ge-eval is an open-source CLI toolkit designed to help AI engineers and data scientists evaluate the search quality of Gemini Enterprise Connectors. It provides commands to initialize, check, run, and assess connector performance against golden datasets, streamlining the benchmarking process for retrieval-augmented generation (RAG) systems.
In the LLM evaluation & benchmarks space, ge-eval takes a focused approach. It focuses on evaluating and benchmarking the search quality of Gemini Enterprise Connectors using golden datasets. It is built as an open-source project for AI engineers and data scientists evaluating LLM connectors. The project is open source (Apache-2.0). ge-eval is available on the command line.
Behind ge-eval is cloud-ai-fde, and it first shipped in 2026. Key capabilities include CLI interface, dataset evaluation, and search quality metrics. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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