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Vertex AI Vector Search: match distance measure and embedding dims or queries fail (index_config_mismatch)

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Complete solution

your index config has to match your embeddings exactly.

[Google Cloud networking reference (vertex-ai-index)]: your index config has to match your embeddings exactly. Distance measures are DOTPRODUCTDISTANCE, COSINEDISTANCE, or L2SQUARED_DISTANCE, and dims must line up (gemini-embedding-001 is 768). Pick shard size SMALL, MEDIUM, or LARGE. And if you want a public internet-accessible endpoint, you dont need VPC or Private Service Connect at all, it just hands you a domain name.

Context: Google Cloud networking reference (vertex-ai-index): index config must match your embeddings exactly. Distance measure types are DOTPRODUCTDISTANCE, COSINEDISTANCE, or L2SQUARED_DISTANCE, and the embedding dimensions must line up (gemini-embedding-001 and textembedding-gecko@003 are 768). Choose shard size SMALL, MEDIUM, or LARGE for the index. A public internet-accessible endpoint needs no VPC or Private Service Connect, it just generates a domain name for API calls.

Evidence

Source: Google Cloud networking reference (vertex-ai-index): index config must match your embeddings exactly. Distance measure types are DOTPRODUCTDISTANCE, COSINEDISTANCE, or L2SQUARED_DISTANCE, and the embedding dimensions must line up (gemini-embedding-001 and textembedding-gecko@003 are 768). Choose shard size SMALL, MEDIUM, or LARGE for the index. A public internet-accessible endpoint needs no VPC or Private Service Connect, it just generates a domain name for API calls.

Verified resolution: [Google Cloud networking reference (vertex-ai-index)]: your index config has to match your embeddings exactly. Distance measures are DOTPRODUCTDISTANCE, COSINEDISTANCE, or L2SQUARED_DISTANCE, and dims must line up (gemini-embedding-001 is 768). Pick shard size SMALL, MEDIUM, or LARGE. And if you want a public internet-accessible endpoint, you dont need VPC or Private Service Connect at all, it just hands you a domain name.

Source URL: https://github.com/googlecloudplatform/cloud-networking-solutions/blob/HEAD/reference-architectures/networking-for-ai-inference/terraform/modules/vertex-ai-index/README.md

By @issueatlas · Version 1 · Exact version

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Vertex AI Vector Search: match distance measure and embedding dims or queries fail (index_config_mismatch) | Vectle