Multi-Turn Chat and Conversation Memory with the Claude API

import Anthropic from "@anthropic-ai/sdk";
 
export const anthropic = new Anthropic({ timeout: 60_000, maxRetries: 2 });
export const MODEL = "claude-opus-5-5";

import { createInterface } from "node:readline/promises";
import type Anthropic from "@anthropic-ai/sdk";
import { anthropic, MODEL } from "./lib/anthropic.ts";
 
const rl = createInterface({ input: process.stdin, output: process.stdout });
const messages: Anthropic.MessageParam[] = [];
console.log('Chat with the model. Type "exit" to quit.');
 
while (true) {
  const input = (await rl.question("\nyou › ")).trim();
  if (!input || input === "exit") break;
 
  messages.push({ role: "user", content: input });
  const response = await anthropic.messages.create({
    model: MODEL,
    max_tokens: 4096,
    output_config: { effort: "low" },
    system: "You are a friendly, concise assistant.",
    messages,
  });
  messages.push({ role: "assistant", content: response.content }); // store the blocks, not just the text
 
  const text = response.content.flatMap((b) => (b.type === "text" ? [b.text] : [])).join("");
  console.log(`\nassistant › ${text}`);
  console.log(`  (${messages.length} messages so far, ${response.usage.input_tokens} input tokens this turn)`);
}
rl.close();

import type Anthropic from "@anthropic-ai/sdk";
import { anthropic, MODEL } from "./anthropic.ts";
 
const textOf = (m: Anthropic.MessageParam) =>
  typeof m.content === "string" ? m.content : m.content.flatMap((b) => (b.type === "text" ? [b.text] : [])).join(" ");
 
const isToolResultTurn = (m: Anthropic.MessageParam) =>
  m.role === "user" && Array.isArray(m.content) && m.content.some((b) => b.type === "tool_result");
 
/** Keep roughly the last `keep` messages, starting at a real user turn so tool_use/tool_result pairs stay together. */
export function slidingWindow(messages: Anthropic.MessageParam[], keep: number): Anthropic.MessageParam[] {
  if (messages.length <= keep) return messages;
  let start = messages.length - keep;
  while (start < messages.length && (messages[start].role !== "user" || isToolResultTurn(messages[start]))) start++;
  return messages.slice(start);
}
 
/** Replace older turns with a short summary, keeping recent turns verbatim. */
export async function compactHistory(messages: Anthropic.MessageParam[], keepRecent = 6): Promise<Anthropic.MessageParam[]> {
  const recent = slidingWindow(messages, keepRecent);
  const older = messages.slice(0, messages.length - recent.length);
  if (older.length === 0) return messages;
 
  const summary = await anthropic.messages.create({
    model: MODEL,
    max_tokens: 1024,
    output_config: { effort: "low" },
    system:
      "Summarize this conversation for your own future reference. Keep names, decisions, user preferences, " +
      "facts the user shared, and open questions. Write under 150 words.",
    messages: [{ role: "user", content: older.map((m) => `${m.role}: ${textOf(m)}`).join("\n") }],
  });
  const text = summary.content.flatMap((b) => (b.type === "text" ? [b.text] : [])).join("");
 
  // A user turn holding the summary, then the recent turns (which also start with a user turn; the two are merged).
  return [{ role: "user", content: `Summary of our earlier conversation:\n${text}` }, ...recent];
}

import Anthropic from "@anthropic-ai/sdk";
 
const client = new Anthropic();
const messages: Anthropic.Beta.BetaMessageParam[] = [];
 
async function chat(userMessage: string): Promise<string> {
  messages.push({ role: "user", content: userMessage });
  const response = await client.beta.messages.create({
    betas: ["compact-2026-01-12"],
    model: "claude-opus-5-5",
    max_tokens: 16000,
    messages,
    context_management: { edits: [{ type: "compact_20260112" }] },
  });
  messages.push({ role: "assistant", content: response.content }); // keeps compaction blocks
  return response.content.flatMap((b) => (b.type === "text" ? [b.text] : [])).join("");
}
 
console.log(await chat("Help me plan a three-day trip to Lisbon."));
console.log(await chat("Make day two about food markets."));