Network-AI
TypeScript/Node.js multi-agent orchestrator — shared state, guardrails, budgets, and cross-framework coordination
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Network-AI is a TypeScript/Node.js multi-agent orchestrator that adds coordination, guardrails, and governance to any AI agent stack.
- Shared blackboard with locking — atomic
propose → validate → commitprevents race conditions and split-brain failures across parallel agents - Guardrails and budgets — FSM governance, per-agent token ceilings, HMAC / Ed25519 audit trails, and permission gating
- 29 adapters — LangChain (+ streaming), AutoGen, CrewAI, OpenAI Assistants, LlamaIndex, Semantic Kernel, Haystack, DSPy, Agno, MCP, Custom (+ streaming), OpenClaw, A2A, Codex, MiniMax, NemoClaw, APS, Copilot, LangGraph, Anthropic Computer Use, OpenAI Agents SDK, Vertex AI, Pydantic AI, Browser Agent, Hermes (NousResearch Hermes / any OpenAI-compatible endpoint), Orchestrator (hierarchical multi-orchestrator), and RLM (Recursive Language Model / any RLM-compatible HTTP endpoint) — no glue code, no lock-in
- Persistent project memory (Layer 3) —
context_manager.pyinjects decisions, goals, stack, milestones, and banned patterns into every system prompt so agents always have full project context - v5.0 modules — Agent VCR (record/replay), comparison runner, coverage reporter, goal DSL, approval inbox, job queue, gRPC/HTTP transport, playground REPL, adapter test harness, and more
- Model-interaction lifecycle governance (v5.13) —
GovernedModelGatewayabsorbs the model refusal → fallback → billing chain (cross-model fallback, fallback-credit repricing, effort governance, thinking-block handoff) behind one governed, budgeted, audited call






