MemoryWell Beta Kit

curl -X POST https://app.base44.com/api/apps/YOUR_APP_ID/functions/mwStoreMemory \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "content": "This is my first MemoryWell memory. Hello world.",
    "metadata": { "name": "First Memory", "source": "curl-test" }
  }'

# Your App ID: 68fd7f06eefc7c2e6c12ec5e

// MemoryWell SDK — Golden Path
// Store → List → Search in ~20 lines

const BASE_URL = "https://app.base44.com/api/apps/68fd7f06eefc7c2e6c12ec5e/functions";
const API_KEY = "your-api-key";

const mw = async (fn, body) => {
  const res = await fetch(`${BASE_URL}/${fn}`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "Authorization": `Bearer ${API_KEY}`
    },
    body: JSON.stringify(body)
  });
  return res.json();
};

// 1. Store a memory
const stored = await mw("mwStoreMemory", {
  content: "We discussed building a persistent memory layer for AI apps.",
  metadata: { name: "Architecture Chat", source: "my-app" }
});
console.log("Stored:", stored.memory_id);

// 2. List recent memories
const list = await mw("mwListMemories", { tiers: ["WARM"], limit: 10 });
console.log("Memories:", list.count);

// 3. Recall full content
const memory = await mw("mwRecallMemory", { memory_id: stored.memory_id });
console.log("Recalled:", memory.conversation);

// 4. Semantic search
const results = await mw("mwSearchMemories", {
  query: "persistent memory for AI",
  limit: 5
});
console.log("Search results:", results.results);

// BEFORE each AI response — inject relevant memories as context
async function getMemoryContext(userMessage) {
  const relevant = await mw("mwSearchMemories", {
    query: userMessage,
    limit: 5
  });
  return relevant.results
    .filter(r => r.score > 0.7)
    .map(r => r.bottle_name)
    .join("\n");
}

// AFTER each AI response — store the conversation
async function saveConversation(userMessage, aiResponse) {
  await mw("mwStoreMemory", {
    content: `User: ${userMessage}\nAssistant: ${aiResponse}`,
    metadata: { name: `Chat ${new Date().toLocaleDateString()}`, source: "my-chatbot" }
  });
}

// In your chat handler:
const context = await getMemoryContext(userInput);
const systemPrompt = `You are a helpful assistant.
Relevant past context:\n${context}`;

const aiResponse = await callYourLLM(systemPrompt, userInput);
await saveConversation(userInput, aiResponse);