Harnesses & SDKs

Python framework that models an application as a state machine, with a trace UI and persisted state.

Python framework for LLM apps built from collaborating agents that hold conversation state, tools and vector-store memory.

Python library that turns files in S3, GCS and Azure into versioned, typed datasets for pipelines and agents.

Python agent runtime with an SDK for building your own agent, and an app that adds plugins and channel integrations.

TypeScript agent framework with persistent cognitive memory, multi-agent orchestration and one dispatch interface across 13 LLM providers.

Ruby library for LLM-powered apps with a unified LLM interface, prompt tools, output parsers, RAG and assistants.

Python library for autonomous agents that run scheduled tasks and exchange messages on the Fetch.ai network.

Python framework for real-time voice and vision agents that process video with pluggable models and processors over WebRTC.

The batteries included agent harness.

Python runtime and framework for long-running agents, with durable sessions, approvals, spend caps and multi-agent collaboration.

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

Open-source infrastructure for continually self-improving agents that serves requests, learns from feedback and versions updates.

Reliability layer for tool calling with self-hosted LLMs, offered as a proxy, a workflow runner and middleware.

Open-source Python evaluation framework with ready-made and custom graders for scoring AI agent quality and producing reward signals.

Python library of 35 agentic AI architectures with one run() interface, built on LangGraph and multiple LLM providers.

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

Rust framework with an agent harness, typed task graphs and streaming indexing and RAG pipelines for LLM applications.

Python framework for durable AI agents built as dataflows that resume after crashes, retry safely and record each step.

Open agent harness for AI applications, with a YAML-configured coding agent, sessions, tools, MCP support and a CLI.

Python agent framework for OpenAI-compatible agents with tools, memory, MCP connections, multi-agent collaboration and workflows.

Python library for steering language models by constraining output with regex and grammars and mixing control flow with generation.

Python platform that gives agents a cryptographic identity, A2A communication and x402 payment requirements behind one bindufy() call.

Framework for AI agents and multi-agent networks where a router picks which agent runs, with tools and MCP support.

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