LLM-Insights, local demo for people comments and ideas
LLM InSights is a local-first tool designed for iterative content creation and optimization. It allows users to run multi-model A/B tests, refine prompts automatically, and generate synthetic data while keeping all data on local hardware. The system features customizable grading rubrics, automatic prompt optimization, and detailed session analysis capabilities.
- ▪LLM InSights enables users to write prompts and compare outputs from competing LLM models.
- ▪The tool automatically rewrites prompts based on feedback and grades them using customizable rubrics.
- ▪It produces structured records of prompts and scores, which can be used for content quality benchmarks.
Opening excerpt (first ~120 words) tap to expand
LLM InSights A local-first testing and optimization harness for iterative content creation — run multi-model A/B tests, refine prompts automatically with rubric-based grading, and generate scored synthetic data. Built for brand content workflows, prompt engineering, and LLM evaluation on your own hardware. Walkthrough (~1.5 min) What It Does You write a prompt — a piece of brand copy, a product description, a creative brief, or any content task. The tool sends it to two competing LLM models, grades both answers against a configurable rubric, optionally rewrites the prompt using grader feedback, and repeats the cycle — keeping the best answer each round.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.