“Python”

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

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

PyTorch-style Python framework for multi-agent, multi-session workflows, with a durable production runtime in v2.0.0.

CLI-first Python agent framework and coding agent with MCP, A2A and Agent Skills support, live streaming and human input.

Python framework for generative AI agents, pipelines and parallel workflows, with RAG engines, tools, memory and swappable drivers.

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

Python framework for structured LLM outputs and agentic workflows built from tasks, agents and threads.

Python framework for orchestrating multiple LLM agents in sequential, concurrent, hierarchical and graph-based workflows.

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

Minimal Python graph framework of about 100 lines for LLM agents, workflows, RAG and map-reduce pipelines.

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

Model-agnostic SDK for building agents and multi-agent systems in Python, .NET and Java; Microsoft names Agent Framework as its successor.

Python framework for multi-agent applications where agents with defined roles talk through explicit flows, built on the OpenAI Agents SDK.

Python interface for running and evaluating agents from several frameworks, with OpenTelemetry traces; now in soft deprecation.

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

Python SDK for building agents on Volcengine AgentKit, with a bundled Web UI, Studio deployment and short- and long-term memory.

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

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

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

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

Experimental Python library that teaches agent handoffs on the Chat Completions API; OpenAI now points users to its Agents SDK.

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

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

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