[LangGraph] Add Autoembedding to core VectorStore

XMLWordPrintableJSON

    • Type: Task
    • Resolution: Unresolved
    • Priority: Critical - P2
    • None
    • Affects Version/s: None
    • Component/s: LangChain
    • None
    • None
    • Python Drivers
    • Hide

      1. What would you like to communicate to the user about this feature?
      2. Would you like the user to see examples of the syntax and/or executable code and its output?
      3. Which versions of the driver/connector does this apply to?

      Show
      1. What would you like to communicate to the user about this feature? 2. Would you like the user to see examples of the syntax and/or executable code and its output? 3. Which versions of the driver/connector does this apply to?
    • None
    • None
    • None
    • None
    • None
    • None

      Context

      We would like to add support for Voyage AI auto-embedding in our LangGraph integrations as the default method to generate embeddings for MongoDB LongTerm Store. We would ideally make passing an embedding instance optional, where customers can use Voyage as the default embedding model. We will still support the ability for customers to pick their own model but as an optional parameter. More specifically we'd update the MongoDB LangGraph Store (Long-term Memory).

      [Proof of Concept PR for langchain | https://github.com/langchain-ai/langchain-mongodb/pull/204]

      Definition of done

      This tracks adding the feature to the LangGraph Store.

      Pitfalls

      potential issues may arise due to general availability in the server. 

            Assignee:
            Unassigned
            Reporter:
            Gaurab Aryal
            Votes:
            0 Vote for this issue
            Watchers:
            3 Start watching this issue

              Created:
              Updated: