Document field types
Strings
These are vectorised, unless the field is specified is in non_tensor_fields
during index time.
Floats
These aren't vectorised, but can be used to filter search results.
Bools
These aren't vectorised, but can be used to filter search results.
Ints
These aren't vectorised, but can be used to filter search results.
Array
Currently, only arrays of strings are supported.
Array fields must be given as a non_tensor_fields
during index time, else an error will be thrown.
This type of field can be used to filter search results and for lexical search.
Example
# index an array field called "my tags", making sure it is in non_tensor_fields
mq.index("my_index").add_documents(documents=[
{"Title": "Cool summer t-shirt", "_id": "1234", 'my tags': ['summer', 'yellow']}],
non_tensor_fields=['my tags']
)
# do a search request that filters based on the tags
mq.index("my_index").search(
q="Something to wear in warm weather",
filter_string="(my\ tags:yellow) AND (my\ tags:summer)"
)