Error like "Vector dimension X does not match the dimension of the index Y" or "expected Z dimensions, not W" when upserting embeddings to vector store in AI agent workflows. [LightRAG GitHub Issue](https://github.com/HKUDS/LightRAG/issues/2119)

Voyage AI embedding models output vectors of specific dimensions (default 1024), but agent tools/vector stores are often pre-configured for different sizes (e.g. 1536 for OpenAI, 768 for some local models), causing insert/query failures when dimensions don't align. [DEV Community Post](https://dev.to/hijazi313/resolving-vector-dimension-mismatches-in-ai-workflows-47m)