RedisVectorStoreRetriever similarity search similarity_distance_threshold is not implemented asyncronously

Checked other resources

[X] I added a very descriptive title to this issue.
[X] I searched the LangChain documentation with the integrated search.
[X] I used the GitHub search to find a similar question and didn't find it.

Example Code

from langchain_community.vectorstores.redis import Redis

embedding = ...
redis_url = ...
schema_path = ...

vectorstore = Redis.from_existing_index(
    embedding,
    index_name='index',
    redis_url=redis_url,
    schema=schema_path,
)
retriever = vectorstore.as_retriever(search_type="similarity_distance_threshold", search_kwargs={"distance_threshold": 0.9, "k": 5})
retriever.aget_relevant_documents('query')

Description

The asynchronous method _aget_relevant_documents is not defined for RedisVectorStoreRetriever. As such, the method of the parent of RedisVectorStoreRetriever (VectorStoreRetriever) is called. In VectorStoreRetriever however, similarity_distance_threshold is not available. This makes the chain crash when RedisVectorStoreRetriever is called asynchronously in a chain.

I will make a PR to solve this

System Info

langchain                         0.1.0
langchain-community               0.0.12
langchain-core                    0.1.10

Related Components

[ ] LLMs/Chat Models
[ ] Embedding Models
[ ] Prompts / Prompt Templates / Prompt Selectors
[ ] Output Parsers
[ ] Document Loaders
[X] Vector Stores / Retrievers
[ ] Memory
[ ] Agents / Agent Executors
[ ] Tools / Toolkits
[ ] Chains
[ ] Callbacks/Tracing
[x] Async

🤖

That's great to hear that you're willing to make a PR to solve this issue! Your contribution will definitely help improve LangChain for everyone. Thank you for taking the initiative to address this and for your willingness to contribute to the project. If you have any questions or need any assistance while working on the PR, feel free to ask for help. Good luck with your contribution!

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