Google AI Studio Managed Agents on LiteLLM

LiteLLM now supports the Google AI Studio Managed Agents API. Create, manage, and run custom agents through LiteLLM.

Overview

There are two distinct steps:

1. Create a custom agent: /v1beta/agents defines your agent on the Gemini side (name, base model, instructions).
2. Run the agent: Once you have created a named agent, you can interact with it by specifying its resource name in the agent field of the /interactions request.

LiteLLM does not store the agent in its own database. The agent lives entirely on Google's side. LiteLLM is just the auth + routing layer.

Quick start

Proxy

Add your Gemini API key to the environment:

export GEMINI_API_KEY="AIzaSy..."

Minimal proxy_config.yaml:

general_settings:
  master_key: "sk-1234"

environment_variables:
  GEMINI_API_KEY: "AIzaSy..."   # or set in shell env

Start the proxy:

litellm --config proxy_config.yaml

If GEMINI_API_KEY is not set, all managed-agent calls will fail with an auth error from Google.

SDK

import os
import litellm

os.environ["GEMINI_API_KEY"] = "AIzaSy..."

You can also pass api_key="AIzaSy..." to each call instead of setting the environment variable.

1. Create an agent

Proxy

curl -X POST "http://localhost:4000/v1beta/agents" \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "my-custom-slides-agent",
    "base_agent": "antigravity-preview-05-2026",
    "instructions": "You are a helpful assistant that creates slides.",
    "base_environment": {"env_id": "YOUR_ENVIRONMENT_ID"}
}'

Response:

{
  "id": "my-slides-agent",
  "base_agent": "antigravity-preview-05-2026",
  "system_instruction": "You are a helpful assistant that creates slides."
}

SDK

response = litellm.interactions.agents.create(
    name="my-slides-agent",
    base_agent="antigravity-preview-05-2026",
    instructions="You are a helpful assistant that creates slides.",
    custom_llm_provider="gemini",
    base_environment={"env_id": "YOUR_ENVIRONMENT_ID"}
)
print(response.id)  # "my-slides-agent"

Async variant: litellm.interactions.agents.acreate(...).

Parameters:

Field	Required	Description
name	Yes	Unique agent identifier, used as the ID in later calls
base_agent	Yes	Base model to build on. Currently only "antigravity-preview-05-2026" is supported by Google
instructions	No	System-level instructions for the agent
base_environment	No	Environment config (e.g. GCS skill sources)

Calling create twice with the same name returns a 409 Conflict from Google.

2. Run an agent

Proxy

curl -X POST "http://localhost:4000/v1beta/interactions" \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "agent": "my-slides-agent",
    "input": "Create a slide deck on the Fibonacci sequence",
    "environment": "remote" # required for agents
  }'

SDK

response = litellm.interactions.create(
    agent="my-slides-agent",
    input="Create a slide deck on the Fibonacci sequence",
    environment="remote"
)
print(response)

Async variant: litellm.interactions.acreate(...).

Note: pass agent, not model. The agent name is not a LiteLLM model, do not put it in the model field.

See also: /interactions for the full Interactions API.

Manage agents

List agents

Proxy

curl "http://localhost:4000/v1beta/agents" \
  -H "Authorization: Bearer sk-1234"

Response

{
    "agents": [
        {
            "id": "my-custom-slides-agent"
        },
        {
            "id": "my-custom-slides-agent-1"
        }
    ]
}

SDK

agents = litellm.interactions.agents.list()

Get an agent

Proxy

curl "http://localhost:4000/v1beta/agents/my-slides-agent" \
  -H "Authorization: Bearer sk-1234"

Response

{
    "id": "my-custom-slides-agent",
    "base_agent": "antigravity-preview-05-2026",
    "system_instruction": "You are a helpful assistant that creates slides.",
    "base_environment": {
        "sources": [
            {
                "type": "gcs",
                "source": "gs://eap-templates/slides-skill",
                "target": "/.agents/skills/slides-skill"
            }
        ],
        "type": "remote"
    }
}

SDK

agent = litellm.interactions.agents.get(
    name="my-slides-agent"
)

Delete an agent

Proxy

curl -X DELETE "http://localhost:4000/v1beta/agents/my-slides-agent" \
  -H "Authorization: Bearer sk-1234"

SDK

litellm.interactions.agents.delete(
    name="my-slides-agent",
    custom_llm_provider="gemini",
)

List agent versions

Proxy

curl "http://localhost:4000/v1beta/agents/my-slides-agent/versions" \
  -H "Authorization: Bearer sk-1234"

Response

{
    "agentVersions": [
        {
            "agent": "antigravity-preview-05-2026",
            "base_environment": {
                "env_id": "sdsdd"
            },
            "instructions": "You are a helpful assistant that creates slides",
            "name": "agents/my-custom-slides-agent-1/versions/a7616fd3-4e3e-48e7-aea7-9ac76b4f37ab"
        }
    ]
}

SDK

versions = litellm.interactions.agents.list_versions(
    name="my-slides-agent",
    custom_llm_provider="gemini",
)

Authentication

Method	How to provide the key
Proxy	Set GEMINI_API_KEY (or GOOGLE_API_KEY) in the proxy's environment. Virtual keys (sk-...) authenticate users to the proxy; the proxy uses your Gemini key to talk to Google.
SDK	Set GEMINI_API_KEY in the environment, or pass api_key="AIzaSy..." to each call.

There is no way to use managed agents with any provider other than Google AI Studio. Other providers are not supported by this API.

Limitations

• base_agent only accepts "antigravity-preview-05-2026" (Google's current restriction).
• Agents are stored on Google's side only. LiteLLM does not persist them in its database. If you delete an agent via Google's API directly, the proxy will not know.
• Using the Interactions API via the agent param is only supported by Gemini as of now. Use the model param to call other providers' models.
• GEMINI_API_KEY / GOOGLE_API_KEY must be present in the proxy environment. Passing the key per-request via api_key is supported in the SDK but not currently via the proxy endpoint.