Gemini Deep Research 现已推出预览版，支持协作规划、可视化、MCP 等功能。

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受管代理中的环境

环境是托管式 Linux 沙盒，可为智能体提供一个隔离的位置来执行代码和保留文件。它们与互动上下文分离，因此您可以在多个互动中重复使用同一环境，也可以随时重新开始。

以下示例演示了如何使用新的远程环境创建互动并检索其 ID：

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Install pandas and matplotlib, verify the imports, and print the versions.",
    environment="remote",
)

print(f"Environment ID: {interaction.environment_id}")

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Install pandas and matplotlib, verify the imports, and print the versions.",
    environment: "remote",
});

console.log(`Environment ID: ${interaction.environment_id}`);

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Install pandas and matplotlib, verify the imports, and print the versions.",
    "environment": "remote"
}'

`environment` 参数

environment 参数接受三种形式：

姿势	示例	适用情形
`"remote"`	`environment="remote"`	预配新的沙盒。
环境 ID	`environment="env_abc123"`	重复使用包含所有文件和软件包的现有沙盒。
配置对象	`environment={...}`	预配包含来源、网络规则或两者的新沙盒。

以下示例演示了使用 environment 参数的三种方式。

Python

from google import genai

client = genai.Client()

# Fresh sandbox
interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Write a hello world script.",
    environment="remote",
)

# Reuse an existing sandbox
interaction_2 = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Modify the script to accept a name argument.",
    environment=interaction.environment_id,
    previous_interaction_id=interaction.id,
)

# New sandbox with sources
interaction_3 = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="List all files and summarize the project.",
    environment={
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/octocat/Spoon-Knife",
                "target": "/workspace/spoon-knife",
            }
        ],
    },
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

// Fresh sandbox
const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Write a hello world script.",
    environment: "remote",
});

// Reuse an existing sandbox
const interaction2 = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Modify the script to accept a name argument.",
    environment: interaction.environment_id,
    previous_interaction_id: interaction.id,
});

// New sandbox with sources
const interaction3 = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "List all files and summarize the project.",
    environment: {
        type: "remote",
        sources: [
            {
                type: "repository",
                source: "https://github.com/octocat/Spoon-Knife",
                target: "/workspace/spoon-knife",
            },
        ],
    },
});

console.log(interaction.output_text);

REST

# Fresh sandbox
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": [{"type": "text", "text": "Write a hello world script."}],
    "environment": "remote"
}'

# Reuse an existing sandbox (replace $ENV_ID and $INTERACTION_ID with values from the previous response)
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d "{
    \"agent\": \"antigravity-preview-05-2026\",
    \"input\": [{\"type\": \"text\", \"text\": \"Modify the script to accept a name argument.\"}],
    \"environment\": \"$ENV_ID\",
    \"previous_interaction_id\": \"$INTERACTION_ID\"
}"

# New sandbox with sources
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": [{"type": "text", "text": "List all files and summarize the project."}],
    "environment": {
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/octocat/Spoon-Knife",
                "target": "/workspace/spoon-knife"
            }
        ]
    }
}'

配置环境

设置环境的一种方法是告知智能体您需要安装的内容。它会处理依赖项解析和问题排查。环境准备就绪后，保存 environment_id 并重复使用。

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Install pandas, matplotlib, and seaborn. Verify all imports work and print the installed versions.",
    environment="remote",
)

# Reuse the configured environment
interaction_2 = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Clone https://github.com/octocat/Spoon-Knife into /workspace/tools. Run the test suite and fix any missing dependencies.",
    environment=interaction.environment_id,
    previous_interaction_id=interaction.id,
)

# Reuse the configured environment
interaction_3 = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Using the tools in /workspace/tools, list the files.",
    environment=interaction.environment_id,
    previous_interaction_id=interaction_2.id,
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Install pandas, matplotlib, and seaborn. Verify all imports work and print the installed versions.",
    environment: "remote",
});

const interaction2 = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Clone https://github.com/octocat/Spoon-Knife into /workspace/tools. Run the test suite and fix any missing dependencies.",
    environment: interaction.environment_id,
    previous_interaction_id: interaction.id,
});

const interaction3 = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Using the tools in /workspace/tools, list the files.",
    environment: interaction.environment_id,
    previous_interaction_id: interaction2.id,
});
console.log(interaction.output_text);

REST

# Create interaction
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Install pandas, matplotlib, and seaborn. Verify all imports work and print the installed versions.",
    "environment": "remote"
}'

从来源装载

如果您确切知道智能体需要哪些文件，请在一次调用中装载这些文件，而不是进行迭代。environment 配置对象接受包含三种类型的 sources 数组：

来源类型	`type` 值	说明	限制
Git 代码库	`repository`	将代码库从网址克隆到 `target` 处的沙盒中。	500 MB
Cloud Storage	`gcs`	将文件或目录从 Cloud Storage 复制到 `target` 处的沙盒中。	2 GB
内嵌内容	`inline`	将原始文本内容写入 `target` 处的沙盒中的文件。	每个文件 1 MB，总共 2 MB

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="List all files under /workspace and describe what you find.",
    environment={
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/octocat/Spoon-Knife",
                "target": "/workspace/spoon-knife",
            },
            {
                "type": "gcs",
                "source": "gs://cloud-samples-data/bigquery/us-states/",
                "target": "/workspace/gcs-data",
            },
            {
                "type": "inline",
                "content": "# Project Notes\n\n- Analyze state population data\n- Create visualizations\n",
                "target": "/workspace/notes/readme.md",
            },
        ],
    },
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "List all files under /workspace and describe what you find.",
    environment: {
        type: "remote",
        sources: [
            {
                type: "repository",
                source: "https://github.com/octocat/Spoon-Knife",
                target: "/workspace/spoon-knife",
            },
            {
                type: "gcs",
                source: "gs://cloud-samples-data/bigquery/us-states/",
                target: "/workspace/gcs-data",
            },
            {
                type: "inline",
                content: "# Project Notes\n\n- Analyze state population data\n- Create visualizations\n",
                target: "/workspace/notes/readme.md",
            },
        ],
    },
});

console.log(interaction.output_text);

REST

# Create interaction with sources
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "List all files under /workspace and describe what you find.",
    "environment": {
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/octocat/Spoon-Knife",
                "target": "/workspace/spoon-knife"
            },
            {
                "type": "gcs",
                "source": "gs://cloud-samples-data/bigquery/us-states/",
                "target": "/workspace/gcs-data"
            },
            {
                "type": "inline",
                "content": "# Project Notes\n\n- Analyze state population data\n- Create visualizations\n",
                "target": "/workspace/notes/readme.md"
            }
        ]
    }
}'

您可以结合使用这两种方法：以声明方式装载已知来源，然后通过后续互动进行迭代以安装软件包或运行设置脚本。添加自定义来源时，您无法将根目录 (/) 设置为目标，必须始终指定子目录。

私有来源

您还可以通过在网络配置中添加凭据，从私有 GitHub 代码库或私有 Cloud Storage 存储分区下载内容：

对于私有 Git 代码库，请使用Basic身份验证和您的 GitHub 个人访问令牌 (PAT)。使用 x-oauth-basic 作为用户名对令牌进行编码：

echo -n "x-oauth-basic:ghp_YourPATHere" | base64

Python

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Run the test for my backend app and fix any issue.",
    environment={
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/your-org/backend",
                "target": "/backend-app"
            }
        ],
        "network": {
            "allowlist": [
                {
                    "domain": "github.com",
                    "transform": {
                        "Authorization": "Basic YOUR_BASE64_TOKEN"
                    }
                },
                {
                    "domain": "*"
                }
            ]
        }
    }
)

JavaScript

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Run the test for my backend app and fix any issue.",
    environment: {
        type: "remote",
        sources: [
            {
                type: "repository",
                source: "https://github.com/your-org/backend",
                target: "/backend-app"
            }
        ],
        network: {
            allowlist: [
                {
                    domain: "github.com",
                    transform: {
                        "Authorization": "Basic YOUR_BASE64_TOKEN"
                    }
                },
                {
                    domain: "*"
                }
            ]
        }
    },
});

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Run the test for my backend app and fix any issue.",
    "environment": {
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/your-org/backend",
                "target": "/backend-app"
            }
        ],
        "network": {
            "allowlist": [
                {
                    "domain": "github.com",
                    "transform": {
                        "Authorization": "Basic YOUR_BASE64_TOKEN"
                    }
                },
                {
                    "domain": "*"
                }
            ]
        }
    }
}'

对于私有 Cloud Storage 存储分区，请使用标准 OAuth 2.0 不记名令牌：

gcloud auth print-access-token

Python

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Analyze the discrepancies across the data in workspace",
    environment={
        "type": "remote",
        "sources": [
            {
                "type": "gcs",
                "source": "gs://my-private-bucket/data",
                "target": "/workspace",
            }
        ],
        "network": {
            "allowlist": [
                {
                    "domain": "*.googleapis.com",
                    "transform": {
                        "Authorization": "Bearer YOUR_GCS_TOKEN"
                    }
                },
                {
                    "domain": "*"
                }
            ]
        }
    },
)

JavaScript

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Analyze the discrepancies across the data in workspace",
    environment: {
        type: "remote",
        sources: [
            {
                type: "gcs",
                source: "gs://my-private-bucket/data",
                target: "/workspace",
            }
        ],
        network: {
            allowlist: [
                {
                    domain: "storage.googleapis.com",
                    transform: {
                        "Authorization": "Bearer YOUR_GCS_TOKEN"
                    }
                },
                {
                    domain: "*"
                }
            ]
        }
    },
});

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Analyze the discrepancies across the data in workspace",
    "environment": {
        "type": "remote",
        "sources": [
            {
                "type": "gcs",
                "source": "gs://my-private-bucket/data",
                "target": "/workspace"
            }
        ],
        "network": {
            "allowlist": [
                {
                    "domain": "storage.googleapis.com",
                    "transform": {
                        "Authorization": "Bearer YOUR_GCS_TOKEN"
                    }
                },
                {
                    "domain": "*"
                }
            ]
        }
    }
}'

预装软件

沙盒在 Ubuntu 上运行，并预装了运行时和常用软件包。智能体可以在运行时使用 pip install 或 npm install 安装其他软件包。当您重复使用同一 environment_id 时，在互动期间安装的软件包会保留。

类别	预装软件包
UNIX 工具	`curl`、`wget`、`git`、`rsync`、`unzip`、`ripgrep`、`fd-find`、`gawk`、`bc`、`tree`、`which`、`lsof`、`htop`、`jq`、`iproute2`、`procps`、`gcloud CLI`
Python 3.12	`numpy`、`pandas`、`requests`、`google-genai`、`beautifulsoup4`、`pyyaml`、`ast-grep-cli`
Node.js 22	`create-next-app`、`create-vite`、`typescript`

网络配置

默认情况下，环境具有不受限制的出站网络访问权限。使用 network 字段将出站流量限制为特定网域。每条规则都指定一个 domain 和一个可选的 transform 对象，以将标头注入到匹配的请求中。这些标头对于每次互动可以是唯一的，并且您可以为同一环境更新这些标头。

字段	类型	说明
`domain`	`string`	要匹配的网域。使用确切的主机名或 `*` 来指定所有网域。
`transform`	`object`	包含扁平键值对的对象，这些键值对表示要注入到匹配请求中的标头，例如 `{"Authorization": "Bearer ..."}`。

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Fetch the latest issues from the GitHub API for my-org/my-repo.",
    environment={
        "type": "remote",
        "network": {
            "allowlist": [
                {
                    "domain": "api.github.com",
                    "transform": {
                        "Authorization": "Bearer ghp_your_github_token"
                    },
                },
                {"domain": "pypi.org"},
                {"domain": "*"},
            ]
        },
    },
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Fetch the latest issues from the GitHub API for my-org/my-repo.",
    environment: {
        type: "remote",
        network: {
            allowlist: [
                {
                    domain: "api.github.com",
                    transform: {
                        "Authorization": "Bearer ghp_your_github_token"
                    },
                },
                { domain: "pypi.org" },
                { domain: "*" },
            ]
        }
    },
});

console.log(interaction.output_text);

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": [{"type": "text", "text": "Fetch the latest issues from the GitHub API for my-org/my-repo."}],
    "environment": {
        "type": "remote",
        "network": {
            "allowlist": [
                {
                    "domain": "api.github.com",
                    "transform": {
                        "Authorization": "Bearer ghp_your_github_token"
                    }
                },
                {"domain": "pypi.org"},
                {"domain": "*"}
            ]
        }
    }
}'

设置许可名单后，系统仅允许向明确列出的网域发出请求。您可以使用通配符来匹配子网域（例如 {"domain": "*.example.com"}），但请注意，这不会匹配根域名 example.com，您必须单独添加该域名。如需允许所有其他流量（例如在不注入标头的情况下路由未列出的网域），请添加 {"domain": "*"} 作为全能条目。

凭据

您可以通过添加标头转换来添加凭据，供智能体使用。凭据由出站代理注入到相应的 HTTP 标头中，它们绝不会作为环境变量或文件在沙盒内公开。

Python

import subprocess
from google import genai

# Fetch a short-lived access token from your local gcloud CLI
gcloud_token = subprocess.check_output(
    ["gcloud", "auth", "print-access-token"], text=True
).strip()

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="List the files in gs://my-bucket/reports/ using the GCS JSON API.",
    environment={
        "type": "remote",
        "network": {
            "allowlist": [
                {
                    "domain": "storage.googleapis.com",
                    "transform": {
                        "Authorization": f"Bearer {gcloud_token}"
                    },
                }
            ]
        },
    },
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

import { execSync } from "child_process";

const gcloudToken = execSync("gcloud auth print-access-token").toString().trim();

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "List the files in gs://my-bucket/reports/ using the GCS JSON API.",
    environment: {
        type: "remote",
        network: {
            allowlist: [
                {
                    domain: "storage.googleapis.com",
                    transform: {
                        "Authorization": `Bearer ${gcloudToken}`
                    },
                }
            ]
        }
    },
});

console.log(interaction.output_text);

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "List the files in gs://my-bucket/reports/ using the GCS JSON API.",
    "environment": {
        "type": "remote",
        "network": {
            "allowlist": [
                {
                    "domain": "storage.googleapis.com",
                    "transform": {
                        "Authorization": "Bearer <YOUR_GCLOUD_TOKEN>"
                    }
                }
            ]
        }
    }
}'

停用网络访问权限

如需阻止所有出站网络访问，请将 network 设置为 disabled：

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Analyze the local files only.",
    environment={
        "type": "remote",
        "network": "disabled",
    },
)

print(interaction.output_text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Analyze the local files only.",
    environment: {
        type: "remote",
        network: "disabled",
    },
});

console.log(interaction.output_text);

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Analyze the local files only.",
    "environment": {
        "type": "remote",
        "network": "disabled"
    }
}'

环境生命周期

环境遵循以下生命周期：

状态	行为
已创建	当互动指定 `environment: "remote"` 或配置对象时，系统会预配环境。
有效	在互动进行期间运行。
空闲	闲置 15 分钟后，系统会自动创建快照并停止环境。
离线	自上次使用以来保留 7 天。可以通过传递其 ID 来恢复。
已删除	从系统中移除。

从环境下载文件

智能体在执行期间会在沙盒内创建文件。您可以使用 Files API 将完整环境快照下载为 tar 文件：

Python

import os
import requests
import tarfile
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Write a file environments_test.txt with content 'Environments' inside the sandbox.",
    environment="remote",
)

env_id = interaction.environment_id
api_key = os.environ.get("GEMINI_API_KEY")

response = requests.get(
    f"https://generativelanguage.googleapis.com/v1beta/files/environment-{env_id}:download",
    params={"alt": "media"},
    headers={"x-goog-api-key": api_key},
    allow_redirects=True,
)

with open("snapshot_env.tar", "wb") as f:
    f.write(response.content)

os.makedirs("extracted_env_snapshot", exist_ok=True)
with tarfile.open("snapshot_env.tar") as tar:
    tar.extractall(path="extracted_env_snapshot")

print(os.listdir("extracted_env_snapshot"))

JavaScript

import { GoogleGenAI } from "@google/genai";
import { execSync } from "child_process";
import * as fs from "fs";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Write a file environments_test.txt with content 'Environments' inside the sandbox.",
    environment: "remote",
});

const envId = interaction.environment_id;
const apiKey = process.env.GEMINI_API_KEY || "";

const url = `https://generativelanguage.googleapis.com/v1beta/files/environment-${envId}:download?alt=media`;
const response = await fetch(url, {
    headers: {
        "x-goog-api-key": apiKey,
    },
});

if (!response.ok) {
    throw new Error(`Failed to download file: ${response.statusText}`);
}

const buffer = Buffer.from(await response.arrayBuffer());
fs.writeFileSync("snapshot_env.tar", buffer);

if (!fs.existsSync("extracted_env_snapshot")) {
    fs.mkdirSync("extracted_env_snapshot");
}
execSync("tar -xf snapshot_env.tar -C extracted_env_snapshot");

console.log(fs.readdirSync("extracted_env_snapshot"));

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Api-Revision: 2026-05-20" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Write a file environments_test.txt with content '\''Environments'\'' inside the sandbox.",
    "environment": "remote"
}'
# Step 2: Download snapshot (reusing environment ID from Step 1)
# curl -L -X GET "https://generativelanguage.googleapis.com/v1beta/files/environment-$ENV_ID:download?alt=media" \
#   -H "x-goog-api-key: $API_KEY" \
#   -o snapshot.tar

价格和资源

每个环境都以固定的资源分配运行：

资源	值
CPU	4 核
内存	16 GB

在预览版期间，环境计算（CPU、内存、沙盒执行）不收费 。如需了解智能体令牌费用，请参阅价格。

限制

预览版状态 ：环境和托管式智能体处于预览版阶段。功能和架构可能会发生变化。
内嵌来源大小 ：内嵌来源限制为每个文件 1 MB，所有文件总共 2 MB。
来源大小：Git 代码库限制为 500 MB，Cloud Storage 代码库限制为 2 GB。
环境启动 ：预配新环境最多需要约 5 秒。大型来源代码库可能会增加此时间。
文件支持 ：智能体目前只能读取文本和图片文件。尚不支持二进制文件。
无法从根目录装载 ：添加自定义来源时，您无法将根目录 (/) 设置为目标，必须始终指定子目录。

后续步骤

智能体概览：了解托管式智能体的核心概念。
快速入门：开始构建多轮对话和流式传输。
Antigravity 智能体：了解默认智能体的功能、工具和价格。
构建自定义智能体：使用 AGENTS.md 和 SKILL.md 定义您自己的智能体。

受管代理中的环境

Python

JavaScript

REST

environment 参数

Python

JavaScript

REST

配置环境

Python

JavaScript

REST

从来源装载

Python

JavaScript

REST

私有来源

Python

JavaScript

REST

Python

JavaScript

REST

预装软件

网络配置

Python

JavaScript

REST

凭据

Python

JavaScript

REST

停用网络访问权限

Python

JavaScript

REST

环境生命周期

从环境下载文件

Python

JavaScript

REST

价格和资源

限制

后续步骤

`environment` 参数