AsyncSearchIndex vector query failure

[sraza1983]

The example mentioned in the documentation here fails with errors. See below.

---

TypeError Traceback (most recent call last)
File ~/Library/Python/3.9/lib/python/site-packages/redisvl/index/index.py:1730, in AsyncSearchIndex.search(self, *args, **kwargs)
1729 try:
-> 1730 client = await self._get_client()
1731 if isinstance(client, AsyncRedisCluster):
1732 # Use special cluster search for AsyncRedisCluster

File ~/Library/Python/3.9/lib/python/site-packages/redisvl/index/index.py:1265, in AsyncSearchIndex._get_client(self)
1264 if not self._validated_client:
-> 1265 await RedisConnectionFactory.validate_async_redis(
1266 self._redis_client,
1267 self._lib_name,
1268 )
1269 self._validated_client = True

File ~/Library/Python/3.9/lib/python/site-packages/redisvl/redis/connection.py:421, in RedisConnectionFactory.validate_async_redis(redis_client, lib_name, required_modules)
420 if not issubclass(type(redis_client), (AsyncRedis, AsyncRedisCluster)):
--> 421 raise TypeError(
422 "Invalid async Redis client instance. Must be async Redis or async RedisCluster."
423 )
424 # Set client library name

TypeError: Invalid async Redis client instance. Must be async Redis or async RedisCluster.
...
1745 raise RedisSearchError(f"Error while searching: {str(e)}") from e
1746 except Exception as e:
-> 1747 raise RedisSearchError(f"Unexpected error while searching: {str(e)}") from e

RedisSearchError: Unexpected error while searching: Invalid async Redis client instance. Must be async Redis or async RedisCluster.
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Name: redisvl
Version: 0.8.0
Summary: Python client library and CLI for using Redis as a vector database
Home-page:
Author:
Author-email: "Redis Inc." applied.ai@redis.com
License:
Location: /Users/salmanraza/Library/Python/3.9/lib/python/site-packages
Requires: redis, pyyaml, jsonpath-ng, python-ulid, numpy, pydantic, ml-dtypes, tenacity
Required-by:
Note: you may need to restart the kernel to use updated packages.
Name: sentence-transformers
Version: 4.1.0
Summary: Embeddings, Retrieval, and Reranking
Home-page:
Author:
Author-email: Nils Reimers info@nils-reimers.de, Tom Aarsen tom.aarsen@huggingface.co
License: Apache 2.0
Location: /Users/salmanraza/Library/Python/3.9/lib/python/site-packages
Requires: typing_extensions, torch, tqdm, transformers, scikit-learn, scipy, huggingface-hub, Pillow
Required-by:
Note: you may need to restart the kernel to use updated packages.
Name: pandas
Version: 2.2.2
Summary: Powerful data structures for data analysis, time series, and statistics

`from redisvl.index import AsyncSearchIndex

from redis.asyncio import Redis

from redisvl.query import VectorQuery

Create Redis client

redis_client = Redis(

host=REDIS_HOST,

port=REDIS_PORT,

password=REDIS_PASSWORD,

decode_responses=True,

ssl_cert_reqs="none",

ssl=True)

index = AsyncSearchIndex.from_dict(schema, redis_client=client)

query = VectorQuery(
vector=[0.1, 0.1, 0.5],
vector_field_name="vector", # use the correct field name from your schema
return_fields=["caption", "subtitle", "views", "vector_distance"], # use fields that exist in your schema/data
num_results=3
)

execute the vector query async

results = await index.query(query)

print(results)`

[tylerhutcherson]

@sraza1983 can you clarify the exact code that's being run to generate this error? I am not able to reproduce. Also the stacktrace here is incomplete if you can share the entire output. Thanks!

[tylerhutcherson]

I can run the docs notebook end to end no problem. This specific exception is raised with the Redis client object is not of the correct type. The async search index expects an async Redis connection object.

[abrookins]

@claude Explain how to use the async redis client in this case

[abrookins]

@sraza1983 Just to mirror Tyler, make sure you use the async Redis client with the async RedisVL index:

from redisvl.index import AsyncSearchIndex
from redis.asyncio import Redis. # ✅ Fixed - import the async Redis client
from redisvl.query import VectorQuery

# Create async Redis client
redis_client = Redis(
    host=REDIS_HOST,
    port=REDIS_PORT,
    password=REDIS_PASSWORD,
    decode_responses=True,
    ssl_cert_reqs="none",
    ssl=True
)

# Use the correct variable name
index = AsyncSearchIndex.from_dict(schema, redis_client=redis_client)

query = VectorQuery(
    vector=[0.1, 0.1, 0.5],
    vector_field_name="vector",
    return_fields=["caption", "subtitle", "views", "vector_distance"],
    num_results=3
)

# Execute the vector query async
results = await index.query(query)
print(results)