResult(BaseModel):
"""Result of schema + content validation for a document."""
is_valid: bool
errors: list[str] = Field(default_factory=list)
warnings: list[str] = Field(default_factory=list)
@property
def has_warnings(self) -> bool:
return len(self.warnings) > 0
# ──────────────────────────────────────────────────────────────────────────────
# Core Model
# ──────────────────────────────────────────────────────────────────────────────
class DocumentMeta(BaseModel):
"""Complete metadata for a single corpus document."""
model_config = {"use_enum_values": True}
# Identity
id: UUID = Field(default_factory=uuid4, description="Unique document UUID")
filename: str = Field(..., min_length=1, description="PDF filename (no path)")
# Classification
language: Language = Language.unknown
category: Category = Category.other
# Dimensions
pages: int = Field(..., ge=1, description="Total page count")
file_size_bytes: int = Field(..., ge=0, description="Raw PDF file size in bytes")
# Content flags
native_pdf: bool = Field(False, description="True if text is embedded in the PDF")
scanned: bool = Field(False, description="True if the PDF requires OCR")
has_tables: bool = False
has_images: bool = False
has_header: bool = False
has_footer: bool = False
# Deduplication
sha256: str | None = Field(None, description="SHA-256 hex digest of raw file bytes")
simhash: int | None = Field(None, description="SimHash fingerprint of extracted text")
# Provenance
source: str | None = Field(None, description="Source URL or institution name")
license: str | None = Field(None, description="Original document license")
# Paths (relative to corpus root)
pdf_path: str | None = None
preview_path: str | None = Field(None, description="Path to the preview image folder")
# Per-page detail (optional, not always populated)
pages_meta: list[PageMeta] = Field(default_factory=list)
# ── Validators ────────────────────────────────────────────────────────────
@field_validator("filename")
@classmethod
def filename_must_be_pdf(cls, v: str) -> str:
if not v.lower().endswith(".pdf"):
raise ValueError(f"filename must end with .pdf, got: {v!r}")
return v
@field_validator("sha256")
@classmethod
def sha256_format(cls, v: str | None) -> str | None:
if v is not None and len(v) != 64:
raise ValueError("sha256 must be a 64-character hex string")
return v
@model_validator(mode="after")
def pages_meta_length(self) -> DocumentMeta:
if self.pages_meta and len(self.pages_meta) != self.pages:
raise ValueError(
f"pages_meta has {len(self.pages_meta)} entries but pages={self.pages}"
)
return self
# ── Helpers ───────────────────────────────────────────────────────────────
@property
def file_size_kb(self) -> float:
return self.file_size_bytes / 1024
@property
def file_size_mb(self) -> float:
return self.file_size_bytes / (1024 * 1024)
def to_flat_dict(self) -> dict[str, object]:
"""Return a flat dict suitable for a Polars row (no nested objects)."""
return {
"id": str(self.id),
"filename": self.filename,
"language": self.language,
"category": self.category,
"pages": self.pages,
"file_size_bytes": self.file_size_bytes,
"native_pdf": self.native_pdf,
"scanned": self.scanned,
"has_tables": self.has_tables,
"has_images": self.has_images,
"has_header": self.has_header,
"has_footer": self.has_footer,
"sha256": self.sha256,
"simhash": self.simhash,
"source": self.source,
"license": self.license,
"pdf_path": self.pdf_path,
"preview_path": self.preview_path,
}
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