for await (const chunk of agent.stream("Tell me a short story.")) {
  if (chunk.type === "text") process.stdout.write(chunk.text);
  if (chunk.type === "finish") console.log("\nDone.", chunk.usage);
}

interface TokenUsage {
  promptTokens: number;
  completionTokens: number;
  totalTokens: number;
  reasoningTokens?: number;
  cachedTokens?: number;
  audioInputTokens?: number;
  audioOutputTokens?: number;
  providerMetrics?: Record<string, unknown>;
}

interface RunMetrics {
  inputTokens: number;
  outputTokens: number;
  totalTokens: number;
  timeToFirstTokenMs?: number;
  durationMs?: number;
}

import {
  Agent, anthropic, CostTracker, MongoDBStorage,
  defineTool, type ContentPart,
} from "@radaros/core";
import { z } from "zod";

const storage = new MongoDBStorage("mongodb://localhost:27017/myapp");
const costTracker = new CostTracker({
  budget: { maxCostPerSession: 2.0, onBudgetExceeded: "warn" },
});

const searchTool = defineTool({
  name: "searchDatabase",
  description: "Search the product database by query",
  parameters: z.object({
    query: z.string().describe("Search query"),
    limit: z.number().optional().describe("Max results (default 10)"),
  }),
  execute: async ({ query, limit }) => {
    const results = await db.search(query, limit ?? 10);
    return JSON.stringify(results);
  },
});

const agent = new Agent({
  name: "product-assistant",
  model: anthropic("claude-sonnet-4-6"),
  instructions: "You help customers find products. Be concise and helpful.",
  tools: [searchTool],

  // Memory: persistent sessions + summaries + user personalization
  memory: {
    storage,
    maxMessages: 20,
    summaries: true,
    userFacts: true,
    userProfile: true,
    model: anthropic("claude-haiku-4-5-20251001"),
  },

  // Tool routing: only send relevant tools to the model
  toolRouter: {
    model: anthropic("claude-haiku-4-5-20251001"),
    maxTools: 5,
  },

  // Tool result limits: summarize large API responses
  toolResultLimit: {
    maxChars: 20000,
    strategy: "summarize",
    model: anthropic("claude-haiku-4-5-20251001"),
  },

  // Extended thinking for complex queries
  reasoning: { enabled: true, budgetTokens: 2000 },

  // Cost tracking with session budget
  costTracker,

  // Lifecycle hooks
  hooks: {
    beforeRun: async (ctx) => {
      console.log(`[${ctx.runId}] Starting run for session ${ctx.sessionId}`);
    },
    afterRun: async (ctx, output) => {
      console.log(`[${ctx.runId}] Completed in ${output.durationMs}ms, ${output.usage.totalTokens} tokens`);
    },
    onError: async (ctx, error) => {
      console.error(`[${ctx.runId}] Error: ${error.message}`);
    },
  },

  logLevel: "info",
  maxToolRoundtrips: 3,
});

const result = await agent.run("Find me wireless headphones under $100", {
  sessionId: "session-abc",
  userId: "user-42",
});

console.log(result.text);
console.log(`Cost: $${costTracker.getSummary().totalCost.toFixed(4)}`);

const agent = new Agent({
  name: "support-bot",
  model: openai("gpt-4o"),
  instructions: (ctx) => {
    const role = ctx.metadata?.role ?? "customer";
    const lang = ctx.metadata?.language ?? "English";
    return `You are a support agent. The user's role is "${role}".
Respond in ${lang}. Be concise and professional.
Session state: ${JSON.stringify(ctx.sessionState)}`;
  },
});

// The instructions function is called fresh on every run
const result = await agent.run("How do I reset my password?", {
  metadata: { role: "admin", language: "Spanish" },
});