Awesome AI AgentsEnd-to-End Optimizers

statelyai/agent

⭐ 458 TypeScript added to this list on 2025-03-09 repository created 2023-12-21

Stately Expert is a sophisticated framework designed for building AI agents powered by state machines, leveraging the XState library. Unlike traditional large language model (LLM) based agents that rely solely on text generation, Stately Expert enhances agent behavior by incorporating structured state machines to guide decision-making processes. This approach allows agents to utilize observations, message history, and feedback to make more informed and context-aware decisions. The framework supports custom planning capabilities, enabling agents to achieve specific goals through state machine logic combined with real-time observations and feedback. A key feature of Stately Expert is its integration with the Vercel AI SDK, which facilitates support for multiple AI model providers such as OpenAI, Anthropic, Google, Mistral, Groq, and Perplexity. This flexibility allows developers to choose or switch between different models seamlessly. The core concepts of the framework include observations, which track state transitions and metadata; decisions, which are actions taken based on current and goal states along with past experiences; feedback, which serves as rewards or evaluations to improve agent learning; insights, providing additional context to understand cause and effect; and episodes, representing complete sequences of state transitions akin to reinforcement learning episodes. Stately Expert aims to overcome limitations of traditional LLM agents by offering structured decision-making through state machines, enabling agents to learn from experience via feedback and observations, and providing contextual awareness for improved decision quality. The framework supports multiple decision-making policies and optional storage integration for persisting experiences and learning data. Overall, Stately Expert is a powerful tool for developers looking to create intelligent, adaptive AI agents that combine the rigor of state machines with the flexibility of modern AI models, enhancing both decision-making and learning capabilities.

https://github.com/statelyai/agent

agentsaiai-agentsanthropiccontextual-awarenessdecision-makingepisodesfeedbackflexible-policiesgooglegroqinsightslearning-from-experiencellmmessage-historymistralmodel-providersobservationsopenaiperplexityplanningreinforcement-learningstate-machinestate-machinesstatechartstorage-integrationstructured-decision-makingvercel-ai-sdkworkflowxstate

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