Use parse results

A ParseResult holds everything the parser saw: markdown, structure, figures, and page renders. This page shows how to get each out.

Whole-document markdown

result = parse("report.pdf")
print(result.markdown)          # every page, assembled

Tables come out as HTML (merged cells preserved), formulas as LaTeX, charts as markdown data tables with a caption. This single string is often all you need if you're feeding another system.

Per-page structure

for page in result.pages:
    print(page.page_num, len(page.regions), "regions")
    print(page.markdown)        # this page only

Every block on a page is a Region with a type, its recognized content, and a bounding box:

for region in result.pages[0].regions:
    print(region.region_id, region.region_type, region.bbox.as_tuple())
    # 0 text     (72.0, 90.5, 523.0, 140.2)
    # 1 table    (72.0, 160.0, 523.0, 380.9)
    # 2 chart    (90.0, 400.0, 500.0, 640.0)

Region ids are what chunks cite later — the provenance chain hangs off them.

Figures and charts

Charts and figures are cropped out as PNGs with captions and AI descriptions:

for page in result.pages:
    for fig in page.figures:
        print(fig.caption, "—", fig.description[:60])

result.save_images("out/")      # writes every crop as a PNG file

Page renders

Each page keeps its rendered image (page.image_bytes, PNG) — the canvas for drawing citation highlights.

Persist and reload

Parsing is the expensive stage — store the result once, reuse it forever:

from ingestlib.storage import artifacts

doc_id = artifacts.save_parse(result)          # everything, keyed by checksum

light = artifacts.load_parse(doc_id)                       # structure only
full  = artifacts.load_parse(doc_id, include_images=True)  # + page renders & crops

The light form loads with image_bytes=None on pages and empty bytes on figure crops — cheap when you only need text and structure. ingest() does this save automatically; loading an unknown doc_id raises a clear error pointing you at artifacts.list_documents().

Feed the other operations

label  = classify(result)                        # no OCR — reuses the parse
chunks = split(result, category=label.category)  # chunks with region provenance

Passing the ParseResult (rather than the file path) is what gives split exact region ids — the standalone-path chunks cite pages only.

---

Next: Extract structured data — your schema, filled and cited from the parse.