Use this when the user wants structured tabular data — financial
statements, scientific tables, invoices, spreadsheet-style PDFs. Xberg
detects tables via a layout model (RT-DETR v2) and reconstructs cell
structure with a configurable table model.
# Markdown tables embedded in the content stream
xberg extract report.pdf --layout --content-format markdown
# Structured JSON output, tables appear under result.tables
xberg extract report.pdf --layout --format json
--layout turns on layout-aware extraction; without it, tables fall back
to plain text reflow and you lose cell boundaries.
Two surfaces, picked via --format (CLI shape) and --content-format
(content rendering):
content — --content-format markdown. Tablesappear inline as | col | col | blocks. Good for LLM ingestion.
tables array — --format json. Each entry hascells[][] (rows × cols), markdown (pre-rendered), page_number,bounding_box. Use this when downstream code needs exact cell access.
(bounding_box is omitted when no position data is available.)
Both are populated at once when --layout is on. The tables array is
always structured; the content stream switches representation.
xberg extract financials.pdf --layout --format json \
| jq '.result.tables[] | {page: .page_number, rows: (.cells | length)}'
--layout-table-model picks the reconstruction backend:
| Model | Best for | Notes |
|---|---|---|
tatr | dense complex tables (academic, financial) | Default. Heaviest, highest accuracy. |
slanet_auto | dispatches per-table to wired/wireless | Good when table styles are mixed. |
slanet_wired | tables with visible borders | Faster than tatr. |
slanet_wireless | tables without borders (whitespace-separated) | For invoices, simple grids. |
slanet_plus | hybrid wired / wireless | Lighter than slanet_auto. |
disabled | layout detection only, no table structure | Use to skip table model cost. |
xberg extract bank-statement.pdf \
--layout --layout-table-model tatr --content-format markdown
Drop --layout-confidence when the layout model misses tables (default
threshold ~0.5):
xberg extract noisy-scan.pdf --layout --layout-confidence 0.3
.xlsx, .ods, .csv, .tsv are extracted by dedicated parsers — no
layout model needed. Each sheet becomes a markdown table (or structured
table) automatically:
xberg extract workbook.xlsx --content-format markdown
xberg extract data.csv --format json
Pass --no-cache=true only when iterating on the same file with different
configs.
# `output_format` in config files equals `--content-format` on the CLI.
output_format = "markdown"
[layout]
confidence_threshold = 0.5
table_model = "tatr"
Then:
xberg extract report.pdf --format json
From Python, structured tables live on the document in the result envelope
(result.results[0].tables):
from xberg import ExtractInput, extract, ExtractionConfig, LayoutDetectionConfig
config = ExtractionConfig(
layout=LayoutDetectionConfig(table_model="tatr"),
output_format="markdown",
)
result = await extract(ExtractInput(uri="report.pdf"), config)
for table in result.results[0].tables:
print(table.markdown) # rendered markdown
print(table.cells[0][0]) # cell access
Node.js mirrors this (extract, output.results[0].tables, camelCase fields).
See references/python-api.md and references/nodejs-api.md in the
sibling xberg skill for full type signatures.
region; the merge is not preserved as metadata.
--ocr-auto-rotate true for image-basedPDFs before extraction.
lost.
tables[] entry.Stitch by matching column headers if needed.
WASM builds and on the Android x86_64 emulator; native targets ship
full support.
tables with --layout on — confidence threshold too high ortable model mismatched. Drop --layout-confidence to 0.3, try--layout-table-model tatr.
--layout-table-model toslanet_wired for bordered grids or slanet_wireless for invoices.
tatr is heavy. Use slanet_auto orslanet_plus as a default; reach for tatr only when accuracy matters.
See references/cli-reference.md for the full layout flag set andreferences/advanced-features.md for the layout pipeline internals.