deer-flow/llm-space

Agent debugging is miserable when your tools are scattered: one window for logs, another for prompt inspection, a third for eval scripts. This project puts the prototype-inspect-replay-evaluate loop into a single desktop app. Local-first with a path to cloud-managed agents means it does not force a hosting decision on day one. The failure replay feature is the real differentiator — being able to rerun a specific harness step with modified inputs without re-executing the full pipeline is something most agent devs rig together manually. Reservation: desktop-first agent tooling has a crowded field right now, and it is not immediately clear what this does that a well-configured LangSmith or a local Weave setup cannot. The value proposition sharpens if you are allergic to SaaS observability tools or working in an airgapped environment. Worth a pull and a thirty-minute test run. -> Best for: AI engineer or indie hacker iterating on multi-step agent pipelines locally.