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0580de5 bbbfba8 0580de5 bbbfba8 0580de5 bbbfba8 0580de5 bbbfba8 0580de5 | 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 | """text_only adapter — handles providers that return structured text without geometry.
Expected payload format:
{
"text": "full page text",
"blocks": [ # optional
{"text": "block text"},
...
]
}
or simply:
{"text": "full text"}
This adapter is honest: geometry is marked as 'unknown' since the
provider doesn't supply coordinates. ALTO export will be refused
(no word geometry), but PAGE export may be partial and the viewer
will show text without positioned overlays.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from src.app.domain.models import (
CanonicalDocument,
Geometry,
Provenance,
RawProviderPayload,
)
from src.app.domain.models.status import EvidenceType, GeometryStatus, InputType
from src.app.normalization.canonical_builder import CanonicalBuilder
from src.app.providers.adapters.base import BaseAdapter
if TYPE_CHECKING:
from src.app.domain.models.geometry import GeometryContext
class TextOnlyAdapter(BaseAdapter):
"""Adapter for the text_only family (mLLM without geometry)."""
@property
def family(self) -> str:
return "text_only"
@property
def version(self) -> str:
return "adapter.text_only.v1"
def normalize(
self,
raw: RawProviderPayload,
geometry_context: GeometryContext,
*,
document_id: str,
source_filename: str | None = None,
) -> CanonicalDocument:
payload = raw.payload
if not isinstance(payload, dict):
raise ValueError(
f"text_only expects a dict payload, got {type(payload).__name__}"
)
builder = CanonicalBuilder(
document_id=document_id,
input_type=InputType.IMAGE,
filename=source_filename,
)
page_w = geometry_context.source_width
page_h = geometry_context.source_height
page = builder.add_page("p1", 0, page_w, page_h)
# Placeholder bbox covering the full page — marked unknown
full_page_geo = Geometry(
bbox=(0, 0, page_w, page_h),
status=GeometryStatus.UNKNOWN,
)
# Extract text blocks
blocks = payload.get("blocks")
if blocks and isinstance(blocks, list):
texts = [
str(b.get("text", ""))
for b in blocks
if isinstance(b, dict) and b.get("text")
]
else:
# Single text blob — split into paragraphs
full_text = str(payload.get("text", ""))
if not full_text.strip():
raise ValueError("text_only payload has no text content")
texts = [p.strip() for p in full_text.split("\n\n") if p.strip()]
if not texts:
texts = [full_text.strip()]
for bi, block_text in enumerate(texts):
block_id = f"tb{bi + 1}"
prov = Provenance(
provider=raw.provider_id,
adapter=self.version,
source_ref=f"$.blocks[{bi}]" if blocks else f"$.text.paragraph[{bi}]",
evidence_type=EvidenceType.PROVIDER_NATIVE,
)
region = page.add_text_region(
region_id=block_id,
geometry=full_page_geo,
provenance=prov,
)
# Split block into lines
lines = [ln.strip() for ln in block_text.split("\n") if ln.strip()]
if not lines:
lines = [block_text]
for li, line_text in enumerate(lines):
line_id = f"tl{bi + 1}_{li + 1}"
word_id = f"w{bi + 1}_{li + 1}"
line = region.add_line(
line_id, geometry=full_page_geo, provenance=prov,
)
# Each line becomes a single word (no word segmentation available)
line.add_word(
word_id,
text=line_text,
geometry=full_page_geo,
provenance=prov,
)
return builder.build()
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