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### What problem does this PR solve? This PR solve the problems metioned in the pr(https://github.com/infiniflow/ragflow/pull/7140) which is also submitted by me ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [ ] New Feature (non-breaking change which adds functionality) - [ ] Documentation Update - [ ] Refactoring - [ ] Performance Improvement - [ ] Other (please describe): ### Introduction I fixed the problems when using OpenSearch as the DOC_ENGINE, the failures of pytest and the wrong API's return. Mainly about delete chunk, list chunks, update chunk, retrieval chunk. The pytest comand "cd sdk/python && uv sync --python 3.10 --group test --frozen && source .venv/bin/activate && cd test/test_http_api && DOC_ENGINE=opensearch pytest test_chunk_management_within_dataset -s --tb=short " is finally successful. ###Others As some changes between Elasticsearch And Opensearch differ, some pytest results about OpenSearch are correct and resonable. However, some pytest params (skipif params) are incompatible. So I changed some pytest params about skipif. As a search engine programmer, I will still focus on the usage of vector databases (especially OpenSearch) for the RAG stuff. Thanks for your review
ragflow-sdk
build and publish python SDK to pypi.org
uv build
uv pip install twine
export TWINE_USERNAME="__token__"
export TWINE_PASSWORD=$YOUR_PYPI_API_TOKEN
twine upload dist/*.whl