Files
ragflow/test/testcases/test_web_api/test_document_app/conftest.py
Zhichang Yu b7744e053e fix: support dense_vector from ES fields response (ES 9.x compatibility) (#13972)
fix: support dense_vector from ES fields response (ES 9.x compatibility)

- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Configuration Chore (non-breaking change which updates
configuration)


## Summary by CodeRabbit

* **Bug Fixes**
* More accurate handling and unwrapping of dense-vector fields so
returned values have correct shapes.
* Field selection reliably limits returned data and falls back to
alternate result locations when needed.
* Use of consistent result IDs and tolerant handling when score values
are missing.

* **Chores / Configuration**
* Increased build memory and adjusted build-time flags for the frontend
build.
* Simplified runtime model/GPU checks and removed an automated runtime
GPU-install attempt.

* **Build Fixes**
* `web/vite.config.ts`: make `build.minify` and `build.sourcemap`
respect `VITE_MINIFY` and `VITE_BUILD_SOURCEMAP` env vars from
Dockerfile instead of hardcoding `terser` and `true`.

* **Environment**
* Allow stack version override and default the runtime image tag to
"latest".

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **Bug Fixes**
* Correct unwrapping of dense-vector fields and reliable field selection
with fallback locations.
* Consistent use of hit-level IDs and tolerant handling when score
values are missing.

* **Chores / Configuration**
* Increased frontend build memory and added build-time minify/sourcemap
flags; build minification and sourcemap now configurable.
* Removed runtime GPU detection for model initialization; force CPU
initialization.

* **Environment**
* Allow stack version override and default runtime image tag to
"latest".

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-09 17:44:13 +08:00

131 lines
4.5 KiB
Python

#
# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import importlib.util
import sys
from pathlib import Path
from types import ModuleType, SimpleNamespace
import pytest
from test_common import bulk_upload_documents, delete_document, list_documents
class _DummyManager:
def route(self, *_args, **_kwargs):
def decorator(func):
return func
return decorator
@pytest.fixture(scope="function")
def add_document_func(request, WebApiAuth, add_dataset, ragflow_tmp_dir):
def cleanup():
res = list_documents(WebApiAuth, {"id": dataset_id})
for doc in res["data"]["docs"]:
delete_document(WebApiAuth, {"doc_id": doc["id"]})
request.addfinalizer(cleanup)
dataset_id = add_dataset
return dataset_id, bulk_upload_documents(WebApiAuth, dataset_id, 1, ragflow_tmp_dir)[0]
@pytest.fixture(scope="class")
def add_documents(request, WebApiAuth, add_dataset, ragflow_tmp_dir):
def cleanup():
res = list_documents(WebApiAuth, {"id": dataset_id})
for doc in res["data"]["docs"]:
delete_document(WebApiAuth, {"doc_id": doc["id"]})
request.addfinalizer(cleanup)
dataset_id = add_dataset
return dataset_id, bulk_upload_documents(WebApiAuth, dataset_id, 5, ragflow_tmp_dir)
@pytest.fixture(scope="function")
def add_documents_func(request, WebApiAuth, add_dataset_func, ragflow_tmp_dir):
def cleanup():
res = list_documents(WebApiAuth, {"id": dataset_id})
for doc in res["data"]["docs"]:
delete_document(WebApiAuth, {"doc_id": doc["id"]})
request.addfinalizer(cleanup)
dataset_id = add_dataset_func
return dataset_id, bulk_upload_documents(WebApiAuth, dataset_id, 3, ragflow_tmp_dir)
@pytest.fixture()
def document_app_module(monkeypatch):
repo_root = Path(__file__).resolve().parents[4]
common_pkg = ModuleType("common")
common_pkg.__path__ = [str(repo_root / "common")]
monkeypatch.setitem(sys.modules, "common", common_pkg)
deepdoc_pkg = ModuleType("deepdoc")
deepdoc_parser_pkg = ModuleType("deepdoc.parser")
deepdoc_parser_pkg.__path__ = []
class _StubPdfParser:
pass
class _StubExcelParser:
pass
deepdoc_parser_pkg.PdfParser = _StubPdfParser
deepdoc_pkg.parser = deepdoc_parser_pkg
monkeypatch.setitem(sys.modules, "deepdoc", deepdoc_pkg)
monkeypatch.setitem(sys.modules, "deepdoc.parser", deepdoc_parser_pkg)
deepdoc_excel_module = ModuleType("deepdoc.parser.excel_parser")
deepdoc_excel_module.RAGFlowExcelParser = _StubExcelParser
monkeypatch.setitem(sys.modules, "deepdoc.parser.excel_parser", deepdoc_excel_module)
deepdoc_html_module = ModuleType("deepdoc.parser.html_parser")
class _StubHtmlParser:
pass
deepdoc_html_module.RAGFlowHtmlParser = _StubHtmlParser
monkeypatch.setitem(sys.modules, "deepdoc.parser.html_parser", deepdoc_html_module)
deepdoc_mineru_module = ModuleType("deepdoc.parser.mineru_parser")
class _StubMinerUParser:
pass
deepdoc_mineru_module.MinerUParser = _StubMinerUParser
monkeypatch.setitem(sys.modules, "deepdoc.parser.mineru_parser", deepdoc_mineru_module)
deepdoc_paddleocr_module = ModuleType("deepdoc.parser.paddleocr_parser")
class _StubPaddleOCRParser:
pass
deepdoc_paddleocr_module.PaddleOCRParser = _StubPaddleOCRParser
monkeypatch.setitem(sys.modules, "deepdoc.parser.paddleocr_parser", deepdoc_paddleocr_module)
monkeypatch.setitem(sys.modules, "xgboost", ModuleType("xgboost"))
stub_apps = ModuleType("api.apps")
stub_apps.current_user = SimpleNamespace(id="user-1")
stub_apps.login_required = lambda func: func
monkeypatch.setitem(sys.modules, "api.apps", stub_apps)
module_path = repo_root / "api" / "apps" / "document_app.py"
spec = importlib.util.spec_from_file_location("test_document_app_unit", module_path)
module = importlib.util.module_from_spec(spec)
module.manager = _DummyManager()
spec.loader.exec_module(module)
return module