feat: TSR auto-fallback to heuristic on quality issues, v1.7.1

Adds extract_tables_with_structure_auto_mem (Rust) /
extractTablesWithStructureAuto (napi). Returns
TableExtractionResult { markdown, fallback_reason } per input.

The wrapper runs the existing TSR-hybrid path then checks the
resulting cells for two known SLANet detection pathologies:

* phantom_empty_row: empty row sandwiched between non-empty rows
  (cheap, cell-metadata only).
* multi_row_in_cell: re-reads PDF text items, flags any cell whose
  contained items span >1.3× either the smallest cell height or
  the tallest contained item height. Catches the FNBO failure mode
  where a tall TSR cell absorbs two adjacent PDF rows.

When either fires, extract_tables_in_regions_mem runs over the same
crop bbox and its markdown replaces the TSR markdown.
fallback_reason carries the diagnostic label so callers can emit
metrics and watch each pathology independently.

Validated on FNBO branches PDF page 1 (Kansas region):
- TSR-only: merges Shawnee into BVP, wrong census tract on Sonoma.
- Auto fallback (phantom_empty_row): each row separate, correct tracts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

napi/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@firecrawl/pdf-inspector",
-  "version": "1.7.0",
+  "version": "1.7.1",
   "description": "Fast PDF classification and text extraction. Detect text-based vs scanned PDFs, extract text by region with quality checks. Native Rust performance via napi-rs.",
   "main": "index.js",
   "types": "index.d.ts",

napi/src/lib.rs

@@ -422,6 +422,52 @@ pub fn extract_tables_with_structure_cells(
     })
 }
 
+/// One result from `extractTablesWithStructureAuto` — markdown plus a
+/// diagnostic flag identifying which path produced it.
+///
+/// `fallbackReason` is `null` when the TSR-hybrid path produced the
+/// markdown directly. When stage 1's quality check fires (the cells
+/// look like a SLANet detection pathology — phantom rows or multi-row
+/// content in a single cell), the heuristic table extractor is run on
+/// the same region instead, and `fallbackReason` carries the diagnostic
+/// label (`"phantom_empty_row"`, `"multi_row_in_cell"`).
+#[napi(object)]
+pub struct TableExtractionResultJs {
+    pub markdown: String,
+    pub fallback_reason: Option<String>,
+}
+
+/// Auto-fallback variant of [`extractTablesWithStructure`].
+///
+/// Runs the TSR-hybrid path, checks the resulting cells for known
+/// SLANet detection pathologies, and falls back to the heuristic
+/// `extractTablesInRegions` for any input where the TSR path looks
+/// compromised.
+///
+/// On clean inputs this returns identical markdown to
+/// `extractTablesWithStructure`; on flagged inputs the heuristic
+/// markdown replaces the TSR markdown and `fallbackReason` is set.
+#[napi]
+pub fn extract_tables_with_structure_auto(
+    buffer: Buffer,
+    inputs: Vec<TsrTableInputJs>,
+) -> Result<Vec<TableExtractionResultJs>> {
+    let bytes: Vec<u8> = buffer.to_vec();
+    let parsed = parse_tsr_inputs(&inputs);
+
+    catch_panic("extract_tables_with_structure_auto", move || {
+        let result = pdf_inspector::extract_tables_with_structure_auto_mem(&bytes, &parsed)
+            .map_err(|e| to_napi_err(e, "extract_tables_with_structure_auto"))?;
+        Ok(result
+            .into_iter()
+            .map(|r| TableExtractionResultJs {
+                markdown: r.markdown,
+                fallback_reason: r.fallback_reason,
+            })
+            .collect())
+    })
+}
+
 fn parse_tsr_inputs(inputs: &[TsrTableInputJs]) -> Vec<pdf_inspector::TsrTableInput> {
     inputs
         .iter()

src/lib.rs

@@ -1185,6 +1185,200 @@ pub fn extract_tables_with_structure_mem(
         .collect())
 }
 
+/// Markdown for one extracted table plus a diagnostic flag describing
+/// which path produced it.
+///
+/// `fallback_reason` is `None` when the TSR-hybrid path produced the
+/// markdown directly; `Some(<short identifier>)` when stage 1's quality
+/// check fired and the heuristic `extract_tables_in_regions_mem` was
+/// substituted instead. The reason string is stable enough to use as a
+/// metric label (e.g. `phantom_empty_row`, `multi_row_in_cell`).
+#[derive(Debug, Clone)]
+pub struct TableExtractionResult {
+    pub markdown: String,
+    pub fallback_reason: Option<String>,
+}
+
+/// Detect quality issues in the TSR-hybrid output for a single input.
+///
+/// Returns `Some(reason)` if the cells look like they reflect a known
+/// SLANet detection pathology that the heuristic table extractor would
+/// likely handle better. Reasons (also used as metric labels):
+///
+/// * `phantom_empty_row` — a row whose every cell is empty, surrounded
+///   above and below by rows with content. SLANet sometimes emits an
+///   extra row that doesn't correspond to any visible PDF row.
+/// * `multi_row_in_cell` — at least one cell's matched PDF text items
+///   span more than 1.3× either the smallest cell height or the tallest
+///   contained item's own height, meaning the cell has absorbed text
+///   from two adjacent visual rows. SLANet's row under-detection on
+///   tightly-packed tables produces this.
+fn detect_tsr_quality_issue(
+    buffer: &[u8],
+    input: &TsrTableInput,
+    cells: &[tables::StructuredCell],
+) -> Result<Option<String>, PdfError> {
+    if cells.is_empty() {
+        return Ok(None);
+    }
+
+    // Phantom row: cheap, computed from cell metadata alone.
+    let max_row = cells.iter().map(|c| c.row).max().unwrap_or(0);
+    if max_row >= 2 {
+        let mut row_has_content = vec![false; max_row + 1];
+        for cell in cells {
+            if !cell.text.trim().is_empty() {
+                row_has_content[cell.row] = true;
+            }
+        }
+        for r in 1..max_row {
+            if !row_has_content[r] && row_has_content[r - 1] && row_has_content[r + 1] {
+                return Ok(Some("phantom_empty_row".to_string()));
+            }
+        }
+    }
+
+    // Multi-row-in-cell: re-extract PDF text items in the page and check
+    // whether any non-empty cell's bbox encloses items whose y-centers
+    // span across multiple visual lines. This is the FNBO failure mode —
+    // a tall TSR cell catches text from two adjacent PDF rows.
+    let (doc, _page_count) = load_document_from_mem(buffer)?;
+    let pages = doc.get_pages();
+    let page_1idx = input.page + 1;
+    let Some(&page_id) = pages.get(&page_1idx) else {
+        return Ok(None);
+    };
+    let page_h = get_page_height(&doc, page_id).unwrap_or(792.0);
+    let mut needed: HashSet<u32> = HashSet::new();
+    needed.insert(page_1idx);
+    let font_cmaps = FontCMaps::from_doc_pages_fast(&doc, Some(&needed));
+    let ((mut items, _rects, _lines), _has_gid, coords_rotated) =
+        extractor::content_stream::extract_page_text_items(
+            &doc,
+            page_id,
+            page_1idx,
+            &font_cmaps,
+            false,
+        )?;
+    let _ = text_utils::fix_letterspaced_items(&mut items);
+    let coords = if coords_rotated {
+        RegionCoordSpace::Rotated90Ccw
+    } else {
+        RegionCoordSpace::Standard
+    };
+
+    // Use the minimum non-empty cell height as the typical-row baseline.
+    // The pathology is that some cells are abnormally tall (multi-row),
+    // so taking the median or mean would scale with the bad cells. The
+    // smallest cell is likely a tightly-bound single-row cell, which is
+    // a better proxy for a real row's height.
+    let mut heights: Vec<f32> = cells
+        .iter()
+        .map(|c| (c.page_pt_bbox[3] - c.page_pt_bbox[1]).abs())
+        .filter(|h| *h > 0.0)
+        .collect();
+    heights.sort_by(|a, b| a.total_cmp(b));
+    let typical_row_h = heights.first().copied().unwrap_or(15.0).max(5.0);
+
+    for cell in cells {
+        if cell.text.trim().is_empty() {
+            continue;
+        }
+        let [x1, y1, x2, y2] = cell.page_pt_bbox;
+        if x1 >= x2 || y1 >= y2 {
+            continue;
+        }
+        let bounds = region_bounds(x1, y1, x2, y2, page_h, coords);
+        let mut min_y = f32::INFINITY;
+        let mut max_y = f32::NEG_INFINITY;
+        let mut max_item_h = 0f32;
+        let mut count = 0u32;
+        for item in &items {
+            if tsr_region_contains_item(item, bounds) {
+                let cy = item.y + item.height * 0.5;
+                min_y = min_y.min(cy);
+                max_y = max_y.max(cy);
+                max_item_h = max_item_h.max(item.height);
+                count += 1;
+            }
+        }
+        if count < 2 {
+            continue;
+        }
+        // Items on the same visual line have y-centers within ~one
+        // line-height. Flag a cell whose items span > 1.3× both the
+        // typical row height AND the largest item's own height —
+        // either signal alone is a strong indicator of multi-line text
+        // inside a cell that should be a single row.
+        let span = max_y - min_y;
+        let row_threshold = typical_row_h * 1.3;
+        let item_threshold = max_item_h.max(5.0) * 1.3;
+        if span > row_threshold || span > item_threshold {
+            return Ok(Some("multi_row_in_cell".to_string()));
+        }
+    }
+
+    Ok(None)
+}
+
+/// Auto-fallback variant of [`extract_tables_with_structure_mem`]:
+/// runs the TSR-hybrid path, checks the resulting cells for known
+/// SLANet detection pathologies (phantom rows, multi-row-in-cell text),
+/// and falls back to the heuristic [`extract_tables_in_regions_mem`]
+/// for any input where the TSR path looks compromised.
+///
+/// On clean inputs this is identical to the markdown variant.
+/// On flagged inputs the heuristic markdown replaces the TSR markdown
+/// and the result's `fallback_reason` is set to the diagnostic label.
+///
+/// Use this from production callers that want self-healing output.
+/// Use [`extract_tables_with_structure_mem`] when you want raw TSR
+/// output regardless of quality (e.g. eval harnesses comparing the
+/// two paths).
+pub fn extract_tables_with_structure_auto_mem(
+    buffer: &[u8],
+    inputs: &[TsrTableInput],
+) -> Result<Vec<TableExtractionResult>, PdfError> {
+    let tsr_cells = extract_tables_with_structure_cells_mem(buffer, inputs)?;
+    let mut results = Vec::with_capacity(inputs.len());
+
+    for (i, input) in inputs.iter().enumerate() {
+        let cells = &tsr_cells[i];
+        let issue = detect_tsr_quality_issue(buffer, input, cells)?;
+
+        let result = match issue {
+            None => TableExtractionResult {
+                markdown: if cells.is_empty() {
+                    String::new()
+                } else {
+                    tables::cells_to_markdown(cells)
+                },
+                fallback_reason: None,
+            },
+            Some(reason) => {
+                // Fall back to heuristic on the input's table region.
+                // The crop's PDF-pt bbox IS the table region.
+                let heuristic = extract_tables_in_regions_mem(
+                    buffer,
+                    &[(input.page, vec![input.crop_pdf_pt_bbox])],
+                )?;
+                let md = heuristic
+                    .into_iter()
+                    .next()
+                    .and_then(|page_result| page_result.regions.into_iter().next().map(|r| r.text))
+                    .unwrap_or_default();
+                TableExtractionResult {
+                    markdown: md,
+                    fallback_reason: Some(reason),
+                }
+            }
+        };
+        results.push(result);
+    }
+
+    Ok(results)
+}
+
 /// Get page height in points from MediaBox.
 fn get_page_height(doc: &Document, page_id: lopdf::ObjectId) -> Option<f32> {
     let page_dict = doc.get_dictionary(page_id).ok()?;

tests/integration_tests.rs

@@ -2052,6 +2052,144 @@ fn test_extract_tables_with_structure_separator_after_thead() {
     assert_eq!(mds[0], "|Department|Core Courses|\n|---|---|\n|BIO|8.23|\n");
 }
 
+// =========================================================================
+// extract_tables_with_structure_auto_mem tests (TSR + heuristic fallback)
+// =========================================================================
+
+#[test]
+fn test_auto_passes_through_clean_tsr_output() {
+    use pdf_inspector::{extract_tables_with_structure_auto_mem, TsrTableInput};
+
+    let buf = synthetic_dense_table_pdf();
+    let tokens: Vec<String> = [
+        "<table>",
+        "<thead>",
+        "<tr>",
+        "<th></th>",
+        "<th></th>",
+        "</tr>",
+        "</thead>",
+        "<tbody>",
+        "<tr>",
+        "<td></td>",
+        "<td></td>",
+        "</tr>",
+        "<tr>",
+        "<td></td>",
+        "<td></td>",
+        "</tr>",
+        "</tbody>",
+        "</table>",
+    ]
+    .into_iter()
+    .map(String::from)
+    .collect();
+    // Cells fit each visible row cleanly. Same shape as the existing
+    // dense-overlap regression test — TSR should produce clean output
+    // and the auto wrapper should pass through with no fallback.
+    let cell_bboxes = vec![
+        poly(10.0, 72.0, 100.0, 112.0),
+        poly(90.0, 72.0, 180.0, 112.0),
+        poly(10.0, 88.8, 100.0, 128.8),
+        poly(90.0, 88.8, 180.0, 128.8),
+        poly(10.0, 105.6, 100.0, 145.6),
+        poly(90.0, 105.6, 180.0, 145.6),
+    ];
+
+    let results = extract_tables_with_structure_auto_mem(
+        &buf,
+        &[TsrTableInput {
+            page: 0,
+            crop_pdf_pt_bbox: [0.0, 0.0, 200.0, 800.0],
+            render_dpi: 72.0,
+            structure_tokens: tokens,
+            cell_bboxes,
+        }],
+    )
+    .unwrap();
+    assert_eq!(results.len(), 1);
+    assert!(
+        results[0].fallback_reason.is_none(),
+        "expected no fallback, got {:?}",
+        results[0].fallback_reason
+    );
+    assert!(results[0].markdown.contains("Oak Street"));
+    assert!(results[0].markdown.contains("Boardwalk"));
+    assert!(!results[0].markdown.contains("Oak Street Boardwalk"));
+}
+
+#[test]
+fn test_auto_falls_back_on_multi_row_in_cell() {
+    use pdf_inspector::{extract_tables_with_structure_auto_mem, TsrTableInput};
+
+    let buf = synthetic_dense_table_pdf();
+    // TSR returns only 2 rows for what's actually 3 visible PDF rows.
+    // Row 1's cells are tall enough to encompass both Oak Street and
+    // Boardwalk text — the FNBO row-undercount pattern.
+    let tokens: Vec<String> = [
+        "<table>",
+        "<thead>",
+        "<tr>",
+        "<th></th>",
+        "<th></th>",
+        "</tr>",
+        "</thead>",
+        "<tbody>",
+        "<tr>",
+        "<td></td>",
+        "<td></td>",
+        "</tr>",
+        "</tbody>",
+        "</table>",
+    ]
+    .into_iter()
+    .map(String::from)
+    .collect();
+    // Header row at top-left y=[88, 105] (covers "Branch Name"/"Deposits"
+    // at native y=700, top-left y≈92-103). The "data" row at top-left
+    // y=[105, 145] is intentionally tall — covers BOTH the Oak Street
+    // line (top-left y≈108-119) AND the Boardwalk line (y≈124-135).
+    let cell_bboxes = vec![
+        poly(10.0, 88.0, 100.0, 105.0),
+        poly(90.0, 88.0, 180.0, 105.0),
+        poly(10.0, 105.0, 100.0, 145.0),
+        poly(90.0, 105.0, 180.0, 145.0),
+    ];
+
+    let results = extract_tables_with_structure_auto_mem(
+        &buf,
+        &[TsrTableInput {
+            page: 0,
+            crop_pdf_pt_bbox: [0.0, 0.0, 200.0, 800.0],
+            render_dpi: 72.0,
+            structure_tokens: tokens,
+            cell_bboxes,
+        }],
+    )
+    .unwrap();
+    assert_eq!(results.len(), 1);
+    assert_eq!(
+        results[0].fallback_reason.as_deref(),
+        Some("multi_row_in_cell"),
+        "expected multi_row_in_cell fallback, got {:?}",
+        results[0].fallback_reason
+    );
+    // The heuristic-fallback markdown should preserve all three PDF rows.
+    let md = &results[0].markdown;
+    assert!(md.contains("Oak Street"), "missing Oak Street: {md}");
+    assert!(md.contains("Boardwalk"), "missing Boardwalk: {md}");
+    assert!(md.contains("100"), "missing 100: {md}");
+    assert!(md.contains("200"), "missing 200: {md}");
+}
+
+#[test]
+fn test_auto_returns_empty_inputs() {
+    use pdf_inspector::extract_tables_with_structure_auto_mem;
+    let buf = synthetic_dense_table_pdf();
+    let results = extract_tables_with_structure_auto_mem(&buf, &[]).unwrap();
+    assert!(results.is_empty());
+}
+
 // =========================================================================
 // extract_pages_markdown_mem tests
 // =========================================================================