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letta-ai/letta

📈 Trending22,790PythonAudience · developerComplexity · 3/5ActiveLicenseSetup · moderate

TLDR

AI agent platform where agents remember past conversations and learn over time through persistent memory blocks, enabling assistants that improve with each interaction.

Mindmap

mindmap
  root((Letta))
    What it does
      Persistent agent memory
      Cross-session learning
      Memory block system
    How to use
      Python SDK
      TypeScript SDK
      REST API
    Use cases
      Personal coding assistant
      Customer support bot
      AI companion
    Tech stack
      Python backend
      Model-agnostic
      CLI tool

Things people build with this

USE CASE 1

Build a personal coding assistant that remembers your coding style and past projects across sessions.

USE CASE 2

Create a customer support bot that recalls ticket history and customer preferences to provide better service.

USE CASE 3

Develop an AI companion that learns about the user's interests and personality over time.

USE CASE 4

Run a local AI agent in your terminal that maintains context and improves from repeated interactions.

Tech stack

PythonTypeScriptNode.jsREST API

Getting it running

Difficulty · moderate Time to first run · 30min

Requires setting up a persistent memory backend (likely database) and configuring API endpoints before agents can demonstrate learning behavior.

Use freely for any purpose including commercial. Keep the notice and disclose changes to the patent grant.

In plain English

Letta (formerly known as MemGPT) is a platform for building AI agents that have persistent memory, meaning they can remember past conversations, learn from interactions, and improve over time rather than starting fresh with every session. Most AI chatbots forget everything the moment a conversation ends; Letta solves that problem by giving agents a memory system that persists across sessions. The way it works is you create an agent through the Letta API or SDK, define what it should know about itself and the people it talks to using "memory blocks" (basically named notes the agent can read and update), and then send messages to it. The agent reads and writes to its memory as it works, so future conversations can build on earlier ones. You would use Letta when building an AI assistant that needs to know who you are across multiple sessions, for example, a personal coding assistant, a customer support bot that remembers ticket history, or an AI companion. It can also run locally in your terminal via a command-line tool. Letta is written in Python and supports both Python and TypeScript/Node.js SDKs. It works with any AI model (model-agnostic) and exposes a REST API for integration into applications.

Copy-paste prompts

Prompt 1
How do I set up a Letta agent using the Python SDK that remembers user preferences across conversations?
Prompt 2
Show me how to define memory blocks for an AI customer support agent using Letta's API.
Prompt 3
I want to build a coding assistant with Letta that learns my coding patterns, what's the quickest way to get started?
Prompt 4
How do I integrate Letta into my application using the REST API instead of the SDK?
Prompt 5
Can you walk me through running a Letta agent locally via the command-line tool?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.