Issue with hybrid search requests in python client

[vincetrep]

Description:

I've done both vector searches and hybrid searches on a weaviate Class. When there are 0 value vectors within a vector e..g [0. 0. 0.] the hybrid search doesn't interpretate the raw value correctly.

In a vector search, it works properly.

Issue: This is the error that comes up upon doing a hybrid search with 0. values in a vector:

{'errors': [{'locations': [{'column': 65, 'line': 1}], 'message': 'Syntax Error GraphQL request (1:65) Invalid number, expected digit but got: " ".\n\n1: {Get{SmallIngredientDoc(hybrid:{query: "dummy text", vector: [0. 0. 0. ... 0. 0. 0.], alpha: 0.5}){base_food_nametext, titletext, title__embedding _additional {distance }}}}\n ^\n', 'path': None}]}

When I apply a regex to replace the 0. values by 0.0, then the hybrid search runs properly.

built_query = re.sub(r'(0.|0.)(\s|])','0.0\2',built_query)

I've put sample code to test out the hybrid search.

In the code sample, using random values to the vector works. If you use np.zeros(5) instead without string manipulation, it won't work. With string manipulation, it works.

`import re

class SampleDoc(BaseDoc): title: TextDoc embedding: Optional[AnyEmbedding] = Field(is_embedding=True)

dbconfig = WeaviateDocumentIndex.DBConfig( host="http://localhost:9999" ) # Replace with your endpoint)

store = WeaviateDocumentIndexSampleDoc

create a sample doc

sample_doc = SampleDoc (title = 'test text', embedding = np.random.rand(5))

Try to query for that doc with a hybrid search

query = client.query.get("SampleDoc", ["title__text"]).with_additional("distance").with_hybrid("dummy text", alpha=0.5,vector=np.random.rand(5)) built_query = query.build() print(built_query) built_query = re.sub(r'(0.|0.)(\s|])','0.0\2',built_query) print(built_query)

client.query.raw(built_query)

result = store.execute_query(built_query) print(result)`

[nilskulawiak]

This is not really a bug, as the Python client only allows lists and currently does not implement numpy arrays. Because no proper type checking is implemented, the Python client simply writes the vector in the request as [0 0] with numpy arrays, instead of [0, 0] with lists. In other words, there are no commas. This works with floats for some reason, but it really should not work at all.

[stale[bot]]

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