Letta: Complete Guide 2026
PythonAI Agent Framework12k+ stars
Last updated:
Overview
An open-source framework for building stateful LLM agents with long-term memory. Formerly MemGPT, Letta enables agents that can manage their own memory, learn from interactions, and maintain persistent context across sessions.
Key Features
✓Self-editing long-term memory system
✓Persistent agent state across sessions
✓Memory management with archival and recall
✓Tool use and function calling
✓Multi-agent communication
✓REST API server for production deployment
Use Cases
- → Long-running personal AI assistants
- → Customer service agents with interaction history
- → Research agents that accumulate knowledge
- → Persistent AI companions and tutors
Pros & Cons
Pros
- +Unique memory management approach for long-running agents
- +Agents that learn and adapt over time
- +Production-ready with REST API server
- +Strong research backing from academic origins
Cons
- -Memory system adds complexity to simple use cases
- -Smaller community than mainstream frameworks
- -Opinionated architecture may not fit all patterns
Frequently Asked Questions
What is Letta?▾
An open-source framework for building stateful LLM agents with long-term memory. Formerly MemGPT, Letta enables agents that can manage their own memory, learn from interactions, and maintain persistent context across sessions.
What language is Letta built in?▾
Letta is primarily built in Python.
Is Letta good for production?▾
Letta has 12k+ GitHub stars. Unique memory management approach for long-running agents for long-running personal ai assistants.