Letta v0.6.4 release
We just released Letta 0.6.4, which adds for 🐍 Python 3.13 support and a TypeScript SDK (alpha build)!
The TS SDK is in early alpha, and can be downloaded on npm via @letta-ai/letta:
npm i @letta-ai/letta@0.1.0-alpha.5
The Letta TS client makes it easy to create agents, message them, and render their responses:
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For the full release notes, see our GitHub releases:
Traditional LLMs operate in a stateless paradigm—each interaction exists in isolation, with no knowledge carried forward from previous conversations. Agent memory solves this problem.
As AI agents become more sophisticated, understanding how to design and manage their context windows (via context engineering) has become crucial for developers.
Memory blocks offer an elegant abstraction for context window management. By structuring the context into discrete, functional units, we can give LLM agents more consistent, usable memory.
Although RAG provides a way to connect LLMs and agents to more data than what can fit into context, traditional RAG is insufficient for building agent memory.
Introducing “stateful agents”: AI systems that maintain persistent memory and actually learn during deployment, not just during training.
Introducing Letta's new agent architecture, optimized for frontier reasoning models.
Letta agents can now take full advantage of Sonnet 4.5’s advanced memory tool capabilities to dynamically manage their own memory blocks.
Today we're announcing Letta Filesystem, which provides an interface for agents to organize and reference content from documents like PDFs, transcripts, documentation, and more.
We've releasing new client SDKs (support for TypeScript and Python) and upgraded developer documentation
Introducing Agent File (.af): An open file format for serializing stateful agents with persistent memory and behavior.
Introducing the Letta Agent Development Environment (ADE): Agents as Context + Tools
Letta v0.5.2 adds tool rules, which allows you to constrain the behavior of your Letta agents similar to graphs.
Letta v0.5.1 adds support for auto-loading entire external tool libraries into your Letta server.
We're excited to announce Recovery-Bench, a benchmark and evaluation method for measuring how well agents can recover from errors and corrupted states.
Letta Filesystem scores 74.0% of the LoCoMo benchmark by simply storing conversational histories in a file, beating out specialized memory tool libraries.
We built the #1 open-source agent for terminal use, achieving 42.5% overall score on Terminal-Bench ranking 4th overall and 2nd among agents using Claude 4 Sonnet.
