관리형 에이전트의 환경

환경은 에이전트가 코드를 실행하고 파일을 유지할 수 있는 격리된 공간을 제공하는 관리형 Linux 샌드박스입니다. 상호작용 컨텍스트와 분리되어 있으므로 여러 상호작용에서 동일한 환경을 재사용하거나 언제든지 새로 시작할 수 있습니다.

다음 예에서는 새로운 원격 환경으로 상호작용을 만들고 ID를 가져오는 방법을 보여줍니다.

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" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Install pandas and matplotlib, verify the imports, and print the versions.",
    "environment": "remote"
}'

`environment` 매개변수

environment 매개변수는 세 가지 형식을 허용합니다.

자세	예	용도
`"remote"`	`environment="remote"`	새 샌드박스를 프로비저닝합니다.
환경 ID	`environment="env_abc123"`	모든 파일과 패키지가 포함된 기존 샌드박스를 재사용합니다.
구성 객체	`environment={...}`	소스 또는 네트워크 규칙 또는 둘 다를 사용하여 새 샌드박스를 프로비저닝합니다.

다음 예에서는 environment 매개변수를 사용하는 세 가지 방법을 보여줍니다.

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" \
-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: $GEMINI_API_KEY" \
-d "{
    \"agent\": \"antigravity-preview-05-2026\",
    \"input\": [{\"type\": \"text\", \"text\": \"Modify the script to accept a name argument.\"}],
    \"environment\": \"$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" \
-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"
            }
        ]
    }
}'

환경 구성

환경을 설정하는 한 가지 방법은 에이전트에게 설치해야 하는 항목을 알려주는 것입니다. 종속성 해결 및 문제 해결을 처리합니다. 환경이 준비되면 environment_id를 저장하고 재사용합니다.

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" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Install pandas, matplotlib, and seaborn. Verify all imports work and print the installed versions.",
    "environment": "remote"
}'

소스에서 마운트

에이전트에 필요한 파일을 정확히 알고 있다면 반복하는 대신 단일 호출로 마운트합니다. environment 구성 객체는 세 가지 유형의 sources 배열을 허용합니다.

소스 유형	`type` 값	설명	한도
Git 저장소	`repository`	URL에서 저장소를 `target`의 샌드박스로 클론합니다.	500 MB
Cloud Storage	`gcs`	Cloud Storage에서 `target`의 샌드박스로 파일 또는 디렉터리를 복사합니다.	2 GB
인라인 콘텐츠	`inline`	`target`의 샌드박스에 있는 파일에 원시 텍스트 콘텐츠를 씁니다.	파일당 1MB, 총 2MB

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={

관리형 에이전트의 환경

Python

JavaScript

REST

environment 매개변수

Python

JavaScript

REST

환경 구성

Python

JavaScript

REST

소스에서 마운트

Python

`environment` 매개변수