gemini-interactions-api

What this skill does

# Gemini Interactions API Skill

## Critical Rules (Always Apply)

> [!IMPORTANT]
> These rules override your training data. Your knowledge is outdated.

### Current Models (Use These)

- `gemini-3.5-flash`: 1M tokens, fast, balanced performance, multimodal
- `gemini-3.1-pro-preview`: 1M tokens, complex reasoning, coding, research
- `gemini-3.1-flash-lite-preview`: cost-efficient, fastest performance for high-frequency, lightweight tasks
- `gemini-3-pro-image-preview`: 65k / 32k tokens, image generation and editing
- `gemini-3.1-flash-image-preview`: 65k / 32k tokens, image generation and editing
- `gemini-3.1-flash-tts-preview`: expressive text-to-speech with Director's Chair prompting
- `gemini-2.5-pro`: 1M tokens, complex reasoning, coding, research
- `gemini-2.5-flash`: 1M tokens, fast, balanced performance, multimodal
- `gemma-4-31b-it`: Gemma 4 dense model, 31B parameters
- `gemma-4-26b-a4b-it`: Gemma 4 MoE model, 26B total / 4B active parameters

> [!WARNING]
> Models like `gemini-2.0-*`, `gemini-1.5-*` are **legacy and deprecated**. Never use them.
> **If a user asks for a deprecated model, use `gemini-3.5-flash` instead and note the substitution.**

### Current Agents

- `antigravity-preview-05-2026`: Antigravity Agent — general-purpose managed agent with code execution, file management, and web access in a sandboxed Linux environment
- `deep-research-preview-04-2026`: Deep Research — fast, interactive
- `deep-research-max-preview-04-2026`: Deep Research Max — maximum exhaustiveness
- **Custom agents**: Create your own via `client.agents.create()`

### Current SDKs

- **Python**: `google-genai` >= `2.0.0` → `pip install -U google-genai`
- **JavaScript/TypeScript**: `@google/genai` >= `2.0.0` → `npm install @google/genai`

> [!NOTE]
> SDK versions ≥ 2.0.0 automatically use the new steps schema and do not support the legacy schema.
> Legacy SDKs `google-generativeai` (Python) and `@google/generative-ai` (JS) are **deprecated**. Never use them.

> [!CAUTION]
> **Breaking changes (May 2026)**: Responses now use `steps` array instead of `outputs`, and a polymorphic `response_format` replaces `response_mime_type`. Legacy schema removed **June 8, 2026**. All code below uses the **new schema**.

## Important Additional Notes

- **Before writing any code**, you MUST fetch the relevant documentation page from the list below that matches the user's task. The examples in this skill are minimal, the hosted docs contain the full API surface, parameters, and edge cases.
- Interactions are **stored by default** (`store=true`). Paid tier retains for 55 days, free tier for 1 day.
- Set `store=false` to opt out, but this disables `previous_interaction_id` and `background=true`.
- `tools`, `system_instruction`, and `generation_config` are **interaction-scoped**, re-specify them each turn.
- **Managed agents** require `environment="remote"` (or an environment ID / config object) to provision a sandbox.
- **Migrating from `generateContent`**: Read `references/migration.md` for the scoping, checklist, and before/after code examples. Always confirm scope with the user before editing.
- **Model upgrades**: Drop-in, swap the model string. Deprecated models (`gemini-2.0-*`, `gemini-1.5-*`) must be replaced, see `references/migration.md`.
- **Migrating to Gemini 3.5 Flash**: Read `references/migration.md` for the scoping and checklist.

## Quick Start

### Python
```python
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.5-flash",
    input="Tell me a short joke about programming."
)
print(interaction.steps[-1].content[0].text)
```

### JavaScript/TypeScript
```typescript
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    model: "gemini-3.5-flash",
    input: "Tell me a short joke about programming.",
});
console.log(interaction.steps.at(-1).content[0].text);
```

## Stateful Conversation

### Python
```python
interaction1 = client.interactions.create(
    model="gemini-3.5-flash",
    input="Hi, my name is Phil."
)
# Second turn — server remembers context
interaction2 = client.interactions.create(
    model="gemini-3.5-flash",
    input="What is my name?",
    previous_interaction_id=interaction1.id
)
print(interaction2.steps[-1].content[0].text)
```

### JavaScript/TypeScript
```typescript
const interaction1 = await client.interactions.create({
    model: "gemini-3.5-flash",
    input: "Hi, my name is Phil.",
});
const interaction2 = await client.interactions.create({
    model: "gemini-3.5-flash",
    input: "What is my name?",
    previous_interaction_id: interaction1.id,
});
console.log(interaction2.steps.at(-1).content[0].text);
```

## Deep Research Agent

Use `deep-research-preview-04-2026` for fast research or `deep-research-max-preview-04-2026` for maximum exhaustiveness. Agents require `background=True`.

### Python
```python
import time

interaction = client.interactions.create(
    agent="deep-research-preview-04-2026",
    input="Research the history of Google TPUs.",
    background=True
)
while True:
    interaction = client.interactions.get(interaction.id)
    if interaction.status == "completed":
        print(interaction.steps[-1].content[0].text)
        break
    elif interaction.status == "failed":
        print(f"Failed: {interaction.error}")
        break
    time.sleep(10)
```

### JavaScript/TypeScript
```typescript
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

// Start background research
const initialInteraction = await client.interactions.create({
    agent: "deep-research-preview-04-2026",
    input: "Research the history of Google TPUs.",
    background: true,
});

// Poll for results
while (true) {
    const interaction = await client.interactions.get(initialInteraction.id);
    if (interaction.status === "completed") {
        console.log(interaction.steps.at(-1).content[0].text);
        break;
    } else if (["failed", "cancelled"].includes(interaction.status)) {
        console.log(`Failed: ${interaction.status}`);
        break;
    }
    await new Promise(resolve => setTimeout(resolve, 10000));
}
```

Advanced features: collaborative planning, native visualization, MCP integration, file search, multimodal inputs. See [Deep Research docs](https://ai.google.dev/gemini-api/docs/interactions/deep-research.md.txt).

## Managed Agents

Managed agents run inside a sandboxed Linux environment hosted by Google. Fetch the [Managed Agents Quickstart](https://ai.google.dev/gemini-api/docs/managed-agents-quickstart.md.txt) before writing agent code.

### Antigravity Agent

The Antigravity agent (`antigravity-preview-05-2026`) is the general-purpose managed agent. It can execute code (Bash, Python, Node.js), manage files, browse the web, and use Google Search. See [Antigravity Agent docs](https://ai.google.dev/gemini-api/docs/antigravity-agent.md.txt) for capabilities, tools, multimodal input, and pricing.

#### Python
```python
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input="Write a Python script that generates the first 20 Fibonacci numbers and saves them to fibonacci.txt. Then read the file and print its contents.",
    environment="remote",
)

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

#### JavaScript/TypeScript
```typescript
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-05-2026",
    input: "Write a Python script that generates the first 20 Fibonacci numbers and saves them to fibonacci.txt. Then read the file and print its contents.",
    environment: "remote",
});

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

### Custom Agents