Source code for langchain.vectorstores.redis
"""Wrapper around Redis vector database."""
from __future__ import annotations
import json
import logging
import uuid
from typing import (
    TYPE_CHECKING,
    Any,
    Callable,
    Dict,
    Iterable,
    List,
    Literal,
    Mapping,
    Optional,
    Tuple,
    Type,
)
import numpy as np
from pydantic import BaseModel, root_validator
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from langchain.utils import get_from_dict_or_env
from langchain.vectorstores.base import VectorStore, VectorStoreRetriever
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
    from redis.client import Redis as RedisType
    from redis.commands.search.query import Query
# required modules
REDIS_REQUIRED_MODULES = [
    {"name": "search", "ver": 20400},
    {"name": "searchlight", "ver": 20400},
]
# distance mmetrics
REDIS_DISTANCE_METRICS = Literal["COSINE", "IP", "L2"]
def _check_redis_module_exist(client: RedisType, required_modules: List[dict]) -> None:
    """Check if the correct Redis modules are installed."""
    installed_modules = client.module_list()
    installed_modules = {
        module[b"name"].decode("utf-8"): module for module in installed_modules
    }
    for module in required_modules:
        if module["name"] in installed_modules and int(
            installed_modules[module["name"]][b"ver"]
        ) >= int(module["ver"]):
            return
    # otherwise raise error
    error_message = (
        "Redis cannot be used as a vector database without RediSearch >=2.4"
rtdocs_stable/api.python.langchain.com/en/stable/_modules/langchain/vectorstores/redis.html