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Fix: Enforce default embedding model in create_dataset / update_dataset (#8486 )

### What problem does this PR solve?

Previous:
- Defaulted to hardcoded model 'BAAI/bge-large-zh-v1.5@BAAI'
- Did not respect user-configured default embedding_model

Now:
- Correctly prioritizes user-configured default embedding_model

Other:
- Make embedding_model optional in CreateDatasetReq with proper None
handling
- Add default embedding model fallback in dataset update when empty
- Enhance validation utils to handle None values and string
normalization
- Update SDK default embedding model to None to match API changes
- Adjust related test cases to reflect new validation rules

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

2025-06-25 16:41:32 +08:00

ragflow_sdk

Fix: Enforce default embedding model in create_dataset / update_dataset (#8486 )

2025-06-25 16:41:32 +08:00

test

Refactor code (#8341 )

2025-06-18 16:40:30 +08:00

hello_ragflow.py

Update comments (#4569 )

2025-01-21 20:52:28 +08:00

pyproject.toml

Docs: Update version references to v0.19.1 in READMEs and docs (#8366 )

2025-06-19 14:39:27 +08:00

README.md

Replace poetry with uv (#4471 )

2025-01-14 11:49:43 +08:00

uv.lock

Docs: Update version references to v0.19.1 in READMEs and docs (#8366 )

2025-06-19 14:39:27 +08:00

README.md

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