Search Index Classes#

Class

Description

SearchIndex

Primary class to write, read, and search across data structures in Redis.

AsyncSearchIndex

Async version of the SearchIndex to write, read, and search across data structures in Redis.

SearchIndex#

class SearchIndex(schema, redis_client=None, redis_url=None, connection_args={}, **kwargs)[source]#

A search index class for interacting with Redis as a vector database.

The SearchIndex is instantiated with a reference to a Redis database and an IndexSchema (YAML path or dictionary object) that describes the various settings and field configurations.

from redisvl.index import SearchIndex

# initialize the index object with schema from file
index = SearchIndex.from_yaml("schemas/schema.yaml")
index.connect(redis_url="redis://localhost:6379")

# create the index
index.create(overwrite=True)

# data is an iterable of dictionaries
index.load(data)

# delete index and data
index.delete(drop=True)

Initialize the RedisVL search index with a schema, Redis client (or URL string with other connection args), connection_args, and other kwargs.

Parameters:
  • schema (IndexSchema) – Index schema object.

  • redis_client (Union[redis.Redis, aredis.Redis], optional) – An instantiated redis client.

  • redis_url (str, optional) – The URL of the Redis server to connect to.

  • connection_args (Dict[str, Any], optional) – Redis client connection args.

connect(redis_url=None, **kwargs)[source]#

Connect to a Redis instance using the provided redis_url, falling back to the REDIS_URL environment variable (if available).

Note: Additional keyword arguments (**kwargs) can be used to provide extra options specific to the Redis connection.

Parameters:

redis_url (Optional[str], optional) – The URL of the Redis server to connect to. If not provided, the method defaults to using the REDIS_URL environment variable.

Raises:
  • redis.exceptions.ConnectionError – If the connection to the Redis server fails.

  • ValueError – If the Redis URL is not provided nor accessible through the REDIS_URL environment variable.

index.connect(redis_url="redis://localhost:6379")
create(overwrite=False, drop=False)[source]#

Create an index in Redis with the current schema and properties.

Parameters:
  • overwrite (bool, optional) – Whether to overwrite the index if it already exists. Defaults to False.

  • drop (bool, optional) – Whether to drop all keys associated with the index in the case of overwriting. Defaults to False.

Raises:
  • RuntimeError – If the index already exists and ‘overwrite’ is False.

  • ValueError – If no fields are defined for the index.

Return type:

None

# create an index in Redis; only if one does not exist with given name
index.create()

# overwrite an index in Redis without dropping associated data
index.create(overwrite=True)

# overwrite an index in Redis; drop associated data (clean slate)
index.create(overwrite=True, drop=True)
delete(drop=True)[source]#

Delete the search index while optionally dropping all keys associated with the index.

Parameters:

drop (bool, optional) – Delete the key / documents pairs in the index. Defaults to True.

Raises:

redis.exceptions.ResponseError – If the index does not exist.

disconnect()#

Disconnect from the Redis database.

exists()[source]#

Check if the index exists in Redis.

Returns:

True if the index exists, False otherwise.

Return type:

bool

fetch(id)[source]#

Fetch an object from Redis by id.

The id is typically either a unique identifier, or derived from some domain-specific metadata combination (like a document id or chunk id).

Parameters:

id (str) – The specified unique identifier for a particular document indexed in Redis.

Returns:

The fetched object.

Return type:

Dict[str, Any]

classmethod from_dict(schema_dict, **kwargs)#

Create a SearchIndex from a dictionary.

Parameters:
  • schema_dict (Dict[str, Any]) – A dictionary containing the schema.

  • connection_args (Dict[str, Any], optional) – Redis client connection args.

Returns:

A RedisVL SearchIndex object.

Return type:

SearchIndex

from redisvl.index import SearchIndex

index = SearchIndex.from_dict({
    "index": {
        "name": "my-index",
        "prefix": "rvl",
        "storage_type": "hash",
    },
    "fields": [
        {"name": "doc-id", "type": "tag"}
    ]
})
classmethod from_yaml(schema_path, **kwargs)#

Create a SearchIndex from a YAML schema file.

Parameters:

schema_path (str) – Path to the YAML schema file.

Returns:

A RedisVL SearchIndex object.

Return type:

SearchIndex

from redisvl.index import SearchIndex

index = SearchIndex.from_yaml("schemas/schema.yaml")
info()[source]#

Get information about the index.

Returns:

A dictionary containing the information about the index.

Return type:

dict

key(id)#

Construct a redis key as a combination of an index key prefix (optional) and specified id.

The id is typically either a unique identifier, or derived from some domain-specific metadata combination (like a document id or chunk id).

Parameters:

id (str) – The specified unique identifier for a particular document indexed in Redis.

Returns:

The full Redis key including key prefix and value as a string.

Return type:

str

listall()[source]#

List all search indices in Redis database.

Returns:

The list of indices in the database.

Return type:

List[str]

load(data, id_field=None, keys=None, ttl=None, preprocess=None, batch_size=None)[source]#

Load objects to the Redis database. Returns the list of keys loaded to Redis.

RedisVL automatically handles constructing the object keys, batching, optional preprocessing steps, and setting optional expiration (TTL policies) on keys.

Parameters:
  • data (Iterable[Any]) – An iterable of objects to store.

  • id_field (Optional[str], optional) – Specified field used as the id portion of the redis key (after the prefix) for each object. Defaults to None.

  • keys (Optional[Iterable[str]], optional) – Optional iterable of keys. Must match the length of objects if provided. Defaults to None.

  • ttl (Optional[int], optional) – Time-to-live in seconds for each key. Defaults to None.

  • preprocess (Optional[Callable], optional) – A function to preprocess objects before storage. Defaults to None.

  • batch_size (Optional[int], optional) – Number of objects to write in a single Redis pipeline execution. Defaults to class’s default batch size.

Returns:

List of keys loaded to Redis.

Return type:

List[str]

Raises:

ValueError – If the length of provided keys does not match the length of objects.

data = [{"test": "foo"}, {"test": "bar"}]

# simple case
keys = index.load(data)

# set 360 second ttl policy on data
keys = index.load(data, ttl=360)

# load data with predefined keys
keys = index.load(data, keys=["rvl:foo", "rvl:bar"])

# load data with preprocessing step
def add_field(d):
    d["new_field"] = 123
    return d
keys = index.load(data, preprocess=add_field)
paginate(query, page_size=30)[source]#

Execute a given query against the index and return results in paginated batches.

This method accepts a RedisVL query instance, enabling pagination of results which allows for subsequent processing over each batch with a generator.

Parameters:
  • query (BaseQuery) – The search query to be executed.

  • page_size (int, optional) – The number of results to return in each batch. Defaults to 30.

Yields:

A generator yielding batches of search results.

Raises:
  • TypeError – If the page_size argument is not of type int.

  • ValueError – If the page_size argument is less than or equal to zero.

Return type:

Generator

Example

# Iterate over paginated search results in batches of 10 for result_batch in index.paginate(query, page_size=10):

# Process each batch of results pass

Note

The page_size parameter controls the number of items each result batch contains. Adjust this value based on performance considerations and the expected volume of search results.

query(query)[source]#

Execute a query on the index.

This method takes a BaseQuery object directly, runs the search, and handles post-processing of the search.

Parameters:

query (BaseQuery) – The query to run.

Returns:

A list of search results.

Return type:

List[Result]

from redisvl.query import VectorQuery

query = VectorQuery(
    vector=[0.16, -0.34, 0.98, 0.23],
    vector_field_name="embedding",
    num_results=3
)

results = index.query(query)
search(*args, **kwargs)[source]#

Perform a search against the index.

Wrapper around redis.search.Search that adds the index name to the search query and passes along the rest of the arguments to the redis-py ft.search() method.

Returns:

Raw Redis search results.

Return type:

Result

set_client(client)[source]#

Manually set the Redis client to use with the search index.

This method configures the search index to use a specific Redis or Async Redis client. It is useful for cases where an external, custom-configured client is preferred instead of creating a new one.

Parameters:

client (redis.Redis) – A Redis or Async Redis client instance to be used for the connection.

Raises:

TypeError – If the provided client is not valid.

import redis
from redisvl.index import SearchIndex

client = redis.Redis.from_url("redis://localhost:6379")
index = SearchIndex.from_yaml("schemas/schema.yaml")
index.set_client(client)
property client: Redis | Redis | None#

The underlying redis-py client object.

property key_separator: str#

The optional separator between a defined prefix and key value in forming a Redis key.

property name: str#

The name of the Redis search index.

property prefix: str#

The optional key prefix that comes before a unique key value in forming a Redis key.

property storage_type: StorageType#

The underlying storage type for the search index; either hash or json.

AsyncSearchIndex#

class AsyncSearchIndex(schema, redis_client=None, redis_url=None, connection_args={}, **kwargs)[source]#

A search index class for interacting with Redis as a vector database in async-mode.

The AsyncSearchIndex is instantiated with a reference to a Redis database and an IndexSchema (YAML path or dictionary object) that describes the various settings and field configurations.

from redisvl.index import AsyncSearchIndex

# initialize the index object with schema from file
index = AsyncSearchIndex.from_yaml("schemas/schema.yaml")
index.connect(redis_url="redis://localhost:6379")

# create the index
await index.create(overwrite=True)

# data is an iterable of dictionaries
await index.load(data)

# delete index and data
await index.delete(drop=True)

Initialize the RedisVL search index with a schema, Redis client (or URL string with other connection args), connection_args, and other kwargs.

Parameters:
  • schema (IndexSchema) – Index schema object.

  • redis_client (Union[redis.Redis, aredis.Redis], optional) – An instantiated redis client.

  • redis_url (str, optional) – The URL of the Redis server to connect to.

  • connection_args (Dict[str, Any], optional) – Redis client connection args.

connect(redis_url=None, **kwargs)[source]#

Connect to a Redis instance using the provided redis_url, falling back to the REDIS_URL environment variable (if available).

Note: Additional keyword arguments (**kwargs) can be used to provide extra options specific to the Redis connection.

Parameters:

redis_url (Optional[str], optional) – The URL of the Redis server to connect to. If not provided, the method defaults to using the REDIS_URL environment variable.

Raises:
  • redis.exceptions.ConnectionError – If the connection to the Redis server fails.

  • ValueError – If the Redis URL is not provided nor accessible through the REDIS_URL environment variable.

index.connect(redis_url="redis://localhost:6379")
async create(overwrite=False, drop=False)[source]#
Asynchronously create an index in Redis with the current schema

and properties.

Parameters:
  • overwrite (bool, optional) – Whether to overwrite the index if it already exists. Defaults to False.

  • drop (bool, optional) – Whether to drop all keys associated with the index in the case of overwriting. Defaults to False.

Raises:
  • RuntimeError – If the index already exists and ‘overwrite’ is False.

  • ValueError – If no fields are defined for the index.

Return type:

None

# create an index in Redis; only if one does not exist with given name
await index.create()

# overwrite an index in Redis without dropping associated data
await index.create(overwrite=True)

# overwrite an index in Redis; drop associated data (clean slate)
await index.create(overwrite=True, drop=True)
async delete(drop=True)[source]#

Delete the search index.

Parameters:

drop (bool, optional) – Delete the documents in the index. Defaults to True.

Raises:

redis.exceptions.ResponseError – If the index does not exist.

disconnect()#

Disconnect from the Redis database.

async exists()[source]#

Check if the index exists in Redis.

Returns:

True if the index exists, False otherwise.

Return type:

bool

async fetch(id)[source]#

Asynchronously etch an object from Redis by id. The id is typically either a unique identifier, or derived from some domain-specific metadata combination (like a document id or chunk id).

Parameters:

id (str) – The specified unique identifier for a particular document indexed in Redis.

Returns:

The fetched object.

Return type:

Dict[str, Any]

classmethod from_dict(schema_dict, **kwargs)#

Create a SearchIndex from a dictionary.

Parameters:
  • schema_dict (Dict[str, Any]) – A dictionary containing the schema.

  • connection_args (Dict[str, Any], optional) – Redis client connection args.

Returns:

A RedisVL SearchIndex object.

Return type:

SearchIndex

from redisvl.index import SearchIndex

index = SearchIndex.from_dict({
    "index": {
        "name": "my-index",
        "prefix": "rvl",
        "storage_type": "hash",
    },
    "fields": [
        {"name": "doc-id", "type": "tag"}
    ]
})
classmethod from_yaml(schema_path, **kwargs)#

Create a SearchIndex from a YAML schema file.

Parameters:

schema_path (str) – Path to the YAML schema file.

Returns:

A RedisVL SearchIndex object.

Return type:

SearchIndex

from redisvl.index import SearchIndex

index = SearchIndex.from_yaml("schemas/schema.yaml")
async info()[source]#

Get information about the index.

Returns:

A dictionary containing the information about the index.

Return type:

dict

key(id)#

Construct a redis key as a combination of an index key prefix (optional) and specified id.

The id is typically either a unique identifier, or derived from some domain-specific metadata combination (like a document id or chunk id).

Parameters:

id (str) – The specified unique identifier for a particular document indexed in Redis.

Returns:

The full Redis key including key prefix and value as a string.

Return type:

str

async listall()[source]#

List all search indices in Redis database.

Returns:

The list of indices in the database.

Return type:

List[str]

async load(data, id_field=None, keys=None, ttl=None, preprocess=None, concurrency=None)[source]#

Asynchronously load objects to Redis with concurrency control. Returns the list of keys loaded to Redis.

RedisVL automatically handles constructing the object keys, batching, optional preprocessing steps, and setting optional expiration (TTL policies) on keys.

Parameters:
  • data (Iterable[Any]) – An iterable of objects to store.

  • id_field (Optional[str], optional) – Specified field used as the id portion of the redis key (after the prefix) for each object. Defaults to None.

  • keys (Optional[Iterable[str]], optional) – Optional iterable of keys. Must match the length of objects if provided. Defaults to None.

  • ttl (Optional[int], optional) – Time-to-live in seconds for each key. Defaults to None.

  • preprocess (Optional[Callable], optional) – An async function to preprocess objects before storage. Defaults to None.

  • concurrency (Optional[int], optional) – The maximum number of concurrent write operations. Defaults to class’s default concurrency level.

Returns:

List of keys loaded to Redis.

Return type:

List[str]

Raises:

ValueError – If the length of provided keys does not match the length of objects.

data = [{"test": "foo"}, {"test": "bar"}]

# simple case
keys = await index.load(data)

# set 360 second ttl policy on data
keys = await index.load(data, ttl=360)

# load data with predefined keys
keys = await index.load(data, keys=["rvl:foo", "rvl:bar"])

# load data with preprocessing step
async def add_field(d):
    d["new_field"] = 123
    return d
keys = await index.load(data, preprocess=add_field)
async paginate(query, page_size=30)[source]#

Execute a given query against the index and return results in paginated batches.

This method accepts a RedisVL query instance, enabling async pagination of results which allows for subsequent processing over each batch with a generator.

Parameters:
  • query (BaseQuery) – The search query to be executed.

  • page_size (int, optional) – The number of results to return in each batch. Defaults to 30.

Yields:

An async generator yielding batches of search results.

Raises:
  • TypeError – If the page_size argument is not of type int.

  • ValueError – If the page_size argument is less than or equal to zero.

Return type:

AsyncGenerator

Example

# Iterate over paginated search results in batches of 10 async for result_batch in index.paginate(query, page_size=10):

# Process each batch of results pass

Note

The page_size parameter controls the number of items each result batch contains. Adjust this value based on performance considerations and the expected volume of search results.

async query(query)[source]#

Asynchronously execute a query on the index.

This method takes a BaseQuery object directly, runs the search, and handles post-processing of the search.

Parameters:

query (BaseQuery) – The query to run.

Returns:

A list of search results.

Return type:

List[Result]

from redisvl.query import VectorQuery

query = VectorQuery(
    vector=[0.16, -0.34, 0.98, 0.23],
    vector_field_name="embedding",
    num_results=3
)

results = await index.query(query)
async search(*args, **kwargs)[source]#

Perform a search on this index.

Wrapper around redis.search.Search that adds the index name to the search query and passes along the rest of the arguments to the redis-py ft.search() method.

Returns:

Raw Redis search results.

Return type:

Result

set_client(client)[source]#

Manually set the Redis client to use with the search index.

This method configures the search index to use a specific Async Redis client. It is useful for cases where an external, custom-configured client is preferred instead of creating a new one.

Parameters:

client (aredis.Redis) – An Async Redis client instance to be used for the connection.

Raises:

TypeError – If the provided client is not valid.

import redis.asyncio as aredis
from redisvl.index import AsyncSearchIndex

# async Redis client and index
client = aredis.Redis.from_url("redis://localhost:6379")
index = AsyncSearchIndex.from_yaml("schemas/schema.yaml")
index.set_client(client)
property client: Redis | Redis | None#

The underlying redis-py client object.

property key_separator: str#

The optional separator between a defined prefix and key value in forming a Redis key.

property name: str#

The name of the Redis search index.

property prefix: str#

The optional key prefix that comes before a unique key value in forming a Redis key.

property storage_type: StorageType#

The underlying storage type for the search index; either hash or json.