OpenAI API

The user’s memory behind the OpenAI API or any function-calling model: declare search_memories and add_memory as functions and call the SDK when the model asks.

Everything below assumes MEMBASE_API_KEY in the environment, minted at Read & write with Your profile ticked (Authentication & Scopes), and your model provider’s key beside it. The loop is the same in every harness:

The tool-calling loop

Declare the two verbs as functions and call the SDK when the model asks. The shape is the Chat Completions tool-calling loop; any provider with the same loop takes the same two definitions.

import OpenAI from "openai";
import { Membase } from "membase-sdk";

const memory = new Membase();
const openai = new OpenAI();

const tools: OpenAI.Chat.Completions.ChatCompletionTool[] = [
  { type: "function", function: {
      name: "search_memories",
      description: "Search the user's memory. Use it before answering anything about their past work, decisions or preferences.",
      parameters: { type: "object", properties: { q: { type: "string" } }, required: ["q"] } } },
  { type: "function", function: {
      name: "add_memory",
      description: "Save one fact the user asked to remember, in their own words.",
      parameters: { type: "object", properties: { content: { type: "string" } }, required: ["content"] } } },
];

async function runTool(name: string, args: Record<string, string>): Promise<string> {
  if (name === "search_memories") {
    const { results } = await memory.search({ q: args.q, limit: 5 });
    return JSON.stringify(results.map((h) => ({ memory: h.container_name, content: h.content })));
  }
  await memory.memories.add({ content: args.content });
  return "saved";
}

const profile = await memory.profile();
const messages: OpenAI.Chat.Completions.ChatCompletionMessageParam[] = [
  { role: "system", content: "Standing facts about the user: " + profile.static.join("; ") },
  { role: "user", content: "What did we decide about the ledger?" },
];

for (;;) {
  const turn = await openai.chat.completions.create({ model: process.env.OPENAI_MODEL!, messages, tools });
  const reply = turn.choices[0].message;
  messages.push(reply);
  if (!reply.tool_calls?.length) { console.log(reply.content); break; }
  for (const call of reply.tool_calls) {
    if (call.type !== "function") continue;          // tool_calls is a union; custom tool calls carry no `function`
    const content = await runTool(call.function.name, JSON.parse(call.function.arguments));
    messages.push({ role: "tool", tool_call_id: call.id, content });
  }
}

The same loop in Python is the SDK’s client.search(...) and client.memories.add(...) behind two function definitions; nothing else changes.

Rules that hold in every shape

• Profile once, search per question. The profile is small and standing; search is a turn inside the user’s container.
• Cite the container. Every hit names container_name; say where an answer came from.
• Save what the user supplied, in their words, and only when they asked or plainly meant to.
• Never confirm on your own. A delete or forget without confirm=true answers with a how sentence; relay it and stop.
• Treat 403 as withdrawn access. The owner narrowed or revoked the key; do not retry with it.
• Expect the first search to be slow. Up to a minute after a quiet spell; keep the SDK’s timeout.

The same rules, with the reasons, are on Memory operations.