"""
GLM-OCR Hugging Face Space app for PDF/image OCR with header inclusion
and table-structure stabilization for downstream bank-statement pipelines.
Hard-coded knobs (no environment variables required).
Primary goals for reconcile rate:
- preserve right-most columns (often "Balance") by higher DPI render + right padding
- keep tables as tables (convert markdown pipe tables -> HTML table)
- return ---page-separator--- between pages
- normalize HTML tables generically so downstream parsing/classification is stable:
  1) expand colspan/rowspan into a rectangular grid
  2) drop truly-empty columns (common in summary tables)
  3) merge "blank header" columns that contain text into the left column (common when DESCRIPTION is split)
  4) clean common header artifacts (e.g. "DESCRIPTIONBeginning Balance", "BALANCE$3,447.10")
  5) recover fused first data row generically (two-signal guard: text fusion + money fusion must both fire)
  6) promote misplaced header row: when real column headers land in a data row, restructure the grid
  7) fix fused key-value rows in summary sections (e.g. Interest Summary) appended to transaction tables
  8) reconstruct mid-table separator rows split across columns by OCR (e.g. 'Card account # XXXX 2 | | 889')
- footer extraction enabled on all pages with deduplication guard (no double-print if body OCR already captured it)
- Fix 4: cross-validate OCR table row counts against PDF text layer; inject missing duplicate rows
         (safe no-op for scanned PDFs and non-transaction pages); after injection, re-run normalize_html_tables
         + subset dedupe so UCB-style fused cells from the text layer get Fix 13/14
- Fix NF-1: extract Navy Federal "Summary of your deposit accounts" table from PDF text layer
            using spatial word positions (GLM-OCR fails on this wide-column layout)
- Fix 13: collapse Date|Description|Amount|Description|Amount tables to 3 columns; fix fused
            Beginning/Ending balance rows (UCB-style wide summary tables)
- Fix 14: UCB 3-col tables where Beginning Balance amount is fused into description and Amount is $0.00
- Fix 15: UCB (and similar) 3-col rows where Date+Description are fused in col1 and Amount sits in col2 with col3 empty
- Fix 16: remove duplicate rows within a single Date|Description|Amount table; multi-pass table dedupe + final doc-wide dedupe
- Fix 17: UCB page 3 — split one merged table under Deposits (continued) into Deposits + Electronic Credits +
            Electronic Debits (PDF text order); drop orphan empty EC/ED headers that followed the merged table
- Post-pass: dedupe 3-col Date|Description|Amount tables when one is a duplicate fragment
            (later subset of earlier, earlier subset of later, or identical row sets)
- Fix 18: adjacent DA3 tables — if the last K data rows of table N match the first K rows of table N+1
            (same normalized Date|Description|Amount keys), strip that suffix from table N. Fixes
            formats (e.g. Truist) where deposit rows are glued onto the withdrawals table and repeated
            under the proper deposits heading (K>=2; first table must keep >=1 data row).
- Fix 19: DA3 rows whose Amount cell is not strict currency (e.g. fused card digits + merchant tail)
            — take the rightmost plausible money token from Description+Amount text for the amount.
- Fix 20: DA3 in-table dedupe — cap consecutive identical normalized keys at 2 rows (keeps legitimate
            back-to-back identical charges; still collapses 3+ OCR stutters).
- Fix 21: Cross-table DA3 repair for MSBILL / MICROSOFT#G… PIN rows — when Amount is junk in one table
            but another table repeats the same authorization id with a strict amount, copy that amount
            (then subset dedupe can drop the stray duplicate block, e.g. under Deposits).
- Fix 22: Drop a single OCR "flat line" between pages: (continued) + DESCRIPTION + AMOUNT + many MM/DD
            tokens (noise before a proper <table>).
- Fix 23: Doc-wide DA3 table dedupe using multiset of (date, amount) keys — catches duplicate sections when
            OCR varies description text between copies (e.g. withdrawals repeated under Deposits).
- Fix 24: Run orphan flatline strip on merged PDF output and after text-layer patch so page-boundary
            noise is removed consistently.
- Fix 25: After a centered "deposits + credits/interest" heading, if two DA3 tables appear back-to-back
            and the first is mostly credit/deposit rows while the second is mostly debit/withdrawal-style
            rows (generic keywords), drop the second — fixes OCR pasting the withdrawals block again.
- Fix 23b: Loose multiset keys use normalized float amounts so comma/spacing variants still match.
- Fix 26: Drop small DA3 fragments (3–14 rows) that are a multiset subset of an earlier larger DA3
            table — matches PDF layouts that re-print a header and repeat a few rows.
- Fix 27: Strip a lone "…(continued)" account banner line (no DATE/DESCRIPTION/AMOUNT) between
            page separators — duplicate header noise without the long flatline.
- Fix 28: Strip leading credit/deposit rows that OCR prepends to a withdrawals/debits DA3 table
            when the preceding DA3 table was under a deposits/credits heading. Only strips the
            contiguous prefix of the debit table whose rows appear in the credit table; requires
            ≥1 data row to remain; entire function wrapped in try/except (safe no-op on any error).
"""

# Patch asyncio first (before Gradio imports it) to suppress Python 3.13 cleanup noise
import asyncio
try:
    _orig_close = asyncio.BaseEventLoop.close
    def _safe_close(self):
        try:
            _orig_close(self)
        except (ValueError, OSError):
            pass
    asyncio.BaseEventLoop.close = _safe_close
except Exception:
    pass

import logging
import os
import re
import html
import tempfile
from typing import List, Tuple
from collections import Counter, defaultdict
from html.parser import HTMLParser

import yaml
import gradio as gr
import glmocr

log = logging.getLogger("glmocr_app")
logging.basicConfig(level=logging.INFO)

GLMOCR_BASE = os.path.dirname(glmocr.__file__)
CONFIG_PATH = os.path.join(GLMOCR_BASE, "config.yaml")
FORMATTER_PATH = os.path.join(GLMOCR_BASE, "postprocess", "result_formatter.py")

# ============================================================
# HARD-CODED SETTINGS (edit these numbers to tune quality/speed)
# ============================================================

GLMOCR_API_KEY = "cee1d52dd91a4ab591b3f6e105f8ad89.LgbQTECuzX0zrito"

# Higher = better OCR for small/right-aligned digits; slower
RENDER_SCALE = 2.2  # try 2.5 if right-side numbers are missed

# Padding to protect columns near edges (Balance is often right-most)
PAD_LEFT_FRAC = 0.02
PAD_RIGHT_FRAC = 0.06  # try 0.10 if right-most balances are missing
PAD_TOP_FRAC = 0.01
PAD_BOTTOM_FRAC = 0.01

ENABLE_CONTRAST = True

DEFAULT_ZONE_FRAC = 0.12
PDF_HEADER_BAND_FRAC = 0.10

ENABLE_FOOTER_OCR = True        # enabled — 3-step fallback with dedup guard
PDF_FOOTER_BAND_FRAC = 0.88

MIN_CROP_HEIGHT = 112
MIN_CROP_PIXELS = 112 * 112

# ============================================================

_parser = None

def get_parser():
    global _parser
    if _parser is None:
        from glmocr import GlmOcr
        _parser = GlmOcr(api_key=GLMOCR_API_KEY, mode="maas")
    return _parser

# ---------------------------------------------------------------------------
# Best-effort config tweaks (safe to fail on read-only HF env)
# ---------------------------------------------------------------------------
try:
    with open(CONFIG_PATH, "r") as f:
        config = yaml.safe_load(f)
    config["pipeline"]["maas"]["enabled"] = True
    config["pipeline"]["maas"]["api_key"] = GLMOCR_API_KEY
    with open(CONFIG_PATH, "w") as f:
        yaml.dump(config, f, default_flow_style=False, sort_keys=False)
except Exception:
    pass

# Best-effort formatter tweak: avoid stripping header/footer labels
try:
    with open(FORMATTER_PATH, "r") as f:
        source = f.read()
    for label in (
        '"header"', "'header'",
        '"footer"', "'footer'",
        '"doc_header"', "'doc_header'",
        '"doc_footer"', "'doc_footer'",
    ):
        source = re.sub(r",\s*" + re.escape(label), "", source)
        source = re.sub(re.escape(label) + r"\s*,", "", source)
        source = re.sub(re.escape(label), "", source)
    with open(FORMATTER_PATH, "w") as f:
        f.write(source)
except Exception:
    pass

# --------------------------
# Header/footer helpers
# --------------------------
def get_header_footer_zones(regions, norm_height=1000):
    if not regions:
        return None, None
    y_tops, y_bottoms = [], []
    for r in regions:
        bbox = r.get("bbox_2d") if isinstance(r, dict) else getattr(r, "bbox_2d", None)
        if bbox and len(bbox) >= 4:
            y_tops.append(bbox[1])
            y_bottoms.append(bbox[3])
    if not y_tops:
        return None, None
    return min(y_tops) / norm_height, max(y_bottoms) / norm_height

def extract_zone_text_pdf(pdf_path, page_num, y_start_frac, y_end_frac):
    try:
        import pymupdf as fitz
        doc = fitz.open(pdf_path)
        page = doc[page_num]
        h, w = page.rect.height, page.rect.width
        rect = fitz.Rect(0, h * y_start_frac, w, h * y_end_frac)
        text = page.get_text(clip=rect).strip()
        doc.close()
        return text
    except Exception:
        return ""

def extract_pdf_text_in_band(pdf_path, page_num, y_start_frac, y_end_frac):
    try:
        import pymupdf as fitz
        doc = fitz.open(pdf_path)
        page = doc[page_num]
        h = page.rect.height
        y_lo = h * y_start_frac
        y_hi = h * y_end_frac
        words = page.get_text("words")
        doc.close()
        parts = []
        for w in words:
            if len(w) >= 5:
                y0, y1 = float(w[1]), float(w[3])
                if y0 < y_hi and y1 > y_lo:
                    parts.append(w[4])
        return " ".join(parts).strip()
    except Exception:
        return ""

def ocr_zone(image_path, y_start_frac, y_end_frac):
    zone_name = "header" if y_end_frac < 0.5 else "footer"
    try:
        from PIL import Image
        img = Image.open(image_path).convert("RGB")
        w, h = img.size
        y0 = max(0, int(h * y_start_frac))
        y1 = min(h, int(h * y_end_frac))
        if y1 <= y0:
            return ""

        crop = img.crop((0, y0, w, y1))
        cw, ch = crop.size

        if ch < MIN_CROP_HEIGHT or (cw * ch) < MIN_CROP_PIXELS:
            need_h = max(ch, MIN_CROP_HEIGHT)
            need_w = max(cw, 1)
            if (need_w * need_h) < MIN_CROP_PIXELS:
                need_w = max(need_w, (MIN_CROP_PIXELS + need_h - 1) // need_h)
            canvas = Image.new("RGB", (need_w, need_h), (255, 255, 255))
            if zone_name == "header":
                canvas.paste(crop, (0, 0))
            else:
                canvas.paste(crop, (0, need_h - ch))
            crop = canvas

        fd, path = tempfile.mkstemp(suffix=".jpg")
        os.close(fd)
        try:
            crop.save(path, "JPEG", quality=92)
            parser = get_parser()
            out = parser.parse(path)
            if not isinstance(out, list):
                out = [out]
            if out and getattr(out[0], "markdown_result", None):
                return (out[0].markdown_result or "").strip()
        finally:
            try:
                os.unlink(path)
            except Exception:
                pass
    except Exception as e:
        log.warning("[%s] ocr_zone failed: %s", zone_name, e, exc_info=True)
    return ""

def fix_account_number(hdr: str) -> str:
    if not hdr:
        return hdr
    if "Account Number:" in hdr and "Account Number: " not in hdr:
        m = re.search(r"[0-9]{5,}", hdr)
        if m:
            hdr = hdr.replace("Account Number:", "Account Number: " + m.group(0))
    acct_match = re.search(r"Account Number: ([0-9]{5,})", hdr)
    if acct_match:
        acct = acct_match.group(1)
        if hdr.startswith(acct):
            hdr = hdr[len(acct):].lstrip()
    return hdr

# --------------------------
# Table stabilization helpers
# --------------------------
def close_unclosed_html(md: str) -> str:
    if not md:
        return md
    open_tags = re.findall(r"<(table|tbody|thead|tr|td|th)\b", md, flags=re.IGNORECASE)
    close_tags = re.findall(r"</(table|tbody|thead|tr|td|th)>", md, flags=re.IGNORECASE)

    def count(tags, name):
        return sum(1 for t in tags if t.lower() == name)

    for tag in reversed(["td", "th", "tr", "thead", "tbody", "table"]):
        opened = count(open_tags, tag)
        closed = count(close_tags, tag)
        if opened > closed:
            md += ("</%s>" % tag) * (opened - closed)
    return md

def looks_like_markdown_table(block: str) -> bool:
    lines = [ln.rstrip() for ln in block.strip().splitlines() if ln.strip()]
    if len(lines) < 2:
        return False
    if "|" not in lines[0]:
        return False
    sep = lines[1].replace(" ", "")
    return ("---" in sep) and ("|" in sep)

def md_table_to_html(block: str) -> str:
    lines = [ln.strip() for ln in block.strip().splitlines() if ln.strip()]
    if len(lines) < 2:
        return block

    def split_row(row: str):
        row = row.strip()
        if row.startswith("|"):
            row = row[1:]
        if row.endswith("|"):
            row = row[:-1]
        return [p.strip() for p in row.split("|")]

    header = split_row(lines[0])
    body_lines = [ln for ln in lines[2:] if "|" in ln]

    html_rows = []
    html_rows.append("<tr>" + "".join(f"<th>{html.escape(c)}</th>" for c in header) + "</tr>")
    for ln in body_lines:
        cols = split_row(ln)
        if len(cols) < len(header):
            cols += [""] * (len(header) - len(cols))
        html_rows.append("<tr>" + "".join(f"<td>{html.escape(c)}</td>" for c in cols[: len(header)]) + "</tr>")
    return "<table>\n" + "\n".join(html_rows) + "\n</table>"

def normalize_money_glyphs(text: str) -> str:
    if not text:
        return text
    t = text.replace("−", "-").replace("–", "-").replace("—", "-")
    t = re.sub(
        r"\(\s*\$?\s*([0-9]{1,3}(?:,[0-9]{3})*|[0-9]+)(\.[0-9]{2})\s*\)",
        r"-\1\2",
        t,
    )

    def o_to_zero(m):
        token = m.group(0)
        return token.replace("O", "0").replace("o", "0")

    t = re.sub(r"\b[0-9Oo\$,.\-]{4,}\b", o_to_zero, t)
    return t

# ---- Generic HTML table normalizer ----
class TableGridParser(HTMLParser):
    """Parse a <table> into rows of (text, colspan, rowspan)."""

    def __init__(self):
        super().__init__()
        self.rows = []
        self._current_row = []
        self._cell_text = []
        self._colspan = 1
        self._rowspan = 1
        self._in_cell = False

    def handle_starttag(self, tag, attrs):
        if tag == "tr":
            self._current_row = []
        elif tag in ("td", "th"):
            attrs_d = dict(attrs)
            self._colspan = max(1, int(attrs_d.get("colspan", 1)))
            self._rowspan = max(1, int(attrs_d.get("rowspan", 1)))
            self._cell_text = []
            self._in_cell = True

    def handle_endtag(self, tag):
        if tag in ("td", "th"):
            text = "".join(self._cell_text).strip().replace("\n", " ")
            self._current_row.append((text, self._colspan, self._rowspan))
            self._in_cell = False
        elif tag == "tr":
            self.rows.append(self._current_row)

    def handle_data(self, data):
        if self._in_cell:
            self._cell_text.append(data)

def _build_grid(rows_data):
    if not rows_data:
        return []
    blocked = defaultdict(set)
    grid = []

    for r, row_cells in enumerate(rows_data):
        grid.append([])
        col = 0
        for content, C, R in row_cells:
            while col in blocked[r]:
                grid[r].append("")
                col += 1
            for k in range(C):
                grid[r].append(content if k == 0 else "")
            for k in range(1, R):
                blocked[r + k].add(col)
            col += C

    max_cols = max(len(row) for row in grid) if grid else 0
    for row in grid:
        while len(row) < max_cols:
            row.append("")
    return grid

def _grid_to_html(grid):
    if not grid:
        return ""
    lines = ["<table>"]
    for r, row in enumerate(grid):
        lines.append("<tr>")
        tag = "th" if r == 0 else "td"
        for cell in row:
            escaped = (
                (cell or "")
                .replace("&", "&amp;")
                .replace("<", "&lt;")
                .replace(">", "&gt;")
                .replace('"', "&quot;")
            )
            lines.append(f"<{tag}>{escaped}</{tag}>")
        lines.append("</tr>")
    lines.append("</table>")
    return "\n".join(lines)

def _is_amount_like(s: str) -> bool:
    if not s:
        return False
    return re.fullmatch(r"\$?-?\d{1,3}(?:,\d{3})*(?:\.\d{2})?", s.strip()) is not None

def _drop_truly_empty_columns(grid):
    """
    Drop columns that are empty in header AND almost always empty in body.
    This fixes summary tables that have an extra blank trailing column.
    """
    if not grid or len(grid) < 1:
        return grid

    header = [str(c or "").strip() for c in grid[0]]
    ncols = len(header)
    if ncols <= 1:
        return grid

    body = grid[1:]
    keep = [True] * ncols

    for i in range(ncols):
        if header[i] != "":
            continue
        total = 0
        non_empty = 0
        for row in body:
            if i >= len(row):
                continue
            total += 1
            if str(row[i] or "").strip():
                non_empty += 1
        if total > 0 and (non_empty / total) <= 0.05:
            keep[i] = False

    if all(keep):
        return grid

    new_grid = []
    for row in grid:
        new_grid.append([cell for idx, cell in enumerate(row) if idx < len(keep) and keep[idx]])
    return new_grid

def _merge_blank_header_text_columns(grid):
    """
    If the header row has blank columns, and most body rows have non-empty *text* in that
    blank column, merge that column into the nearest non-empty header to the left (usually
    DESCRIPTION), then remove the blank column.
    This fixes transaction tables where DESCRIPTION is split across two columns.
    """
    if not grid or len(grid) < 2:
        return grid

    header = [str(c or "").strip() for c in grid[0]]
    ncols = len(header)
    body = grid[1:]
    blank_cols = [i for i, h in enumerate(header) if h == ""]
    if not blank_cols:
        return grid

    keep = [True] * ncols

    for i in blank_cols:
        j = i - 1
        while j >= 0 and header[j] == "":
            j -= 1
        if j < 0:
            continue

        total = 0
        non_empty = 0
        texty = 0
        for row in body:
            if i >= len(row) or j >= len(row):
                continue
            v = str(row[i] or "").strip()
            total += 1
            if v:
                non_empty += 1
                if not _is_amount_like(v):
                    texty += 1

        if total == 0:
            continue
        non_empty_ratio = non_empty / total
        texty_ratio = (texty / non_empty) if non_empty else 0.0

        if non_empty_ratio >= 0.55 and texty_ratio >= 0.70:
            for r in range(1, len(grid)):
                row = grid[r]
                if i >= len(row) or j >= len(row):
                    continue
                left = str(row[j] or "").strip()
                right = str(row[i] or "").strip()
                if right:
                    row[j] = (left + " " + right).strip() if left else right
            keep[i] = False

    if all(keep):
        return grid

    new_grid = []
    for row in grid:
        new_grid.append([cell for idx, cell in enumerate(row) if idx < len(keep) and keep[idx]])
    return new_grid

# --------------------------
# Shared keyword definitions
# --------------------------

# Matches a standalone money value across currencies.
# Covers: $3,447.10  -1,234.56  £500.00  Rs1000  etc.
_MONEY_RE = re.compile(
    r"^(?:[\$£€¥]|Rs\.?|INR|PKR)?\s*-?\s?\d{1,3}(?:,\d{3})*(?:\.\d{1,4})?$",
    re.IGNORECASE,
)

# All column-header keywords recognised across any bank statement format.
_HEADER_KW_PATTERNS = [
    # Date variants
    r"DATE",
    r"POSTING\s+DATE",
    r"VALUE\s+DATE",
    r"TXN\s+DATE",
    r"TRANSACTION\s+DATE",
    r"ENTRY\s+DATE",
    r"EFFECTIVE\s+DATE",
    # Transaction ID / reference
    r"TRANSACTION(?:\s+(?:ID|TYPE|NO|NUMBER))?",
    r"TXN(?:\s+(?:ID|NO|TYPE))?",
    r"REF(?:ERENCE)?(?:\s*(?:NO|NUM|NUMBER))?",
    r"CHEQUE(?:\s*(?:NO|NUMBER))?",
    r"CHQ(?:\s*(?:NO|NUMBER))?",
    r"VOUCHER(?:\s*(?:NO|NUMBER))?",
    r"SR\.?\s*NO\.?",
    r"SERIAL(?:\s*(?:NO|NUMBER))?",
    # Description variants
    r"DESCRIPTION",
    r"DETAILS?",
    r"PARTICULARS?(?:\s+OF\s+TRANSACTION)?",
    r"NARRATION",
    r"REMARKS?",
    r"NOTES?",
    # Debit variants
    r"DEBIT",
    r"DEBITS?",
    r"DR\.?",
    r"WITHDRAWALS?",
    r"PAID\s+OUT",
    r"MONEY\s+OUT",
    # Credit variants
    r"CREDIT",
    r"CREDITS?",
    r"CR\.?",
    r"DEPOSITS?",
    r"PAID\s+IN",
    r"MONEY\s+IN",
    # Amount
    r"AMOUNT",
    # Balance variants
    r"BALANCE",
    r"BAL\.?",
    r"RUNNING\s+BALANCE",
    r"RUNNING\s+BAL\.?",
    r"AVAILABLE\s+BALANCE",
    r"AVAILABLE\s+BAL\.?",
    r"AVAIL\.?\s+BAL\.?",
    r"LEDGER\s+BALANCE",
    r"LEDGER\s+BAL\.?",
    r"CLOSING\s+BALANCE",
    r"CLOSING\s+BAL\.?",
    r"OPENING\s+BALANCE",
    r"OPENING\s+BAL\.?",
]

# Pre-compiled: each pattern anchored at start, case-insensitive
_HEADER_KW_RES = [
    re.compile(r"^(" + p + r")(.*)", re.IGNORECASE | re.DOTALL)
    for p in _HEADER_KW_PATTERNS
]

# Quick exact-match check: "is this entire string a known keyword?"
_HEADER_KW_EXACT_RE = re.compile(
    r"^(?:" + r"|".join(_HEADER_KW_PATTERNS) + r")$",
    re.IGNORECASE,
)

# Minimum fraction of cells in a row that must be pure keywords for that row
# to be considered a misplaced header row.
_HEADER_ROW_KEYWORD_THRESHOLD = 0.5

# --------------------------
# Fix 1: Fused-header recovery
# --------------------------

def _split_keyword_remainder(cell_text: str):
    s = cell_text.strip()
    for pattern in _HEADER_KW_RES:
        m = pattern.match(s)
        if m:
            keyword = m.group(1).strip()
            remainder = m.group(2).strip()
            return keyword, remainder
    return s, ""

def _extract_fused_header_artifacts(header_row):
    if not header_row:
        return list(header_row), None

    ncols = len(header_row)
    cleaned = list(header_row)
    recovered = [""] * ncols

    text_fused = []
    money_fused = []

    for idx, cell in enumerate(header_row):
        cell_s = str(cell or "").strip()
        if not cell_s:
            continue

        keyword, remainder = _split_keyword_remainder(cell_s)

        if not remainder:
            continue

        remainder_no_space = remainder.replace(" ", "")

        if _MONEY_RE.match(remainder_no_space):
            cleaned[idx] = keyword
            recovered[idx] = remainder
            money_fused.append(idx)

        elif not _HEADER_KW_EXACT_RE.match(remainder.split()[0] if remainder.split() else ""):
            cleaned[idx] = keyword
            recovered[idx] = remainder
            text_fused.append(idx)

    if text_fused and money_fused:
        return cleaned, recovered

    return list(header_row), None

def _clean_header_artifacts(grid):
    if not grid or not grid[0]:
        return grid, None

    cleaned_header, recovered_row = _extract_fused_header_artifacts(grid[0])
    grid[0] = cleaned_header
    return grid, recovered_row

# --------------------------
# Fix 2: Misplaced header row promotion
# --------------------------

def _row_keyword_score(row):
    non_empty = [str(c or "").strip() for c in row if str(c or "").strip()]
    if not non_empty:
        return 0.0

    keyword_hits = 0
    for cell in non_empty:
        if _HEADER_KW_EXACT_RE.match(cell):
            keyword_hits += 1
            continue
        parts = cell.split()
        if all(_HEADER_KW_EXACT_RE.match(p) for p in parts) and len(parts) > 1:
            keyword_hits += 1
            continue

    return keyword_hits / len(non_empty)

_BALANCE_INFO_RE = re.compile(
    r"(beginning|ending|opening|closing)\s+balance"
    r"|account\s*#?\s*\d{5,}"
    r"|\b\d{7,}\b"
    r"|\$\d{1,3}(?:,\d{3})*\.\d{2}",
    re.IGNORECASE,
)

def _header_contains_balance_info(header_row):
    for cell in header_row:
        if _BALANCE_INFO_RE.search(str(cell or "")):
            return True
    return False

def _promote_misplaced_header_row(grid):
    if not grid or len(grid) < 2:
        return grid

    current_header_score = _row_keyword_score(grid[0])
    if current_header_score >= _HEADER_ROW_KEYWORD_THRESHOLD:
        return grid

    candidate_idx = None
    candidate_score = 0.0
    for i in range(1, min(len(grid), 6)):
        score = _row_keyword_score(grid[i])
        if score >= _HEADER_ROW_KEYWORD_THRESHOLD and score > candidate_score:
            candidate_score = score
            candidate_idx = i

    if candidate_idx is None:
        return grid

    candidate_row = grid[candidate_idx]

    expanded_header = []
    for cell in candidate_row:
        cell_s = str(cell or "").strip()
        parts = cell_s.split()
        if len(parts) > 1 and all(_HEADER_KW_EXACT_RE.match(p) for p in parts):
            expanded_header.extend(parts)
        else:
            expanded_header.append(cell_s)

    new_ncols = len(expanded_header)
    col_expansion = new_ncols - len(candidate_row)

    metadata_row = None
    if _header_contains_balance_info(grid[0]):
        meta_cells = [str(c or "").strip() for c in grid[0]]
        meta_text = " ".join(c for c in meta_cells if c).strip()
        if meta_text:
            metadata_row = [meta_text] + [""] * (new_ncols - 1)

    new_data_rows = []
    for row in grid[candidate_idx + 1:]:
        if col_expansion > 0 and row:
            first_cell = str(row[0] or "").strip()
            date_match = re.match(r"^(\d{1,2}/\d{1,2})\s+(.*)", first_cell, re.DOTALL)
            if date_match and col_expansion == 1:
                new_row = [date_match.group(1), date_match.group(2).strip()] + list(row[1:])
            else:
                new_row = list(row) + [""] * col_expansion
            new_data_rows.append(new_row)
        else:
            new_data_rows.append(list(row))

    def pad(row, n):
        r = list(row)
        while len(r) < n:
            r.append("")
        return r[:n]

    new_grid = [pad(expanded_header, new_ncols)]
    if metadata_row is not None:
        new_grid.append(pad(metadata_row, new_ncols))
    for row in new_data_rows:
        new_grid.append(pad(row, new_ncols))

    return new_grid

# --------------------------
# Fix 3: Fused key-value rows in summary sections
# --------------------------

_FUSED_KV_RE = re.compile(
    r"^(.+?)(-?\d{1,3}(?:,\d{3})*(?:\.\d+)?%?)$",
    re.DOTALL,
)

def _fix_fused_keyvalue_rows(grid):
    if not grid or len(grid) < 2:
        return grid

    _DOLLAR_AMOUNT_RE = re.compile(r"\$\s*\d{1,3}(?:,\d{3})*\.\d{2}")
    _LONG_NUMBER_RE = re.compile(r"\d{7,}")

    ncols = len(grid[0])
    new_grid = [grid[0]]

    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        if not cells:
            new_grid.append(row)
            continue

        first = cells[0]
        rest_empty = all(c == "" for c in cells[1:])

        if not rest_empty or not first:
            new_grid.append(row)
            continue

        if _DOLLAR_AMOUNT_RE.search(first):
            new_grid.append(row)
            continue

        if _LONG_NUMBER_RE.search(first):
            new_grid.append(row)
            continue

        if re.search(r"#\s*[\dX]", first):
            new_grid.append(row)
            continue

        m = _FUSED_KV_RE.match(first)
        if not m:
            new_grid.append(row)
            continue

        label_raw = m.group(1)
        value = m.group(2).strip()

        if label_raw != label_raw.rstrip():
            new_grid.append(row)
            continue

        label = label_raw.strip()

        if not label or not value:
            new_grid.append(row)
            continue

        new_row = [""] * ncols
        new_row[0] = label
        new_row[ncols - 1] = value
        new_grid.append(new_row)

    return new_grid

# --------------------------
# Fix 4: PDF text-layer row-count patch
# --------------------------

def _extract_textlayer_rows(pdf_path: str, page_num: int):
    try:
        import pymupdf as fitz

        doc = fitz.open(pdf_path)
        page = doc[page_num]
        words = page.get_text("words")
        doc.close()

        if not words:
            return []

        lines_by_y = {}
        for w in words:
            x0, y0, word = float(w[0]), float(w[1]), w[4]
            bucket = None
            for existing_y in lines_by_y:
                if abs(existing_y - y0) <= 5:
                    bucket = existing_y
                    break
            if bucket is None:
                bucket = y0
            lines_by_y.setdefault(bucket, []).append((x0, word))

        sorted_lines = []
        for y in sorted(lines_by_y):
            line_words = sorted(lines_by_y[y], key=lambda t: t[0])
            sorted_lines.append([w for _, w in line_words])

        _MONTHS = r"(?:Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)"
        date_re = re.compile(
            r"^\d{1,2}/\d{2}(?:/\d{2,4})?$"
            r"|^\d{1,2}-\d{2}(?:-\d{2,4})?$"
            r"|^\d{4}-\d{2}-\d{2}$"
            r"|^" + _MONTHS + r"$",
            re.IGNORECASE,
        )
        month_re = re.compile(r"^" + _MONTHS + r"$", re.IGNORECASE)
        day_re   = re.compile(r"^\d{1,2}$")

        amount_re = re.compile(
            r"^-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{1,4})?$"
            r"|^\$-?\d{1,3}(?:,\d{3})*(?:\.\d{1,4})?$"
            r"|^-\s+\$\d{1,3}(?:,\d{3})*(?:\.\d{1,4})?$"
        )

        rows = []
        for line in sorted_lines:
            if len(line) < 2:
                continue

            date_str = None
            desc_start = None

            if date_re.match(line[0]):
                if month_re.match(line[0]) and len(line) > 1 and day_re.match(line[1]):
                    date_str = line[0] + " " + line[1]
                    desc_start = 2
                else:
                    date_str = line[0]
                    desc_start = 1
            else:
                continue

            if desc_start is None or desc_start >= len(line):
                continue

            remaining = line[desc_start:]
            post_date_str = ""
            if remaining and month_re.match(remaining[0]):
                if len(remaining) > 1 and day_re.match(remaining[1]):
                    post_date_str = remaining[0] + " " + remaining[1]
                    remaining = remaining[2:]
                elif len(remaining) > 0:
                    remaining = remaining[1:]
            elif remaining and date_re.match(remaining[0]) and not month_re.match(remaining[0]):
                post_date_str = remaining[0]
                remaining = remaining[1:]

            if len(remaining) < 2:
                continue

            if (len(remaining) >= 2
                    and remaining[-2] == "-"
                    and remaining[-1].startswith("$")):
                amount_candidate = remaining[-2] + " " + remaining[-1]
                desc_tokens = remaining[:-2]
            else:
                amount_candidate = remaining[-1]
                desc_tokens = remaining[:-1]

            if not amount_re.match(amount_candidate):
                continue

            desc = " ".join(desc_tokens).strip()
            if not desc:
                continue

            if not re.search(r"[A-Za-z]", desc):
                continue

            rows.append({"date": date_str, "post_date": post_date_str, "desc": desc, "amount": amount_candidate})

        return rows if len(rows) >= 2 else []

    except Exception as e:
        log.debug("_extract_textlayer_rows failed (page %d): %s", page_num, e)
        return []

def _jb_extract_checks_fallback(text_layer: str) -> List[Tuple[str, str, str]]:
    if not text_layer:
        return []
    m = re.search(
        r"Checks\s*\([^\n]*\n(.*?)(?=^Daily\s+Account\s+Balance\s*$)",
        text_layer,
        re.DOTALL | re.MULTILINE | re.IGNORECASE,
    )
    if not m:
        return []
    chunk = m.group(1)
    chunk = re.sub(
        r"^\s*Date\s+Number\s+Amount\s*$",
        "",
        chunk,
        flags=re.MULTILINE | re.IGNORECASE,
    )
    _triplet = re.compile(
        r"(\d{2}-\d{2})\s+(\*?\d+)\s+(\d{1,3}(?:,\d{3})*\.\d{2})"
    )
    out: List[Tuple[str, str, str]] = []
    seen = set()
    for t in _triplet.findall(chunk):
        if t not in seen:
            seen.add(t)
            out.append(t)
    return out

def _extract_jb_summary_sections(text_layer: str, needs_checks: bool = True, needs_dab: bool = True) -> str:
    if not text_layer:
        return ""

    _DATE_RE  = re.compile(r"^\d{2}-\d{2}$")
    _MONEY_RE = re.compile(r"^\d{1,3}(?:,\d{3})*\.\d{2}$")
    _CHECK_RE = re.compile(r"^\*?\d+$")

    lines = [l.strip() for l in text_layer.splitlines()]
    output = []

    if needs_checks:
        checks = []
        i = 0
        while i < len(lines):
            if lines[i].lower().startswith("checks"):
                i += 1
                while i < len(lines):
                    if "daily account balance" in lines[i].lower():
                        break
                    if lines[i] == "Date":
                        i += 1
                        dates = []
                        while i < len(lines) and _DATE_RE.match(lines[i]):
                            dates.append(lines[i]); i += 1
                        while i < len(lines) and lines[i] != "Number":
                            i += 1
                        i += 1
                        numbers = []
                        while i < len(lines):
                            if _CHECK_RE.match(lines[i]):
                                numbers.append(lines[i]); i += 1
                            elif lines[i] == "":
                                i += 1
                            else:
                                break
                        while i < len(lines) and lines[i] != "Amount":
                            i += 1
                        i += 1
                        amounts = []
                        while i < len(lines):
                            if _MONEY_RE.match(lines[i]):
                                amounts.append(lines[i]); i += 1
                            elif lines[i] == "":
                                i += 1
                            else:
                                break
                        for d, n, a in zip(dates, numbers, amounts):
                            checks.append((d, n, a))
                    else:
                        i += 1
                break
            i += 1

        if not checks and re.search(r"\bChecks\s*\(", text_layer, re.I):
            checks = _jb_extract_checks_fallback(text_layer)

        if checks:
            rows = "\n".join(
                "<tr><td>" + d + "</td><td>" + n + "</td><td>" + a + "</td></tr>"
                for d, n, a in checks
            )
            output.append("Checks")
            output.append(
                '<table class="jb-summary-checks">\n<tr><th>Date</th><th>Number</th><th>Amount</th></tr>\n'
                + rows + "\n</table>"
            )

    if needs_dab:
        balances = []
        i = 0
        while i < len(lines):
            if "daily account balance" in lines[i].lower():
                i += 1
                while i < len(lines):
                    if lines[i] == "Date":
                        i += 1
                        dates = []
                        while i < len(lines) and _DATE_RE.match(lines[i]):
                            dates.append(lines[i]); i += 1
                        while i < len(lines) and lines[i] != "Balance":
                            i += 1
                        i += 1
                        bals = []
                        while i < len(lines):
                            if _MONEY_RE.match(lines[i]):
                                bals.append(lines[i]); i += 1
                            elif lines[i] == "":
                                i += 1
                            else:
                                break
                        for d, b in zip(dates, bals):
                            balances.append((d, b))
                    else:
                        i += 1
                break
            i += 1

        if balances:
            rows = "\n".join(
                "<tr><td>" + d + "</td><td>" + b + "</td></tr>"
                for d, b in balances
            )
            output.append("Daily Account Balance")
            output.append(
                "<table>\n<tr><th>Date</th><th>Balance</th></tr>\n"
                + rows + "\n</table>"
            )

    return "\n\n".join(output)

def _patch_ocr_with_textlayer(page_md: str, pdf_path: str, page_num: int) -> str:
    if not page_md or "<table" not in page_md.lower():
        return page_md

    try:
        tl_rows = _extract_textlayer_rows(pdf_path, page_num)
        if not tl_rows:
            return page_md

        def _norm(s):
            return re.sub(r"\s+", " ", str(s or "").strip().lower())

        tl_freq = {}
        for r in tl_rows:
            key = (_norm(r["date"]), _norm(r["desc"]), _norm(r["amount"]))
            tl_freq[key] = tl_freq.get(key, 0) + 1

        table_pattern = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)
        result = page_md

        for tbl_match in table_pattern.finditer(page_md):
            table_html = tbl_match.group(0)

            p = TableGridParser()
            p.feed(table_html)
            grid = _build_grid(p.rows)
            if len(grid) < 2:
                continue

            header = [str(c or "").strip().upper() for c in grid[0]]
            date_col = desc_col = amt_col = None
            for ci, h in enumerate(header):
                if re.search(r"\bDATE\b", h) and date_col is None:
                    date_col = ci
                elif re.search(r"\b(DESCRIPTION|DETAILS?|NARRATION|PARTICULARS?)\b", h) and desc_col is None:
                    desc_col = ci
                elif re.search(r"\b(AMOUNT|DEBIT|CREDIT|DR|CR)\b", h) and amt_col is None:
                    amt_col = ci

            if date_col is None or desc_col is None or amt_col is None:
                continue

            ocr_freq = {}
            ocr_rows_indexed = []
            for ri, row in enumerate(grid[1:], start=1):
                cells = [str(c or "").strip() for c in row]
                if len(cells) <= max(date_col, desc_col, amt_col):
                    continue
                d = _norm(cells[date_col])
                desc = _norm(cells[desc_col])
                amt = _norm(cells[amt_col])
                if not d or not desc:
                    continue
                key = (d, desc, amt)
                ocr_freq[key] = ocr_freq.get(key, 0) + 1
                ocr_rows_indexed.append((ri, key))

            overlap = set(ocr_freq.keys()) & set(tl_freq.keys())

            _ocr_dates = [
                _norm(str(row[date_col] or ""))
                for row in grid[1:]
                if len(row) > date_col and str(row[date_col] or "").strip()
            ]
            _tl_dates = [_norm(r["date"]) for r in tl_rows]
            _slash_re  = re.compile(r"^\d{1,2}/\d{2}")
            _hyphen_re = re.compile(r"^\d{1,2}-\d{2}")
            def _date_fmt(dates):
                if any(_slash_re.match(d) for d in dates):  return "slash"
                if any(_hyphen_re.match(d) for d in dates): return "hyphen"
                return "other"
            ocr_fmt = _date_fmt(_ocr_dates)
            tl_fmt  = _date_fmt(_tl_dates)
            date_fmt_match = (ocr_fmt == tl_fmt) or "other" in (ocr_fmt, tl_fmt)

            to_inject = {}
            to_inject_new = {}

            for key in tl_freq:
                ocr_count = ocr_freq.get(key, 0)
                tl_count = tl_freq[key]
                if tl_count > ocr_count:
                    missing = tl_count - ocr_count
                    if ocr_count > 0:
                        if overlap:
                            to_inject[key] = missing
                    else:
                        if date_fmt_match:
                            tl_row_data = next(
                                (r for r in tl_rows
                                 if (_norm(r["date"]), _norm(r["desc"]), _norm(r["amount"])) == key),
                                None
                            )
                            if tl_row_data:
                                to_inject_new[key] = (missing, tl_row_data)

            if not to_inject and not to_inject_new:
                continue

            new_grid = [grid[0]]
            for ri, row in enumerate(grid[1:], start=1):
                new_grid.append(row)
                cells = [str(c or "").strip() for c in row]
                if len(cells) <= max(date_col, desc_col, amt_col):
                    continue
                d = _norm(cells[date_col])
                desc = _norm(cells[desc_col])
                amt = _norm(cells[amt_col])
                key = (d, desc, amt)
                if key in to_inject and to_inject[key] > 0:
                    last_occ = max(idx for idx, k in ocr_rows_indexed if k == key)
                    if ri == last_occ:
                        for _ in range(to_inject[key]):
                            new_grid.append(list(row))
                        to_inject[key] = 0

            new_table_html = _grid_to_html(new_grid)
            result = result.replace(table_html, new_table_html, 1)

            if to_inject_new:
                ncols = len(grid[0])
                header_row = grid[0]

                post_date_col = None
                for ci, h in enumerate(header_row):
                    hh = str(h or "").strip().upper()
                    if "POST" in hh and "DATE" in hh:
                        post_date_col = ci
                        break

                new_rows = []
                for key, (count, tl_row_data) in to_inject_new.items():
                    for _ in range(count):
                        new_row = [""] * ncols
                        new_row[date_col] = tl_row_data["date"]
                        new_row[desc_col] = tl_row_data["desc"]
                        new_row[amt_col]  = tl_row_data["amount"]
                        if post_date_col is not None:
                            new_row[post_date_col] = tl_row_data.get("post_date", "")
                        new_rows.append(new_row)
                        log.info(
                            "page %d: new table row from text layer: %s %s",
                            page_num, tl_row_data["date"], tl_row_data["desc"][:40]
                        )

                if new_rows:
                    extra_grid = [header_row] + new_rows
                    extra_html = "\n\n" + _grid_to_html(extra_grid)
                    insert_pos = result.find(new_table_html) + len(new_table_html)
                    result = result[:insert_pos] + extra_html + result[insert_pos:]

        if tl_rows:
            _has_txn_table = False
            for _tbl in table_pattern.finditer(result):
                _p2 = TableGridParser()
                _p2.feed(_tbl.group(0))
                _g2 = _build_grid(_p2.rows)
                if len(_g2) < 2:
                    continue
                _h2 = [str(c or "").strip().upper() for c in _g2[0]]
                if (any(re.search(r"\bDATE\b", x) for x in _h2) and
                        any(re.search(r"\b(DESCRIPTION|DETAILS?|NARRATION|PARTICULARS?)\b", x) for x in _h2)):
                    _has_txn_table = True
                    break

            if not _has_txn_table:
                _has_post = any(r.get("post_date") for r in tl_rows)
                if _has_post:
                    _chdr = ["Date", "Post Date", "Transaction Description", "Amount"]
                    _di2, _pi2, _xi2, _ai2 = 0, 1, 2, 3
                else:
                    _chdr = ["Date", "Transaction Description", "Amount"]
                    _di2, _xi2, _ai2 = 0, 1, 2
                _cnew_rows = []
                for r in tl_rows:
                    _crow = [""] * len(_chdr)
                    _crow[_di2] = r["date"]
                    _crow[_xi2] = r["desc"]
                    _crow[_ai2] = r["amount"]
                    if _has_post:
                        _crow[_pi2] = r.get("post_date", "")
                    _cnew_rows.append(_crow)
                result = _grid_to_html([_chdr] + _cnew_rows) + "\n\n" + result
                log.info("page %d: Case C — new table (%d rows) from text layer",
                         page_num, len(_cnew_rows))

        return result

    except Exception as e:
        log.warning("_patch_ocr_with_textlayer failed (page %d): %s", page_num, e)
        return page_md

# --------------------------
# Fix 5: Mid-table separator row reconstruction
# --------------------------

_DATE_RE = re.compile(r"^\d{1,2}/\d{2}(?:/\d{2,4})?$")
_SPLIT_AMOUNT_RE = re.compile(
    r"^-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{1,4})?$|^\$-?\d{1,3}(?:,\d{3})*(?:\.\d{1,4})?$"
)

def _reconstruct_separator_rows(grid):
    if not grid or len(grid) < 2:
        return grid

    ncols = len(grid[0])
    if ncols < 2:
        return grid

    new_grid = [grid[0]]

    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < ncols:
            cells.append("")

        non_empty = [(i, c) for i, c in enumerate(cells) if c]

        if len(non_empty) == 0:
            new_grid.append(row)
            continue

        first_idx, first_val = non_empty[0]

        if _DATE_RE.match(first_val):
            new_grid.append(row)
            continue

        if not re.search(r"[A-Za-z]", first_val):
            new_grid.append(row)
            continue

        if len(non_empty) == 1:
            new_row = [""] * ncols
            new_row[0] = first_val
            new_grid.append(new_row)
            continue

        trailing = [val for _, val in non_empty[1:]]
        all_trailing_are_digit_fragments = all(
            re.fullmatch(r"\d{1,4}", v) for v in trailing
        )

        if not all_trailing_are_digit_fragments:
            new_grid.append(row)
            continue

        reconstructed = "".join(val for _, val in non_empty).strip()
        new_row = [""] * ncols
        new_row[0] = reconstructed
        new_grid.append(new_row)

    return new_grid

# --------------------------
# Normalizer entry point
# --------------------------

def _merge_split_rows(grid):
    if not grid or len(grid) < 3:
        return grid

    ncols = len(grid[0])
    if ncols < 3:
        return grid

    header = [str(c or "").strip().upper() for c in grid[0]]
    date_col = desc_col = bal_col = None
    debit_cols = []
    credit_cols = []

    for ci, h in enumerate(header):
        if re.search(r"\bDATE\b", h) and date_col is None:
            date_col = ci
        if re.search(r"\b(DESCRIPTION|DETAILS?|NARRATION|PARTICULARS?|TRANSACTION)\b", h) and desc_col is None:
            desc_col = ci
        if re.search(r"\bBALANCE\b", h) and bal_col is None:
            bal_col = ci
        if re.search(r"\b(DEBIT|DEBITS|DR|WITHDRAWAL|SUBTRACTIONS?)\b", h):
            debit_cols.append(ci)
        if re.search(r"\b(CREDIT|CREDITS|CR|DEPOSIT|ADDITIONS?)\b", h):
            credit_cols.append(ci)

    if date_col is None or desc_col is None:
        return grid
    if not debit_cols and not credit_cols:
        return grid

    money_cols = debit_cols + credit_cols
    _MONEY_RE2 = re.compile(r"^-?\$?\d{1,3}(?:,\d{3})*\.\d{1,4}$")
    _DATE_RE2  = re.compile(r"^\d{1,2}/\d{2}(?:/\d{2,4})?$|^\d{1,2}-\d{2}(?:-\d{2,4})?$")
    _FRAGMENT_RE = re.compile(r"^[^\s\.]{1,6}$")

    new_grid = [grid[0]]
    i = 1
    while i < len(grid):
        row = [str(c or "").strip() for c in grid[i]]
        while len(row) < ncols:
            row.append("")

        has_desc    = bool(row[desc_col])
        no_date     = not row[date_col]
        no_money    = all(not row[c] for c in money_cols)
        bal_is_frag = (bal_col is not None and
                       (_FRAGMENT_RE.match(row[bal_col]) or not row[bal_col]))

        if has_desc and no_date and no_money and bal_is_frag and (i + 1) < len(grid):
            next_row = [str(c or "").strip() for c in grid[i + 1]]
            while len(next_row) < ncols:
                next_row.append("")

            next_has_date  = bool(next_row[date_col]) and _DATE_RE2.match(next_row[date_col])
            next_has_money = any(bool(next_row[c]) for c in money_cols)

            if next_has_date and next_has_money:
                merged = list(next_row)
                if next_row[desc_col]:
                    merged[desc_col] = row[desc_col] + " " + next_row[desc_col]
                else:
                    merged[desc_col] = row[desc_col]
                new_grid.append(merged)
                i += 2
                continue

        new_grid.append(row)
        i += 1

    return new_grid

def _extract_fused_desc_amount(grid):
    if not grid or len(grid) < 2:
        return grid

    ncols = len(grid[0])
    header = [str(c or "").strip().upper() for c in grid[0]]

    date_col = desc_col = None
    debit_cols = []
    credit_cols = []
    for ci, h in enumerate(header):
        if re.search(r"\bDATE\b", h) and date_col is None:
            date_col = ci
        if re.search(r"\b(DESCRIPTION|DETAILS?|NARRATION|PARTICULARS?|TRANSACTION)\b", h) and desc_col is None:
            desc_col = ci
        if re.search(r"\b(DEBIT|DEBITS|DR|WITHDRAWAL|SUBTRACTIONS?)\b", h):
            debit_cols.append(ci)
        if re.search(r"\b(CREDIT|CREDITS|CR|DEPOSIT|ADDITIONS?)\b", h):
            credit_cols.append(ci)

    if date_col is None or desc_col is None or not debit_cols:
        return grid

    money_cols = debit_cols + credit_cols
    _TRAILING_AMT = re.compile(r"^(.+?)\s+(-?\d{1,3}(?:,\d{3})*\.\d{2})$")
    debit_col = debit_cols[0]

    new_grid = [grid[0]]
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < ncols:
            cells.append("")

        desc = cells[desc_col]
        no_money = all(not cells[c] for c in money_cols)
        has_date = bool(cells[date_col])

        if desc and no_money and has_date:
            m = _TRAILING_AMT.match(desc)
            if m:
                cells = list(cells)
                cells[desc_col] = m.group(1).strip()
                cells[debit_col] = m.group(2)
                new_grid.append(cells)
                continue

        new_grid.append(cells)

    return new_grid

def _is_junk_table(grid):
    if not grid or len(grid) < 2:
        return False
    ncols = len(grid[0])
    if ncols != 1:
        return False
    header_text = str(grid[0][0] or "").strip().upper()
    if "CUSTOMER INFORMATION" in header_text:
        data_rows = grid[1:]
        if all(len(str(r[0] or "").strip()) <= 10 for r in data_rows):
            return True
    return False

def _split_fused_multicolumn_header(grid):
    if not grid or len(grid) < 2:
        return grid

    ncols = len(grid[0])
    if ncols < 2:
        return grid

    first_header = str(grid[0][0] or "").strip()
    parts = first_header.split()
    kw_hits = [p for p in parts if _HEADER_KW_EXACT_RE.match(p)]
    if len(kw_hits) < 2:
        return grid

    rest_headers = [str(c or "").strip() for c in grid[0][1:]]
    if not all(_HEADER_KW_EXACT_RE.match(h) for h in rest_headers if h):
        return grid

    new_header_cols = []
    non_kw_parts = []
    for p in parts:
        if _HEADER_KW_EXACT_RE.match(p):
            if non_kw_parts:
                new_header_cols.append(" ".join(non_kw_parts))
                non_kw_parts = []
            new_header_cols.append(p)
        else:
            non_kw_parts.append(p)
    if non_kw_parts:
        new_header_cols.append(" ".join(non_kw_parts))

    new_header = new_header_cols + rest_headers
    new_ncols = len(new_header)
    extra_cols = new_ncols - ncols

    _DATE_COL_RE   = re.compile(r"\bDATE\b", re.IGNORECASE)
    _CARD_COL_RE   = re.compile(r"\bCARD\b", re.IGNORECASE)
    _DESC_COL_RE   = re.compile(r"\b(DESCRIPTION|DETAILS?|NARRATION|PARTICULARS?)\b", re.IGNORECASE)
    _MONEY_COL_RE  = re.compile(r"\b(DEPOSIT|WITHDRAWAL|DEBIT|CREDIT|AMOUNT|ADDITION|SUBTRACTION)S?\b", re.IGNORECASE)

    new_date_col = next((i for i,h in enumerate(new_header) if _DATE_COL_RE.search(h)), None)
    new_desc_col = next((i for i,h in enumerate(new_header) if _DESC_COL_RE.search(h)), None)
    new_card_col = next((i for i,h in enumerate(new_header) if _CARD_COL_RE.search(h)), None)

    if new_date_col is None or new_desc_col is None:
        return grid

    _DATE_PREFIX = re.compile(r"^(\d{1,2}/\d{2}(?:/\d{2,4})?)\s+(.*)", re.DOTALL)
    _CARD_SUFFIX = re.compile(r"^(.*?)\s+(\d{4})$", re.DOTALL)

    def pad(row, n):
        r = list(row)
        while len(r) < n: r.append("")
        return r[:n]

    new_grid = [pad(new_header, new_ncols)]
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < ncols: cells.append("")

        fused_cell = cells[0]
        rest_cells = cells[1:]

        date_val = ""
        desc_val = fused_cell
        card_val = ""

        dm = _DATE_PREFIX.match(fused_cell)
        if dm:
            date_val = dm.group(1)
            desc_val = dm.group(2).strip()

        if new_card_col is not None:
            cm = _CARD_SUFFIX.match(desc_val)
            if cm:
                desc_val = cm.group(1).strip()
                card_val = cm.group(2)

        new_row = [""] * new_ncols
        new_row[new_date_col] = date_val
        new_row[new_desc_col] = desc_val
        if new_card_col is not None:
            new_row[new_card_col] = card_val
        money_col_indices = [i for i,h in enumerate(new_header) if _MONEY_COL_RE.search(h)]
        for mi, ri in enumerate(range(len(rest_cells))):
            if mi < len(money_col_indices):
                new_row[money_col_indices[mi]] = rest_cells[ri]

        new_grid.append(new_row)

    return new_grid

def _normalize_daily_balance_table(grid):
    if not grid or len(grid) < 2:
        return grid

    header = [str(c or "").strip().upper() for c in grid[0]]
    ncols = len(header)

    if ncols < 4 or ncols % 2 != 0:
        return grid

    half = ncols // 2
    date_half  = header[:half]
    bal_half   = header[half:]

    if not all(h == "DATE" for h in date_half):
        return grid
    if not all(h == "BALANCE" for h in bal_half):
        return grid

    new_header = []
    for i in range(half):
        new_header.append("DATE")
        new_header.append("BALANCE")

    new_rows = []
    _DATE_RE3 = re.compile(r"^\d{1,2}/\d{2}(?:/\d{2,4})?$")

    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < ncols:
            cells.append("")

        date_cells = [cells[0]]
        bal_cells  = cells[1:]

        first = date_cells[0]
        tokens = re.split(r"[\n\r\s]+", first)
        date_tokens = [t.strip() for t in tokens if t.strip() and _DATE_RE3.match(t.strip())]
        if len(date_tokens) >= 2:
            stacked = date_tokens
        else:
            stacked = date_cells

        new_row = [""] * ncols
        for i, date_val in enumerate(stacked):
            if not _DATE_RE3.match(date_val):
                continue
            bal_val = bal_cells[i] if i < len(bal_cells) else ""
            new_row[i * 2]     = date_val
            new_row[i * 2 + 1] = bal_val
        new_rows.append(new_row)

    if not new_rows:
        return grid

    return [new_header] + new_rows

def _normalize_checks_paid_table(grid):
    if not grid or len(grid) < 2:
        return grid

    ncols = len(grid[0])
    if ncols < 2:
        return grid

    first_h = str(grid[0][0] or "").strip()
    _CHECKS_HDR = re.compile(r"^(DATE\s+CHECK\s+#\s*)+$", re.IGNORECASE)
    if not _CHECKS_HDR.match(first_h):
        return grid

    rest_h = [str(c or "").strip().upper() for c in grid[0][1:]]
    if not all(h in ("AMOUNT", "") for h in rest_h if h):
        return grid

    n_groups = len(re.findall(r"\bDATE\b", first_h, re.IGNORECASE))
    if n_groups < 1:
        return grid

    new_header = []
    for _ in range(n_groups):
        new_header.extend(["DATE", "CHECK #", "AMOUNT"])

    _DATE_RE = re.compile(r"^\d{1,2}/\d{2}$")

    new_rows = [new_header]
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < ncols:
            cells.append("")

        fused_data = cells[0]
        amounts    = cells[1:]

        tokens = fused_data.split()
        groups = []
        current = []
        for tok in tokens:
            if _DATE_RE.match(tok) and current:
                groups.append(current)
                current = [tok]
            else:
                current.append(tok)
        if current and current[0]:
            groups.append(current)

        new_row = [""] * len(new_header)
        for i, grp in enumerate(groups):
            if i >= n_groups:
                break
            new_row[i * 3]     = grp[0]
            new_row[i * 3 + 1] = " ".join(grp[1:]).strip()
            new_row[i * 3 + 2] = amounts[i] if i < len(amounts) else ""

        new_rows.append(new_row)

    return new_rows

_JB_SECTION_HDR = re.compile(
    r"^(Deposits?|Withdrawals?|Checks?(?:\s+Paid)?|Daily\s+Account\s+Balance)"
    r"\s*(?:\(cont\.?\))?\s*$",
    re.IGNORECASE,
)
_JB_COL_HDR = re.compile(
    r"^Date\s+(Description|Number)\s+Amount\s*$"
    r"|^Date\s+(?:Number\s+)?(?:Balance|Amount)\s*$",
    re.IGNORECASE,
)
_JB_DATE_DD  = re.compile(r"^\d{2}-\d{2}\s+")
_JB_TXN_ROW  = re.compile(r"^(\d{2}-\d{2})\s+(.+?)\s+(-?\d{1,3}(?:,\d{3})*\.\d{2})\s*$")
_JB_BAL_ROW  = re.compile(r"^(\d{2}-\d{2})\s+(\d{1,3}(?:,\d{3})*\.\d{2})\s*$")

def _jb_rows_to_html(header_cols, rows):
    th    = "".join("<th>" + h + "</th>" for h in header_cols)
    parts = ["<table>", "<tr>" + th + "</tr>"]
    for row in rows:
        td = "".join("<td>" + str(row.get(h, "")) + "</td>" for h in header_cols)
        parts.append("<tr>" + td + "</tr>")
    parts.append("</table>")
    return "\n".join(parts)

def _jb_section_has_table(lines, start, end):
    return any("<table" in l.lower() for l in lines[start:end])

def _find_first_data_row(lines, start):
    for i in range(start, min(start + 20, len(lines))):
        if lines[i].strip():
            return i
    return None

def convert_plaintext_bank_sections(text: str) -> str:
    lines = text.splitlines()
    out   = []
    i     = 0

    while i < len(lines):
        line = lines[i].strip()

        if not _JB_SECTION_HDR.match(line):
            out.append(lines[i])
            i += 1
            continue

        section_title = line
        j = i + 1

        while j < len(lines) and not lines[j].strip():
            j += 1

        if j >= len(lines) or not _JB_COL_HDR.match(lines[j].strip()):
            out.append(lines[i])
            i += 1
            continue

        col_hdr_line = lines[j].strip()
        data_start   = j + 1

        first_data_idx = _find_first_data_row(lines, data_start)

        if first_data_idx is None or not _JB_DATE_DD.match(lines[first_data_idx].strip()):
            out.append(lines[i])
            i += 1
            continue

        section_end = len(lines)
        for k in range(data_start, len(lines)):
            l = lines[k].strip()
            if (l != section_title and _JB_SECTION_HDR.match(l)
                    or l.startswith("---page-separator")
                    or l.startswith("Page:")):
                section_end = k
                break

        if _jb_section_has_table(lines, i, section_end):
            out.append(lines[i])
            i += 1
            continue

        parts_upper = col_hdr_line.upper().split()
        if len(parts_upper) == 2 and parts_upper[1] == "BALANCE":
            header_cols = ["Date", "Balance"]
        elif "NUMBER" in parts_upper:
            header_cols = ["Date", "Number", "Amount"]
        else:
            header_cols = ["Date", "Description", "Amount"]

        out.append(section_title)
        rows    = []
        current = None
        k       = data_start

        while k < section_end:
            raw      = lines[k]
            row_line = raw.strip()

            if not row_line:
                k += 1
                continue

            if (_JB_SECTION_HDR.match(row_line)
                    or row_line.startswith("---page-separator")
                    or row_line.startswith("Page:")):
                break

            mb = _JB_BAL_ROW.match(row_line)
            if mb and header_cols == ["Date", "Balance"]:
                if current:
                    rows.append(current)
                current = {"Date": mb.group(1), "Balance": mb.group(2)}
                k += 1
                continue

            mt = _JB_TXN_ROW.match(row_line)
            if mt:
                if current:
                    rows.append(current)
                desc_key = "Description" if "Description" in header_cols else "Number"
                current  = {
                    "Date":    mt.group(1),
                    desc_key:  mt.group(2).strip(),
                    "Amount":  mt.group(3),
                }
                k += 1
                continue

            if current and row_line:
                desc_key = "Description" if "Description" in header_cols else "Number"
                if desc_key in current:
                    current[desc_key] += " " + row_line
                k += 1
                continue

            k += 1

        if current:
            rows.append(current)

        if rows:
            out.append(_jb_rows_to_html(header_cols, rows))

        i = section_end
        continue

    return "\n".join(out)

# --------------------------
# Navy Federal full-page text-layer parser (Fix NF-1)
# --------------------------

def _is_nfcu_document(pdf_path: str) -> bool:
    try:
        import pymupdf as fitz
        doc = fitz.open(pdf_path)
        pages_to_check = min(2, len(doc))
        text = ""
        for i in range(pages_to_check):
            text += "\n" + (doc[i].get_text() or "")
        doc.close()
        t = text.lower()
        return (
            ("statement of account" in t)
            and ("access no." in t)
            and ("routing number" in t)
            and ("navy federal" in t or "navyfederal.org" in t)
        )
    except Exception:
        return False


def _parse_nfcu_page(pdf_path: str, page_num: int) -> str:
    try:
        import pymupdf as fitz

        doc = fitz.open(pdf_path)
        if page_num >= len(doc):
            doc.close()
            return ""
        page = doc[page_num]
        page_text = page.get_text() or ""
        words = page.get_text("words") or []
        doc.close()

        if not page_text or not words:
            return ""

        t = page_text.lower()
        is_nfcu = (
            ("statement of account" in t)
            and (("access no." in t) or ("routing number" in t) or ("navy federal" in t) or ("navyfederal.org" in t))
        )
        if not is_nfcu:
            return ""

        buckets = []
        for w in words:
            if len(w) < 5:
                continue
            x0 = float(w[0])
            y0 = float(w[1])
            token = w[4].strip()
            if not token:
                continue
            bi = None
            for i, (yb, _) in enumerate(buckets):
                if abs(yb - y0) <= 2.0:
                    bi = i
                    break
            if bi is None:
                buckets.append((y0, [(x0, token)]))
            else:
                buckets[bi][1].append((x0, token))

        lines = []
        for y, arr in sorted(buckets, key=lambda x: x[0]):
            toks = [tok for _, tok in sorted(arr, key=lambda x: x[0])]
            xs = [x for x, _ in sorted(arr, key=lambda x: x[0])]
            lines.append((y, xs, toks, " ".join(toks)))

        date_re = re.compile(r"^\d{2}-\d{2}$")
        money_re = re.compile(r"^[\d,]+\.\d{2}-?$")
        acct_re = re.compile(r"^(Business Checking|Mbr Business Savings)\s*-\s*(\d+)")
        stop_markers = (
            "Items Paid",
            "Average Daily Balance",
            "2024 Year to Date",
            "Disclosure",
            "What to Do",
            "Errors",
            "Payments",
            "SAVINGS DIVIDENDS",
            "REMITTANCE RECEIVED",
            "DEPOSIT VOUCHER",
            "ACCOUNT NUMBER",
            "MARK \"X\"",
            "ADDRESS/ORDER",
            "ITEMS ON REVERSE",
            "CHANGE OF ADDRESS",
            "PLEASE PRINT",
            "RANK/RATE",
            "PO BOX",
            "MERRIFIELD",
            "Questions about this Statement",
        )

        def parse_account_rows(start_idx):
            rows = []
            i = start_idx
            pending = None
            while i < len(lines):
                _, _, toks, text = lines[i]
                if not text:
                    i += 1
                    continue

                if acct_re.match(text) and i != start_idx:
                    break
                if any(text.startswith(s) for s in stop_markers):
                    break
                upper_text = text.upper()
                if (
                    "REMITTANCE RECEIVED" in upper_text
                    or "DEPOSIT VOUCHER" in upper_text
                    or "ACCOUNT NUMBER" in upper_text
                    or "ADDRESS/ORDER" in upper_text
                    or "ITEMS ON REVERSE" in upper_text
                    or "CHANGE OF ADDRESS" in upper_text
                    or "PLEASE PRINT" in upper_text
                ):
                    break
                if text in ("Checking", "Savings"):
                    break
                if text.startswith("Date Transaction Detail"):
                    i += 1
                    continue

                def flush_pending():
                    nonlocal pending
                    if pending is not None:
                        rows.append(pending)
                        pending = None

                if toks and date_re.match(toks[0]):
                    flush_pending()
                    date = toks[0]
                    rest = toks[1:]
                    mvals = [tok for tok in rest if money_re.match(tok)]
                    desc_tokens = [tok for tok in rest if not money_re.match(tok)]

                    amount = ""
                    balance = ""
                    if len(mvals) >= 2:
                        amount = mvals[-2]
                        balance = mvals[-1]
                    elif len(mvals) == 1:
                        balance = mvals[-1]

                    pending = {
                        "date": date,
                        "desc": " ".join(desc_tokens).strip(),
                        "amount": amount,
                        "balance": balance,
                    }
                else:
                    if pending is not None:
                        mvals = [tok for tok in toks if money_re.match(tok)]
                        desc_tokens = [tok for tok in toks if not money_re.match(tok)]

                        upper = text.upper()
                        if pending["balance"] and (
                            "REMITTANCE" in upper
                            or "DEPOSIT VOUCHER" in upper
                            or "ACCOUNT NUMBER" in upper
                            or "ADDRESS/ORDER" in upper
                            or "ITEMS ON REVERSE" in upper
                            or "PO BOX" in upper
                        ):
                            break

                        if (
                            ("BEGINNING BALANCE" in pending["desc"].upper() or "ENDING BALANCE" in pending["desc"].upper())
                            and not mvals
                            and not (toks and date_re.match(toks[0]))
                        ):
                            break
                        if desc_tokens:
                            pending["desc"] = (pending["desc"] + " " + " ".join(desc_tokens)).strip()
                        if len(mvals) >= 2 and (not pending["amount"] or not pending["balance"]):
                            if not pending["amount"]:
                                pending["amount"] = mvals[-2]
                            if not pending["balance"]:
                                pending["balance"] = mvals[-1]
                        elif len(mvals) == 1 and not pending["balance"]:
                            pending["balance"] = mvals[-1]
                i += 1

            if pending is not None:
                rows.append(pending)
            cleaned = [r for r in rows if r["date"] and r["desc"] and (r["amount"] or r["balance"])]
            return cleaned, i

        out = []
        i = 0
        while i < len(lines):
            _, _, _, text = lines[i]
            if not text:
                i += 1
                continue

            m = acct_re.match(text)
            if m:
                acct_name = m.group(1)
                acct_no = m.group(2)
                title = f"{acct_name} - {acct_no}"
                if i + 1 < len(lines) and "Continued" in lines[i + 1][3]:
                    title += " (Continued from previous page)"
                out.append(f"<b>{title}</b>")
                out.append("<table>")
                out.append("<tr><th>Date</th><th>Transaction Detail</th><th>Amount($)</th><th>Balance($)</th></tr>")
                rows, i2 = parse_account_rows(i + 1)
                for r in rows:
                    out.append(
                        f"<tr><td>{r['date']}</td><td>{r['desc']}</td><td>{r['amount']}</td><td>{r['balance']}</td></tr>"
                    )
                out.append("</table>")
                i = i2
                continue

            if text in ("Checking", "Savings"):
                out.append(f"<h3>{text}</h3>")
            elif text.startswith("Items Paid"):
                out.append("<b>Items Paid</b>")
            i += 1

        return "\n".join(out).strip()

    except Exception as e:
        log.warning("_parse_nfcu_page failed (page %d): %s", page_num, e)
        return ""

def _extract_nfcu_summary_table(pdf_path: str, page_num: int) -> str:
    try:
        import pymupdf as fitz

        doc = fitz.open(pdf_path)
        if page_num >= len(doc):
            doc.close()
            return ""
        page = doc[page_num]
        words = page.get_text("words") or []
        doc.close()
        if not words:
            return ""

        buckets = []
        for w in words:
            if len(w) < 5:
                continue
            x0 = float(w[0])
            y0 = float(w[1])
            tok = str(w[4] or "").strip()
            if not tok:
                continue
            bi = None
            for i, (yb, _) in enumerate(buckets):
                if abs(yb - y0) <= 2.0:
                    bi = i
                    break
            if bi is None:
                buckets.append((y0, [(x0, tok)]))
            else:
                buckets[bi][1].append((x0, tok))

        lines = []
        for y, arr in sorted(buckets, key=lambda x: x[0]):
            arr2 = sorted(arr, key=lambda x: x[0])
            toks = [t for _, t in arr2]
            text = " ".join(toks).strip()
            lines.append((y, toks, text))

        anchor_idx = None
        for i, (_, _, text) in enumerate(lines):
            tl = text.lower()
            if "summary of your deposit accounts" in tl or ("summary" in tl and "deposit accounts" in tl):
                anchor_idx = i
                break
        if anchor_idx is None:
            return ""

        money_re = re.compile(r"^\$?[\d,]+\.\d{2}-?$")
        acct_no_re = re.compile(r"^\d{8,12}$")
        stop_re = re.compile(
            r"(business checking\s*-|mbr business savings\s*-|date\s+transaction\s+detail|items paid)",
            re.IGNORECASE,
        )

        rows = []
        pending_account = ""
        account_name_re = re.compile(
            r"^(business checking|mbr business savings|checking|savings|money market|certificate).*$",
            re.IGNORECASE,
        )

        for _, toks, text in lines[anchor_idx + 1:]:
            if not text:
                continue
            if stop_re.search(text):
                break
            if not toks:
                continue
            t0 = toks[0].lower()
            tl = text.lower()

            if (
                "previous" in tl
                or "deposits" in tl
                or "withdrawals" in tl
                or "ending" in tl
                or "dividends" in tl
            ) and not any(money_re.match(t) for t in toks):
                continue

            if account_name_re.match(text.strip()) and not any(money_re.match(t) for t in toks):
                pending_account = text.strip()
                continue

            mvals = [t.replace("$", "") for t in toks if money_re.match(t)]
            acct_tokens = [t for t in toks if acct_no_re.match(t)]

            if t0 == "totals" and len(mvals) >= 5:
                rows.append(["Totals", mvals[0], mvals[1], mvals[2], mvals[3], mvals[4]])
                continue

            if acct_tokens and len(mvals) >= 5:
                acct = acct_tokens[0]
                acct_label = (pending_account + " - " + acct).strip(" -") if pending_account else acct
                rows.append([acct_label, mvals[0], mvals[1], mvals[2], mvals[3], mvals[4]])
                pending_account = ""
                continue

        if not rows:
            return ""

        hdr = [
            "Account",
            "Previous Balance",
            "Deposits/Credits",
            "Withdrawals/Debits",
            "Ending Balance",
            "YTD Dividends",
        ]
        return _grid_to_html([hdr] + rows)
    except Exception:
        return ""

def _replace_nfcu_summary_table(page_md: str, summary_table_html: str) -> str:
    if not page_md or not summary_table_html:
        return page_md
    table_pattern = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)
    lower = page_md.lower()
    anchor = lower.find("summary of your deposit accounts")

    if anchor >= 0:
        for m in table_pattern.finditer(page_md):
            if m.start() > anchor:
                old_table = m.group(0)
                return page_md.replace(old_table, summary_table_html, 1)

    for m in table_pattern.finditer(page_md):
        tbl = m.group(0)
        p = TableGridParser()
        p.feed(tbl)
        g = _build_grid(p.rows)
        if not g:
            continue
        h = " ".join(str(c or "").strip().lower() for c in g[0])
        if (
            "previous" in h
            and "deposits" in h
            and "withdrawals" in h
            and "ending" in h
            and "dividends" in h
        ):
            return page_md.replace(tbl, summary_table_html, 1)

    return page_md

def _split_fused_date_transaction_header(grid):
    if not grid or len(grid) < 2:
        return grid
    ncols = max(len(r) for r in grid if isinstance(r, list))
    if ncols < 3:
        return grid

    header_row_idx = None
    fused_col_idx = None
    for ri in range(min(4, len(grid))):
        r = [str(c or "").strip() for c in (grid[ri] + [""] * (ncols - len(grid[ri])))]
        for ci, c in enumerate(r):
            cc = re.sub(r"\s+", " ", c).strip().lower()
            if cc == "date transaction detail":
                row_text = " ".join(re.sub(r"\s+", " ", x).strip().lower() for x in r)
                if "amount" in row_text and "balance" in row_text:
                    header_row_idx = ri
                    fused_col_idx = ci
                    break
        if header_row_idx is not None:
            break
    if header_row_idx is None or fused_col_idx is None:
        return grid

    date_tok = re.compile(r"^\d{1,2}(?:[-/])\d{2}(?:[-/]\d{2,4})?$")

    new_grid = []
    for ri, row in enumerate(grid):
        cells = [str(c or "").strip() for c in (row + [""] * (ncols - len(row)))]
        first = cells[fused_col_idx]
        dval = ""
        tval = first
        if first:
            parts = first.split()
            if parts and date_tok.match(parts[0]):
                dval = parts[0]
                tval = " ".join(parts[1:]).strip()
        if ri == header_row_idx:
            split_row = (
                cells[:fused_col_idx]
                + ["Date", "Transaction Detail"]
                + cells[fused_col_idx + 1:]
            )
        elif ri < header_row_idx:
            split_row = cells[:fused_col_idx] + [cells[fused_col_idx], ""] + cells[fused_col_idx + 1:]
        else:
            split_row = cells[:fused_col_idx] + [dval, tval] + cells[fused_col_idx + 1:]
        new_grid.append(split_row)
    return new_grid

def _split_combined_summary_daily_balance_grid(grid):
    if not grid or len(grid) < 4:
        return None

    def _norm(s):
        return re.sub(r"\s+", " ", str(s or "").strip().lower())

    daily_idx = None
    for i, row in enumerate(grid):
        row_text = " ".join(_norm(c) for c in row if str(c or "").strip())
        if "daily balance" in row_text:
            daily_idx = i
            break
    if daily_idx is None or daily_idx <= 1 or daily_idx >= len(grid) - 2:
        return None

    date_re = re.compile(r"^\d{1,2}/\d{2}(?:/\d{2,4})?$")
    money_re = re.compile(r"^-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?$")

    daily_rows = []
    for row in grid[daily_idx + 1:]:
        tokens = []
        for cell in row:
            ct = str(cell or "").strip()
            if not ct:
                continue
            tokens.extend(re.split(r"\s+", ct))
        dates = [t for t in tokens if date_re.match(t)]
        amts = [t for t in tokens if money_re.match(t)]
        if not dates or not amts:
            continue
        for d, a in zip(dates, amts):
            daily_rows.append([d, a])

    if len(daily_rows) < 2:
        return None

    summary = [r for r in grid[:daily_idx] if any(str(c or "").strip() for c in r)]
    if len(summary) < 2:
        return None

    daily = [["Date", "Ledger Balance"]] + daily_rows
    return [summary, daily]

def _normalize_double_desc_amount_header_table(grid):
    if not grid or len(grid) < 2:
        return grid

    def _hdr_tight(s):
        return re.sub(r"\s+", "", str(s or "").strip().lower())

    expected5_t = ["date", "description", "amount", "description", "amount"]
    expected4_t = ["date", "description", "amount", "description"]

    def _row_is_ucb_header(cells):
        if len(cells) == 5:
            return [_hdr_tight(c) for c in cells] == expected5_t
        if len(cells) == 4:
            return [_hdr_tight(c) for c in cells] == expected4_t
        return False

    hdr_idx = None
    ncols = 0
    for i in range(min(5, len(grid))):
        raw_try = [str(c or "").strip() for c in grid[i]]
        if _row_is_ucb_header(raw_try):
            hdr_idx = i
            ncols = len(raw_try)
            break
    if hdr_idx is None:
        return grid

    date_only_re = re.compile(r"^\d{1,2}/\d{1,2}/\d{2,4}$")
    date_prefix_re = re.compile(r"^(\d{1,2}/\d{1,2}/\d{2,4})\s*(.*)$")
    money_cell_re = re.compile(r"^-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?$")

    def _is_money(s):
        if not s or not str(s).strip():
            return False
        return bool(money_cell_re.match(str(s).strip()))

    def _extract_money(s):
        if not s:
            return ""
        m = re.search(r"(-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?)", str(s))
        return m.group(1).strip() if m else ""

    out = [["Date", "Description", "Amount"]]

    for row in grid[hdr_idx + 1 :]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < ncols:
            cells.append("")
        c0, c1, c2 = cells[0], cells[1] if len(cells) > 1 else "", cells[2] if len(cells) > 2 else ""
        c3 = cells[3] if len(cells) > 3 else ""
        c4 = cells[4] if len(cells) > 4 else ""

        if not any(cells[:ncols]):
            continue

        mpre = date_prefix_re.match(c0)
        if mpre and _is_money(c1):
            date_s = mpre.group(1).strip()
            low = (c0 + " " + (mpre.group(2) or "")).lower()
            if "beginning balance" in low:
                desc = "Beginning Balance"
            elif "ending balance" in low:
                desc = "Ending Balance"
            else:
                desc = (mpre.group(2) or "").strip() or "Transaction"
            out.append([date_s, desc, c1])
            continue

        if date_only_re.match(c0.strip()):
            date_s = c0.strip()
            desc = c1
            amt = c2
            if desc and "beginning balance" in desc.lower():
                mx = _extract_money(desc)
                if mx and (not amt or amt in ("$0.00", "0.00", "$0", ".00", "$.00")):
                    amt = mx
                    desc = re.sub(
                        r"(?i)beginning\s+balance\s*\$?[\d,]+\.?\d*\s*",
                        "Beginning Balance ",
                        desc,
                    )
                    desc = re.sub(r"(?i)\s*average\s+ledger\s+balance\s*", " ", desc).strip()
                    if not desc or desc == "Beginning Balance":
                        desc = "Beginning Balance"
            out.append([date_s, desc, amt])
            continue

        if not date_prefix_re.match(c0) and not date_only_re.match(c0.strip()) and _is_money(c1):
            out.append(["", c0, c1])
            continue

        out.append([c0, c1, c2])

    return out if len(out) >= 2 else grid


def _normalize_ucb_three_col_beginning_balance_fusion(grid):
    if not grid or len(grid) < 2:
        return grid

    def _tight(s):
        return re.sub(r"\s+", "", str(s or "").strip().lower())

    h0 = [str(c or "").strip() for c in grid[0]]
    if len(h0) < 3:
        return grid
    if _tight(h0[0]) != "date" or _tight(h0[1]) != "description" or _tight(h0[2]) != "amount":
        return grid

    date_only_re = re.compile(r"^\d{1,2}/\d{1,2}/\d{2,4}$")

    def _extract_money(s):
        if not s:
            return ""
        m = re.search(r"(-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?)", str(s))
        return m.group(1).strip() if m else ""

    zeroish = {"", "$0.00", "0.00", "$0", ".00", "$.00", "0"}

    out = [list(grid[0])]
    changed = False
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < 3:
            cells.append("")
        c0, c1, c2 = cells[0], cells[1], cells[2]
        if (
            date_only_re.match(c0.strip())
            and c1
            and "beginning balance" in c1.lower()
        ):
            mx = _extract_money(c1)
            c2n = c2.strip() if c2 else ""
            if mx and (not c2n or c2n in zeroish):
                out.append([c0.strip(), "Beginning Balance", mx])
                changed = True
                continue
        out.append([c0, c1, c2])

    return out if changed else grid


def _fix_three_col_date_desc_amount_left_shift(grid):
    if not grid or len(grid) < 2:
        return grid

    def _tight(s):
        return re.sub(r"\s+", "", str(s or "").strip().lower())

    h0 = [str(c or "").strip() for c in grid[0]]
    if len(h0) < 3:
        return grid
    if _tight(h0[0]) != "date" or _tight(h0[1]) != "description" or _tight(h0[2]) != "amount":
        return grid

    date_then_desc = re.compile(
        r"^(\d{1,2}/\d{1,2}/\d{2,4})\s+(.+)$"
    )
    money_re = re.compile(r"^-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?$")

    out = [list(grid[0])]
    changed = False
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < 3:
            cells.append("")
        c0, c1, c2 = cells[0], cells[1], cells[2]
        if not c0:
            out.append([c0, c1, c2])
            continue
        m = date_then_desc.match(c0)
        if not m:
            out.append([c0, c1, c2])
            continue
        desc_part = (m.group(2) or "").strip()
        if not desc_part:
            out.append([c0, c1, c2])
            continue
        if not (c1 and money_re.match(c1.strip())):
            out.append([c0, c1, c2])
            continue
        if c2 and str(c2).strip():
            out.append([c0, c1, c2])
            continue
        out.append([m.group(1).strip(), desc_part, c1.strip()])
        changed = True

    return out if changed else grid


def _normalize_fused_date_posted_amount_table(grid):
    if not grid or len(grid) < 2:
        return grid

    ncols = max(len(r) for r in grid if isinstance(r, list))
    if ncols < 2:
        return grid

    def _row_cells(r):
        return [str(c or "").strip() for c in (r + [""] * (ncols - len(r)))]

    hdr_idx = None
    for ri in range(min(6, len(grid))):
        cells = _row_cells(grid[ri])
        row_text = " ".join(cells).lower()
        if (
            "date posted transaction description" in row_text
            and "amount" in row_text
        ):
            hdr_idx = ri
            break
    if hdr_idx is None:
        return grid

    date_re = re.compile(r"^\d{1,2}[/-]\d{1,2}(?:[/-]\d{2,4})?$")
    out = []

    for ri, row in enumerate(grid):
        cells = _row_cells(row)
        if ri == hdr_idx:
            out.append(["Date", "Transaction Description", "Amount"])
            continue
        if ri < hdr_idx:
            joined = " ".join(c for c in cells if c).strip()
            out.append(["", joined, ""])
            continue

        c1 = cells[0].strip()
        c2 = cells[1].strip() if len(cells) > 1 else ""

        lower_c1 = c1.lower()
        if (
            lower_c1.startswith("date posted transaction description")
            or lower_c1 in {"ach additions", "ach deductions", "other additions", "other deductions", "service charges and fees"}
        ):
            continue

        date = ""
        desc = c1
        if c1:
            parts = c1.split()
            if parts and date_re.match(parts[0]):
                date = parts[0]
                desc = " ".join(parts[1:]).strip()

        amount = c2
        if not amount:
            money_cells = []
            for x in cells[1:]:
                t = str(x or "").strip()
                if re.match(r"^-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?$", t):
                    money_cells.append(t)
            if money_cells:
                amount = money_cells[-1]

        if not amount and desc:
            m = re.search(r"(-?\$?\d{1,3}(?:,\d{3})*(?:\.\d{2})-?)\s*$", desc)
            if m:
                amount = m.group(1)
                desc = desc[:m.start()].strip()

        if not (date or desc or amount):
            continue
        out.append([date, desc, amount])

    if len(out) < 2:
        return grid
    return out

def normalize_html_tables(text: str) -> str:
    if not text or "<table" not in text.lower():
        return text

    pattern = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)
    out = []
    last = 0

    for m in pattern.finditer(text):
        out.append(text[last : m.start()])
        table_html = m.group(0)
        try:
            p = TableGridParser()
            p.feed(table_html)
            grid = _build_grid(p.rows)

            if _is_junk_table(grid):
                out.append("")
                last = m.end()
                continue

            grid = _normalize_double_desc_amount_header_table(grid)
            grid = _normalize_ucb_three_col_beginning_balance_fusion(grid)
            grid = _fix_three_col_date_desc_amount_left_shift(grid)

            grid = _drop_truly_empty_columns(grid)
            grid = _merge_blank_header_text_columns(grid)

            grid = _reconstruct_separator_rows(grid)

            grid, recovered_row = _clean_header_artifacts(grid)
            if recovered_row is not None:
                grid.insert(1, recovered_row)

            grid = _promote_misplaced_header_row(grid)

            grid = _split_fused_date_transaction_header(grid)

            grid = _normalize_fused_date_posted_amount_table(grid)

            grid = _split_fused_multicolumn_header(grid)

            grid = _normalize_daily_balance_table(grid)

            grid = _normalize_checks_paid_table(grid)

            grid = _merge_split_rows(grid)

            grid = _extract_fused_desc_amount(grid)

            grid = _repair_da3_garbled_amount_cells(grid)

            grid = _fix_fused_keyvalue_rows(grid)
            grid = _dedupe_duplicate_rows_in_da3_table(grid)
            split_tables = _split_combined_summary_daily_balance_grid(grid)
            if split_tables:
                out.append("\n\n".join(_grid_to_html(g) for g in split_tables if g))
            else:
                out.append(_grid_to_html(grid) if grid else table_html)
        except Exception:
            out.append(table_html)
        last = m.end()

    out.append(text[last:])
    return "".join(out)


def _transaction_row_dedupe_key(cells):
    parts = [str(c or "").strip() for c in cells[:3]]
    while len(parts) < 3:
        parts.append("")
    date_s, desc_s, amt_s = parts[0], parts[1], parts[2]
    date_s = re.sub(r"\s+", "", date_s)
    amt_s = re.sub(r"[\s$,]", "", amt_s).lower().replace("−", "-")
    desc_s = html.unescape(desc_s)
    desc_s = desc_s.replace("`", "'").replace("'", "'")
    desc_s = re.sub(r"\s+", "", desc_s.lower())
    return (date_s, desc_s, amt_s)


def _da3_loose_key(cells):
    parts = [str(c or "").strip() for c in cells[:3]]
    while len(parts) < 3:
        parts.append("")
    date_s, desc_s, amt_s = parts[0], parts[1], parts[2]
    if not _DA3_LEADING_DATE.match(date_s):
        return None
    comb = f"{date_s} {desc_s}".lower()
    if re.search(r"\btotal\b", comb) and len(desc_s) > 25:
        return None
    if not _DA3_STRICT_AMOUNT.match(amt_s.strip()):
        return None
    t_amt = re.sub(r"[\s$,]", "", amt_s).replace("−", "-").replace("$", "")
    try:
        af = round(float(t_amt), 2)
    except ValueError:
        return None
    d_norm = re.sub(r"\s+", "", date_s)
    return (d_norm, af)


def _row_counter_loose_da3(g):
    c = Counter()
    if not g or len(g) < 2:
        return c
    for r in g[1:]:
        cells = [str(x or "").strip() for x in r]
        if not any(cells):
            continue
        k = _da3_loose_key(cells)
        if k:
            c[k] += 1
    return c


def _overlap_ratio_counter(c_num, c_den):
    tot = sum(c_num.values())
    if tot == 0:
        return 0.0
    hit = sum(min(c_num[k], c_den.get(k, 0)) for k in c_num)
    return hit / tot


def _multiset_leq(c_small, c_big):
    return all(c_small[k] <= c_big.get(k, 0) for k in c_small)


def _is_da3_header(grid):
    if not grid or len(grid[0]) < 3:
        return False
    h = [re.sub(r"\s+", " ", str(c or "").strip().lower()) for c in grid[0]]
    if len(h) != 3:
        return False
    return h[0] == "date" and "description" in h[1] and (
        h[2] == "amount" or h[2].startswith("amount")
    )


_DA3_STRICT_AMOUNT = re.compile(r"^-?\$?\d{1,3}(?:,\d{3})*\.\d{2}-?$")
_DA3_MONEY_TOKEN = re.compile(
    r"(?<![\d,])(-?\$?\d{1,3}(?:,\d{3})*\.\d{2}|-?\$?\d{2,6}\.\d{2})(?!\d)"
)
_MSFT_PIN_G_REF = re.compile(r"MICROSOFT#(G\d{6,16})", re.IGNORECASE)
_DA3_LEADING_DATE = re.compile(r"^\d{1,2}/\d{1,2}(?:/\d{2,4})?$")


def _repair_da3_garbled_amount_cells(grid):
    if not grid or len(grid) < 2 or not _is_da3_header(grid):
        return grid

    date_re = re.compile(r"^\d{1,2}/\d{1,2}(?:/\d{2,4})?$")
    out = [list(grid[0])]
    changed = False

    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < 3:
            cells.append("")
        c0, c1, c2 = cells[0], cells[1], cells[2]
        if not date_re.match(c0):
            out.append(cells)
            continue
        c2s = c2.strip()
        if _DA3_STRICT_AMOUNT.match(c2s):
            out.append(cells)
            continue
        blob = f"{c1} {c2}".strip()
        if not blob:
            out.append(cells)
            continue
        found = _DA3_MONEY_TOKEN.findall(blob)
        if not found:
            out.append(cells)
            continue
        pick_raw = None
        for m in reversed(found):
            t = m.replace("$", "").replace(",", "")
            try:
                v = float(t)
            except ValueError:
                continue
            if 0.01 <= v <= 9_999_999.99:
                pick_raw = m.replace("$", "").strip()
                break
        if not pick_raw:
            out.append(cells)
            continue
        new_desc = c1
        for suf in (
            pick_raw,
            pick_raw.replace(",", ""),
            f"${pick_raw}",
            f"${pick_raw.replace(',', '')}",
        ):
            if suf and new_desc.rstrip().endswith(suf):
                new_desc = new_desc[: -len(suf)].rstrip()
                break
        out.append([c0, new_desc, pick_raw])
        changed = True

    return out if changed else grid


def _dedupe_duplicate_rows_in_da3_table(grid):
    if not grid or len(grid) < 2:
        return grid
    if not _is_da3_header(grid):
        return grid
    data_rows = []
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        if not any(cells):
            continue
        data_rows.append(row)

    if not data_rows:
        return grid

    out = [grid[0]]
    i = 0
    while i < len(data_rows):
        row = data_rows[i]
        cells = [str(c or "").strip() for c in row]
        k = _transaction_row_dedupe_key(cells)
        j = i + 1
        while j < len(data_rows):
            ncells = [str(c or "").strip() for c in data_rows[j]]
            if _transaction_row_dedupe_key(ncells) != k:
                break
            j += 1
        run_len = j - i
        take = min(run_len, 2)
        for t in range(take):
            out.append(data_rows[i + t])
        i = j

    return out


def _row_text_full_ucb(grid, r: int) -> str:
    if not grid or r < 0 or r >= len(grid):
        return ""
    parts = [str(c or "").strip().lower() for c in grid[r]]
    return " ".join(parts)


def _is_itm_deposit_row_ucb(grid, r: int) -> bool:
    if not grid or r >= len(grid) or len(grid[r]) < 2:
        return False
    desc = str(grid[r][1] or "").strip().lower()
    return "itm deposit" in desc


def _ucb_verify_electronic_credits_rows(grid, ec_start: int) -> bool:
    if ec_start + 2 >= len(grid):
        return False
    t0 = _row_text_full_ucb(grid, ec_start)
    t1 = _row_text_full_ucb(grid, ec_start + 1)
    t2 = _row_text_full_ucb(grid, ec_start + 2)
    ok0 = "pos return" in t0 or ("pos" in t0 and "return" in t0)
    ok1 = "acct fund" in t1 or ("apple" in t1 and "inst" in t1)
    ok2 = "dda transfer" in t2 and "in" in t2
    return bool(ok0 and ok1 and ok2)


def _ucb_split_grid_deposits_ec_ed(grid):
    if not grid or len(grid) < 2:
        return None
    if not _is_da3_header(grid):
        return None
    data_start = 1
    i = data_start
    while i < len(grid) and _is_itm_deposit_row_ucb(grid, i):
        i += 1
    if i == data_start:
        return None
    if i + 3 > len(grid):
        return None
    if not _ucb_verify_electronic_credits_rows(grid, i):
        return None
    ec_end = i + 3
    if ec_end >= len(grid):
        return None
    hdr = [list(grid[0])]
    g_dep = hdr + grid[data_start:i]
    g_ec = hdr + grid[i:ec_end]
    g_ed = hdr + grid[ec_end:]
    if len(g_ed) <= 1:
        return None
    return g_dep, g_ec, g_ed


def _try_split_ucb_deposits_table_to_three(prefix: str, table_html: str):
    try:
        p = TableGridParser()
        p.feed(table_html)
        grid = _build_grid(p.rows)
    except Exception:
        return None
    triple = _ucb_split_grid_deposits_ec_ed(grid)
    if not triple:
        return None
    g_dep, g_ec, g_ed = triple
    sect = '<div align="center">\n\n{title}\n\n</div>\n\n'
    parts = [prefix.rstrip(), _grid_to_html(g_dep), sect.format(title="Electronic Credits"), _grid_to_html(g_ec)]
    parts.append(sect.format(title="Electronic Debits"))
    parts.append(_grid_to_html(g_ed))
    return "\n\n".join(parts)


_UCB_DEP_CONT_BLOCK = re.compile(
    r'(<div\s+align=["\']center["\']\s*>\s*Deposits\s*\(continued\)\s*</div>\s*)'
    r'(<table[^>]*>.*?</table>)'
    r'(?:\s*<div\s+align=["\']center["\']\s*>\s*Electronic\s+Credits\s*</div>\s*'
    r'<div\s+align=["\']center["\']\s*>\s*Electronic\s+Debits\s*</div>)?',
    re.DOTALL | re.IGNORECASE,
)


def _split_ucb_deposits_electronic_sections_html(text: str) -> str:
    if not text or "deposits (continued)" not in text.lower():
        return text

    def _repl(m):
        prefix = m.group(1)
        table_html = m.group(2)
        new = _try_split_ucb_deposits_table_to_three(prefix, table_html)
        if new is None:
            return m.group(0)
        return new

    return _UCB_DEP_CONT_BLOCK.sub(_repl, text)


def _parse_da3_grid_from_table_html(table_html: str):
    try:
        p = TableGridParser()
        p.feed(table_html)
        grid = _build_grid(p.rows)
        if grid and _is_da3_header(grid):
            return grid
    except Exception:
        pass
    return None


def _strip_orphan_continued_da3_flatline(text: str) -> str:
    if not text or "(continued)" not in text.lower():
        return text
    lines = text.splitlines(keepends=True)
    out = []
    for line in lines:
        core = line.rstrip("\r\n")
        date_hits = len(re.findall(r"\d{2}/\d{2}", core)) + len(
            re.findall(r"\b\d{2}-\d{2}-\d{2}\b", core)
        )
        if (
            len(core) > 80
            and "(continued)" in core.lower()
            and "description" in core.lower()
            and "amount" in core.lower()
            and date_hits >= 3
        ):
            continue
        out.append(line)
    return "".join(out)


def _strip_standalone_continued_banner_line(text: str) -> str:
    if not text or "(continued)" not in text.lower():
        return text
    lines = text.splitlines(keepends=True)
    out = []
    for line in lines:
        core = line.rstrip("\r\n")
        if not core.strip():
            out.append(line)
            continue
        c = core.lower()
        if "$" in core or "=" in core:
            out.append(line)
            continue
        if (
            "(continued)" in c
            and "date" not in c
            and "description" not in c
            and "amount" not in c
            and len(re.findall(r"\d{2}/\d{2}", core)) == 0
            and len(core) < 240
        ):
            continue
        out.append(line)
    return "".join(out)


def _patch_da3_msft_g_ref_amounts_across_tables(text: str) -> str:
    if not text or "<table" not in text.lower():
        return text
    if "microsoft#" not in text.lower():
        return text

    tbl_pat = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)

    def _collect():
        g_map = {}
        ambiguous = set()
        for m in tbl_pat.finditer(text):
            g = _parse_da3_grid_from_table_html(m.group(0))
            if not g:
                continue
            for row in g[1:]:
                cells = [str(c or "").strip() for c in row]
                while len(cells) < 3:
                    cells.append("")
                c0, c1, c2 = cells[0], cells[1], cells[2]
                if not _DA3_LEADING_DATE.match(c0):
                    continue
                if not _DA3_STRICT_AMOUNT.match(c2):
                    continue
                blob = f"{c0} {c1} {c2}"
                for gid in _MSFT_PIN_G_REF.findall(blob):
                    k = gid.upper()
                    if k in ambiguous:
                        continue
                    trip = (c0, c1, c2)
                    prev = g_map.get(k)
                    if prev is not None and prev != trip:
                        ambiguous.add(k)
                        g_map.pop(k, None)
                    elif prev is None:
                        g_map[k] = trip
        return g_map, ambiguous

    g_map, ambiguous = _collect()
    if not g_map:
        return text

    out_chunks = []
    last = 0
    changed_any = False
    for m in tbl_pat.finditer(text):
        out_chunks.append(text[last : m.start()])
        table_html = m.group(0)
        grid = _parse_da3_grid_from_table_html(table_html)
        if not grid:
            out_chunks.append(table_html)
            last = m.end()
            continue
        new_grid = [list(grid[0])]
        changed = False
        for row in grid[1:]:
            cells = [str(c or "").strip() for c in row]
            while len(cells) < 3:
                cells.append("")
            c0, c1, c2 = cells[0], cells[1], cells[2]
            if not _DA3_LEADING_DATE.match(c0):
                new_grid.append(row)
                continue
            if _DA3_STRICT_AMOUNT.match(c2):
                new_grid.append(row)
                continue
            blob = f"{c0} {c1} {c2}"
            ids = _MSFT_PIN_G_REF.findall(blob)
            if len(ids) != 1:
                new_grid.append(row)
                continue
            k = ids[0].upper()
            if k in ambiguous or k not in g_map:
                new_grid.append(row)
                continue
            d0, d1, d2 = g_map[k]
            new_grid.append([d0, d1, d2])
            changed = True
        if changed:
            out_chunks.append(_grid_to_html(new_grid))
            changed_any = True
        else:
            out_chunks.append(table_html)
        last = m.end()
    out_chunks.append(text[last:])
    return "".join(out_chunks) if changed_any else text


def _trim_adjacent_da3_suffix_duplicating_next_table_prefix(text: str) -> str:
    if not text or "<table" not in text.lower():
        return text

    pattern = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)

    for _ in range(48):
        matches = list(pattern.finditer(text))
        if len(matches) < 2:
            break
        changed = False
        for i in range(len(matches) - 1):
            g1 = _parse_da3_grid_from_table_html(matches[i].group(0))
            g2 = _parse_da3_grid_from_table_html(matches[i + 1].group(0))
            if not g1 or not g2 or len(g1) < 3 or len(g2) < 2:
                continue
            d1 = g1[1:]
            d2 = g2[1:]
            if len(d1) < 2 or len(d2) < 2:
                continue
            max_k = min(len(d1), len(d2))
            best_k = 0
            for k in range(max_k, 1, -1):
                ok = True
                for j in range(k):
                    c1 = [str(x or "").strip() for x in d1[-k + j][:3]]
                    c2 = [str(x or "").strip() for x in d2[j][:3]]
                    while len(c1) < 3:
                        c1.append("")
                    while len(c2) < 3:
                        c2.append("")
                    if _transaction_row_dedupe_key(c1) != _transaction_row_dedupe_key(c2):
                        ok = False
                        break
                if ok:
                    best_k = k
                    break
            if best_k < 2:
                continue
            if len(d1) - best_k < 1:
                continue
            new_grid = [g1[0]] + d1[:-best_k]
            new_html = _grid_to_html(new_grid)
            m = matches[i]
            text = text[: m.start()] + new_html + text[m.end() :]
            changed = True
            break
        if not changed:
            break
    return text


def _dedupe_subset_transaction_tables_html(text: str) -> str:
    if not text or "<table" not in text.lower():
        return text

    pattern = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)

    def _parse_grid(html: str):
        try:
            p = TableGridParser()
            p.feed(html)
            return _build_grid(p.rows)
        except Exception:
            return None

    def _row_set(g):
        s = set()
        for r in g[1:]:
            if not any(str(c or "").strip() for c in r):
                continue
            cells = [str(c or "").strip() for c in r]
            if not any(cells):
                continue
            s.add(_transaction_row_dedupe_key(cells))
        return s

    def _one_pass(t: str) -> str:
        matches = list(pattern.finditer(t))
        if len(matches) < 2:
            return t

        grids = []
        for m in matches:
            grids.append((m, _parse_grid(m.group(0))))

        drop_idx = set()
        for i in range(1, len(grids)):
            if i in drop_idx:
                continue
            mi, gi = grids[i]
            if not _is_da3_header(gi):
                continue
            si = _row_set(gi)
            if not si:
                continue

            for j in range(i):
                if j in drop_idx:
                    continue
                mj, gj = grids[j]
                if not _is_da3_header(gj):
                    continue
                sj = _row_set(gj)
                if not sj:
                    continue

                if sj <= si and len(sj) < len(si):
                    drop_idx.add(j)
                    continue

                if si <= sj and len(si) < len(sj):
                    drop_idx.add(i)
                    break

                if si == sj:
                    drop_idx.add(i)
                    break

                inter = si & sj
                ri = len(inter) / len(si) if si else 0.0
                rj = len(inter) / len(sj) if sj else 0.0
                if ri >= 0.88 and len(si) <= len(sj):
                    drop_idx.add(i)
                    break
                if rj >= 0.88 and len(sj) < len(si):
                    drop_idx.add(j)
                    continue

                ci = _row_counter_loose_da3(gi)
                cj = _row_counter_loose_da3(gj)
                ni, nj = sum(ci.values()), sum(cj.values())
                if ni >= 1 and nj >= 1:
                    oi_j = _overlap_ratio_counter(ci, cj)
                    oj_i = _overlap_ratio_counter(cj, ci)
                    if (
                        nj >= 8
                        and 3 <= ni <= 14
                        and ni < nj
                        and _multiset_leq(ci, cj)
                        and oi_j >= 0.9
                    ):
                        drop_idx.add(i)
                        break
                    if ni >= 6 and nj >= 6:
                        if oi_j >= 0.88 and oj_i >= 0.88:
                            drop_idx.add(i)
                            break
                        if _multiset_leq(ci, cj) and ni < nj and oi_j >= 0.9:
                            drop_idx.add(i)
                            break
                        if _multiset_leq(cj, ci) and nj < ni and oj_i >= 0.9:
                            drop_idx.add(j)
                            continue

        if not drop_idx:
            return t

        out = []
        last = 0
        for idx, m in enumerate(matches):
            out.append(t[last : m.start()])
            if idx not in drop_idx:
                out.append(m.group(0))
            last = m.end()
        out.append(t[last:])
        return "".join(out)

    out = text
    for _ in range(12):
        nxt = _one_pass(out)
        if nxt == out:
            break
        out = nxt
    return out


_RE_CENTER_DIV_TWO_DA3_TABLES = re.compile(
    r'(<div\s+align=["\']center["\']\s*>\s*[^<]*?</div>\s*)'
    r'(<table[^>]*>.*?</table>)'
    r'(\s*<table[^>]*>.*?</table>)',
    re.IGNORECASE | re.DOTALL,
)


def _da3_row_credit_vs_debit_category(desc: str) -> str:
    d = (desc or "").lower()
    if "debit card return" in d:
        return "credit"
    if "debit card" in d and "return" in d:
        return "credit"
    if "deposit" in d and "debit card" not in d[:60]:
        return "credit"
    if "incoming wire" in d or "wire ref" in d:
        return "credit"
    if "zelle business reversal" in d or ("reversal" in d and "zelle" in d):
        return "credit"
    if "lrm claims" in d or ("claims" in d and "adj" in d):
        return "credit"
    if "adp tax" in d and "customer" in d:
        return "credit"
    if "debit card" in d:
        return "debit"
    if "ach corp debit" in d:
        return "debit"
    if "bus online ach settlement" in d:
        return "debit"
    if "zelle business payment to" in d:
        return "debit"
    if "visa money transfer debit" in d:
        return "debit"
    if "telephone payment" in d or "service charges" in d:
        return "debit"
    if "merch fee" in d:
        return "debit"
    if "deposit" in d:
        return "credit"
    return "unknown"


def _da3_table_credit_debit_fractions(grid):
    deb = cre = unk = 0
    if not grid or len(grid) < 2:
        return 0.0, 0.0, 0.0, 0
    for row in grid[1:]:
        cells = [str(c or "").strip() for c in row]
        while len(cells) < 3:
            cells.append("")
        if not _DA3_LEADING_DATE.match(cells[0]):
            continue
        if not _DA3_STRICT_AMOUNT.match((cells[2] or "").strip()):
            continue
        cat = _da3_row_credit_vs_debit_category(cells[1])
        if cat == "debit":
            deb += 1
        elif cat == "credit":
            cre += 1
        else:
            unk += 1
    tot = deb + cre + unk
    if tot == 0:
        return 0.0, 0.0, 0.0, 0
    return deb / tot, cre / tot, unk / tot, tot


def _drop_da3_misplaced_debit_after_deposit_heading_tables(text: str) -> str:
    if not text or "<table" not in text.lower():
        return text
    if "deposit" not in text.lower():
        return text

    for _ in range(12):
        replaced = False
        pos = 0
        while True:
            m = _RE_CENTER_DIV_TWO_DA3_TABLES.search(text, pos)
            if not m:
                break
            div = m.group(1)
            t1 = m.group(2)
            t2 = m.group(3)
            sl = div.lower()
            if "deposit" not in sl or not any(k in sl for k in ("credit", "interest", "credits")):
                pos = m.start() + 1
                continue

            g1 = _parse_da3_grid_from_table_html(t1)
            g2 = _parse_da3_grid_from_table_html(t2)
            if not g1 or not g2 or not _is_da3_header(g1) or not _is_da3_header(g2):
                pos = m.start() + 1
                continue

            db1, cr1, unk1, n1 = _da3_table_credit_debit_fractions(g1)
            db2, cr2, _unk2, n2 = _da3_table_credit_debit_fractions(g2)
            if n1 < 5 or n2 < 10:
                pos = m.start() + 1
                continue
            credit_like_first = cr1 + 0.42 * unk1
            if credit_like_first < 0.30 and credit_like_first <= db1 + 0.05:
                pos = m.start() + 1
                continue
            if db2 < 0.74 or db2 <= cr2 + 0.07:
                pos = m.start() + 1
                continue

            text = text[: m.start()] + div + t1 + text[m.end() :]
            replaced = True
            break
        if not replaced:
            break

    return text


# --------------------------
# Fix 28: Strip credit-row prefix from debit DA3 table
# --------------------------

# Keywords that identify a section heading as debit/withdrawal-oriented.
_DEBIT_HEADING_KEYWORDS = re.compile(
    r"\b(withdrawal|withdrawals|debit|debits|charges?|subtraction|subtractions|"
    r"payments?\s+made|money\s+out|paid\s+out|electronic\s+debit)\b",
    re.IGNORECASE,
)
# Keywords that identify a section heading as credit/deposit-oriented.
_CREDIT_HEADING_KEYWORDS = re.compile(
    r"\b(deposit|deposits|credit|credits|addition|additions|interest\s+paid|"
    r"money\s+in|paid\s+in|incoming|received)\b",
    re.IGNORECASE,
)
# How many characters before a table start to scan for a section heading.
_HEADING_SCAN_WINDOW = 600


def _get_heading_before_table(text: str, table_start: int) -> str:
    """
    Return the last non-trivial text line in the _HEADING_SCAN_WINDOW chars
    that precede `table_start`.  HTML tags are stripped before scanning so that
    centered <div> headings are picked up correctly.
    """
    window = text[max(0, table_start - _HEADING_SCAN_WINDOW): table_start]
    clean = re.sub(r"<[^>]+>", " ", window)
    lines = [ln.strip() for ln in clean.splitlines() if ln.strip()]
    for line in reversed(lines):
        if len(line) > 3 and "---" not in line:
            return line
    return ""


def _strip_credits_prefix_from_debit_da3_table(text: str) -> str:
    """
    Fix 28: When OCR prepends the rows of a preceding credits/deposits DA3 table
    onto the top of a debits/withdrawals DA3 table, strip that prefix.
    Safety guards (ALL must pass):
      1. Both tables must be valid DA3 (Date|Description|Amount header).
      2. Target (later) table must follow a debit/withdrawal heading.
      3. Source (earlier) table must follow a credit/deposit heading.
      4. Only the contiguous leading prefix of matching rows is removed.
      5. At least 1 data row must remain in the target after stripping.
      6. Strip count must be >= 1.
      7. Entire function wrapped in try/except — returns input unchanged on error.
    """
    if not text or "<table" not in text.lower():
        return text
    try:
        pattern = re.compile(r"<table[^>]*>.*?</table>", re.DOTALL | re.IGNORECASE)
        matches = list(pattern.finditer(text))
        if len(matches) < 2:
            return text

        # Collect all DA3 tables with their heading context.
        da3_tables = []
        for m in matches:
            g = _parse_da3_grid_from_table_html(m.group(0))
            if not g or not _is_da3_header(g):
                continue
            heading = _get_heading_before_table(text, m.start())
            da3_tables.append({"match": m, "grid": g, "heading": heading})

        if len(da3_tables) < 2:
            return text

        def _row_keys(grid):
            keys = set()
            for row in grid[1:]:
                cells = [str(c or "").strip() for c in row]
                if any(cells):
                    keys.add(_transaction_row_dedupe_key(cells))
            return keys

        # For each DA3 table preceded by a debit heading, look backward for the
        # nearest DA3 table preceded by a credit heading, and measure how many
        # of the debit table's leading rows appear in that credit table.
        drop_map = {}  # table match start -> number of rows to strip
        for i in range(1, len(da3_tables)):
            ti = da3_tables[i]
            hi = ti["heading"].lower()
            if not _DEBIT_HEADING_KEYWORDS.search(hi):
                continue
            gi = ti["grid"]
            data_i = gi[1:]
            if len(data_i) < 2:
                continue
            for j in range(i - 1, -1, -1):
                tj = da3_tables[j]
                hj = tj["heading"].lower()
                if not _CREDIT_HEADING_KEYWORDS.search(hj):
                    continue
                gj = tj["grid"]
                keys_j = _row_keys(gj)
                if not keys_j:
                    continue
                # Count the contiguous leading rows of data_i that are in keys_j.
                strip_count = 0
                for row in data_i:
                    cells = [str(c or "").strip() for c in row]
                    k = _transaction_row_dedupe_key(cells)
                    if k in keys_j:
                        strip_count += 1
                    else:
                        break
                if strip_count < 1:
                    continue
                # Guard: at least 1 data row must survive.
                if len(data_i) - strip_count < 1:
                    continue
                drop_map[ti["match"].start()] = strip_count
                log.info(
                    "Fix 28: stripped %d leading credit row(s) from debit table at offset %d",
                    strip_count, ti["match"].start(),
                )
                break  # found nearest credit table — stop looking further back

        if not drop_map:
            return text

        # Apply the strip.
        out_chunks = []
        last = 0
        for m in matches:
            out_chunks.append(text[last: m.start()])
            if m.start() in drop_map:
                strip_n = drop_map[m.start()]
                g = _parse_da3_grid_from_table_html(m.group(0))
                if g and _is_da3_header(g) and len(g) - 1 - strip_n >= 1:
                    new_grid = [g[0]] + g[1 + strip_n:]
                    out_chunks.append(_grid_to_html(new_grid))
                else:
                    out_chunks.append(m.group(0))
            else:
                out_chunks.append(m.group(0))
            last = m.end()
        out_chunks.append(text[last:])
        return "".join(out_chunks)

    except Exception as e:
        log.warning("_strip_credits_prefix_from_debit_da3_table failed: %s", e)
        return text


def stabilize_tables_and_text(page_md: str) -> str:
    if not page_md:
        return page_md

    page_md = normalize_money_glyphs(page_md)

    blocks = re.split(r"\n\s*\n", page_md.strip())
    out_blocks = []
    for b in blocks:
        if looks_like_markdown_table(b):
            out_blocks.append(md_table_to_html(b))
        else:
            out_blocks.append(b)

    stabilized = "\n\n".join(out_blocks)
    stabilized = convert_plaintext_bank_sections(stabilized)
    stabilized = _strip_orphan_continued_da3_flatline(stabilized)
    stabilized = _strip_standalone_continued_banner_line(stabilized)
    stabilized = normalize_html_tables(stabilized)
    stabilized = _trim_adjacent_da3_suffix_duplicating_next_table_prefix(stabilized)
    stabilized = _split_ucb_deposits_electronic_sections_html(stabilized)
    stabilized = _patch_da3_msft_g_ref_amounts_across_tables(stabilized)
    stabilized = _dedupe_subset_transaction_tables_html(stabilized)
    stabilized = _drop_da3_misplaced_debit_after_deposit_heading_tables(stabilized)
    stabilized = _strip_credits_prefix_from_debit_da3_table(stabilized)  # Fix 28
    stabilized = _strip_orphan_continued_da3_flatline(stabilized)
    stabilized = _strip_standalone_continued_banner_line(stabilized)
    return close_unclosed_html(stabilized)

# --------------------------
# PDF rendering with padding
# --------------------------
def render_pdf_pages_to_images(pdf_path: str) -> Tuple[List[str], List[int]]:
    import pymupdf as fitz
    from PIL import Image, ImageEnhance

    doc = fitz.open(pdf_path)
    page_images: List[str] = []
    page_heights: List[int] = []

    for i in range(len(doc)):
        page = doc[i]
        pix = page.get_pixmap(matrix=fitz.Matrix(RENDER_SCALE, RENDER_SCALE), alpha=False)

        img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)

        if ENABLE_CONTRAST:
            img = ImageEnhance.Contrast(img).enhance(1.12)

        w, h = img.size
        pad_l = int(w * PAD_LEFT_FRAC)
        pad_r = int(w * PAD_RIGHT_FRAC)
        pad_t = int(h * PAD_TOP_FRAC)
        pad_b = int(h * PAD_BOTTOM_FRAC)

        if any(p > 0 for p in (pad_l, pad_r, pad_t, pad_b)):
            canvas = Image.new("RGB", (w + pad_l + pad_r, h + pad_t + pad_b), (255, 255, 255))
            canvas.paste(img, (pad_l, pad_t))
            img = canvas

        img_path = os.path.join(tempfile.gettempdir(), f"glmocr_page_{os.getpid()}_{i}.png")
        img.save(img_path, "PNG", compress_level=6)
        page_images.append(img_path)
        page_heights.append(img.height)

    doc.close()
    return page_images, page_heights

# --------------------------
# GLM-OCR result extraction
# --------------------------
def get_page_md_and_regions(page_result):
    md = ""
    if hasattr(page_result, "markdown_result") and page_result.markdown_result:
        md = (page_result.markdown_result or "").strip()
    regions = []
    if hasattr(page_result, "json_result"):
        jr = page_result.json_result
        if isinstance(jr, dict) and "regions" in jr:
            regions = jr.get("regions") or []
        elif isinstance(jr, list) and len(jr) > 0:
            r = jr[0] if isinstance(jr[0], list) else jr
            if isinstance(r, list):
                regions = r
            elif isinstance(r, dict) and "regions" in r:
                regions = r.get("regions") or []
    return md, regions

# --------------------------
# Main entry
# --------------------------
def run_ocr(uploaded_file):
    if uploaded_file is None:
        return "Please upload a file."

    page_images = []
    try:
        path = uploaded_file.name if hasattr(uploaded_file, "name") else str(uploaded_file)
        is_pdf = path.lower().endswith(".pdf")
        is_nfcu_doc = _is_nfcu_document(path) if is_pdf else False
        parser = get_parser()

        page_heights = []

        if is_pdf:
            page_images, page_heights = render_pdf_pages_to_images(path)
            results = parser.parse(page_images)
        else:
            page_images = [path]
            page_heights = [1000]
            results = parser.parse(path)

        if not isinstance(results, list):
            results = [results]

        all_pages = []
        for page_num, page_result in enumerate(results):
            page_md, regions = get_page_md_and_regions(page_result)
            img_h = page_heights[page_num] if page_num < len(page_heights) else 1000
            header_end_frac, footer_start_frac = get_header_footer_zones(regions, img_h)

            he = header_end_frac if header_end_frac is not None else DEFAULT_ZONE_FRAC
            fs = footer_start_frac if footer_start_frac is not None else (1.0 - DEFAULT_ZONE_FRAC)

            he = max(0.02, min(0.25, he))
            fs = max(0.75, min(0.98, fs))

            parts = []

            hdr = ""
            if is_pdf:
                hdr = extract_zone_text_pdf(path, page_num, 0, he)
                if not (hdr and hdr.strip()):
                    hdr = extract_pdf_text_in_band(path, page_num, 0, PDF_HEADER_BAND_FRAC)
            if not (hdr and hdr.strip()) and page_num < len(page_images):
                hdr = ocr_zone(page_images[page_num], 0, he)
            if hdr and hdr.strip():
                parts.append(normalize_html_tables(fix_account_number(normalize_money_glyphs(hdr.strip()))))

            if page_md and page_md.strip():
                stabilized = stabilize_tables_and_text(page_md.strip())
                if is_pdf and not is_nfcu_doc:
                    stabilized = _patch_ocr_with_textlayer(stabilized, path, page_num)
                    stabilized = _strip_orphan_continued_da3_flatline(stabilized)
                    stabilized = _strip_standalone_continued_banner_line(stabilized)
                    stabilized = normalize_html_tables(stabilized)
                    stabilized = _trim_adjacent_da3_suffix_duplicating_next_table_prefix(stabilized)
                    stabilized = _split_ucb_deposits_electronic_sections_html(stabilized)
                    stabilized = _patch_da3_msft_g_ref_amounts_across_tables(stabilized)
                    stabilized = _dedupe_subset_transaction_tables_html(stabilized)
                    stabilized = _drop_da3_misplaced_debit_after_deposit_heading_tables(stabilized)
                    stabilized = _strip_credits_prefix_from_debit_da3_table(stabilized)  # Fix 28
                    stabilized = _strip_standalone_continued_banner_line(stabilized)
                elif is_pdf and is_nfcu_doc:
                    nfcu_summary = _extract_nfcu_summary_table(path, page_num)
                    if nfcu_summary:
                        stabilized = _replace_nfcu_summary_table(stabilized, nfcu_summary)

                if is_pdf:
                    try:
                        needs_checks = 'class="jb-summary-checks"' not in stabilized
                        needs_dab    = "daily account balance" not in stabilized.lower()
                        if needs_checks or needs_dab:
                            _txt4d = ""
                            try:
                                from pdfminer.high_level import extract_text as _pm_extract
                                _txt4d = _pm_extract(path, page_numbers=[page_num])
                            except Exception:
                                pass
                            if not _txt4d:
                                try:
                                    import pymupdf as _fitz4d
                                    _d4 = _fitz4d.open(path)
                                    _txt4d = _d4[page_num].get_text()
                                    _d4.close()
                                except Exception:
                                    pass
                            if _txt4d:
                                jb_extra = _extract_jb_summary_sections(_txt4d, needs_checks, needs_dab)
                                if jb_extra:
                                    stabilized = stabilized.rstrip() + "\n\n" + jb_extra
                    except Exception:
                        pass

                parts.append(stabilized)

            if ENABLE_FOOTER_OCR and page_num < len(page_images):
                ftr = ""
                if is_pdf:
                    ftr = extract_zone_text_pdf(path, page_num, fs, 1.0)
                    if not (ftr and ftr.strip()):
                        ftr = extract_pdf_text_in_band(path, page_num, PDF_FOOTER_BAND_FRAC, 1.0)
                if not (ftr and ftr.strip()):
                    ftr = ocr_zone(page_images[page_num], fs, 1.0)
                if ftr and ftr.strip():
                    ftr_clean = normalize_money_glyphs(ftr.strip())

                    ftr_first_line = next(
                        (ln.strip().lower() for ln in ftr_clean.splitlines() if ln.strip()),
                        ""
                    )
                    already_present = ftr_first_line and any(
                        ftr_first_line in part.lower() for part in parts
                    )

                    _footer_date_re = re.compile(r"\b\d{1,2}[-/]\d{2}\b")
                    _footer_amt_re  = re.compile(r"\b\d{1,3}(?:,\d{3})*\.\d{2}\b")
                    _date_hits = len(_footer_date_re.findall(ftr_clean))
                    _amt_hits  = len(_footer_amt_re.findall(ftr_clean))
                    is_txn_dump = _date_hits >= 3 and _amt_hits >= 3

                    if not already_present and not is_txn_dump:
                        parts.append(ftr_clean)

            if parts:
                all_pages.append("\n\n".join(parts))

        merged = "\n\n---page-separator---\n\n".join(all_pages) if all_pages else "(No content)"
        if all_pages and merged and not merged.startswith("Error") and "<table" in merged.lower():
            merged = _strip_orphan_continued_da3_flatline(merged)
            merged = _strip_standalone_continued_banner_line(merged)
            merged = _trim_adjacent_da3_suffix_duplicating_next_table_prefix(merged)
            merged = _split_ucb_deposits_electronic_sections_html(merged)
            merged = _patch_da3_msft_g_ref_amounts_across_tables(merged)
            merged = _dedupe_subset_transaction_tables_html(merged)
            merged = _drop_da3_misplaced_debit_after_deposit_heading_tables(merged)
            merged = _strip_credits_prefix_from_debit_da3_table(merged)  # Fix 28
            merged = _strip_orphan_continued_da3_flatline(merged)
            merged = _strip_standalone_continued_banner_line(merged)
        return merged

    except Exception as e:
        import traceback
        log.exception("run_ocr failed: %s", e)
        return f"Error: {e}\n\n{traceback.format_exc()}"

    finally:
        for p in page_images:
            try:
                if isinstance(p, str) and p.endswith(".png") and "glmocr_page_" in os.path.basename(p):
                    os.unlink(p)
            except Exception:
                pass

with gr.Blocks(title="GLM-OCR") as demo:
    gr.Markdown("# GLM-OCR\nUpload a PDF or image. Headers included; tables stabilized.")
    file_in = gr.File(label="Upload PDF or image", file_types=[".pdf", ".png", ".jpg", ".jpeg", ".tiff", ".bmp"])
    run_btn = gr.Button("Run OCR", variant="primary")
    out = gr.Textbox(lines=40, label="Output (markdown)")
    run_btn.click(fn=run_ocr, inputs=file_in, outputs=out)

if __name__ == "__main__":
    demo.launch()