“deployment”

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

Code-first Go toolkit for building agents with a tool ecosystem, composable multi-agent systems and Cloud Run deployment.

Python framework for multi-agent teams and workflows, with a CLI and Docker, MCP and A2A deployment options.

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

Browser infrastructure for AI agents: local and cloud Playwright-based browser sessions, scraping and deployable browser functions.

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

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

Python SDK for deploying agents to Amazon Bedrock AgentCore, a managed runtime with memory, gateway, tools and observability.

SDK for building durable, responsive services, including agentic AI services, that cluster automatically and deploy to any infrastructure.

TypeScript framework for AI agents with tools, memory, RAG, MCP and sub-agents, paired with a Cloud or self-hosted console.

Framework for Python or Node.js programs that join LiveKit rooms as realtime voice and video agents.

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

Low-level Python orchestration framework for long-running stateful agents, with durable execution, human review points and short- and long-term memory.

Open-source Python framework for multi-agent workflows, with role-based Crews and event-driven Flows.

Python framework and runtime for building agents, serving them over a REST API and MCP server, and managing them from a web control plane.

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

Open-source Python framework from deepset for modular pipelines and agent workflows covering retrieval, tool use and generation.

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

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

Open-source LLM function calling framework for AI agents, with serverless LLM tools and geo-distributed infrastructure.

Library for LLM post-training (SFT, DPO, GRPO and agentic RL) and classic RL, with evolutionary hyperparameter optimization.

Python runtime for agent apps with tool sandboxing and streaming agent APIs; archived, with features moved to AgentScope 2.0.