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Refa: HTTP API delete dataset / test cases / docs (#7657)

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### What problem does this PR solve?

This PR introduces Pydantic-based validation for the delete dataset HTTP
API, improving code clarity and robustness. Key changes include:

1. Pydantic Validation
2. Error Handling
3. Test Updates
4. Documentation Updates

### Type of change

- [x] Documentation Update
- [x] Refactoring
This commit is contained in:
liu an
2025-05-16 10:16:43 +08:00
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commit ae8b628f0a
8 changed files with 341 additions and 173 deletions
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docs/references/python_api_reference.md
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@ -200,16 +200,19 @@ dataset = rag_object.create_dataset(name="kb_1")
### Delete datasets
```python
RAGFlow.delete_datasets(ids: list[str] = None)
RAGFlow.delete_datasets(ids: list[str] | None = None)
```
Deletes datasets by ID.
#### Parameters
##### ids: `list[str]`, *Required*
##### ids: `list[str]` or `None`, *Required*
The IDs of the datasets to delete. Defaults to `None`. If it is not specified, all datasets will be deleted.
The IDs of the datasets to delete. Defaults to `None`.
- If `None`, all datasets will be deleted.
- If an array of IDs, only the specified datasets will be deleted.
- If an empty array, no datasets will be deleted.
#### Returns
@ -219,7 +222,7 @@ The IDs of the datasets to delete. Defaults to `None`. If it is not specified, a
#### Examples
```python
rag_object.delete_datasets(ids=["id_1","id_2"])
rag_object.delete_datasets(ids=["d94a8dc02c9711f0930f7fbc369eab6d","e94a8dc02c9711f0930f7fbc369eab6e"])
```
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