# Gemini Omni — Text To Video

> AI model for generating video content

## Overview

- **Model ID**: `gemini-omni-text-to-video`
- **Category**: video
- **Provider**: google
- **Source Type**: Closed Source Model
- **Status**: model_ready
- **Screenshot**: `https://assets.modelslab.ai/generations/15a3427d-6311-4c41-939f-63711d22ebe3.webp`

## API Information

This model can be used via our HTTP API. See the API documentation and usage examples below.

### Endpoint

- **URL**: `https://modelslab.com/api/v7/video-fusion/text-to-video`
- **Method**: POST

### Parameters

- **`prompt`** (required): 
  - Type: textarea
  - Example: Enter prompt for video

- **`aspect_ratio`** (required): The aspect ratio of the generated video — 16:9 is wide, 9:16 for Vertical video generation 
  - Type: select (options: 16:9, 9:16)

- **`duration`** (required): Supported duration 3-10 Sec
  - Type: number (range: 3-10)

- **`model_id`** (optional): model_id is required for selecting the right model for API
  - Type: text

## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://modelslab.com/api/v7/video-fusion/text-to-video \
  --header "Content-Type: application/json" \
  --data '{
    "key": "YOUR_API_KEY",
    "model_id": "gemini-omni-text-to-video",
    "prompt": "A wide, eye-level cinematic shot captures a man walking slowly across a frost-covered bridge at dawn, his hands tucked into the pockets of a heavy coat. Pale morning light glows faintly through soft, curling fog that clings to the bridge railings. In the distance, bare trees fade into the mist, their skeletal branches barely visible. The pace is unhurried and reflective, evoking a naturalistic and quiet mood. The scene is filled with subtle, atmospheric sounds—faint footsteps crunching on frost, steady breaths in the cold air, and the distant caw of a crow echoing across the stillness.",
    "aspect_ratio": "16:9",
    "duration": "5"
  }'
```

### Python

```python
import requests

response = requests.post(
    "https://modelslab.com/api/v7/video-fusion/text-to-video",
    headers={
        "Content-Type": "application/json"
    },
    json={
        "key": "YOUR_API_KEY",
        "model_id": "gemini-omni-text-to-video",
        "prompt": "A wide, eye-level cinematic shot captures a man walking slowly across a frost-covered bridge at dawn, his hands tucked into the pockets of a heavy coat. Pale morning light glows faintly through soft, curling fog that clings to the bridge railings. In the distance, bare trees fade into the mist, their skeletal branches barely visible. The pace is unhurried and reflective, evoking a naturalistic and quiet mood. The scene is filled with subtle, atmospheric sounds—faint footsteps crunching on frost, steady breaths in the cold air, and the distant caw of a crow echoing across the stillness.",
        "aspect_ratio": "16:9",
        "duration": "5"
    }
)

print(response.json())
```

### JavaScript

```javascript
fetch("https://modelslab.com/api/v7/video-fusion/text-to-video", {
  method: "POST",
  headers: {
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    "key": "YOUR_API_KEY",
    "model_id": "gemini-omni-text-to-video",
    "prompt": "A wide, eye-level cinematic shot captures a man walking slowly across a frost-covered bridge at dawn, his hands tucked into the pockets of a heavy coat. Pale morning light glows faintly through soft, curling fog that clings to the bridge railings. In the distance, bare trees fade into the mist, their skeletal branches barely visible. The pace is unhurried and reflective, evoking a naturalistic and quiet mood. The scene is filled with subtle, atmospheric sounds—faint footsteps crunching on frost, steady breaths in the cold air, and the distant caw of a crow echoing across the stillness.",
    "aspect_ratio": "16:9",
    "duration": "5"
  })
})
.then(response => response.json())
.then(data => console.log(data));
```

## Integration Options

### CLI

Install: `curl -fsSL https://modelslab.sh/install.sh | sh` or `brew install modelslab/tap/modelslab`

```bash
modelslab auth login                                    # Authenticate
modelslab models search "gemini-omni-text-to-video"                       # Find this model
modelslab models detail --id gemini-omni-text-to-video                    # Get model details
modelslab generate image --prompt "..." --model gemini-omni-text-to-video  # Generate with model
modelslab config set generation.default_model gemini-omni-text-to-video   # Set as default
```

- Website: https://modelslab.sh
- GitHub: https://github.com/ModelsLab/modelslab-cli

### MCP Servers (Model Context Protocol)

For Claude Code, Cursor, VS Code, Windsurf, and any MCP-compatible agent.

- Generation: `https://modelslab.com/mcp/v7` (API key auth, 23 tools)
- Agent Control Plane: `https://modelslab.com/mcp/agents` (Bearer token auth, 10 tools)

Claude Code config (`~/.claude/settings.json`):

```json
{
  "mcpServers": {
    "modelslab-v7": {
      "url": "https://modelslab.com/mcp/v7",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}
```

- Documentation: https://docs.modelslab.com/mcp-web-api/overview

### Agent Skills

Install skill files directly into AI coding agents:

```bash
npx skills add modelslab/skills --all                          # All skills
npx skills add modelslab/skills --skill image-generation       # Specific skill
npx skills add modelslab/skills --all -a claude-code -a cursor # Target agents
```

- GitHub: https://github.com/ModelsLab/skills
- Documentation: https://docs.modelslab.com/agent-skills

### SDKs

- Python: `pip install modelslab`
- TypeScript: `npm install modelslab`
- PHP: `composer require modelslab/modelslab`
- Go: `go get github.com/modelslab/modelslab-go`
- Dart: `dart pub add modelslab`

## Links

- [Model Playground](https://modelslab.com/models/gemini-omni-text-to-video/gemini-omni-text-to-video)
- [API Documentation](https://docs.modelslab.com)
- [ModelsLab Platform](https://modelslab.com)