feat!: Resolve nested clusters for DoclingDocument

deepsearch_glm/utils/doc_utils.py

@@ -1,20 +1,7 @@
 import re
-from pathlib import Path
-from typing import List
 
 import pandas as pd
-from docling_core.types.doc import (
-    BoundingBox,
-    CoordOrigin,
-    DocItemLabel,
-    DoclingDocument,
-    DocumentOrigin,
-    GroupLabel,
-    ProvenanceItem,
-    Size,
-    TableCell,
-    TableData,
-)
+from docling_core.types.doc import DocItemLabel
 
 
 def resolve_item(paths, obj):
@@ -51,252 +38,6 @@ def resolve_item(paths, obj):
         return None
 
 
-def _flatten_table_grid(grid: List[List[dict]]) -> List[dict]:
-    unique_objects = []
-    seen_spans = set()
-
-    for sublist in grid:
-        for obj in sublist:
-            # Convert the spans list to a tuple of tuples for hashing
-            spans_tuple = tuple(tuple(span) for span in obj["spans"])
-            if spans_tuple not in seen_spans:
-                seen_spans.add(spans_tuple)
-                unique_objects.append(obj)
-
-    return unique_objects
-
-
-def to_docling_document(doc_glm, update_name_label=False) -> DoclingDocument:
-    origin = DocumentOrigin(
-        mimetype="application/pdf",
-        filename=doc_glm["file-info"]["filename"],
-        binary_hash=doc_glm["file-info"]["document-hash"],
-    )
-    doc_name = Path(origin.filename).stem
-
-    doc: DoclingDocument = DoclingDocument(name=doc_name, origin=origin)
-
-    if "properties" in doc_glm:
-        props = pd.DataFrame(
-            doc_glm["properties"]["data"], columns=doc_glm["properties"]["headers"]
-        )
-    else:
-        props = pd.DataFrame()
-
-    current_list = None
-
-    for ix, pelem in enumerate(doc_glm["page-elements"]):
-        ptype = pelem["type"]
-        span_i = pelem["span"][0]
-        span_j = pelem["span"][1]
-
-        if "iref" not in pelem:
-            # print(json.dumps(pelem, indent=2))
-            continue
-
-        iref = pelem["iref"]
-
-        if re.match("#/figures/(\\d+)/captions/(.+)", iref):
-            # print(f"skip {iref}")
-            continue
-
-        if re.match("#/tables/(\\d+)/captions/(.+)", iref):
-            # print(f"skip {iref}")
-            continue
-
-        path = iref.split("/")
-        obj = resolve_item(path, doc_glm)
-
-        if obj is None:
-            current_list = None
-            print(f"warning: undefined {path}")
-            continue
-
-        if ptype == "figure":
-            current_list = None
-            text = ""
-            caption_refs = []
-            for caption in obj["captions"]:
-                text += caption["text"]
-
-                for nprov in caption["prov"]:
-                    npaths = nprov["$ref"].split("/")
-                    nelem = resolve_item(npaths, doc_glm)
-
-                    if nelem is None:
-                        # print(f"warning: undefined caption {npaths}")
-                        continue
-
-                    span_i = nelem["span"][0]
-                    span_j = nelem["span"][1]
-
-                    cap_text = caption["text"][span_i:span_j]
-
-                    # doc_glm["page-elements"].remove(nelem)
-
-                    prov = ProvenanceItem(
-                        page_no=nelem["page"],
-                        charspan=tuple(nelem["span"]),
-                        bbox=BoundingBox.from_tuple(
-                            nelem["bbox"], origin=CoordOrigin.BOTTOMLEFT
-                        ),
-                    )
-
-                    caption_obj = doc.add_text(
-                        label=DocItemLabel.CAPTION, text=cap_text, prov=prov
-                    )
-                    caption_refs.append(caption_obj.get_ref())
-
-            prov = ProvenanceItem(
-                page_no=pelem["page"],
-                charspan=(0, len(text)),
-                bbox=BoundingBox.from_tuple(
-                    pelem["bbox"], origin=CoordOrigin.BOTTOMLEFT
-                ),
-            )
-
-            pic = doc.add_picture(prov=prov)
-            pic.captions.extend(caption_refs)
-
-        elif ptype == "table":
-            current_list = None
-            text = ""
-            caption_refs = []
-            for caption in obj["captions"]:
-                text += caption["text"]
-
-                for nprov in caption["prov"]:
-                    npaths = nprov["$ref"].split("/")
-                    nelem = resolve_item(npaths, doc_glm)
-
-                    if nelem is None:
-                        # print(f"warning: undefined caption {npaths}")
-                        continue
-
-                    span_i = nelem["span"][0]
-                    span_j = nelem["span"][1]
-
-                    cap_text = caption["text"][span_i:span_j]
-
-                    # doc_glm["page-elements"].remove(nelem)
-
-                    prov = ProvenanceItem(
-                        page_no=nelem["page"],
-                        charspan=tuple(nelem["span"]),
-                        bbox=BoundingBox.from_tuple(
-                            nelem["bbox"], origin=CoordOrigin.BOTTOMLEFT
-                        ),
-                    )
-
-                    caption_obj = doc.add_text(
-                        label=DocItemLabel.CAPTION, text=cap_text, prov=prov
-                    )
-                    caption_refs.append(caption_obj.get_ref())
-
-            table_cells_glm = _flatten_table_grid(obj["data"])
-
-            table_cells = []
-            for tbl_cell_glm in table_cells_glm:
-                if tbl_cell_glm["bbox"] is not None:
-                    bbox = BoundingBox.from_tuple(
-                        tbl_cell_glm["bbox"], origin=CoordOrigin.BOTTOMLEFT
-                    )
-                else:
-                    bbox = None
-
-                is_col_header = False
-                is_row_header = False
-                is_row_section = False
-
-                if tbl_cell_glm["type"] == "col_header":
-                    is_col_header = True
-                elif tbl_cell_glm["type"] == "row_header":
-                    is_row_header = True
-                elif tbl_cell_glm["type"] == "row_section":
-                    is_row_section = True
-
-                table_cells.append(
-                    TableCell(
-                        row_span=tbl_cell_glm["row-span"][1]
-                        - tbl_cell_glm["row-span"][0],
-                        col_span=tbl_cell_glm["col-span"][1]
-                        - tbl_cell_glm["col-span"][0],
-                        start_row_offset_idx=tbl_cell_glm["row-span"][0],
-                        end_row_offset_idx=tbl_cell_glm["row-span"][1],
-                        start_col_offset_idx=tbl_cell_glm["col-span"][0],
-                        end_col_offset_idx=tbl_cell_glm["col-span"][1],
-                        text=tbl_cell_glm["text"],
-                        bbox=bbox,
-                        column_header=is_col_header,
-                        row_header=is_row_header,
-                        row_section=is_row_section,
-                    )
-                )
-
-            tbl_data = TableData(
-                num_rows=obj.get("#-rows", 0),
-                num_cols=obj.get("#-cols", 0),
-                table_cells=table_cells,
-            )
-
-            prov = ProvenanceItem(
-                page_no=pelem["page"],
-                charspan=(0, 0),
-                bbox=BoundingBox.from_tuple(
-                    pelem["bbox"], origin=CoordOrigin.BOTTOMLEFT
-                ),
-            )
-
-            tbl = doc.add_table(data=tbl_data, prov=prov)
-            tbl.captions.extend(caption_refs)
-
-        elif "text" in obj:
-            text = obj["text"][span_i:span_j]
-
-            type_label = pelem["type"]
-            name_label = pelem["name"]
-            if update_name_label and len(props) > 0 and type_label == "paragraph":
-                prop = props[
-                    (props["type"] == "semantic") & (props["subj_path"] == iref)
-                ]
-                if len(prop) == 1 and prop.iloc[0]["confidence"] > 0.85:
-                    name_label = prop.iloc[0]["label"]
-
-            prov = ProvenanceItem(
-                page_no=pelem["page"],
-                charspan=(0, len(text)),
-                bbox=BoundingBox.from_tuple(
-                    pelem["bbox"], origin=CoordOrigin.BOTTOMLEFT
-                ),
-            )
-            label = DocItemLabel(name_label)
-
-            if label == DocItemLabel.LIST_ITEM:
-                if current_list is None:
-                    current_list = doc.add_group(label=GroupLabel.LIST, name="list")
-
-                # TODO: Infer if this is a numbered or a bullet list item
-                doc.add_list_item(
-                    text=text, enumerated=False, prov=prov, parent=current_list
-                )
-            elif label == DocItemLabel.SECTION_HEADER:
-                current_list = None
-
-                doc.add_heading(text=text, prov=prov)
-            else:
-                current_list = None
-
-                doc.add_text(label=DocItemLabel(name_label), text=text, prov=prov)
-
-    for page_dim in doc_glm["page-dimensions"]:
-        page_no = int(page_dim["page"])
-        size = Size(width=page_dim["width"], height=page_dim["height"])
-
-        doc.add_page(page_no=page_no, size=size)
-
-    return doc
-
-
 def to_legacy_document_format(doc_glm, doc_leg={}, update_name_label=False):
     """Convert Document object (with `body`) to its legacy format (with `main-text`)"""
 

src/andromeda/tooling/structs/subjects/base.h

@@ -25,6 +25,8 @@ namespace andromeda
 
     const static inline std::string prov_lbl = "prov";
 
+    const static inline std::string payload_lbl = "payload"; // arbitrary data that needs to be carried through
+
     const static inline std::string subj_hash_lbl = "subj_hash";
     const static inline std::string text_hash_lbl = "text_hash"; // for text
 
@@ -141,6 +143,8 @@ namespace andromeda
     std::vector<base_property> properties;
     std::vector<base_instance> instances;
     std::vector<base_relation> relations;
+
+    nlohmann::json payload;
 
     //std::vector<base_entity> entities;
   };
@@ -159,7 +163,9 @@ namespace andromeda
 
     properties({}),
     instances({}),
-    relations({})
+    relations({}),
+
+    payload(nlohmann::json::value_t::null)
   {}
 
   base_subject::base_subject(subject_name name):
@@ -176,7 +182,9 @@ namespace andromeda
 
     properties({}),
     instances({}),
-    relations({})
+    relations({}),
+
+    payload(nlohmann::json::value_t::null)
   {}
 
   base_subject::base_subject(uint64_t dhash,
@@ -195,7 +203,9 @@ namespace andromeda
 
     properties({}),
     instances({}),
-    relations({})
+    relations({}),
+
+    payload(nlohmann::json::value_t::null)
   {
     auto parts = utils::split(dloc, "#");
     if(parts.size()==2)
@@ -321,6 +331,10 @@ namespace andromeda
   {
     nlohmann::json result = nlohmann::json::object({});
 
+    {
+      result[payload_lbl] = payload;      
+    }
+
     {
       result[subj_hash_lbl] = hash;
       result[dloc_lbl] = dloc;
@@ -379,6 +393,8 @@ namespace andromeda
 
   bool base_subject::_from_json(const nlohmann::json& item)
   {
+    payload = item.value(payload_lbl, payload);
+
     hash = item.value(subj_hash_lbl, hash);
 
     dloc = item.value(dloc_lbl, dloc);

src/andromeda/tooling/structs/subjects/document/doc_normalisation.h

@@ -323,14 +323,14 @@ namespace andromeda
 
         std::string base = parts.at(1);
         std::size_t index = std::stoi(parts.at(2));
-
+	
         auto& item = orig.at(base).at(index);
-
+	
         if(is_text.count(prov->get_type()))
           {
             std::stringstream ss;
             ss << doc_name << "#/" << doc_type::texts_lbl << "/" << texts.size();
-
+	    
             std::string dloc = ss.str();
 
             auto subj = std::make_shared<subject<TEXT> >(doc.get_hash(), dloc, prov);

src/andromeda/tooling/structs/subjects/figure.h

@@ -169,6 +169,15 @@ namespace andromeda
   {
     base_subject::valid = true;
 
+    if(data.count(payload_lbl))
+      {
+	payload = data.value(payload_lbl, payload);
+      }
+    else
+      {
+	payload = nlohmann::json::value_t::null;
+      }
+
     return base_subject::valid;
   }
 

src/andromeda/tooling/structs/subjects/table.h

@@ -279,6 +279,15 @@ namespace andromeda
 
     data.clear();
 
+    if(item.count(payload_lbl))
+      {
+	payload = item.value(payload_lbl, payload);
+      }
+    else
+      {
+	payload = nlohmann::json::value_t::null;
+      }
+
     {
       conf = item.value(base_subject::confidence_lbl, conf);
       created_by = item.value(base_subject::created_by_lbl, created_by);