AI Memory — Persistent Memory for AI Agents & Applications

from zerodb import ZeroDB

db = ZeroDB(api_key="zdb_...", project_id="your-project")

# Store a memory
db.memory.remember(
    user_id="user_123",
    session_id="session_abc",
    content="Alice prefers dark mode and uses Neovim as her editor.",
    metadata={
        "source": "conversation",
        "importance": 0.85,
        "tags": ["preferences", "tooling"],
    },
)

# Recall relevant memories for the current query
results = db.memory.recall(
    user_id="user_123",
    query="What editor setup should I recommend?",
    limit=5,
)

for memory in results:
    print(f"[{memory.score:.2f}] {memory.content}")
# [0.93] Alice prefers dark mode and uses Neovim as her editor.

# Reflect: synthesize recent memories into higher-order summaries
summary = db.memory.reflect(
    user_id="user_123",
    lookback_hours=24,
    strategy="summarize",  # or "extract_entities", "update_graph"
)

print(summary.insights)
# [
#   "Alice is working on a billing refactor and prefers Python.",
#   "Alice uses Neovim, prefers dark mode, and values clean code.",
#   "Alice has blocked on the Stripe webhook integration since yesterday.",
# ]

import { ZeroDB } from 'zerodb';

const db = new ZeroDB({ apiKey: 'zdb_...', projectId: 'your-project' });

// Get a structured profile of everything ZeroMemory knows about a user
const profile = await db.memory.profile({ userId: 'user_123' });

console.log(profile);
// {
//   preferences: { editor: 'Neovim', theme: 'dark', language: 'Python' },
//   currentProjects: ['billing-refactor', 'auth-service'],
//   recentBlockers: ['Stripe webhook validation'],
//   communicationStyle: 'concise, prefers code over prose',
// }