see a nice Redis UI at http://localhost:8001. See the Deployment Options section above for other ways to deploy.The Redis VectorStore instance can be initialized in a number of ways. There are multiple class methods that can be used to initialize a Redis VectorStore instance.Redis.__init__ - Initialize directlyRedis.from_documents - Initialize from a list of Langchain.docstore.Document objectsRedis.from_texts - Initialize from a list of texts (optionally with metadata)Redis.from_texts_return_keys - Initialize from a list of texts (optionally with metadata) and return the keysRedis.from_existing_index - Initialize from an existing Redis indexBelow we will use the Redis.from_texts method.from langchain.vectorstores.redis import Redisrds = Redis.from_texts(    texts,    embeddings,    metadatas=metadata,    redis_url="redis://localhost:6379",    index_name="users")rds.index_name    'users'Inspecting the Created Indexâ€‹Once the Redis VectorStore object has been constructed, an index will have been created in Redis if it did not already exist. The index can be inspected with both the rvland the redis-cli command line tool. If you installed redisvl above, you can use the rvl command line tool to inspect the index.# assumes you're running Redis locally (use --host, --port, --password, --username, to change this)rvl index listall    16:58:26 [RedisVL] INFO   Indices:    16:58:26 [RedisVL] INFO   1. usersThe Redis VectorStore implementation will attempt to generate index schema (fields for filtering) for any metadata passed through the from_texts, from_texts_return_keys, and from_documents methods. This way, whatever metadata is passed will be indexed into the Redis search index allowing
Redis vector database introduction and langchain integration guide.
Redis vector database introduction and langchain integration guide. ->: see a nice Redis UI at http://localhost:8001. See the Deployment Options section above for other ways to deploy.The Redis VectorStore instance can be initialized in a number of ways. There are multiple class methods that can be used to initialize a Redis VectorStore instance.Redis.__init__ - Initialize directlyRedis.from_documents - Initialize from a list of Langchain.docstore.Document objectsRedis.from_texts - Initialize from a list of texts (optionally with metadata)Redis.from_texts_return_keys - Initialize from a list of texts (optionally with metadata) and return the keysRedis.from_existing_index - Initialize from an existing Redis indexBelow we will use the Redis.from_texts method.from langchain.vectorstores.redis import Redisrds = Redis.from_texts(    texts,    embeddings,    metadatas=metadata,    redis_url="redis://localhost:6379",    index_name="users")rds.index_name    'users'Inspecting the Created Indexâ€‹Once the Redis VectorStore object has been constructed, an index will have been created in Redis if it did not already exist. The index can be inspected with both the rvland the redis-cli command line tool. If you installed redisvl above, you can use the rvl command line tool to inspect the index.# assumes you're running Redis locally (use --host, --port, --password, --username, to change this)rvl index listall    16:58:26 [RedisVL] INFO   Indices:    16:58:26 [RedisVL] INFO   1. usersThe Redis VectorStore implementation will attempt to generate index schema (fields for filtering) for any metadata passed through the from_texts, from_texts_return_keys, and from_documents methods. This way, whatever metadata is passed will be indexed into the Redis search index allowing