{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"}],"enrichment":{"capability":"Letta is a framework for building LLM agents with persistent memory that can learn and improve over time, accessible both as a local CLI tool and through a Python API for integration into applications.","skillfed_tags":["agent-framework","memory-management","llm-integration"],"use_cases":["Build conversational AI assistants that remember user context and preferences across sessions.","Create autonomous agents that can use web search, fetch webpages, and other tools to complete tasks.","Integrate stateful LLM agents into existing applications via the Python SDK with persistent memory.","Develop self-improving agents that learn from interactions and adapt their behavior over time.","Run local AI agents in the terminal for coding assistance and task automation using Letta Code."],"what_it_does":"Letta is a framework for creating AI agents that maintain long-term memory and can be customized with tools and skills. It offers two main entry points: a local CLI tool (Letta Code, installed via npm) that runs agents on your machine, and a Python API (letta-client) for embedding stateful agents into applications. The framework handles agent state management, memory persistence, and tool integration, allowing agents to learn and adapt over time.\n\nThe package itself (letta) is the backend service and core framework, while letta-client is the Python SDK for API interaction. It supports multiple LLM models and is model-agnostic, though the documentation recommends specific models for optimal performance. The dependency footprint is substantial\u201469 runtime packages including integrations with Anthropic, OpenAI embeddings, LlamaIndex, and observability tools like Datadog\u2014reflecting its role as a full-featured agent platform rather than a lightweight library.","worth_installing":"Yes, if you need a production-grade agent framework with memory management and tool integration. The active maintenance, permissive license, and low install friction support adoption. However, the large dependency tree and requirement for an external API key (for the cloud API) or Node.js 18+ (for the CLI) may be friction points. Start with letta-client if you only need the Python SDK; the full letta package is for running the backend service."},"id":"letta","links":{"html":"https://skillfed.io/packages/letta","md":"https://skillfed.io/packages/letta.md","pypi":"https://pypi.org/project/letta/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-14","license_spdx":null,"license_treatment":"permissive","name":"letta","python_support":"supports_current","summary":"Create LLM agents with long-term memory and custom tools"},"popularity":{"monthly_downloads":148733,"position":11020,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.16.8"}