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[PR #2526] feat: Vector Search #2760

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opened 2026-02-20 17:47:31 -05:00 by yindo · 0 comments
yindo commented 2026-02-20 17:47:31 -05:00
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Original Pull Request: https://github.com/langchain-ai/langgraph/pull/2526

State: closed
Merged: No

Right now you enable it by:

  • Initializing the store with an 'embedding config' -> this contains the 'dims' (used to create the table) and the encoder object (rn langchain embeddings object, though that is ......)
  • Call setup() -> creates the vector table.

Each document has 1 or more vectors associated with it for each json path in the embedding config.

Would welcome critique and requests!

Especially around handling migrations, whether we want to support multimedia (multimodal embeddings is old school already so kinda bad langchain embeddings classes don't support well), querying (do we need mmr or other strategies...?) and anything else that feels off.

Also happy to shelve the use of json path for saving embeddings if we think that's too complicated.

Also the default __root__ embedding of the whole JSON object retains the keys. I'm guessing there's a bit of an impact here but probably better to have it remain self descriptive than to drop the keys before embedding the object.

**Original Pull Request:** https://github.com/langchain-ai/langgraph/pull/2526 **State:** closed **Merged:** No --- Right now you enable it by: - Initializing the store with an 'embedding config' -> this contains the 'dims' (used to create the table) and the encoder object (rn langchain embeddings object, though that is ......) - Call setup() -> creates the vector table. Each document has 1 or more vectors associated with it for each json path in the embedding config. Would welcome critique and requests! Especially around handling migrations, whether we want to support multimedia (multimodal embeddings is old school already so kinda bad langchain embeddings classes don't support well), querying (do we need mmr or other strategies...?) and anything else that feels off. Also happy to shelve the use of json path for saving embeddings if we think that's too complicated. Also the default `__root__` embedding of the whole JSON object retains the keys. I'm guessing there's a bit of an impact here but probably better to have it remain self descriptive than to drop the keys before embedding the object.
yindo added the pull-request label 2026-02-20 17:47:31 -05:00
yindo closed this issue 2026-02-20 17:47:31 -05:00
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Reference: langchain-ai/langgraph#2760
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