Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.
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Simple, unified interface to multiple Generative AI providers
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
Multi-Agent Harness for Production AI
RSI-Anything: Unlocking Recursive Self-Improvement with World Models
- jepa
- llm-agents
- recursive-self-improvement
- world-models
A framework for continual learning and recursive self-improvement through harness adapter evolution.
A unified framework for building, evaluating, and recursively improving embodied agents. 🚀 Code release coming soon.
Scikit-learn for Recursive Self-improvement (RSI). A modular framework for recursive harness evolution.
- meta-learning
- reinforcement-learning
- rsi
- ai-agents
Go AI SDK, the Go way. One unified API across 21+ providers. Streaming, structured output, MCP support, stdlib only. Go AI SDK for AI applications inspired by Vercel AI SDK.
Multi-agent orchestration & workflow engine. Declarative YAML workflows, LLM coordinator with hub-and-spoke mailboxes, race-safe delivery. One YAML file, one Go binary. Runs on any goai-supported provider.
A Go toolkit for building AI agents and applications across multiple providers. Unified LLM client, agent framework with handoffs, tool calling, streaming, structured output, MCP integration, and cost tracking.
- ai
- golang
- llm
- structured-output
The production agent framework for Go — type-safe agents, structured output, multi-provider streaming, guardrails, and multi-agent orchestration with zero core dependencies.
a powerful framework providing a domain-specific language (DSL) for complex knowledge processing and LLM integration. using like hiccup and reagent