#541 · Primary category: AI Agents & Automation
llm-space
A desktop app to prototype agent ideas, inspect every harness step, replay failures, and evaluate performance, all in one place. Local-first, cloud-ready for managed agents.
Project last updated:08/29/26
GitHub Stars
1.7K
Forks
187
Contributors
19
License
MIT
Why we included this project
Most teams building LLM agents debug them by combing through logs and juggling a few scripts. LLM Space replaces that patchwork with a desktop app that shows the whole agent loop in one place: you sketch out an idea, watch each model call and tool run as the harness executes, then replay a failed run step by step to see what went wrong. Evaluation sits in the same tool, so you can measure performance across runs instead of eyeballing output. Everything stays local-first, with your threads and run history kept as files on your own machine, handy for sensitive work or anything you prefer not to push to a cloud. The DeerFlow team uses LLM Space to build every release of DeerFlow, which is a decent sign it holds up under real development rather than just demos.
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