Feat: MinerU supports VLM-Transfomers backend (#10809)

### What problem does this PR solve?

MinerU supports VLM-Transfomers backend.

Set `MINERU_BACKEND="pipeline"` to choose the backend. (Options:
pipeline | vlm-transformers, default is pipeline)

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>

deepdoc/parser/mineru_parser.py

@@ -45,6 +45,9 @@ class MinerUContentType(StrEnum):
     TABLE = "table"
     TEXT = "text"
     EQUATION = "equation"
+    CODE = "code"
+    LIST = "list"
+    DISCARDED = "discarded"
 
 
 class MinerUParser(RAGFlowPdfParser):
@@ -80,8 +83,10 @@ class MinerUParser(RAGFlowPdfParser):
             logging.error(f"[MinerU] Unexpected error during installation check: {e}")
         return False
 
-    def _run_mineru(self, input_path: Path, output_dir: Path, method: str = "auto", lang: Optional[str] = None):
+    def _run_mineru(self, input_path: Path, output_dir: Path, method: str = "auto", backend: str = "pipeline", lang: Optional[str] = None):
         cmd = [str(self.mineru_path), "-p", str(input_path), "-o", str(output_dir), "-m", method]
+        if backend:
+            cmd.extend(["-b", backend])
         if lang:
             cmd.extend(["-l", lang])
 
@@ -231,8 +236,10 @@ class MinerUParser(RAGFlowPdfParser):
             poss.append(([int(p) - 1 for p in pn.split("-")], left, right, top, bottom))
         return poss
 
-    def _read_output(self, output_dir: Path, file_stem: str, method: str = "auto") -> list[dict[str, Any]]:
+    def _read_output(self, output_dir: Path, file_stem: str, method: str = "auto", backend: str = "pipeline") -> list[dict[str, Any]]:
         subdir = output_dir / file_stem / method
+        if backend.startswith("vlm-"):
+            subdir = output_dir / file_stem / "vlm"
         json_file = subdir / f"{file_stem}_content_list.json"
 
         if not json_file.exists():
@@ -259,6 +266,12 @@ class MinerUParser(RAGFlowPdfParser):
                     section = "".join(output["image_caption"]) + "\n" + "".join(output["image_footnote"])
                 case MinerUContentType.EQUATION:
                     section = output["text"]
+                case MinerUContentType.CODE:
+                    section = output["code_body"] + "\n".join(output.get("code_caption", []))
+                case MinerUContentType.LIST:
+                    section = "\n".join(output.get("list_items", []))
+                case MinerUContentType.DISCARDED:
+                    pass
 
             if section:
                 sections.append((section, self._line_tag(output)))
@@ -274,6 +287,7 @@ class MinerUParser(RAGFlowPdfParser):
         callback: Optional[Callable] = None,
         *,
         output_dir: Optional[str] = None,
+        backend: str = "pipeline",
         lang: Optional[str] = None,
         method: str = "auto",
         delete_output: bool = True,
@@ -313,8 +327,8 @@ class MinerUParser(RAGFlowPdfParser):
         self.__images__(pdf, zoomin=1)
 
         try:
-            self._run_mineru(pdf, out_dir, method=method, lang=lang)
-            outputs = self._read_output(out_dir, pdf.stem, method=method)
+            self._run_mineru(pdf, out_dir, method=method, backend=backend, lang=lang)
+            outputs = self._read_output(out_dir, pdf.stem, method=method, backend=backend)
             self.logger.info(f"[MinerU] Parsed {len(outputs)} blocks from PDF.")
             if callback:
                 callback(0.75, f"[MinerU] Parsed {len(outputs)} blocks from PDF.")

docs/faq.mdx

@@ -536,5 +536,16 @@ uv pip install -U "mineru[core]" -i https://mirrors.aliyun.com/pypi/simple
 4. In the web UI, navigate to the **Configuration** page of your dataset. Click **Built-in** in the **Ingestion pipeline** section, select a chunking method from the **Built-in** dropdown, which supports PDF parsing, and slect **MinerU** in **PDF parser**.
 5. If you use a custom ingestion pipeline instead, you must also complete the first three steps before selecting **MinerU** in the **Parsing method** section of the **Parser** component.
 
+---
 
+### How to specify the settings of MinerU?
 
+Set `MINERU_EXECUTABLE` to the path of the MinerU executable. (Default: mineru)
+
+Set `MINERU_DELETE_OUTPUT=0` to keep MinerU's output. (Default: 1, which deletes temporary output)
+
+Set `MINERU_OUTPUT_DIR` to specify the output directory. (Uses a temporary directory if unset)
+
+Set `MINERU_BACKEND="pipeline"` to choose the backend. (Options: pipeline | vlm-transformers, default is pipeline)
+
+Other environment variables listed [here](https://opendatalab.github.io/MinerU/usage/cli_tools/#environment-variables-description) are supported automatically by MinerU.

rag/app/naive.py

@@ -530,6 +530,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
                 binary=binary,
                 callback=callback,
                 output_dir=os.environ.get("MINERU_OUTPUT_DIR", ""),
+                backend=os.environ.get("MINERU_BACKEND", "pipeline"),
                 delete_output=bool(int(os.environ.get("MINERU_DELETE_OUTPUT", 1))),
             )
             parser_config["chunk_token_num"] = 0
@@ -552,7 +553,6 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
             res = tokenize_table(tables, doc, is_english)
             callback(0.8, "Finish parsing.")
 
-
         elif layout_recognizer == "TCADP Parser":
             tcadp_parser = TCADPParser()
             if not tcadp_parser.check_installation():