# EXAMPLE: query_combined

# HIDE_START

import json

import numpy as np

import redis

import warnings

from redis.commands.json.path import Path

from redis.commands.search.field import NumericField, TagField, TextField, VectorField

from redis.commands.search.index_definition import IndexDefinition, IndexType

from redis.commands.search.query import Query

from sentence_transformers import SentenceTransformer

def embed_text(model, text):

return np.array(model.encode(text)).astype(np.float32).tobytes()

warnings.filterwarnings("ignore", category=FutureWarning, message=r".*clean_up_tokenization_spaces.*")

model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')

query = "Bike for small kids"

query_vector = embed_text(model, query)

r = redis.Redis(decode_responses=True)

# create index

schema = (

)

index = r.ft("idx:bicycle")

index.create_index(

schema,

definition=IndexDefinition(prefix=["bicycle:"], index_type=IndexType.JSON),

)

# load data

with open("data/query_vector.json") as f:

bicycles = json.load(f)

pipeline = r.pipeline(transaction=False)

for bid, bicycle in enumerate(bicycles):

pipeline.json().set(f'bicycle:{bid}', Path.root_path(), bicycle)

pipeline.execute()

# HIDE_END

# STEP_START combined1

q = Query("@price:[500 1000] @condition:{new}")

res = index.search(q)

print(res.total) # >>> 1

# REMOVE_START

assert res.total == 1

# REMOVE_END

# STEP_END

# STEP_START combined2

q = Query("kids @price:[500 1000] @condition:{used}")

res = index.search(q)

print(res.total) # >>> 1

# REMOVE_START

assert res.total == 1

# REMOVE_END

# STEP_END

# STEP_START combined3

q = Query("(kids | small) @condition:{used}")

res = index.search(q)

print(res.total) # >>> 2

# REMOVE_START

assert res.total == 2

# REMOVE_END

# STEP_END

# STEP_START combined4

q = Query("@description:(kids | small) @condition:{used}")

res = index.search(q)

print(res.total) # >>> 0

# REMOVE_START

assert res.total == 0

# REMOVE_END

# STEP_END

# STEP_START combined5

q = Query("@description:(kids | small) @condition:{new | used}")

res = index.search(q)

print(res.total) # >>> 0

# REMOVE_START

assert res.total == 0

# REMOVE_END

# STEP_END

# STEP_START combined6

q = Query("@price:[500 1000] -@condition:{new}")

res = index.search(q)

print(res.total) # >>> 2

# REMOVE_START

assert res.total == 2

# REMOVE_END

# STEP_END

# STEP_START combined7

q = Query("(@price:[500 1000] -@condition:{new})=>[KNN 3 @vector $query_vector]").dialect(2)

# put query string here

res = index.search(q,{ 'query_vector': query_vector })

print(res.total) # >>> 2

# REMOVE_START

assert res.total == 2

# REMOVE_END

# STEP_END

# REMOVE_START

# destroy index and data

r.ft("idx:bicycle").dropindex(delete_documents=True)

# REMOVE_END