OpenAI 智能体 API

OpenAI 智能体 API
OpenAI Agents API

原始链接: https://developers.openai.com/api/docs/guides/agents-api/overview

此代码提供了 JavaScript、Python、Go、Java、Ruby 和 cURL 的实现示例，用于创建使用 `gpt-6-astra` 模型的 OpenAI Agent 会话。该配置演示了如何初始化具有以下功能的智能体： * **工具**：集成了对程序化工具调用、基于 HTTP 的模型上下文协议 (MCP) 以及网页搜索的支持。 * **多智能体能力**：支持并发执行子智能体（最多 4 个）。 * **环境**：定义工作区和能力目录的自托管配置。 * **任务处理**：一套自动化指令，引导智能体使用其连接的文档和搜索工具，研究并总结将 MCP 服务器连接到 OpenAI 智能体的推荐设置。每个代码片段都会向 OpenAI API 发送 POST 请求以启动会话，并返回一个唯一的 `session.id` 以跟踪交互过程。

这篇 Hacker News 的讨论围绕 OpenAI 新推出的 Agents API 展开，引发了开发者关于构建智能体系统“正确”方式的辩论。 **“自建”阵营：** 许多贡献者认为，自定义架构（用于管理记忆、上下文和工具编排的代码框架）更具优势。他们优先考虑可移植性，使开发者能够在不同模型提供商（如 Anthropic、DeepSeek、GLM）之间切换，从而避免被单一供应商绑定。对于这些开发者而言，“掌控架构”对于安全性、定制化和长期控制至关重要。 **“托管/API”阵营：** 另一些人则认为，维护自定义架构是一个分散核心产品目标的“无底洞”。他们主张，前沿实验室（如 OpenAI/Anthropic）提供的推理能力和基础设施，是个人开发者无法复制的。对于这些用户，托管 API 带来的操作简便性、安全补丁和可扩展性，足以弥补被供应商绑定的代价。 **核心主题：** * **抽象：** 社区对于是否存在通用的智能体抽象，或者“架构”是否会保持高度的项目专用性，存在分歧。 * **安全与数据：** 人们对沙箱逃逸、数据泄露，以及实验室利用“内部独白”作为训练数据的可能性仍存有严重担忧。 * **未来趋势：** 大家一致认为行业发展迅速，许多人建议，自定义的轻量级自动化依然是“黑客友好”的最佳路径。

原文

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41import OpenAI from "openai";

const client = new OpenAI();

const session = await client.beta.agents.sessions.create({
  agent: {
    model: "gpt-6-astra",
    instructions:
      "Use the OpenAI documentation MCP and web search to answer technical questions accurately. Delegate independent research tasks to subagents when useful.",
    tools: [
      { type: "programmatic_tool_calling" },
      {
        type: "mcp",
        server_label: "openai_docs",
        transport: {
          type: "http",
          server_url: "https://developers.openai.com/mcp",
        },
      },
      { type: "web_search" },
    ],
    multi_agent: { enabled: true, max_concurrent_subagents: 4 },
  },
  environment: {
    type: "self_hosted",
    workspace_directory: "/workspace",
    capability_directories: ["/workspace/capabilities/skills"],
  },
  input: [
    {
      role: "user",
      content: [
        {
          type: "input_text",
          text: "Research how to connect an MCP server to an OpenAI agent, check for recent updates, and summarize the recommended setup.",
        },
      ],
    },
  ],
});
console.log(session.id);

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40from openai import OpenAI

client = OpenAI()

session = client.beta.agents.sessions.create(
    agent={
        "model": "gpt-6-astra",
        "instructions": "Use the OpenAI documentation MCP and web search to answer technical questions accurately. Delegate independent research tasks to subagents when useful.",
        "tools": [
            {"type": "programmatic_tool_calling"},
            {
                "type": "mcp",
                "server_label": "openai_docs",
                "transport": {
                    "type": "http",
                    "server_url": "https://developers.openai.com/mcp",
                },
            },
            {"type": "web_search"},
        ],
        "multi_agent": {"enabled": True, "max_concurrent_subagents": 4},
    },
    environment={
        "type": "self_hosted",
        "workspace_directory": "/workspace",
        "capability_directories": ["/workspace/capabilities/skills"],
    },
    input=[
        {
            "role": "user",
            "content": [
                {
                    "type": "input_text",
                    "text": "Research how to connect an MCP server to an OpenAI agent, check for recent updates, and summarize the recommended setup.",
                }
            ],
        }
    ],
)
print(session.id)

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23import (
	"context"
	"fmt"
	"github.com/openai/openai-go/v3"
)

ctx := context.Background()
client := openai.NewClient()
session, err := client.Beta.Agents.Sessions.New(ctx, openai.BetaAgentSessionNewParams{Agent: openai.BetaAgentSessionNewParamsAgent{Model: openai.String("gpt-6-astra"),
	Instructions: openai.String("Use the OpenAI documentation MCP and web search to answer technical questions accurately. Delegate independent research tasks to subagents when useful."),
	Tools: []openai.AgentToolParamUnion{openai.AgentToolParamUnion{OfParamProgrammaticToolCalling: &openai.AgentToolParamProgrammaticToolCalling{}},
		openai.AgentToolParamUnion{OfParamMcp: &openai.AgentToolParamMcp{ServerLabel: "openai_docs",
			Transport: openai.McpTransportParamUnion{OfParamHTTP: &openai.McpTransportParamHTTP{ServerURL: "https://developers.openai.com/mcp"}}}},
		openai.AgentToolParamUnion{OfParamWebSearch: &openai.AgentToolParamWebSearch{}}},
	MultiAgent: openai.MultiAgentConfigParam{Enabled: true,
		MaxConcurrentSubagents: openai.Int(4)}},
	Environment: openai.EnvironmentParamUnion{OfParamSelfHosted: &openai.EnvironmentParamSelfHosted{WorkspaceDirectory: "/workspace",
		CapabilityDirectories: []string{"/workspace/capabilities/skills"}}},
	Input: openai.BetaAgentSessionNewParamsInputUnion{OfArrayOfInputMessages: []openai.AgentSessionInputMessageParam{openai.AgentSessionInputMessageParam{Content: []openai.InputContentParamUnion{openai.InputContentParamUnion{OfParamInputText: &openai.InputContentParamInputText{Text: "Research how to connect an MCP server to an OpenAI agent, check for recent updates, and summarize the recommended setup."}}}}}}})
if err != nil {
	panic(err)
}
fmt.Println(session.ID)

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50import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.agents.AgentToolParam;
import com.openai.models.beta.agents.EnvironmentParam;
import com.openai.models.beta.agents.McpTransportParam;
import com.openai.models.beta.agents.MultiAgentConfigParam;
import com.openai.models.beta.agents.sessions.SessionCreateParams;
import java.util.List;

OpenAIClient client = OpenAIOkHttpClient.fromEnv();
var session =
    client
        .beta()
        .agents()
        .sessions()
        .create(
            SessionCreateParams.builder()
                .agent(
                    SessionCreateParams.Agent.builder()
                        .model("gpt-6-astra")
                        .instructions(
                            "Use the OpenAI documentation MCP and web search to answer"
                                + " technical questions accurately. Delegate independent"
                                + " research tasks to subagents when useful.")
                        .addTool(AgentToolParam.ProgrammaticToolCalling.builder().build())
                        .addTool(
                            AgentToolParam.Mcp.builder()
                                .serverLabel("openai_docs")
                                .transport(
                                    McpTransportParam.Http.builder()
                                        .serverUrl("https://developers.openai.com/mcp")
                                        .build())
                                .build())
                        .addTool(AgentToolParam.WebSearch.builder().build())
                        .multiAgent(
                            MultiAgentConfigParam.builder()
                                .enabled(true)
                                .maxConcurrentSubagents(4L)
                                .build())
                        .build())
                .environment(
                    EnvironmentParam.SelfHosted.builder()
                        .workspaceDirectory("/workspace")
                        .capabilityDirectories(List.of("/workspace/capabilities/skills"))
                        .build())
                .input(
                    "Research how to connect an MCP server to an OpenAI agent, check for recent"
                        + " updates, and summarize the recommended setup.")
                .build());
System.out.println(session.id());

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21require "openai"

client = OpenAI::Client.new

session = client.beta.agents.sessions.create(agent: {model: "gpt-6-astra",
                                                     instructions: "Use the OpenAI documentation MCP and web search to answer technical questions accurately. Delegate independent research tasks to subagents when useful.",
                                                     tools: [{type: "programmatic_tool_calling"},
                                                       {type: "mcp",
                                                        server_label: "openai_docs",
                                                        transport: {type: "http",
                                                                    server_url: "https://developers.openai.com/mcp"}},
                                                       {type: "web_search"}],
                                                     multi_agent: {enabled: true,
                                                                   max_concurrent_subagents: 4}},
  environment: {type: "self_hosted",
                workspace_directory: "/workspace",
                capability_directories: ["/workspace/capabilities/skills"]},
  input: [{role: "user",
           content: [{type: "input_text",
                      text: "Research how to connect an MCP server to an OpenAI agent, check for recent updates, and summarize the recommended setup."}]}])
puts session.id

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46curl -sS -X POST "https://api.openai.com/v1/agents/sessions" \
  -H "OpenAI-Beta: agents=v1" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "agent": {
      "model": "gpt-6-astra",
      "instructions": "Use the OpenAI documentation MCP and web search to answer technical questions accurately. Delegate independent research tasks to subagents when useful.",
      "tools": [
        {
          "type": "programmatic_tool_calling"
        },
        {
          "type": "mcp",
          "server_label": "openai_docs",
          "transport": {
            "type": "http",
            "server_url": "https://developers.openai.com/mcp"
          }
        },
        {
          "type": "web_search"
        }
      ],
      "multi_agent": {
        "enabled": true,
        "max_concurrent_subagents": 4
      }
    },
    "environment": {
      "type": "self_hosted",
      "workspace_directory": "/workspace",
      "capability_directories": ["/workspace/capabilities/skills"]
    },
    "input": [
      {
        "role": "user",
        "content": [
          {
            "type": "input_text",
            "text": "Research how to connect an MCP server to an OpenAI agent, check for recent updates, and summarize the recommended setup."
          }
        ]
      }
    ]
  }'

OpenAI 智能体 API OpenAI Agents API

OpenAI 智能体 API
OpenAI Agents API