Production Features

import { Agent, openai, anthropic, google, withFallback, EventBus } from "@agentium/core";

const eventBus = new EventBus();
eventBus.on("model.fallback", ({ from, to }) => {
  console.log(`Fallback: ${from} → ${to}`);
});

const resilientModel = withFallback(
  [openai("gpt-4o"), anthropic("claude-sonnet-4-20250514"), google("gemini-2.5-flash")],
  {
    circuitBreaker: { failureThreshold: 3, cooldownMs: 30_000 },
    onFallback: (from, to, error) => {
      eventBus.emit("model.fallback", { from, to, error: String(error) });
    },
  },
);

const agent = new Agent({
  name: "resilient-agent",
  model: resilientModel,
  instructions: "You are a helpful assistant.",
  eventBus,
});

const result = await agent.run("What is the capital of France?");

import { Agent, openai, ModelRouter } from "@agentium/core";

const router = new ModelRouter({
  tiers: [
    { model: openai("gpt-4o-mini"), maxComplexity: 0.3 },
    { model: openai("gpt-4o"), maxComplexity: 0.7 },
    { model: openai("o3"), maxComplexity: 1.0 },
  ],
  outcomeTracking: true,
});

const agent = new Agent({ name: "smart-agent", model: router });
// Simple queries → gpt-4o-mini, complex → gpt-4o, reasoning → o3

import { Agent, openai } from "@agentium/core";

const agent = new Agent({
  name: "reflective-agent",
  model: openai("gpt-4o"),
  reflection: {
    enabled: true,
    maxReflections: 2,
    loopEscapeDetection: true,
    postMortemLearning: true,
  },
});

import { ABRouter, VersionStore, InMemoryStorage } from "@agentium/core";

const store = new VersionStore(new InMemoryStorage());
const v1 = await store.save({ agentName: "support", instructions: "Be concise", ... });
const v2 = await store.save({ agentName: "support", instructions: "Be warm", ... });

const router = new ABRouter({
  name: "instructions-test",
  control: { agentName: "support", versionId: v1.versionId },
  variant: { agentName: "support", versionId: v2.versionId },
  trafficSplit: 0.2,
  routing: "user",
  autoRollback: { errorRateThreshold: 0.15, windowMs: 300_000 },
});

import { AuditLogger, ComplianceReporter, InMemoryStorage } from "@agentium/core";

const logger = new AuditLogger(new InMemoryStorage());
await logger.log({
  traceId: "run-001",
  agentName: "support-agent",
  action: "llm.call",
  userId: "user-123",
  input: "How do I reset my password?",
  output: "Go to Settings > Security...",
});

const { valid } = await logger.verify(); // Verify hash chain

import { TenantScopedStorage, InMemoryStorage } from "@agentium/core";

const base = new InMemoryStorage();
const acme = new TenantScopedStorage(base, "acme");
const globex = new TenantScopedStorage(base, "globex");

await acme.set("sessions", "s1", { user: "alice" });
await globex.set("sessions", "s1", { user: "bob" });
// Same key, completely isolated data

import { TokenRateLimiter, ConcurrencyLimiter } from "@agentium/core";

const limiter = new TokenRateLimiter({
  maxTokensPerMinute: 100_000,
  perTenant: true,
});

const status = limiter.acquire(500, { tenantId: "acme" });
// { allowed: true, remaining: 99500, resetMs: 58000 }

import { Agent, AgentScheduler, openai } from "@agentium/core";

const scheduler = new AgentScheduler(eventBus);
scheduler.schedule(agent, {
  cron: "0 9 * * *",
  input: "Generate today's report.",
  contextContinuity: true,
});

scheduler.trigger(agent, {
  event: "run.error",
  input: (data) => `Error: ${data.error.message}. Investigate.`,
  debounceMs: 60_000,
});

import { ConversationSuite } from "@agentium/eval";

const suite = new ConversationSuite({
  name: "Support Tests",
  scenarios: [{
    name: "Password Reset",
    persona: { name: "Jane", description: "Non-technical user", goal: "Reset password" },
    initialMessage: "I can't log in!",
    expectedTrajectory: { requiredTools: ["send_reset_email"] },
  }],
}, openai("gpt-4o-mini"));

const results = await suite.run(agent);

import { ContextCurator } from "@agentium/core";

const curator = new ContextCurator({
  enabled: true,
  failedResultHandling: "deprioritize",
  relevanceDecay: { enabled: true, halfLifeTurns: 10, minWeight: 0.1 },
});

const cleaned = curator.curate(messages, currentQuery);

import { estimateProgress, toolResultPreview } from "@agentium/core";

// Estimate progress based on roundtrip count
const percent = estimateProgress(2, 10, "tools"); // ~25%

// Generate concise previews for long tool results
const preview = toolResultPreview(longResult, 100);