How to load storage_context in llama-index using Redis as backend, and to load llama-index – EyeVision

Load storage_context from Redis

from llama_index.storage.docstore import RedisDocumentStore
from llama_index.storage.index_store import RedisIndexStore
from llama_index.vector_stores import RedisVectorStore
from llama_index.storage.storage_context import StorageContext
from config import ConfigRedis

def get_storage_context(
    cfg: ConfigRedis,
    collection_id: str
) -> StorageContext:

    docstore = RedisDocumentStore.from_host_and_port(
        host=cfg.redis_host,
        port=cfg.redis_port,
        # namespace="llama_index"
    )
    index_store=RedisIndexStore.from_host_and_port(
        host=cfg.redis_host,
        port=cfg.redis_port,
        # namespace="llama_index"
    )

    vector_store = RedisVectorStore(
        index_name=collection_id,
        # index_prefix="llama",
        redis_url=f"redis://{cfg.redis_host}:{str(cfg.redis_port)}",
        overwrite=True,
    )

    storage_context = StorageContext.from_defaults(
        docstore=docstore,
        index_store=index_store,
        vector_store=vector_store
    )
    return storage_context

Config is here

@dataclass
class ConfigRedis():
    redis_host: str
    redis_port: int

    @classmethod
    def from_defaults(
        cls,
        redis_host: str,
        redis_port: int
    ) -> 'ConfigRedis':
        
        return cls(
            redis_host,
            redis_port
        )

The easiest way to launch Redis is here.

docker run --name redis-vecdb -d -p 6379:6379 -p 8001:8001 redis/redis-stack:latest

Load llama-index from storage_context

from llama_index import load_index_from_storage
index = load_index_from_storage(storage_context)