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OCopenai.com·

Introducing the Agents API

AI 摘要

OpenAI 推出了 Agents API,旨在帮助开发者构建能够长时间运行的智能代理。该 API 提供了一个强大的框架,用于管理上下文、高效使用工具以及协调子代理。它还提供了基础设施,确保代理能够可靠运行数天,并支持文件操作、代码执行和中间结果保存。Agents API 的核心功能包括“Tool search”以减少 token 使用和成本,以及“programmatic tool calling”以实现并行操作、链式调用和数据过滤。该 API 支持 MCP、自定义函数以及内置工具(如网络搜索),目前正处于公开测试阶段。

为什么是这条

该API与此前代理开发方法不同,它通过提供可靠的多日运行基础设施和高效工具使用,专门解决了长时间运行代理的挑战。

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正文

As we’ve scaled Codex and ChatGPT for Work to millions of people around the world, we’ve learned what it takes to make long-running agents work well in practice. Useful agents need a powerful harness that manages context, uses tools efficiently, and coordinates subagents. They also need infrastructure that keeps them running reliably for days, with environments where they can work with files, run code, and save intermediate results.

Today, we’re introducing the Agents API ⁠ (opens in a new window) in public beta, bringing that same harness and infrastructure that powers Codex to developers through a simple, flexible API.

What our customers are saying about Agents API

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Build cloud agents with a single API call

With the Agents API, you can create a production-ready agent in a single API call by specifying the task, model, tools, and environment:

OpenAI hosts and maintains the harness. You choose the agent’s compute environment: in an OpenAI-managed sandbox, on your own infrastructure, or with one of our sandbox partners. The Agents API gives you a strong foundation for building agents on top of our optimized agent harness and infrastructure, so you can focus on the tools, knowledge, and workflows that make your agent unique.

Agents API powers your agents with the same harness and infrastructure behind Codex.

Choose your agent environment

Different workloads need different compute, storage, and deployment options. The Agents API lets you choose a sandbox that fits your application.

We’re partnering with ecosystem providers ⁠ (opens in a new window) , including Blaxel, Cloudflare, Daytona, DigitalOcean, E2B, Modal, Oracle, Runloop, and Vercel, to provide first-class integrations for a range of needs:

- Fully managed environments or deployments within your VPC

- Specific file and secret storage mechanisms

- Different CPU, GPU, and memory configurations, with performance, cold-start, and cost profiles to match your company’s workflow.

The Agents API offers first-class integrations with popular ecosystem providers.

OpenAI hosted sandboxes

For developers who want to get started quickly and scale efficiently, we’re also introducing the OpenAI hosted sandbox ⁠ (opens in a new window) . This leverages the same sandboxing infrastructure that powers Codex and ChatGPT.

OpenAI provisions and manages the sandbox, giving your agent a secure and performant environment to run code, work with files, and produce artifacts. These sandboxes can be flexibly configured with your files, packages, skills and plugins to give the agent what it needs to complete the task.

Build with an evolving Codex harness

Taking advantage of new model capabilities often means reworking your harness, taking valuable time away from improving your application. The Agents API provides versioned access to these capabilities with each model launch. We maintain and continuously improve the harness alongside our models, helping your agents get better performance from every upgrade. For example, recent improvements to the harness include:

Keep agents working across long sessions

To support models working for hours, we’ve built context management that helps agents carry relevant information across longer sessions. The Agents API automatically compacts ⁠ (opens in a new window) earlier context as a session approaches its context limit, preserving information the agent needs to continue. Developers can build workflows that span multiple context windows without implementing their own compaction logic.

Help agents efficiently use more tools

The Agents API helps agents find the right tools and use them efficiently. Tool search ⁠ (opens in a new window) loads relevant tool definitions as needed, helping reduce token usage and cost while preserving the model’s cache. Once tools are available, programmatic tool calling ⁠ (opens in a new window) lets agents run calls in parallel, chain related operations, and filter or combine results in code so they can work through large volumes of data while bringing only the relevant results back into context. The Agents API supports MCP, custom functions, and built-in tools like web search.

来源·openai.com