The memory fabric for enterprise AI

Memori plugs into the software and infrastructure you already use. It is LLM, datastore and framework agnostic and seamlessly integrates into the architecture you've already designed.

→ Memori Cloud — Zero config. Get an API key and start building in minutes.

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Getting Started

Installation

TypeScript SDK

npm install @memorilabs/memori

Python SDK

pip install memori

Quickstart

Sign up at app.memorilabs.ai, get a Memori API key, and start building. Full docs: memorilabs.ai/docs/memori-cloud/.

Set MEMORI_API_KEY and your LLM API key (e.g. OPENAI_API_KEY), then:

TypeScript SDK

import { OpenAI } from 'openai';
import { Memori } from '@memorilabs/memori';

// Requires MEMORI_API_KEY and OPENAI_API_KEY in your environment
const client = new OpenAI();
const mem = new Memori().llm
  .register(client)
  .attribution('user_123', 'support_agent');

async function main() {
  await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [{ role: 'user', content: 'My favorite color is blue.' }],
  });
  // Conversations are persisted and recalled automatically in the background.

  const response = await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [{ role: 'user', content: "What's my favorite color?" }],
  });
  // Memori recalls that your favorite color is blue.
}

Python SDK

from memori import Memori
from openai import OpenAI

# Requires MEMORI_API_KEY and OPENAI_API_KEY in your environment
client = OpenAI()
mem = Memori().llm.register(client)

mem.attribution(entity_id="user_123", process_id="support_agent")

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "My favorite color is blue."}]
)
# Conversations are persisted and recalled automatically.

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "What's my favorite color?"}]
)
# Memori recalls that your favorite color is blue.

Explore the Memories

Use the Dashboard — Memories, Analytics, Playground, and API Keys.

Tip

Want to use your own database? Check out docs for Memori BYODB here: https://memorilabs.ai/docs/memori-byodb/.

Attribution

To get the most out of Memori, you want to attribute your LLM interactions to an entity (think person, place or thing; like a user) and a process (think your agent, LLM interaction or program).

If you do not provide any attribution, Memori cannot make memories for you.

TypeScript SDK

mem.attribution("12345", "my-ai-bot");

Python SDK

mem.attribution(entity_id="12345", process_id="my-ai-bot")

Session Management

Memori uses sessions to group your LLM interactions together. For example, if you have an agent that executes multiple steps you want those to be recorded in a single session.

By default, Memori handles setting the session for you but you can start a new session or override the session by executing the following:

TypeScript SDK

mem.resetSession();
# or
mem.setSession(sessionId);

Python SDK

mem.new_session()
# or
mem.set_session(session_id)

Supported LLMs

• Anthropic
• Bedrock
• DeepSeek
• Gemini
• Grok (xAI)
• OpenAI (Chat Completions & Responses API)

(unstreamed, streamed, synchronous and asynchronous)

Supported Frameworks

• Agno
• LangChain
• Pydantic AI

Supported Platforms

• DeepSeek
• Nebius AI Studio

Examples

For more examples and demos, check out the Memori Cookbook.

Memori Advanced Augmentation

Memories are tracked at several different levels:

• entity: think person, place, or thing; like a user
• process: think your agent, LLM interaction or program
• session: the current interactions between the entity, process and the LLM

Memori's Advanced Augmentation enhances memories at each of these levels with:

• attributes
• events
• facts
• people
• preferences
• relationships
• rules
• skills

Memori knows who your user is, what tasks your agent handles and creates unparalleled context between the two. Augmentation occurs in the background incurring no latency.

By default, Memori Advanced Augmentation is available without an account but rate limited. When you need increased limits, sign up for Memori Advanced Augmentation or use the Memori CLI:

# Install the CLI via pip to manage your account
python -m memori sign-up <email_address>

Memori Advanced Augmentation is always free for developers!

Once you've obtained an API key, set the following environment variable (used by both Python and TypeScript SDKs):

export MEMORI_API_KEY=[api_key]

Managing Your Quota

At any time, you can check your quota using the Memori CLI (works for both SDKs):

python -m memori quota

Or by checking your account at https://app.memorilabs.ai/. If you have reached your IP address quota, sign up and get an API key for increased limits.

If your API key exceeds its quota limits we will email you and let you know.

Command Line Interface (CLI)

The Memori CLI is the unified tool for managing your account, keys, and quotas across all SDKs. To use it, execute the following from the command line:

# Requires Python installed
python -m memori

This will display a menu of the available options. For more information about what you can do with the Memori CLI, please reference Command Line Interface.

Contributing

We welcome contributions from the community! Please see our Contributing Guidelines for details on:

• Setting up your development environment
• Code style and standards
• Submitting pull requests
• Reporting issues

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Support

• Memori Cloud Documentation: memorilabs.ai/docs/memori-cloud/
• Memori BYODB Documentation: https://memorilabs.ai/docs/memori-byodb/
• Discord: https://discord.gg/abD4eGym6v
• Issues: GitHub Issues

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License

Apache 2.0 - see LICENSE