Storing MultiVectorRetriever in Redis for a Multimodal RAG System

[baeGil]

I tried to make a Multimodal RAG system with LangChain and Redis as a cache database. When a person starts a new conversation and uploads a file, it creates a MultiVectorRetriever and uses that retriever to answer questions from the user. I want to store that retriever in Redis to avoid redundant creation.

I figured out that Redis stores the JSON string representing the object, not the actual object itself. So, I convert the MultiVectorRetriever object to JSON by calling the to_json() method, so I can store it in Redis.

However, after storing it in Redis, how can I get the actual data back from it? The json.loads() returns the JSON string, but LangChain does not provide any method to reconstruct the JSON back into a MultiVectorRetriever object after calling the to_json() method.

repr returns a string type, meanwhile my actual data has this datatype: langchain.retrievers.multi_vector.MultiVectorRetriever.

[dosubot[bot]]

Hey @baeGil! I'm here to help you with any bugs, questions, or contributions. Let's tackle this issue together!

To reconstruct a MultiVectorRetriever object from a JSON string in LangChain, you can use the serialization and deserialization utilities provided by the framework. Although the to_json() method might not directly support reconstruction, LangChain offers functions like load and loads for this purpose.

Here's a general approach you can follow:

1. Serialize the Object: Use the dumps function to convert the MultiVectorRetriever object into a JSON string. This ensures that the object is serialized in a way that can be deserialized later.

2. Store in Redis: Save the JSON string in Redis as you are currently doing.

3. Deserialize the Object: Use the loads function to convert the JSON string back into a MultiVectorRetriever object. This function is designed to handle the deserialization of LangChain objects.

Here is an example of how you might serialize and deserialize a LangChain object:

from langchain_core.load import dumps, loads

# Assuming `retriever` is your MultiVectorRetriever object
# Serialize the retriever to a JSON string
json_string = dumps(retriever, pretty=True)

# Store `json_string` in Redis

# Retrieve `json_string` from Redis

# Deserialize the JSON string back into a MultiVectorRetriever object
retriever = loads(json_string)

This approach should help you store and retrieve MultiVectorRetriever objects using Redis without losing the ability to reconstruct them. If you encounter any issues with specific attributes or configurations, ensure that all necessary components are included in the serialization process.

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[baeGil]

Hi @dosu
Your code line retriever = loads(json_string) raises an error:
LangChainBetaWarning: The function loads is in beta. It is actively being worked on, so the API may change. retriever = loads(json_string)