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    Pythonlanggraph-clischemasIndexConfigdims
    Attribute●Since v0.4

    dims

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    dims: int
    View source on GitHub

    Required. Dimensionality of the embedding vectors you will store.

    Must match the output dimension of your selected embedding model or custom embed function. If mismatched, you will likely encounter shape/size errors when inserting or querying vectors.

    Common embedding model output dimensions:

    • openai:text-embedding-3-large: 3072
    • openai:text-embedding-3-small: 1536
    • openai:text-embedding-ada-002: 1536
    • cohere:embed-english-v3.0: 1024
    • cohere:embed-english-light-v3.0: 384
    • cohere:embed-multilingual-v3.0: 1024
    • cohere:embed-multilingual-light-v3.0: 384