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Fixes #16917. ## Problem `deepdoc/parser/docling_parser.py::_parse_pdf_remote` decides whether the response is chunked based on which payload was sent, not on what came back. Docling Serve silently drops unknown fields such as `do_chunking` (Pydantic `extra="ignore"`) and returns a standard `{"document": ..., "status": ...}` conversion response. The code then: 1. sets `is_chunked_response = True` from the request shape, 2. logs `Successfully used native chunking on: <endpoint>`, 3. extracts 0 chunks from `response_json.get("results", [])`, 4. logs `Native chunks received: 0`, 5. falls through to the existing `md_content` fallback. The `md_content` fallback path is fine. The misleading log lines are the problem: operators see "Successfully used native chunking" immediately followed by "Native chunks received: 0" and "No chunk built", which looks like an internal regression rather than a server contract gap. ## Fix Decide chunked-vs-standard from the **response shape**, not the request: ```python response_is_chunk = self._looks_like_chunk_response(response_json) is_chunked_response = chunk_flag and response_is_chunk ``` `_looks_like_chunk_response` returns True iff the response is a non-empty list or a dict with a non-empty `results` or `chunks` list. A standard conversion response (`{"document": ..., "status": ...}`) does not match, so a server that ignored the chunking flag is correctly classified as standard even when the request payload asked for chunking. When chunking was requested but the server returned a standard response, log a single WARNING ("Server ignored chunking request on <endpoint>; treating response as standard conversion.") instead of the INFO success line. The misleading "Prioritizes native chunking endpoints" docstring is replaced with what the code actually does. ## Tests `test/unit_test/deepdoc/parser/test_docling_parser_remote.py` (6 tests, all passing): - `test_remote_chunked_200_standard_payload_falls_back` (existing — still passes; the `md_content` path is unchanged) - `test_chunk_shape_helper_recognises_chunk_payloads` - `test_chunk_shape_helper_rejects_standard_payloads` - `test_remote_chunked_request_with_results_list_is_treated_as_chunked` - `test_remote_top_level_list_response_is_treated_as_chunked` - `test_remote_chunked_request_with_ignored_flag_does_not_log_success` ``` $ uv run pytest test/unit_test/deepdoc/parser/test_docling_parser_remote.py -v ============================== 6 passed in 0.26s ============================== ``` ## Files changed - `deepdoc/parser/docling_parser.py` (+35 / -5) - `test/unit_test/deepdoc/parser/test_docling_parser_remote.py` (+89 / -4) ## Backward compatibility - All four payload/endpoint combinations continue to be tried in the same order. - The bundled-docling happy path (`parse_pdf`, not `_parse_pdf_remote`) is untouched. - A server that returns a real chunked response to a chunked request still goes down the chunked branch. A server that returns a standard response to a chunked request now goes down the standard branch with `is_chunked_response=False` instead of misleadingly logging success. ## Follow-up (out of scope) Calling the real Docling-Serve native chunk endpoints (`/v1/chunk/hybrid/source`, `/v1/chunk/hierarchical/source`) with `HybridChunkerOptions` is a larger feature change and warrants its own PR after this lands. Co-authored-by: Harsh23Kashyap <harsh@example.com>
167 lines
6.4 KiB
Python
167 lines
6.4 KiB
Python
from __future__ import annotations
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import importlib.util
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import logging
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import sys
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import types
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from pathlib import Path
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import pytest
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ROOT = Path(__file__).resolve().parents[4]
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class _Response:
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status_code = 200
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text = ""
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def __init__(self, payload, status_code: int = 200):
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self._payload = payload
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self.status_code = status_code
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def json(self):
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return self._payload
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def _load_docling_parser(monkeypatch):
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common_pkg = types.ModuleType("common")
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constants_mod = types.ModuleType("common.constants")
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constants_mod.MAXIMUM_PAGE_NUMBER = 1000
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deepdoc_pkg = types.ModuleType("deepdoc")
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parser_pkg = types.ModuleType("deepdoc.parser")
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parser_pkg.__path__ = []
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utils_mod = types.ModuleType("deepdoc.parser.utils")
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utils_mod.extract_pdf_outlines = lambda _source: []
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pil_pkg = types.ModuleType("PIL")
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image_mod = types.ModuleType("PIL.Image")
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image_mod.Image = object
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pil_pkg.Image = image_mod
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monkeypatch.setitem(sys.modules, "common", common_pkg)
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monkeypatch.setitem(sys.modules, "common.constants", constants_mod)
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monkeypatch.setitem(sys.modules, "deepdoc", deepdoc_pkg)
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monkeypatch.setitem(sys.modules, "deepdoc.parser", parser_pkg)
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monkeypatch.setitem(sys.modules, "deepdoc.parser.utils", utils_mod)
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monkeypatch.setitem(sys.modules, "pdfplumber", types.ModuleType("pdfplumber"))
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monkeypatch.setitem(sys.modules, "PIL", pil_pkg)
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monkeypatch.setitem(sys.modules, "PIL.Image", image_mod)
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spec = importlib.util.spec_from_file_location(
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"_docling_parser_under_test",
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ROOT / "deepdoc" / "parser" / "docling_parser.py",
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)
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module = importlib.util.module_from_spec(spec)
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monkeypatch.setitem(sys.modules, spec.name, module)
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spec.loader.exec_module(module)
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return module
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@pytest.mark.p2
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def test_remote_chunked_200_standard_payload_falls_back(monkeypatch):
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module = _load_docling_parser(monkeypatch)
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calls = []
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def fake_post(_url, json, timeout):
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calls.append((json, timeout))
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return _Response({"document": {"md_content": "# Parsed\n\nbody"}})
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monkeypatch.setattr(module.requests, "post", fake_post)
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parser = module.DoclingParser(docling_server_url="http://docling.local")
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sections, tables = parser._parse_pdf_remote("sample.pdf", binary=b"%PDF", parse_method="raw")
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assert sections == [("# Parsed\n\nbody", "")]
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assert tables == []
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assert calls[0][0]["options"]["do_chunking"] is True
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@pytest.mark.p2
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def test_chunk_shape_helper_recognises_chunk_payloads(monkeypatch):
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"""A response that is chunk-shaped (list, or dict with non-empty results/chunks)
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is classified as chunked regardless of which payload was sent."""
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module = _load_docling_parser(monkeypatch)
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assert module.DoclingParser._looks_like_chunk_response(
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[{"text": "chunk-1"}]
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) is True
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assert module.DoclingParser._looks_like_chunk_response(
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{"results": [{"text": "chunk-1"}, {"text": "chunk-2"}]}
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) is True
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assert module.DoclingParser._looks_like_chunk_response(
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{"chunks": [{"text": "chunk-1"}]}
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) is True
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@pytest.mark.p2
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def test_chunk_shape_helper_rejects_standard_payloads(monkeypatch):
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"""A standard conversion response, empty containers, and non-payload types
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are correctly classified as not-chunked."""
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module = _load_docling_parser(monkeypatch)
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standard = {"document": {"md_content": "body"}, "status": "success"}
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assert module.DoclingParser._looks_like_chunk_response(standard) is False
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assert module.DoclingParser._looks_like_chunk_response({}) is False
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assert module.DoclingParser._looks_like_chunk_response({"results": []}) is False
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assert module.DoclingParser._looks_like_chunk_response({"chunks": []}) is False
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assert module.DoclingParser._looks_like_chunk_response([]) is False
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assert module.DoclingParser._looks_like_chunk_response("not-a-payload") is False
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assert module.DoclingParser._looks_like_chunk_response(None) is False
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assert module.DoclingParser._looks_like_chunk_response(42) is False
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@pytest.mark.p2
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def test_remote_chunked_request_with_results_list_is_treated_as_chunked(monkeypatch):
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"""A server that returns a ``results`` list (Docling Serve's native chunk
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shape) is treated as chunked and each chunk becomes a section."""
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module = _load_docling_parser(monkeypatch)
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def fake_post(_url, json, timeout):
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return _Response({"results": [{"text": "alpha"}, {"text": "beta"}]})
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monkeypatch.setattr(module.requests, "post", fake_post)
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parser = module.DoclingParser(docling_server_url="http://docling.local")
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sections, tables = parser._parse_pdf_remote("sample.pdf", binary=b"%PDF", parse_method="raw")
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assert sections == [("alpha", ""), ("beta", "")]
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assert tables == []
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@pytest.mark.p2
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def test_remote_top_level_list_response_is_treated_as_chunked(monkeypatch):
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"""A server that returns a top-level JSON array of chunks is treated
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as chunked (matches the existing implicit assumption in the code)."""
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module = _load_docling_parser(monkeypatch)
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def fake_post(_url, json, timeout):
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return _Response([{"text": "first"}, {"text": "second"}])
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monkeypatch.setattr(module.requests, "post", fake_post)
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parser = module.DoclingParser(docling_server_url="http://docling.local")
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sections, _ = parser._parse_pdf_remote("sample.pdf", binary=b"%PDF", parse_method="raw")
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assert sections == [("first", ""), ("second", "")]
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@pytest.mark.p2
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def test_remote_chunked_request_with_ignored_flag_does_not_log_success(monkeypatch, caplog):
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"""When Docling Serve silently drops the ``do_chunking`` flag and returns
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a standard conversion response, RAGFlow must not log a chunking-success
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message and must log a warning instead."""
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module = _load_docling_parser(monkeypatch)
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def fake_post(_url, json, timeout):
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return _Response({"document": {"md_content": "real content"}, "status": "success"})
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monkeypatch.setattr(module.requests, "post", fake_post)
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parser = module.DoclingParser(docling_server_url="http://docling.local")
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with caplog.at_level(logging.DEBUG, logger="DoclingParser"):
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sections, _ = parser._parse_pdf_remote("sample.pdf", binary=b"%PDF", parse_method="raw")
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assert sections == [("real content", "")]
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flat = " ".join(record.getMessage() for record in caplog.records)
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assert "Successfully used native chunking" not in flat
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assert "Server ignored chunking request" in flat |