import asyncio
import atexit
import json
import threading
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
AsyncGenerator,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
Union,
)
if TYPE_CHECKING:
from redis.commands.search.aggregation import AggregateResult
from redis.commands.search.document import Document
from redis.commands.search.result import Result
from redisvl.query.query import BaseQuery
import redis
import redis.asyncio as aredis
from redis.commands.search.indexDefinition import IndexDefinition
from redisvl.exceptions import RedisModuleVersionError, RedisSearchError
from redisvl.index.storage import BaseStorage, HashStorage, JsonStorage
from redisvl.query import BaseQuery, CountQuery, FilterQuery
from redisvl.query.filter import FilterExpression
from redisvl.redis.connection import (
RedisConnectionFactory,
convert_index_info_to_schema,
validate_modules,
)
from redisvl.redis.utils import convert_bytes
from redisvl.schema import IndexSchema, StorageType
from redisvl.utils.log import get_logger
logger = get_logger(__name__)
def process_results(
results: "Result", query: BaseQuery, storage_type: StorageType
) -> List[Dict[str, Any]]:
"""Convert a list of search Result objects into a list of document
dictionaries.
This function processes results from Redis, handling different storage
types and query types. For JSON storage with empty return fields, it
unpacks the JSON object while retaining the document ID. The 'payload'
field is also removed from all resulting documents for consistency.
Args:
results (Result): The search results from Redis.
query (BaseQuery): The query object used for the search.
storage_type (StorageType): The storage type of the search
index (json or hash).
Returns:
List[Dict[str, Any]]: A list of processed document dictionaries.
"""
# Handle count queries
if isinstance(query, CountQuery):
return results.total
# Determine if unpacking JSON is needed
unpack_json = (
(storage_type == StorageType.JSON)
and isinstance(query, FilterQuery)
and not query._return_fields # type: ignore
)
# Process records
def _process(doc: "Document") -> Dict[str, Any]:
doc_dict = doc.__dict__
# Unpack and Project JSON fields properly
if unpack_json and "json" in doc_dict:
json_data = doc_dict.get("json", {})
if isinstance(json_data, str):
json_data = json.loads(json_data)
if isinstance(json_data, dict):
return {"id": doc_dict.get("id"), **json_data}
raise ValueError(f"Unable to parse json data from Redis {json_data}")
# Remove 'payload' if present
doc_dict.pop("payload", None)
return doc_dict
return [_process(doc) for doc in results.docs]
def setup_redis():
def decorator(func):
@wraps(func)
def wrapper(self, *args, **kwargs):
result = func(self, *args, **kwargs)
RedisConnectionFactory.validate_sync_redis(
self._redis_client, self._lib_name
)
return result
return wrapper
return decorator
def setup_async_redis():
def decorator(func):
@wraps(func)
async def wrapper(self, *args, **kwargs):
result = await func(self, *args, **kwargs)
await RedisConnectionFactory.validate_async_redis(
self._redis_client, self._lib_name
)
return result
return wrapper
return decorator
class BaseSearchIndex:
"""Base search engine class"""
_STORAGE_MAP = {
StorageType.HASH: HashStorage,
StorageType.JSON: JsonStorage,
}
schema: IndexSchema
def __init__(*args, **kwargs):
pass
@property
def _storage(self) -> BaseStorage:
"""The storage type for the index schema."""
return self._STORAGE_MAP[self.schema.index.storage_type](
prefix=self.schema.index.prefix,
key_separator=self.schema.index.key_separator,
)
@property
def name(self) -> str:
"""The name of the Redis search index."""
return self.schema.index.name
@property
def prefix(self) -> str:
"""The optional key prefix that comes before a unique key value in
forming a Redis key."""
return self.schema.index.prefix
@property
def key_separator(self) -> str:
"""The optional separator between a defined prefix and key value in
forming a Redis key."""
return self.schema.index.key_separator
@property
def storage_type(self) -> StorageType:
"""The underlying storage type for the search index; either
hash or json."""
return self.schema.index.storage_type
@classmethod
def from_yaml(cls, schema_path: str, **kwargs):
"""Create a SearchIndex from a YAML schema file.
Args:
schema_path (str): Path to the YAML schema file.
Returns:
SearchIndex: A RedisVL SearchIndex object.
.. code-block:: python
from redisvl.index import SearchIndex
index = SearchIndex.from_yaml("schemas/schema.yaml")
"""
schema = IndexSchema.from_yaml(schema_path)
return cls(schema=schema, **kwargs)
@classmethod
def from_dict(cls, schema_dict: Dict[str, Any], **kwargs):
"""Create a SearchIndex from a dictionary.
Args:
schema_dict (Dict[str, Any]): A dictionary containing the schema.
Returns:
SearchIndex: A RedisVL SearchIndex object.
.. code-block:: python
from redisvl.index import SearchIndex
index = SearchIndex.from_dict({
"index": {
"name": "my-index",
"prefix": "rvl",
"storage_type": "hash",
},
"fields": [
{"name": "doc-id", "type": "tag"}
]
})
"""
schema = IndexSchema.from_dict(schema_dict)
return cls(schema=schema, **kwargs)
def disconnect(self):
"""Disconnect from the Redis database."""
self._redis_client = None
return self
def key(self, id: str) -> str:
"""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).
Args:
id (str): The specified unique identifier for a particular
document indexed in Redis.
Returns:
str: The full Redis key including key prefix and value as a string.
"""
return self._storage._key(
id=id,
prefix=self.schema.index.prefix,
key_separator=self.schema.index.key_separator,
)
[docs]
class SearchIndex(BaseSearchIndex):
"""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.
.. code-block:: python
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)
"""
def __init__(
self,
schema: IndexSchema,
redis_client: Optional[redis.Redis] = None,
redis_url: Optional[str] = None,
connection_args: Dict[str, Any] = {},
**kwargs,
):
"""Initialize the RedisVL search index with a schema, Redis client
(or URL string with other connection args), connection_args, and other
kwargs.
Args:
schema (IndexSchema): Index schema object.
redis_client(Optional[redis.Redis]): An
instantiated redis client.
redis_url (Optional[str]): The URL of the Redis server to
connect to.
connection_args (Dict[str, Any], optional): Redis client connection
args.
"""
# final validation on schema object
if not isinstance(schema, IndexSchema):
raise ValueError("Must provide a valid IndexSchema object")
self.schema = schema
self._lib_name: Optional[str] = kwargs.pop("lib_name", None)
# set up redis connection
self._redis_client: Optional[redis.Redis] = None
if redis_client is not None:
self.set_client(redis_client)
elif redis_url is not None:
self.connect(redis_url, **connection_args)
[docs]
@classmethod
def from_existing(
cls,
name: str,
redis_client: Optional[redis.Redis] = None,
redis_url: Optional[str] = None,
**kwargs,
):
"""
Initialize from an existing search index in Redis by index name.
Args:
name (str): Name of the search index in Redis.
redis_client(Optional[redis.Redis]): An
instantiated redis client.
redis_url (Optional[str]): The URL of the Redis server to
connect to.
"""
# Handle redis instance
if redis_url:
redis_client = RedisConnectionFactory.connect(
redis_url=redis_url, use_async=False, **kwargs
)
if not redis_client:
raise ValueError(
"Must provide either a redis_url or redis_client to fetch Redis index info."
)
# Validate modules
installed_modules = RedisConnectionFactory.get_modules(redis_client)
try:
required_modules = [
{"name": "search", "ver": 20810},
{"name": "searchlight", "ver": 20810},
]
validate_modules(installed_modules, required_modules)
except RedisModuleVersionError as e:
raise RedisModuleVersionError(
f"Loading from existing index failed. {str(e)}"
)
# Fetch index info and convert to schema
index_info = cls._info(name, redis_client)
schema_dict = convert_index_info_to_schema(index_info)
schema = IndexSchema.from_dict(schema_dict)
return cls(schema, redis_client, **kwargs)
@property
def client(self) -> Optional[redis.Redis]:
"""The underlying redis-py client object."""
return self._redis_client
[docs]
def connect(self, redis_url: Optional[str] = None, **kwargs):
"""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.
Args:
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.
.. code-block:: python
index.connect(redis_url="redis://localhost:6379")
"""
client = RedisConnectionFactory.connect(
redis_url=redis_url, use_async=False, **kwargs
)
return self.set_client(client)
[docs]
@setup_redis()
def set_client(self, redis_client: redis.Redis, **kwargs):
"""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.
Args:
redis_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.
.. code-block:: python
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)
"""
if not isinstance(redis_client, redis.Redis):
raise TypeError("Invalid Redis client instance")
self._redis_client = redis_client
return self
[docs]
def create(self, overwrite: bool = False, drop: bool = False) -> None:
"""Create an index in Redis with the current schema and properties.
Args:
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.
.. code-block:: python
# 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)
"""
# Check that fields are defined.
redis_fields = self.schema.redis_fields
if not redis_fields:
raise ValueError("No fields defined for index")
if not isinstance(overwrite, bool):
raise TypeError("overwrite must be of type bool")
if self.exists():
if not overwrite:
logger.info("Index already exists, not overwriting.")
return None
logger.info("Index already exists, overwriting.")
self.delete(drop=drop)
try:
self._redis_client.ft(self.name).create_index( # type: ignore
fields=redis_fields,
definition=IndexDefinition(
prefix=[self.schema.index.prefix], index_type=self._storage.type
),
)
except:
logger.exception("Error while trying to create the index")
raise
[docs]
def delete(self, drop: bool = True):
"""Delete the search index while optionally dropping all keys associated
with the index.
Args:
drop (bool, optional): Delete the key / documents pairs in the
index. Defaults to True.
raises:
redis.exceptions.ResponseError: If the index does not exist.
"""
try:
self._redis_client.ft(self.schema.index.name).dropindex( # type: ignore
delete_documents=drop
)
except Exception as e:
raise RedisSearchError(f"Error while deleting index: {str(e)}") from e
[docs]
def clear(self) -> int:
"""Clear all keys in Redis associated with the index, leaving the index
available and in-place for future insertions or updates.
Returns:
int: Count of records deleted from Redis.
"""
# Track deleted records
total_records_deleted: int = 0
# Paginate using queries and delete in batches
for batch in self.paginate(
FilterQuery(FilterExpression("*"), return_fields=["id"]), page_size=500
):
batch_keys = [record["id"] for record in batch]
record_deleted = self._redis_client.delete(*batch_keys) # type: ignore
total_records_deleted += record_deleted # type: ignore
return total_records_deleted
[docs]
def drop_keys(self, keys: Union[str, List[str]]) -> int:
"""Remove a specific entry or entries from the index by it's key ID.
Args:
keys (Union[str, List[str]]): The document ID or IDs to remove from the index.
Returns:
int: Count of records deleted from Redis.
"""
if isinstance(keys, List):
return self._redis_client.delete(*keys) # type: ignore
else:
return self._redis_client.delete(keys) # type: ignore
[docs]
def load(
self,
data: Iterable[Any],
id_field: Optional[str] = None,
keys: Optional[Iterable[str]] = None,
ttl: Optional[int] = None,
preprocess: Optional[Callable] = None,
batch_size: Optional[int] = None,
) -> List[str]:
"""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.
Args:
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[str]: List of keys loaded to Redis.
Raises:
ValueError: If the length of provided keys does not match the length
of objects.
.. code-block:: python
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)
"""
try:
return self._storage.write(
self._redis_client, # type: ignore
objects=data,
id_field=id_field,
keys=keys,
ttl=ttl,
preprocess=preprocess,
batch_size=batch_size,
)
except:
logger.exception("Error while loading data to Redis")
raise
[docs]
def fetch(self, id: str) -> Optional[Dict[str, Any]]:
"""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).
Args:
id (str): The specified unique identifier for a particular
document indexed in Redis.
Returns:
Dict[str, Any]: The fetched object.
"""
obj = self._storage.get(self._redis_client, [self.key(id)]) # type: ignore
if obj:
return convert_bytes(obj[0])
return None
[docs]
def aggregate(self, *args, **kwargs) -> "AggregateResult":
"""Perform an aggregation operation against the index.
Wrapper around the aggregation API that adds the index name
to the query and passes along the rest of the arguments
to the redis-py ft().aggregate() method.
Returns:
Result: Raw Redis aggregation results.
"""
try:
return self._redis_client.ft(self.schema.index.name).aggregate( # type: ignore
*args, **kwargs
)
except Exception as e:
raise RedisSearchError(f"Error while aggregating: {str(e)}") from e
[docs]
def search(self, *args, **kwargs) -> "Result":
"""Perform a search against the index.
Wrapper around the search API that adds the index name
to the query and passes along the rest of the arguments
to the redis-py ft().search() method.
Returns:
Result: Raw Redis search results.
"""
try:
return self._redis_client.ft(self.schema.index.name).search( # type: ignore
*args, **kwargs
)
except Exception as e:
raise RedisSearchError(f"Error while searching: {str(e)}") from e
def _query(self, query: BaseQuery) -> List[Dict[str, Any]]:
"""Execute a query and process results."""
results = self.search(query.query, query_params=query.params)
return process_results(
results, query=query, storage_type=self.schema.index.storage_type
)
[docs]
def query(self, query: BaseQuery) -> List[Dict[str, Any]]:
"""Execute a query on the index.
This method takes a BaseQuery object directly, runs the search, and
handles post-processing of the search.
Args:
query (BaseQuery): The query to run.
Returns:
List[Result]: A list of search results.
.. code-block:: python
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)
"""
return self._query(query)
[docs]
def paginate(self, query: BaseQuery, page_size: int = 30) -> Generator:
"""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.
Args:
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.
.. code-block:: python
# 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.
"""
if not isinstance(page_size, int):
raise TypeError("page_size must be an integer")
if page_size <= 0:
raise ValueError("page_size must be greater than 0")
offset = 0
while True:
query.paging(offset, page_size)
results = self._query(query)
if not results:
break
yield results
# Increment the offset for the next batch of pagination
offset += page_size
[docs]
def listall(self) -> List[str]:
"""List all search indices in Redis database.
Returns:
List[str]: The list of indices in the database.
"""
return convert_bytes(self._redis_client.execute_command("FT._LIST")) # type: ignore
[docs]
def exists(self) -> bool:
"""Check if the index exists in Redis.
Returns:
bool: True if the index exists, False otherwise.
"""
return self.schema.index.name in self.listall()
@staticmethod
def _info(name: str, redis_client: redis.Redis) -> Dict[str, Any]:
"""Run FT.INFO to fetch information about the index."""
try:
return convert_bytes(redis_client.ft(name).info()) # type: ignore
except Exception as e:
raise RedisSearchError(
f"Error while fetching {name} index info: {str(e)}"
) from e
[docs]
def info(self, name: Optional[str] = None) -> Dict[str, Any]:
"""Get information about the index.
Args:
name (str, optional): Index name to fetch info about.
Defaults to None.
Returns:
dict: A dictionary containing the information about the index.
"""
index_name = name or self.schema.index.name
return self._info(index_name, self._redis_client) # type: ignore
[docs]
class AsyncSearchIndex(BaseSearchIndex):
"""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.
.. code-block:: python
from redisvl.index import AsyncSearchIndex
# initialize the index object with schema from file
index = AsyncSearchIndex.from_yaml("schemas/schema.yaml")
await 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)
"""
def __init__(
self,
schema: IndexSchema,
**kwargs,
):
"""Initialize the RedisVL async search index with a schema.
Args:
schema (IndexSchema): Index schema object.
connection_args (Dict[str, Any], optional): Redis client connection
args.
"""
# final validation on schema object
if not isinstance(schema, IndexSchema):
raise ValueError("Must provide a valid IndexSchema object")
self.schema = schema
self._lib_name: Optional[str] = kwargs.pop("lib_name", None)
# set up empty redis connection
self._redis_client: Optional[aredis.Redis] = None
if "redis_client" in kwargs or "redis_url" in kwargs:
logger.warning(
"Must use set_client() or connect() methods to provide a Redis connection to AsyncSearchIndex"
)
atexit.register(self._cleanup_connection)
def _cleanup_connection(self):
if self._redis_client:
def run_in_thread():
try:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
loop.run_until_complete(self._redis_client.aclose())
loop.close()
except RuntimeError:
pass
# Run cleanup in a background thread to avoid event loop issues
thread = threading.Thread(target=run_in_thread)
thread.start()
thread.join()
self._redis_client = None
[docs]
def disconnect(self):
"""Disconnect and cleanup the underlying async redis connection."""
self._cleanup_connection()
[docs]
@classmethod
async def from_existing(
cls,
name: str,
redis_client: Optional[aredis.Redis] = None,
redis_url: Optional[str] = None,
**kwargs,
):
"""
Initialize from an existing search index in Redis by index name.
Args:
name (str): Name of the search index in Redis.
redis_client(Optional[redis.Redis]): An
instantiated redis client.
redis_url (Optional[str]): The URL of the Redis server to
connect to.
"""
if redis_url:
redis_client = RedisConnectionFactory.connect(
redis_url=redis_url, use_async=True, **kwargs
)
if not redis_client:
raise ValueError(
"Must provide either a redis_url or redis_client to fetch Redis index info."
)
# Validate modules
installed_modules = await RedisConnectionFactory.get_modules_async(redis_client)
try:
required_modules = [
{"name": "search", "ver": 20810},
{"name": "searchlight", "ver": 20810},
]
validate_modules(installed_modules, required_modules)
except RedisModuleVersionError as e:
raise RedisModuleVersionError(
f"Loading from existing index failed. {str(e)}"
) from e
# Fetch index info and convert to schema
index_info = await cls._info(name, redis_client)
schema_dict = convert_index_info_to_schema(index_info)
schema = IndexSchema.from_dict(schema_dict)
index = cls(schema, **kwargs)
await index.set_client(redis_client)
return index
@property
def client(self) -> Optional[aredis.Redis]:
"""The underlying redis-py client object."""
return self._redis_client
[docs]
async def connect(self, redis_url: Optional[str] = None, **kwargs):
"""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.
Args:
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.
.. code-block:: python
index.connect(redis_url="redis://localhost:6379")
"""
client = RedisConnectionFactory.connect(
redis_url=redis_url, use_async=True, **kwargs
)
return await self.set_client(client)
[docs]
@setup_async_redis()
async def set_client(self, redis_client: aredis.Redis):
"""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.
Args:
redis_client (aredis.Redis): An Async Redis
client instance to be used for the connection.
Raises:
TypeError: If the provided client is not valid.
.. code-block:: python
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")
await index.set_client(client)
"""
if isinstance(redis_client, redis.Redis):
print("Setting client and converting from async", flush=True)
self._redis_client = RedisConnectionFactory.sync_to_async_redis(
redis_client
)
else:
self._redis_client = redis_client
return self
[docs]
async def create(self, overwrite: bool = False, drop: bool = False) -> None:
"""Asynchronously create an index in Redis with the current schema
and properties.
Args:
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.
.. code-block:: python
# 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)
"""
redis_fields = self.schema.redis_fields
if not redis_fields:
raise ValueError("No fields defined for index")
if not isinstance(overwrite, bool):
raise TypeError("overwrite must be of type bool")
if await self.exists():
if not overwrite:
logger.info("Index already exists, not overwriting.")
return None
logger.info("Index already exists, overwriting.")
await self.delete(drop)
try:
await self._redis_client.ft(self.schema.index.name).create_index( # type: ignore
fields=redis_fields,
definition=IndexDefinition(
prefix=[self.schema.index.prefix], index_type=self._storage.type
),
)
except:
logger.exception("Error while trying to create the index")
raise
[docs]
async def delete(self, drop: bool = True):
"""Delete the search index.
Args:
drop (bool, optional): Delete the documents in the index.
Defaults to True.
Raises:
redis.exceptions.ResponseError: If the index does not exist.
"""
try:
await self._redis_client.ft(self.schema.index.name).dropindex( # type: ignore
delete_documents=drop
)
except Exception as e:
raise RedisSearchError(f"Error while deleting index: {str(e)}") from e
[docs]
async def clear(self) -> int:
"""Clear all keys in Redis associated with the index, leaving the index
available and in-place for future insertions or updates.
Returns:
int: Count of records deleted from Redis.
"""
# Track deleted records
total_records_deleted: int = 0
# Paginate using queries and delete in batches
async for batch in self.paginate(
FilterQuery(FilterExpression("*"), return_fields=["id"]), page_size=500
):
batch_keys = [record["id"] for record in batch]
records_deleted = await self._redis_client.delete(*batch_keys) # type: ignore
total_records_deleted += records_deleted # type: ignore
return total_records_deleted
[docs]
async def drop_keys(self, keys: Union[str, List[str]]) -> int:
"""Remove a specific entry or entries from the index by it's key ID.
Args:
keys (Union[str, List[str]]): The document ID or IDs to remove from the index.
Returns:
int: Count of records deleted from Redis.
"""
if isinstance(keys, List):
return await self._redis_client.delete(*keys) # type: ignore
else:
return await self._redis_client.delete(keys) # type: ignore
[docs]
async def load(
self,
data: Iterable[Any],
id_field: Optional[str] = None,
keys: Optional[Iterable[str]] = None,
ttl: Optional[int] = None,
preprocess: Optional[Callable] = None,
concurrency: Optional[int] = None,
) -> List[str]:
"""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.
Args:
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[str]: List of keys loaded to Redis.
Raises:
ValueError: If the length of provided keys does not match the
length of objects.
.. code-block:: python
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)
"""
try:
return await self._storage.awrite(
self._redis_client, # type: ignore
objects=data,
id_field=id_field,
keys=keys,
ttl=ttl,
preprocess=preprocess,
concurrency=concurrency,
)
except:
logger.exception("Error while loading data to Redis")
raise
[docs]
async def fetch(self, id: str) -> Optional[Dict[str, Any]]:
"""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).
Args:
id (str): The specified unique identifier for a particular
document indexed in Redis.
Returns:
Dict[str, Any]: The fetched object.
"""
obj = await self._storage.aget(self._redis_client, [self.key(id)]) # type: ignore
if obj:
return convert_bytes(obj[0])
return None
[docs]
async def aggregate(self, *args, **kwargs) -> "AggregateResult":
"""Perform an aggregation operation against the index.
Wrapper around the aggregation API that adds the index name
to the query and passes along the rest of the arguments
to the redis-py ft().aggregate() method.
Returns:
Result: Raw Redis aggregation results.
"""
try:
return await self._redis_client.ft(self.schema.index.name).aggregate( # type: ignore
*args, **kwargs
)
except Exception as e:
raise RedisSearchError(f"Error while aggregating: {str(e)}") from e
[docs]
async def search(self, *args, **kwargs) -> "Result":
"""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:
Result: Raw Redis search results.
"""
try:
return await self._redis_client.ft(self.schema.index.name).search( # type: ignore
*args, **kwargs
)
except Exception as e:
raise RedisSearchError(f"Error while searching: {str(e)}") from e
async def _query(self, query: BaseQuery) -> List[Dict[str, Any]]:
"""Asynchronously execute a query and process results."""
results = await self.search(query.query, query_params=query.params)
return process_results(
results, query=query, storage_type=self.schema.index.storage_type
)
[docs]
async def query(self, query: BaseQuery) -> List[Dict[str, Any]]:
"""Asynchronously execute a query on the index.
This method takes a BaseQuery object directly, runs the search, and
handles post-processing of the search.
Args:
query (BaseQuery): The query to run.
Returns:
List[Result]: A list of search results.
.. code-block:: python
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)
"""
return await self._query(query)
[docs]
async def paginate(self, query: BaseQuery, page_size: int = 30) -> AsyncGenerator:
"""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.
Args:
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.
.. code-block:: python
# 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.
"""
if not isinstance(page_size, int):
raise TypeError("page_size must be an integer")
if page_size <= 0:
raise ValueError("page_size must be greater than 0")
first = 0
while True:
query.paging(first, page_size)
results = await self._query(query)
if not results:
break
yield results
# increment the pagination tracker
first += page_size
[docs]
async def listall(self) -> List[str]:
"""List all search indices in Redis database.
Returns:
List[str]: The list of indices in the database.
"""
return convert_bytes(
await self._redis_client.execute_command("FT._LIST") # type: ignore
)
[docs]
async def exists(self) -> bool:
"""Check if the index exists in Redis.
Returns:
bool: True if the index exists, False otherwise.
"""
return self.schema.index.name in await self.listall()
@staticmethod
async def _info(name: str, redis_client: aredis.Redis) -> Dict[str, Any]:
try:
return convert_bytes(await redis_client.ft(name).info()) # type: ignore
except Exception as e:
raise RedisSearchError(
f"Error while fetching {name} index info: {str(e)}"
) from e
[docs]
async def info(self, name: Optional[str] = None) -> Dict[str, Any]:
"""Get information about the index.
Args:
name (str, optional): Index name to fetch info about.
Defaults to None.
Returns:
dict: A dictionary containing the information about the index.
"""
index_name = name or self.schema.index.name
return await self._info(index_name, self._redis_client) # type: ignore
