Harnesses & SDKs

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

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

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.

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

Python framework for LLM applications built on Qwen models, with function calling, MCP, a code interpreter and RAG options.

Python framework for autonomous agents that work in a sandboxed workspace, and task agents with tools and MCP support.

Python framework for data labeling agents that learn skills from a ground-truth dataset through iterative feedback.

Python framework for MCP-based agents with composable workflow patterns, MCP server creation and Temporal-backed durable execution.

Python multi-agent framework that gives LLM agents software-company roles and SOPs to turn a one-line requirement into a project repository.

Lightweight Python framework for LLM agents built as PyTorch-style layers, with agent memory kept as session state.

Framework for building, running and evaluating autonomous agents, with a planner-based multi-agent mode, skills and agent RL training.