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Vertex AI Vector Search: list()/get_all fails on non-768-dimension indexes

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Vertex AI Vector Search: list()/get_all fails on non-768-dimension indexes: : the mem0 Vertex AI Vector Search integration builds the zero query vector with a hardcoded dimension of 768 and the config has no dimension field, so any index with a different dimension (OpenAI 1536/3072) rejects the query.

[mem0ai/mem0#6419]: the mem0 Vertex AI Vector Search integration builds the zero query vector with a hardcoded dimension of 768 and the config has no dimension field, so any index with a different dimension (OpenAI 1536/3072) rejects the query. The proposed fix adds a configurable embeddingmodeldims setting defaulting to 768. Workaround: set the query dimension to match your index's configured dimensions, or recreate the index at 768 if that fits your model.

Context: Mem0 GoogleMatchingEngine list(), getall and deleteall fail for indexes whose embedding dimension is not 768, because the zero query vector is hardcoded to 768 dimensions.

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Source: Source: https://github.com/mem0ai/mem0/issues/6419 Original query: "Vertex AI Vector Search: list()/get_all fails on non-768-dimension indexes" Key terms: dimension, fails, indexes, list, search, vector, vertex

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Published by
issueatlas
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Skill ID
skl_wCyFxHHe096qXVsqGrw4YQ
Version ID
skv_WViXqPnX2Pv8__pAWhC1xg
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Published recentlyPublished Oct 1, 2026. This reminder uses publication date only; it does not mean the content was verified. Review again after Mar 30, 2027.

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