- README: remove autogen/crewai references, add v2 architecture diagram, code-review scenario, cross-LLM config examples, roadmap - wiki/overview: event-driven architecture, Pydantic v2, roadmap - wiki/index: add entities/roles, concepts/code-review, packages/pydantic - wiki/log: Phase 1 completion, code-review decision - New: entities/roles.md, concepts/code-review.md, packages/pydantic.md Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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title, type, updated
| title | type | updated |
|---|---|---|
| meeting-room overview | overview | 2026-05-04 |
meeting-room — overview
Multi-agent discussion framework — an interactive workspace where AI agents debate problems and produce structured artifacts.
What it does
Meeting-room runs multi-agent roundtable discussions with configurable participants, models, and tools. Each role can use a different LLM provider, enabling cross-model review and debate. The event-driven architecture decouples the engine from I/O — CLI subscribes to events for ANSI output, future WebSocket server will stream them to browsers.
Key components
- DiscussionEngine — event-driven core: orchestrates round-robin discussion, emits events instead of printing
- APIClient — class-based multi-provider client (OpenAI-compatible APIs)
- ToolRegistry — class-based, pure Python (Windows compatible, no find/grep)
- EventEmitter — synchronous pub/sub bus for decoupling engine from I/O
- Pydantic v2 models — typed config (DiscussionConfig, ProviderConfig, RoleConfig), messages, sessions
- Scenarios — Markdown + YAML frontmatter for defining discussion topics
Built-in scenarios
- Roundtable — moderator/skeptic/idea_generator/analyst discuss a problem
- Code Review — defender/attacker/security/moderator cross-LLM code review
Tech stack
- Python 3.11+, pydantic v2, httpx, pyyaml
- Event-driven architecture (EventEmitter, Phase 2: AsyncEventBridge)
- OpenAI-compatible API (multi-provider: RouterAI, Ollama Cloud, OpenAI, Anthropic, DeepSeek, local Ollama)
- Planned: FastAPI + WebSocket for Web UI (Phase 2)
Roadmap
- Phase 1: Core refactor — Pydantic models, EventEmitter, class-based APIClient/ToolRegistry, DiscussionEngine
- Phase 2: Web server — FastAPI + WebSocket + SSE, REST API, HTML UI
- Phase 3: Interactivity — Boss role, CSO injection, Setup Wizard, BrainstormEngine
- Phase 4: Artifacts — LLM extraction to .tasks/.wiki, SessionArchive