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Letta (formerly MemGPT)

Letta (formerly MemGPT) is a platform for building stateful agents that maintain advanced memory, learn over time, and self-improve. It provides APIs and SDKs (Python & TypeScript), supports multiple model providers (OpenAI, Anthropic, Google, etc.), built-in tools (web search, run_code), persisted memory blocks, and options for hosted or self-hosted deployments.

Introduction

Letta (formerly MemGPT) is an open-source platform and developer ecosystem designed to build stateful AI agents — systems that keep persistent memory across sessions, learn from interactions, and improve their behavior over time.

Key features and concepts:

  • Memory-first architecture: Letta organizes agent state as memory blocks (labeled units of stored context such as persona, user profile, conversation history, facts). These memory blocks allow agents to recall and update long-term information across sessions.
  • Multi-provider model support: Letta is model-agnostic and can work with various model providers and embeddings (examples in documentation include OpenAI, Anthropic, Google Gemini), so developers can pick providers or switch between them.
  • SDKs & API: Official client libraries for TypeScript/Node.js and Python (npm package @letta-ai/letta-client and pip package letta-client) plus a REST API allow easy integration into applications and services.
  • Tools & integrations: Built-in tool support (examples: web_search, run_code) lets agents consult external tools during reasoning. Letta Code provides a memory-first coding harness to interact with persisted agents from the CLI.
  • Deployment options: Letta offers a hosted developer platform and documentation for self-hosting a Letta server, enabling privacy-sensitive or on-premises deployments.
  • Developer ecosystem: Extensive docs (quickstart, API reference, tutorials), an active OSS repo with many contributors, community channels (Discord, forum, social links) and examples to accelerate adoption.

Typical use cases:

  • Personal assistants and chatbots that must remember user preferences, past interactions, and long-term context.
  • Autonomous agents that learn from feedback and improve workflows over time.
  • Applications that combine multiple tools and external data sources while preserving state across conversations.

Getting started (high-level):

  1. Install the client: npm install @letta-ai/letta-client or pip install letta-client.
  2. Create an agent via the Letta API specifying a model, embedding, memory_blocks, and tools.
  3. Send messages to the agent and let it use memory blocks and tools to maintain state.
  4. Optionally self-host Letta for full control or use the Letta hosted platform for faster setup.

Licensing & community: Letta is an open-source project maintained by the letta-ai organization on GitHub, with community contributions, Discord/forum support, and public docs. The project emphasizes memory-first agent design to enable persistent, improvable AI behaviors.

(Technical note: repository metadata shows the project was created in October 2023 and includes examples for both TypeScript and Python clients, plus references to Letta Code and documentation at docs.letta.com.)

Information

  • Websitegithub.com
  • AuthorsLetta (letta-ai)
  • Published date2023/10/11

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