fix(indexing): pass configured dimension to OpenAI-compatible embedder - #14580
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intentionally-left-nil merged 2 commits intoSep 25, 2026
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Code Review SummaryStatus: No Issues Found | Recommendation: Merge The change correctly forwards Files Reviewed (3 files)
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intentionally-left-nil
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Sep 25, 2026
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Fixes #14579
Summary
Pass
options: { dimensions: config.modelDimension }when instantiatingOpenAICompatibleEmbedderinCodeIndexServiceFactory.createEmbedder().Why
When configuring an OpenAI-compatible embedding provider with a custom dimension (such as 4096 for MRL-enabled models like Qwen3-Embedding-8B or OpenAI text-embedding-3), the vector store table was created with the configured dimension, but
OpenAICompatibleEmbeddernever receivedconfig.modelDimension.As a result, HTTP requests to the embedding endpoint did not include the
"dimensions"parameter, causing the provider to fall back to its server default dimension (e.g. 768) and triggering a dimension mismatch error duringsemantic_search:GenericFailure, Invalid input, No vector column found to match with the query vector dimension: 768This change brings
openai-compatiblein line with the other providers (openrouter,ollama,kilo) which already forwardconfig.modelDimension.Testing
packages/kilo-indexing/test/kilocode/indexing/service-factory.test.tsverifying thatdimensionsis forwarded to OpenAI-compatible embedding requests when configured, and omitted when unset.bun test,tsgo --noEmit).