PanelWise

English · 中文

PanelWise

**Fuse the complementary strengths of multiple models into one stronger result.**

PanelWise starts with a simple question: if every model sees something worth keeping, can their complementary judgments produce a result stronger than any one answer? It is an embeddable Python aggregation engine that sends the same task to a configurable panel, preserves each model's distinct contribution, and coordinates those contributions through one of two execution topologies. The task itself is unrestricted; prompts, providers, and environment adapters define the domain.

Two modes, one interface

Mode	Topology	Best fit
--eval	independent complete attempts → evaluator → synthesis	Answer-centric tasks, including deep research
--no-eval	independent next-action proposals → one coordinated action → shared observable state → repeat	Stateful tasks, including coding

These are execution modes, not hard-coded task categories. Both accept any task string. Custom `ChatClient` and `Executor` implementations can connect the same engine to another provider or environment.

panelwise run "Compare PostgreSQL and MySQL for a large marketplace" --eval
panelwise