diff --git a/deepdoc/parser/docling_parser.py b/deepdoc/parser/docling_parser.py
index 6e4dadd771..56def78034 100644
--- a/deepdoc/parser/docling_parser.py
+++ b/deepdoc/parser/docling_parser.py
@@ -33,9 +33,14 @@ from PIL import Image
 from common.constants import MAXIMUM_PAGE_NUMBER
 
 try:
-    from docling.document_converter import DocumentConverter
+    from docling.document_converter import DocumentConverter, PdfFormatOption
+    from docling.datamodel.base_models import InputFormat
+    from docling.datamodel.pipeline_options import PdfPipelineOptions
 except Exception:
     DocumentConverter = None
+    PdfFormatOption = None
+    InputFormat = None
+    PdfPipelineOptions = None
 
 try:
     from deepdoc.parser.pdf_parser import RAGFlowPdfParser
@@ -217,20 +222,20 @@ class DoclingParser(RAGFlowPdfParser):
 
     def _iter_doc_items(self, doc) -> Iterable[tuple[str, Any, Optional[_BBox]]]:
         for t in getattr(doc, "texts", []):
+            label = getattr(t, "label", "")
+            if label in ("formula",):
+                text = getattr(t, "text", "") or getattr(t, "orig", "")
+                bbox = _extract_bbox_from_prov(t)
+                yield (DoclingContentType.EQUATION.value, text, bbox)
+                continue
+
             parent = getattr(t, "parent", "")
             ref = getattr(parent, "cref", "")
-            label = getattr(t, "label", "")
             if (label in ("section_header", "text") and ref in ("#/body",)) or label in ("list_item",):
                 text = getattr(t, "text", "") or ""
                 bbox = _extract_bbox_from_prov(t)
                 yield (DoclingContentType.TEXT.value, text, bbox)
 
-        for item in getattr(doc, "texts", []):
-            if getattr(item, "label", "") in ("FORMULA",):
-                text = getattr(item, "text", "") or ""
-                bbox = _extract_bbox_from_prov(item)
-                yield (DoclingContentType.EQUATION.value, text, bbox)
-
     def _transfer_to_sections(self, doc, parse_method: str) -> list[tuple[str, ...]]:
         sections: list[tuple[str, ...]] = []
         for typ, payload, bbox in self._iter_doc_items(doc):
@@ -240,6 +245,8 @@ class DoclingParser(RAGFlowPdfParser):
                     continue
             elif typ == DoclingContentType.EQUATION.value:
                 section = payload.strip()
+                if not section:
+                    continue
             else:
                 continue
 
@@ -556,7 +563,11 @@ class DoclingParser(RAGFlowPdfParser):
         except Exception as e:
             self.logger.warning(f"[Docling] render pages failed: {e}")
 
-        conv = DocumentConverter()
+        do_formula_enrichment = os.environ.get("DOCLING_FORMULA_ENRICHMENT", "0").strip().lower() in ("1", "true", "yes", "on")
+        self.logger.info(f"[Docling] Local conversion (formula_enrichment={do_formula_enrichment}): {src_path}")
+        pipeline_options = PdfPipelineOptions()
+        pipeline_options.do_formula_enrichment = do_formula_enrichment
+        conv = DocumentConverter(format_options={InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)})
         conv_res = conv.convert(str(src_path))
         doc = conv_res.document
         if callback:
diff --git a/docs/guides/dataset/select_pdf_parser.md b/docs/guides/dataset/select_pdf_parser.md
index 57eb8b3a67..4a74d3b5b6 100644
--- a/docs/guides/dataset/select_pdf_parser.md
+++ b/docs/guides/dataset/select_pdf_parser.md
@@ -72,6 +72,8 @@ To use an external Docling Serve instance (instead of local in-process Docling),
 
 When `DOCLING_SERVER_URL` is set, RAGFlow sends PDF content to Docling Serve (`/v1/convert/source`, with fallback to `/v1alpha/convert/source`) and ingests the returned markdown/text. If the variable is not set, RAGFlow keeps using local Docling (`USE_DOCLING=true` + installed package) behavior.
 
+- `DOCLING_FORMULA_ENRICHMENT`: (local Docling) Set to `1` to convert formulas to LaTeX (accurate but slow). Default `0` — formulas are still extracted as their original text.
+
 :::note
 All MinerU environment variables are optional. When set, these values are used to auto-provision a MinerU OCR model for the tenant on first use. To avoid auto-provisioning, skip the environment variable settings and only configure MinerU from the **Model providers** page in the UI.
 :::