https://docarray.jina.ai/fundamentals/documentarray/access-attributes/
The bold part is the description that I think is problematic
| Example |
Return |
da[:, 'id'] |
all .id from all root Documents in a List |
da[..., 'id'] |
all .id from all flattened Documents (root, chunks, and matches) in a List |
da['@m', 'id'] |
all .id from all Documents .matches |
da[1:3, ('id', 'scores')] |
a list of two list, first is all .id from the first three Documents, second is all .scores from the first three Documents |
da[:, 'scores__cosine__value'] |
all .scores['cosine'].value from the first three Documents |
da[1:3, 'embedding'], da[1:3].embeddings |
a NdArray-like object of the first three Documents embeddings |
da[:, 'tensor'], da.tensors |
a NdArray-like object of the all top-level Documents tensors |
It should be revised as follows:
da[1:3, 'scores__cosine__value']
https://docarray.jina.ai/fundamentals/documentarray/access-attributes/
The bold part is the description that I think is problematic
da[:, 'id'].idfrom all root Documents in a Listda[..., 'id'].idfrom all flattened Documents (root, chunks, and matches) in a Listda['@m', 'id'].idfrom all Documents.matchesda[1:3, ('id', 'scores')].idfrom the first three Documents, second is all.scoresfrom the first three Documentsda[:, 'scores__cosine__value'].scores['cosine'].valuefrom the first three Documentsda[1:3, 'embedding'],da[1:3].embeddingsda[:, 'tensor'],da.tensorsIt should be revised as follows:
da[1:3, 'scores__cosine__value']