“building AI agents”

Rails framework for building AI agents as controllers, with provider gems for OpenAI, Anthropic, Ollama and more.

Kubernetes-native framework and runtime for building and running AI agents as Kubernetes custom resources.

TypeScript toolkit for AI apps and agents with a unified provider API, streaming, UI hooks and a wrapper for running established agent harnesses.

Go framework for AI agents with memory, tool execution, MCP, agent skills, multi-agent patterns and evaluation.

Low-code Python framework for YAML-defined agents and multi-agent Cogs, with personas, prompt templates and memory nodes.

TypeScript framework for AI agents and apps with graph-based workflows, memory, suspend-and-resume approvals, MCP servers and model routing.

Kotlin and Java framework for AI agents with tools, graph workflows, MCP, streaming and multiplatform targets.

Opinionated agent harness on LangGraph with sub-agents, filesystem access, context management, persistent memory and approval of tool calls.

Java framework for agentic, workflow and multi-agent AI apps, with graph workflows, MCP and A2A support.

Lightweight Python framework for composing AI agents and tools as small, typed pieces built on Instructor and Pydantic.

C# framework on .NET for building multi-agent AI bots with plugins, RAG, MCP integration and a built-in admin UI.

Python framework for LLM agents that run as durable Dapr workflows, with retries, Kubernetes deployment and human-in-the-loop hooks.

Code-first Java toolkit for building and testing AI agents, with multi-agent hierarchies, a dev UI and Maven packages.

Typed Python SDK for building agents with swappable model providers, plus optional capabilities for memory, sub-agents, planning and durable execution.

Managed Microsoft Foundry service for building, deploying and scaling AI agents, with a Python client library on PyPI.

Open framework for building and hosting production-grade AI agents and multi-agent workflows in .NET and Python.

TypeScript platform to build and deploy long-running AI agents and workflows with retries, queues and human approval steps.

Rust multi-agent framework with typed tool calling, sliding-window memory, pluggable LLM backends and OpenTelemetry tracing.

Open-source toolkit for building, evaluating and deploying agents in Python, TypeScript, Go, Java and Kotlin, tuned for Gemini but model-agnostic.

Open-source agent harness for stateful agents whose memory persists and improves with use, with a terminal UI, app server and TypeScript SDK.

Open-source Python framework for AI agents that cooperate on tasks, with human-in-the-loop workflows and multi-agent patterns.

Python framework of interoperable components and integrations for building agents and LLM apps, with LangGraph and Deep Agents layered above it.

Python multi-agent framework with PEER and DOE collaboration patterns and configurable LLM vendors such as Qwen, DeepSeek and OpenAI.

Open-source agent harness from LangChain for building agents with code, with LangSmith for testing and monitoring.