by rentruewang · LLM Plugin · ★ 289
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🫙 Archive This has topped the show HN front page link. This was born as a research project, and I think I have achieved most of what I set out to create. So today (2025/09/14) I'm archiving this repository. Nowadays I'm mainly working on , a deep learning algorithm compiler! Check it out. ☂️ BoCoEL Bayesian Optimization as a Coverage Tool for Evaluating Large Language Models 
🦙 Integrating LLMs into structured NLP pipelines
A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, eva
OpenAI and Anthropic compatible server for Apple Silicon. Run LLMs and vision-language models (Llama, Qwen-VL,
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bocoel is Bayesian Optimization as a Coverage Tool for Evaluating LLMs. Accurate evaluation (benchmarking) that's 10 times faster with just a few lines of modular code.. It is categorized as a LLM Plugin with 289 GitHub stars.
bocoel is primarily written in Python. It covers topics such as bayesian-optimization, benchmarking, evaluation.
You can find installation instructions and usage details in the bocoel GitHub repository at github.com/rentruewang/bocoel. The project has 289 stars and 16 forks, indicating an active community.
bocoel is released under the BSD-3-Clause license, making it free to use and modify according to the license terms.
The top alternatives to bocoel on Agent Skills Hub include Awesome-LLM-Eval, create-llm, Hegelion. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.