AI & LLM Engineering · By lobehub

Maintains LobeHub's model-backed alint rule set: writing rules, removing false positives against real code, deciding warn versus error and tracking token cost.

lobehub/lobehub

Guides building LobeHub builtin agent tools, from the manifest and execution runtime to executors, chat UI renders and registry wiring.

lobehub/lobehub

Implements business-facing LLM calls as explicit, traceable workflows, keeping prompt versions, model policy, structured output and tracing scenarios in separate places.

lobehub/lobehub

Fills and maintains the knowledgeCutoff, family and generation fields on model cards in LobeHub's model bank, from a single new model up to repo-wide backfills.

lobehub/lobehub

Adds an AI model provider to LobeHub end to end: runtime integration, model cards, configuration, branding and documentation, or documentation-only updates.

lobehub/lobehub

Inspects LobeHub agent execution snapshots by operation ID: failed tool calls, arguments and results, available tools, LLM calls and the surrounding context.

lobehub/lobehub