Crafting Superior RAG for Code-Intensive Texts with Zilliz Cloud Pipelines and Voyage AI

Zilliz Cloud Pipelines has integrated the Voyage AI embedding models, voyage-2 and voyage-code-2, which have shown outstanding performance in retrieval tasks related to source code, technical documentation, and general tasks. The incorporation of these models enhances the RAG system implemented with various embedding models for code-related tasks. Notably, when compared to other popular embedding models on code datasets, Voyage's models demonstrate significantly better retrieval capability and lead to over ten percentage point improvements in Answer Correctness and overall performance scores.

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