# WAN 2.7 Pro API Documentation

> LLM-optimized documentation for WAN 2.7 Pro. Copy into your AI assistant for integration help.

## Overview

**Model ID:** `wan-2.7-image-pro`
**Type:** Image Generation
**Credit Cost:** 2 credits per image

Higher quality Wan 2.7 tier with 4K support for text-to-image

## Endpoint

```
POST https://pixeldojo.ai/api/v1/models/wan-2.7-image-pro/run
```

## Authentication

All requests require an API key in the Authorization header:

```
Authorization: Bearer YOUR_API_KEY
```

Get your API key: https://pixeldojo.ai/api-platform/api-keys

## Input Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `prompt` | string | Yes | - | Text description of the image to generate |
| `size` | enum | No | 2K | Output resolution. Use a tier (1K/2K/4K — recommended) or an explicit width*height. 4K (and 4K-tier dimensions like 3840*2160) is supported by the Pro model for text-to-image only; 1K and 2K are supported by both models in all modes. (Options: 1K, 2K, 4K, 1280*1280, 1024*1024...) |
| `thinking_mode` | boolean | No | false | Improves text-to-image quality at the cost of slower generation |
| `n` | integer | No | 1 | Number of images to generate. Default mode: 1-4. Image-set mode (enable_sequential=true): up to 12; the model picks the actual count, capped at n. (min: 1, max: 12) |
| `enable_sequential` | boolean | No | false | When true, generates a coherent set of related images instead of independent variants. Disables thinking_mode and color_palette and lets n go up to 12. |
| `seed` | integer | No | - | Random seed (0–2147483647). Same seed + same inputs yields similar (but not identical) outputs. Omit for random. (min: 0, max: 2147483647) |
| `color_palette` | array | No | - | Custom color theme. Array of 3–10 (8 recommended) objects with `hex` (#RRGGBB) and `ratio` (e.g. "25.00%"); ratios must sum to 100.00%. Only effective when enable_sequential=false. |

## Supported Aspect Ratios

- `1:1`
- `16:9`
- `9:16`
- `4:3`
- `3:4`
- `5:4`
- `4:5`

## Capabilities

- Text to Image
- Image to Image
- NSFW Content

## Quick Start

### 1. Submit a Job

```bash
curl -X POST "https://pixeldojo.ai/api/v1/models/wan-2.7-image-pro/run" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A beautiful mountain landscape at golden hour, photorealistic",
    "aspect_ratio": "1:1"
  }'
```

**Response:**
```json
{
  "jobId": "job_abc123...",
  "status": "pending",
  "statusUrl": "https://pixeldojo.ai/api/v1/jobs/job_abc123",
  "creditCost": 2,
  "creditsRemaining": 95
}
```

### 2. Poll for Results

```bash
curl "https://pixeldojo.ai/api/v1/jobs/job_abc123" \
  -H "Authorization: Bearer YOUR_API_KEY"
```

**Completed Response:**
```json
{
  "jobId": "job_abc123...",
  "status": "completed",
  "output": {
    "images": ["https://temp.pixeldojo.ai/..."]
  },
  "creditCost": 2
}
```

## Python Example

```python
import requests
import time

API_KEY = "YOUR_API_KEY"

# Submit job
response = requests.post(
    "https://pixeldojo.ai/api/v1/models/wan-2.7-image-pro/run",
    headers={
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    },
    json={
        "prompt": "A beautiful mountain landscape at golden hour, photorealistic",
        "aspect_ratio": "1:1"
    }
)

job = response.json()
job_id = job["jobId"]

# Poll for completion
while True:
    status_response = requests.get(
        f"https://pixeldojo.ai/api/v1/jobs/{'{job_id}'}",
        headers={"Authorization": f"Bearer {API_KEY}"}
    )
    status = status_response.json()
    
    if status["status"] == "completed":
        print("Output:", status["output"])
        break
    elif status["status"] == "failed":
        print("Error:", status.get("error"))
        break
    
    time.sleep(2)
```

## JavaScript Example

```javascript
const API_KEY = 'YOUR_API_KEY';

// Submit job
const submitResponse = await fetch('https://pixeldojo.ai/api/v1/models/wan-2.7-image-pro/run', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${API_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    prompt: 'A beautiful mountain landscape at golden hour, photorealistic',
    aspect_ratio: '1:1'
  })
});

const job = await submitResponse.json();

// Poll for completion
const pollForResult = async (jobId) => {
  while (true) {
    const statusResponse = await fetch(`https://pixeldojo.ai/api/v1/jobs/${jobId}`, {
      headers: { 'Authorization': `Bearer ${API_KEY}` }
    });
    const status = await statusResponse.json();
    
    if (status.status === 'completed') return status.output;
    if (status.status === 'failed') throw new Error(status.error);
    
    await new Promise(r => setTimeout(r, 2000));
  }
};

const output = await pollForResult(job.jobId);
console.log('Output:', output);
```

## Error Codes

| Code | Status | Description |
|------|--------|-------------|
| `unauthorized` | 401 | Invalid or missing API key |
| `insufficient_credits` | 402 | Not enough credits |
| `invalid_request` | 400 | Invalid parameters |
| `model_not_found` | 404 | Model ID not found |
| `rate_limited` | 429 | Too many requests |
| `internal_error` | 500 | Server error |

## Links

- **Full Documentation:** https://pixeldojo.ai/api-platform/wan-2.7-image-pro
- **API Keys:** https://pixeldojo.ai/api-platform/api-keys
- **Buy Credits:** https://pixeldojo.ai/api-platform/buy-credits
- **All Models:** https://pixeldojo.ai/api/v1/models
- **OpenAPI Spec:** https://pixeldojo.ai/api/openapi