Mjediset janë sandbox-e të menaxhuara të Linux-it që u japin agjentëve një vend të izoluar për të ekzekutuar kodin dhe për të ruajtur skedarët. Ato janë të shkëputura nga konteksti i ndërveprimit, kështu që ju mund të ripërdorni të njëjtin mjedis në ndërveprime të shumta ose të filloni nga e para në çdo kohë.
Shembulli i mëposhtëm tregon se si të krijoni një bashkëveprim me një mjedis të ri në distancë dhe të merrni ID-në e tij:
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}`);
PUSHTIM
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"
}'
Parametri environment
Parametri i mjedisit environment tre forma:
| Formular | Shembull | Kur të përdoret |
|---|---|---|
"remote" | environment="remote" | Sigurimi i një kutie rëre të re. |
| ID-ja e mjedisit | environment="env_abc123" | Ripërdorni një sandbox ekzistues me të gjithë skedarët dhe paketat e tij. |
| Objekti i konfigurimit | environment={...} | Sigurimi i një sandbox-i të ri me burime, rregulla rrjeti ose të dyja. |
Shembujt e mëposhtëm demonstrojnë tre mënyrat e përdorimit të parametrit environment .
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);
PUSHTIM
# 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"
}
]
}
}'
Konfiguro një mjedis
Një mënyrë për të konfiguruar një mjedis është t'i tregoni agjentit se çfarë duhet të instalohet. Ai merret me zgjidhjen e varësive dhe zgjidhjen e problemeve. Pasi mjedisi të jetë gati, ruani environment_id dhe ripërdoreni atë.
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);
PUSHTIM
# 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"
}'
Montoni nga një burim
Nëse e dini saktësisht se çfarë skedarësh i duhen agjentit, montoni ato në një thirrje të vetme në vend që t'i përsërisni. Objekti i konfigurimit environment pranon një varg sources me tre lloje:
| Lloji i burimit | vlera type | Përshkrimi | Limit |
|---|---|---|---|
| Repozitori i Git | repository | Klonon një depo nga një URL në sandbox në target . | 500 MB |
| Ruajtja në renë kompjuterike | gcs | Kopjon një skedar ose direktori nga Cloud Storage në sandbox në target . | 2 GB |
| Përmbajtje e integruar | inline | Shkruan përmbajtje teksti të papërpunuar në një skedar në sandbox në target . | 1 MB për skedar, 2 MB gjithsej |
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",
},
],
},