@graphrefly/graphrefly
v0.21.0
Published
Reactive harness layer for agent workflows. Describe automations in plain language, trace every decision, enforce policies, persist checkpoints. Zero dependencies.
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GraphReFly
The reactive harness layer for agent workflows. Describe in plain language, review visually, run persistently, trace every decision.
GraphReFly makes long-running human + LLM co-operation reactive, resumable, and causally explainable. State pushes downstream on change (no re-reading), nodes have lifecycles (not infinite append), and every decision has a traceable causal chain — the substrate underneath tools, agents, and personal automations.
Docs | Spec | Python API | TS API Reference
What can you do with it?
Email triage — "Watch my inbox. Urgent emails from my team go to a priority list. Newsletters get summarized weekly. Everything else, count by sender." It watches, classifies, and alerts — and when you ask "why was this flagged?", it walks you through the reasoning.
Spending alerts — Connect bank transactions to budget categories. Get a push notification when monthly dining exceeds your target. No polling, no manual checks — changes propagate the moment data arrives.
Knowledge management — Notes, bookmarks, highlights flow in. Contradictions surface automatically. Related ideas link themselves. Your second brain stays current without you maintaining it.
Quick start
npm install @graphrefly/graphreflyimport { state, derived, effect } from "@graphrefly/graphrefly";
const count = state(0);
const doubled = derived([count], ([c]) => c * 2);
effect([doubled], ([d]) => console.log("doubled:", d));
// → doubled: 0
count.set(3);
// → doubled: 6How it works
You describe what you need — an LLM composes a reactive graph (like SQL for data flows). The graph runs persistently, checkpoints its state, and traces every decision through a causal chain. Ask "why?" at any point and get a human-readable explanation from source to conclusion.
Harness engineering coverage
The eight requirements of a production agent harness cluster into a handful of composed blocks that sit on top of the reactive graph primitives:
| Need | GraphReFly |
|---|---|
| Context & state | persistentState() — autoCheckpoint + snapshot / restore + incremental diff |
| Agent memory | agentMemory() — distill + vectors + knowledge graph + tiers, OpenViking decay |
| Control flow & resilience | resilientPipeline() — rateLimiter → breaker → retry → timeout → fallback, correct ordering built in |
| Execution & policy | guardedExecution() — Actor / Guard ABAC + policy() + budgetGate + scoped describe |
| Observability & causality | graphLens() — reactive topology, health, flow, and why(node) causal chains as structured data |
| Human governance | gate — reactive pending / isOpen with approve / reject / modify(fn, n) |
| Verification | Multi-model eval harness with regression gates |
| Continuous improvement | Strategy model: rootCause × intervention → successRate |
The library computes structured facts reactively; LLMs and UIs render them. Natural language is never the library's job — which keeps the whole stack model-agnostic and testable.
Why GraphReFly?
| | Zustand / Jotai | RxJS | XState | LangGraph | TC39 Signals | GraphReFly | |--|-----------------|------|--------|-----------|-------------|---------------| | Simple store API | yes | no | no | no | yes | yes | | Streaming operators | no | yes | no | no | no | yes | | Diamond resolution | no | n/a | n/a | n/a | partial | glitch-free | | Graph introspection | no | no | visual | checkpoints | no | describe / observe / diagram | | Causal tracing | no | no | no | no | no | explain every decision | | Durable checkpoints | no | no | persistence | yes | no | file / SQLite / IndexedDB | | LLM orchestration | no | no | no | yes | no | agentLoop / chatStream / toolRegistry | | NL → graph composition | no | no | no | no | no | graphFromSpec / llmCompose | | Framework adapters | React | Angular | React / Vue | n/a | varies | React / Vue / Svelte / Solid / NestJS | | Dependencies | 0 | 0 | 0 | many | n/a | 0 |
One primitive
Everything is a node. Sugar constructors give you the right shape:
import { state, derived, producer, effect, pipe } from "@graphrefly/graphrefly";
// Writable state
const name = state("world");
// Computed (re-runs when deps change)
const greeting = derived([name], ([n]) => `Hello, ${n}!`);
// Push source (timers, events, async streams)
const clock = producer((emit) => {
const id = setInterval(() => emit([[DATA, Date.now()]]), 1000);
return () => clearInterval(id);
});
// Side effect
effect([greeting], ([g]) => document.title = g);
// Operator pipeline
const delayed = pipe(clock, delay(500), map(([, ts]) => new Date(ts)));Streaming & operators
70+ operators — transform, combine, buffer, window, rate-limit, retry, circuit-break:
import { pipe, merge, switchMap, debounceTime, retry } from "@graphrefly/graphrefly";
const search = pipe(
input,
debounceTime(300),
switchMap((query) => fromPromise(fetch(`/api?q=${query}`))),
retry({ strategy: "exponential", maxAttempts: 3 }),
);Graph container
Register nodes in a Graph for introspection, snapshot, and persistence:
import { Graph, state, derived } from "@graphrefly/graphrefly";
const g = new Graph("pricing");
const price = g.register("price", state(100));
const tax = g.register("tax", derived([price], ([p]) => p * 0.1));
const total = g.register("total", derived([price, tax], ([p, t]) => p + t));
g.describe(); // → full graph topology as JSON
g.diagram(); // → Mermaid diagram string
g.observe((e) => console.log(e)); // → live change streamAI & orchestration
First-class patterns for LLM streaming, agent loops, and human-in-the-loop workflows:
import { chatStream, agentLoop, toolRegistry } from "@graphrefly/graphrefly";
// Streaming chat with tool use
const chat = chatStream("assistant", {
model: "claude-sonnet-4-20250514",
tools: toolRegistry("tools", { search, calculate }),
});
// Full agent loop: observe → think → act → memory
const agent = agentLoop("researcher", {
llm: chat,
memory: agentMemory({ decay: "openviking" }),
});Framework adapters
Drop-in bindings — your framework, your way:
// React
import { useNode } from "@graphrefly/graphrefly/compat/react";
const [value, setValue] = useNode(count);
// Vue
import { useNode } from "@graphrefly/graphrefly/compat/vue";
const value = useNode(count); // → Ref<number>
// Svelte
import { toStore } from "@graphrefly/graphrefly/compat/svelte";
const value = toStore(count); // → Svelte store
// Solid
import { useNode } from "@graphrefly/graphrefly/compat/solid";
const value = useNode(count); // → Signal<number>
// NestJS
import { GraphReflyModule } from "@graphrefly/graphrefly/compat/nestjs";
@Module({ imports: [GraphReflyModule.forRoot()] })Tree-shaking imports
Prefer subpath imports for minimal bundle:
import { node, batch, DATA } from "@graphrefly/graphrefly/core";
import { map, switchMap } from "@graphrefly/graphrefly/extra";
import { Graph } from "@graphrefly/graphrefly/graph";The root entry re-exports everything:
import { node, map, Graph } from "@graphrefly/graphrefly";Resilience & checkpoints
Built-in retry, circuit breakers, rate limiters, and persistent checkpoints:
import { retry, circuitBreaker, saveGraphCheckpoint, FileCheckpointAdapter } from "@graphrefly/graphrefly";
// Retry with exponential backoff
const resilient = pipe(source, retry({ strategy: "exponential" }));
// Circuit breaker
const breaker = circuitBreaker({ threshold: 5, resetTimeout: 30_000 });
// Checkpoint to file system
const adapter = new FileCheckpointAdapter("./checkpoints");
await saveGraphCheckpoint(graph, adapter);Project layout
| Path | Contents |
|------|----------|
| src/core/ | Message protocol, node primitive, batch, sugar constructors |
| src/extra/ | Operators, sources, data structures, resilience, checkpoints |
| src/graph/ | Graph container, describe/observe, snapshot, persistence |
| src/patterns/ | Orchestration, messaging, memory, AI, CQRS, reactive layout |
| src/compat/ | Framework adapters (React, Vue, Svelte, Solid, NestJS) |
| docs/ | Roadmap, guidance, benchmarks |
| website/ | Astro + Starlight docs site (graphrefly.dev) |
Scripts
pnpm test # vitest run
pnpm run lint # biome check
pnpm run build # tsup (ESM + CJS + .d.ts)
pnpm bench # vitest benchAcknowledgments
GraphReFly builds on ideas from many projects and papers:
Protocol & predecessor:
- Callbag (Andre Staltz) — the original reactive protocol spec. GraphReFly's message-based node communication descends from callbag's function-calling-function model.
- callbag-recharge — GraphReFly's direct predecessor. 170+ modules, 4 architecture iterations, and 30 engineering blog posts that shaped every design decision.
Reactive design patterns:
- SolidJS — two-phase execution (DIRTY propagation + value flow), automatic caching, and effect batching. Identified as the closest philosophical neighbor during design research.
- Preact Signals — fine-grained reactivity and cached-flag optimization patterns that informed RESOLVED signal design.
- TC39 Signals Proposal — the
.get()/.set()contract and the push toward language-level reactivity that clarified where signals end and graphs begin. - RxJS — operator naming conventions (aliases like
combineLatest,mergeMap,catchError) and the DevTools observability philosophy that inspired the Inspector pattern.
AI & memory:
- OpenViking (Volcengine) — the memory decay formula (
sigmoid(log1p(count)) * exp_decay(age, 7d)) and L0/L1/L2 progressive loading strategy used inagentMemory(). - FadeMem (Wei et al., ICASSP 2026) — biologically-inspired dual-layer memory with adaptive exponential decay, validating the decay approach independently.
- MAGMA (Jiang et al., 2026) — four-parallel-graph model (semantic/temporal/causal/entity) that informed
knowledgeGraph()design. - Letta/MemGPT, Mem0, Zep/Graphiti, Cognee — production memory architectures surveyed during
agentMemory()design.
Layout & other:
- Pretext (Cheng Lou) — inspired the reactive layout engine's DOM-free text measurement pipeline, rebuilt as a
state -> derivedgraph. - CASL — declarative
allow()/deny()policy builder DX that inspiredpolicy(), though CASL itself was rejected as a dependency. - Nanostores — tiny framework-agnostic API with near 1:1
.get()/.set()/.subscribe()mapping that validated the store ergonomics.
