OpenAI Agents SDK

A lightweight Python package officially released by OpenAI for building agent AI applications

AI application development framework

https://openai.github.io/openai-agents-python/zh/

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OpenAI Agents SDK is a lightweight Python package officially released by OpenAI, specifically used to build agent AI applications. The framework is a production-ready upgrade of Swarm, a previous project used for agent experiments, and will be officially released in 2025. In April 2026, OpenAI released a major update, introducing native sandbox execution capabilities, allowing agents to safely perform tasks in an isolated environment, marking a substantial transformation of AI Agents from "talking" to "capable of doing work". The framework supports provider-agnostic design and can interface with multiple large language model providers. Its core functions include agent orchestration, task transfer, safety guardrails, built-in tracking, and multi-agent collaboration.
OpenAI Agents SDK is developed and maintained by OpenAI and is an important layout of the company in the field of AI Agents. In 2024, OpenAI first released the Swarm project, a lightweight experimental framework for agent experiments, mainly used to demonstrate the basic concepts of multi-agent collaboration. Although Swarm is a novel concept, its applicability in production environments is limited. In 2025, OpenAI will upgrade Swarm to Agents SDK, a full-featured, production-ready development framework that can meet the needs of enterprise-level AI application development. From a technology evolution perspective, the release of OpenAI Agents SDK is closely related to the company's overall strategy. In early 2025, OpenAI released the Three Musketeers for Agent development - built-in toolset, Responses API and open source Agents SDK, forming a complete Agent development tool chain. As the only open source component, Agents SDK carries OpenAI’s expectations for building a developer ecosystem. On April 15, 2026, OpenAI released a major update to the Agents SDK, most notably the native sandbox execution capability. This update allows agents to run in a truly isolated workspace and supports functions such as file inventory management, sandbox client selection, and resumable sessions, solving security risks in enterprise-level Agent application development.
OpenAI Agents SDK provides a complete set of multi-agent development tools, and the core functions can be divided into the following categories. At the basic component level, the SDK provides the core abstraction of Agent. Each agent consists of a large language model, instruction set and tool set, and developers can define the behavior of the agent through simple Python code. The task transfer mechanism allows agents to transfer execution rights to other agents to achieve multi-agent collaboration. The security guardrail function can verify user input and agent output to prevent the generation of unsafe content. Agent loops are another core capability of the SDK. Unlike traditional solutions that require developers to manually handle tool call loops, Agents SDK provides a built-in agent loop mechanism. The agent automatically handles tool calls and continues to run until the task is completed. This design greatly simplifies the development process and lowers the development threshold for Agent applications. The native sandbox execution capability brought by the April 2026 update is the biggest highlight of this version. Sandbox agents can run in a real isolated workspace and support file inventory management, so developers can precisely control which files the agent can access. Sandbox client selection allows developers to choose different isolation levels, and resumable sessions ensure reliability for long-term tasks. In terms of tool calling, the SDK automatically converts any Python function into a tool and generates corresponding schema and Pydantic verification. This design makes migrating existing Python code into Agent tools very simple. The SDK also has built-in support for the MCP (Model Context Protocol) service, and you can directly call the tools provided by the MCP server. The session management function provides a persistent memory layer to maintain the context of multiple rounds of work. The Human in the Loop mechanism allows humans to intervene during the work of the intelligent agent to achieve human-machine collaboration. The tracking function can collect agent running events to support debugging, monitoring and evaluation. The SDK also supports the use of the gpt-realtime-1.5 model to build voice agents, enabling real-time voice interaction capabilities. From the perspective of user experience, the design concept of Agents SDK is "lightweight, easy to use and almost no abstraction layer". This means that developers do not need to learn complex framework concepts and only need to understand basic Python programming knowledge to get started. The official provides a detailed quick start guide and sample code, and the learning cost is low.
OpenAI Agents SDK is an open source project licensed under the MIT license. Developers are free to use, modify and distribute the framework. However, AI applications built using the Agents SDK may incur additional API call costs. When the agent performs tasks, it calls OpenAI's large language model API, and these API calls are charged according to OpenAI's pricing standards. Currently, the SDK supports multiple models, and developers can choose the appropriate model based on task complexity to control costs. The SDK itself does not provide hosting services, and developers need to deploy and host applications built using the SDK themselves. This model is consistent with the tradition of the open source community. OpenAI provides the tools and developers are responsible for operation and maintenance.
Judging from public information, users’ evaluation of OpenAI Agents SDK is generally positive. Positive comments mainly focus on the following aspects. First, the SDK has been praised for its ease of use. Many developers say that compared to frameworks such as LangChain, Agents SDK has a lower learning curve and the code is simpler and more intuitive. The basic Agent example only requires a few lines of code to complete. Second, the April 2026 sandbox update is widely recognized. Developers say that the native sandbox execution capability solves the previous trouble of building an isolation environment by yourself, making enterprise-level application development safer and more reliable. Third, the provider-agnostic design was well received. The SDK not only supports OpenAI models, but also supports docking with other large language model providers. This flexibility is recognized by developers. Negative feedback mainly focuses on the following aspects. Some developers believe that compared with the mature LangChain ecosystem, the Agents SDK's plug-in and tool ecosystem is not rich enough. For complex application scenarios, you may need to develop more tools yourself. Some developers also mentioned that although the SDK documentation is detailed in the basics, it does not cover advanced use cases comprehensively. Best practices for some functions still need to be explored through the community.
From an industry perspective, the release of OpenAI Agents SDK marks the standardization stage of AI Agent development. In the Agent framework competition, OpenAI Agents SDK faces pressure from multiple competitors. According to industry analysis, LangChain is currently the most ecologically complete entry-level framework, with rich documentation and tutorials. LangGraph is a workflow orchestration tool produced by LangChain, suitable for scenarios that require complex workflows. AutoGen is a multi-agent collaboration framework launched by Microsoft that emphasizes collaboration and role division between agents. CrewAI is another popular multi-agent framework that adopts role-playing design concepts. In the framework selection discussion in 2026, OpenAI Agents SDK was positioned as a lightweight multi-agent development kit, with the core primitives being Agent and task transfer. Compared with frameworks such as LangChain and AutoGen, the advantages of Agents SDK lie in its official support and deep integration with the OpenAI ecosystem, while its disadvantage lies in the richness of the plug-in ecosystem. It is worth noting that Google has also launched ADK (Agent Development Kit), which directly competes with the OpenAI Agents SDK. Industry opinion believes that these two frameworks are becoming the most serious options at the moment, but their design concepts and applicable scenarios are different.
OpenAI Agents SDK is an open source tool, and disputes and risks are mainly focused on the usage level rather than the framework itself. Security risks are the primary concern in Agent application development. Although the SDK provides sandbox execution capabilities, developers still need to carefully configure permission controls in production environments to prevent agents from accessing sensitive data or performing dangerous operations. The biggest risk in the AI era is not technical failure, but a management vacuum - the boundaries drawn by developers determine what the Agent can and cannot touch. Dependence risks cannot be ignored either. Although the SDK supports provider-agnostic design, it is often bound to the OpenAI API for in-depth use. If OpenAI's API policies or pricing change, it may impact applications that use the framework. In addition, the Agent framework is still in the rapid development stage, and API stability cannot be fully guaranteed. Developers need to pay attention to version updates and prepare for migration.
OpenAI Agents SDK is suitable for the following groups of people. Developers who are new to AI Agent development can use it as an introductory framework, and learning is cost-effective. Teams already developing applications using the OpenAI API can quickly expand to Agent applications. Projects that are deeply integrated with the OpenAI ecosystem can use this framework to gain better compatibility. Developers who need to build simple multi-agent collaboration processes can be given priority. The following groups of people may need to consider other options. Applications that require complex workflow orchestration capabilities may be better suited to LangGraph or AutoGen. Projects that have already built complete applications using other frameworks (such as LangChain) can continue to use the original solution, while projects that need to enrich the plug-in ecosystem may need to wait for the further development of the SDK ecosystem.
OpenAI Agents SDK is a lightweight multi-agent development framework officially released by OpenAI. It is upgraded from Swarm. The sandbox update in April 2026 gives it enterprise-level application development capabilities. The framework has a clear positioning - allowing Agents to move from being "able to chat" to "able to work", and providing core capabilities such as agent looping, task transfer, sandbox execution, and tool invocation. For teams or individuals who are new to Agent development, this is an option worth considering; but for scenarios that require complex workflows, you may need to evaluate the suitability of other frameworks. Overall, Agents SDK represents the direction of standardization in AI Agent development and deserves attention.

User Reviews

Daniel_Price168

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I just tried out the sandbox function of Agents SDK, and it’s really great! In the past, you had to set up an isolation environment yourself, but now the official solution is solved directly for you.

TIand

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It is much simpler than LangChain and can be run with just a few lines of code.

EMoralesJr6

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The official documentation is very clear, and you can set it up in five minutes by following the quick start.

JMoralesQ0

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Use Agent as tool to register another Agent as a tool. This design is quite clever. It makes it easy to separate and assemble complex tasks!

bREADbUD660

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It’s 2026, and it’s too difficult to choose an Agent framework. LangGraph, AutoGen, OpenAI Agents SDK, and Google ADK are dazzling to choose from.

JJohnson_2022

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I encountered pitfalls with Swarm before, but now the production version is much more stable.

JGonzalez_Pro

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The sandbox function is finally here, enterprise-level applications are guaranteed!

KarenWrightIII

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Compared with LangChain, Agents SDK has fewer abstractions and is faster to get started with, but the plug-in ecosystem is not that rich.

BHill_2020

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The tracking function is easy to use. You can see which tools the Agent ran and who handed them over, making it easy to debug.

Jeremy.NguyenX7

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Thumbs up for supporting MCP services, tool calls will be more unified in the future.

StakePro

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Just pip install openai-agents and you can run it. What kind of bicycle is needed?

ScottJohnson_99

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A newbie who just learned Agent development said that this is much friendlier than LangChain, and the documentation examples are also new.

IHernandez

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It's very easy to use, and the task transfer mechanism is easy to use.

Jacqueline.Baker369

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I struggled with other frameworks for a long time before, but this one was done in no time.

CryptoTraderRichardson

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Produced by OpenAI, it must be a high-quality product.

JoseHallSr

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The session management function can persist memory, so you no longer need to write context for multiple rounds of conversations.

剑客643

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Very useful!

crazygoose886

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The design of Human in the Loop is very practical and convenient when manual intervention is needed.

安然_1

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There are some pitfalls in the environment configuration. It is recommended to read the environment variable configuration section of the official documentation.

William_ThompsonZ

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There are no big problems in using it so far, but the ecosystem is still young and I look forward to more plug-ins.

BUpow

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Provider-agnostic has good reviews, but you don’t have to use OpenAI’s model.

zOEYoLSEN

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good.

Patricia_Murray_77224

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The guardrail function can verify input and output, taking security to a new level.

Steven.FloresZ

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The built-in agent loop is so worry-free, you don’t have to write while True yourself for a long time.

ScottJackson168

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Voice Agent supports gpt-realtime-1.5, and real-time voice interaction is expected in the future.

OpenAI Agents SDK

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