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Welcome to Letta

Letta adds state to your LLMs to give them advanced reasoning capabilities and transparent long-term memory.

The Letta open source framework is model-agnostic and white box: as a developer, you can use any LLM you want and have full visibility into the inner workings your LLMs and LLM agents.

Letta runs as a service: to use Letta, you deploy a Letta server which powers your AI application (web app, mobile app, Discord bot, workflow, etc.). Your application state and LLM calls are managed by the Letta server, and your frontend application connects to the Letta server via the Letta REST APIs.

Letta enables you to build advanced agents compatible with any model. Letta agents have long-term memory, which is highly configurable and can even be shared between different agents.

Letta is for developers building stateful LLM applications that require advanced memory, such as:

  • personalized chatbots that require long-term memory and personas that should be updated (self-edited) over time (e.g. companions)
  • agents connected to external data sources, e.g. private enterprise deployments of ChatGPT-like applications (connected to your company’s data), or a medical assistant connected to a patient’s medical records
  • agents connected to custom tools, e.g. a chatbot that can answer questions about the latest news by searching the web
  • automated AI workflows, e.g. an agent that monitors your email inbox and sends you text alerts for urgent emails and a daily email summary

… and countless other use cases!

The ADE is a graphical user interface for creating, deploying, interacting with and observing your Letta agents.

The Letta ADE is web application that allows you to create, edit, and monitor agents in your Letta server. You can connect the ADE to your local Letta server, or to a Letta server running on a remote server. For more information, see the Agent Development Environment page.

The Letta server exposes a REST API that allows you to programatically interact with your Letta agents. You can use the API to deploy agents with long-term memory, custom tools, access to external data sources (RAG), multi-step reasoning, and more.

If you’re building an application in Python, you can use the Letta Python SDK to interact with Letta (instead of calling REST APIs directly) for a more seamless experience.

If you’re new to Letta, start by learning the key concepts - or jump straight into creating your first agent!

Check out our YouTube channel for more tutorials. If you have an idea for a tutorial, let us know by suggesting an idea on Discord!