krea-2-turbo/text-to-image

文生图

Krea 2 Trubo Text-to-Image API

krea-2-turbo/text-to-image

Text-to-image

Generate high-fidelity images from text in seconds with Krea 2 Turbo, the speed-optimized open-source version of Krea 2, preserving its aesthetic range for rapid ideation.

输入

提示词 *

Image size

宽高比已锁定：修改一边时另一边会等比缩放。点击锁图标可自由编辑。

图片数量

随机种子

Output format

输出

空闲

生成的图片将在这里显示

配置参数后点击运行开始生成

每次运行将花费 $0.008。$10 可运行约 1250 次。

你可以继续：

图生视频图生图

参数

代码示例
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "krea-2-turbo/text-to-image",  # Required. model name
    "prompt": "A beautiful landscape with mountains and lake",  # Required. The text prompt describing the image to generate
    "image_size": "square_hd",  # Output image size. options: square_hd | square | portrait_3_4 | portrait_9_16 | landscape_4_3 | landscape_16_9
    "num_images": 1,  # Number of images to generate. (min: 1, max: 4)
    "seed": 1,  # Seed for reproducible generation
    "output_format": "png",  # Output image format. options: png | jpeg
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

安装

安装所需的依赖包。

pip install requests

认证

所有 API 请求需要通过 API Key 进行认证。您可以在 Atlas Cloud 控制台获取 API Key。

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP 请求头

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

保护好您的 API Key

切勿在客户端代码或公开仓库中暴露您的 API Key。请使用环境变量或后端代理。

提交请求

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

提交请求

提交一个异步生成请求。API 返回一个 prediction ID，您可以用它来检查状态和获取结果。

POST/api/v1/model/generateImage

请求体

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "krea-2-turbo/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

响应

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

检查状态

轮询 prediction 端点以检查请求的当前状态。

GET/api/v1/model/prediction/{prediction_id}

轮询示例

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

状态值

processing请求仍在处理中。

completed生成完成，输出可用。

succeeded生成成功，输出可用。

failed生成失败，请检查 error 字段。

完成响应

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

上传文件

将文件上传到 Atlas Cloud 存储，获取可在 API 请求中使用的 URL。使用 multipart/form-data 上传。

POST/api/v1/model/uploadMedia

上传示例

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

响应

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

以下参数在请求体中被接受。

总计: 6必填: 2可选: 4

modelstringrequired

model name

Default: "krea-2-turbo/text-to-image"

promptstringrequired

The text prompt describing the image to generate.

image_sizestring

Output image size. Choose a preset or specify custom dimensions.

Default: "square_hd"

square_hdsquareportrait_3_4portrait_9_16landscape_4_3landscape_16_9

num_imagesinteger

Number of images to generate.

Default: 1Min: 1Max: 4

seedinteger

Seed for reproducible generation. Omit for a random seed.

output_formatstring

Output image format.

Default: "png"

pngjpeg

请求体示例

{
  "model": "krea-2-turbo/text-to-image",
  "prompt": "A beautiful landscape",
  "image_size": "square_hd",
  "num_images": 1,
  "output_format": "png"
}

Output Schema

API 返回包含生成输出 URL 的 prediction 响应。

modelstring

model name

Default: "krea-2-turbo/text-to-image"

created_atstring

ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

idstring

Unique identifier for the prediction.

outputsarray

Array of URLs to the generated images. Null when status is not completed.

statusstring

Status of the task: created, processing, completed, or failed.

响应示例

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills 将 400+ AI 模型直接集成到您的 AI 编程助手中。一条命令安装，即可用自然语言生成图像、视频和与 LLM 对话。

支持的客户端

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ 支持的客户端

安装

npx skills add AtlasCloudAI/atlas-cloud-skills

设置 API Key

从 Atlas Cloud 控制台获取 API Key，并将其设置为环境变量。

export ATLASCLOUD_API_KEY="your-api-key-here"

功能

安装后，您可以在 AI 助手中使用自然语言访问所有 Atlas Cloud 模型。

图像生成使用 Nano Banana 2、Z-Image 等模型生成图像。

视频创作使用 Kling、Vidu、Veo 等模型从文本或图像创建视频。

LLM 对话与 Qwen、DeepSeek 等大语言模型对话。

媒体上传上传本地文件用于图像编辑和图生视频工作流。

MCP Server

Atlas Cloud MCP Server 通过 Model Context Protocol 将您的 IDE 与 400+ AI 模型连接。支持任何兼容 MCP 的客户端。

支持的客户端

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ 支持的客户端

安装

npx -y atlascloud-mcp

配置

将以下配置添加到您的 IDE 的 MCP 设置文件中。

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

可用工具

atlas_generate_image从文本提示生成图像。

atlas_generate_video从文本或图像创建视频。

atlas_chat与大语言模型对话。

atlas_list_models浏览 400+ 可用 AI 模型。

atlas_quick_generate一步式内容创建，自动选择最佳模型。

atlas_upload_media上传本地文件用于 API 工作流。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        },
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        },
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "schema": {
              "type": "string",
              "description": "Request ID"
            },
            "required": true
          }
        ]
      },
      "x-api-name": "model_result"
    }
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "krea-2-turbo/text-to-image"
          },
          "prompt": {
            "description": "The text prompt describing the image to generate.",
            "type": "string",
            "minLength": 1
          },
          "image_size": {
            "description": "Output image size. Choose a preset or specify custom dimensions.",
            "type": "string",
            "default": "square_hd",
            "enum": [
              "square_hd",
              "square",
              "portrait_3_4",
              "portrait_9_16",
              "landscape_4_3",
              "landscape_16_9"
            ],
            "x-ui-component": "select",
            "x-enum-labels": {
              "square_hd": "Square HD (1024×1024)",
              "square": "Square (512×512)",
              "portrait_3_4": "Portrait 3:4",
              "portrait_9_16": "Portrait 9:16",
              "landscape_4_3": "Landscape 4:3",
              "landscape_16_9": "Landscape 16:9"
            }
          },
          "num_images": {
            "description": "Number of images to generate.",
            "type": "integer",
            "default": 1,
            "minimum": 1,
            "maximum": 4
          },
          "seed": {
            "description": "Seed for reproducible generation. Omit for a random seed.",
            "type": "integer"
          },
          "output_format": {
            "description": "Output image format.",
            "type": "string",
            "default": "png",
            "enum": [
              "png",
              "jpeg"
            ],
            "x-ui-component": "select"
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "image_size",
          "num_images",
          "seed",
          "output_format"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "krea-2-turbo/text-to-image"
          },
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated images. Null when status is not completed.",
            "items": {
              "type": "string"
            },
            "nullable": true,
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  }
}

LLM 友好的提示词模板

# krea-2-turbo/text-to-image

> Generate high-fidelity images from text in seconds with Krea 2 Turbo, the speed-optimized open-source version of Krea 2, preserving its aesthetic range for rapid ideation.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `krea-2-turbo/text-to-image`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"krea-2-turbo/text-to-image"`

- **`prompt`** (`string`, _required_):
  The text prompt describing the image to generate.

- **`image_size`** (`string`, _optional_):
  Output image size. Choose a preset or specify custom dimensions.
  - Default: `"square_hd"`
  - Options: "square_hd", "square", "portrait_3_4", "portrait_9_16", "landscape_4_3", "landscape_16_9"

- **`num_images`** (`integer`, _optional_):
  Number of images to generate.
  - Default: `1`
  - Min: 1
  - Max: 4

- **`seed`** (`integer`, _optional_):
  Seed for reproducible generation. Omit for a random seed.

- **`output_format`** (`string`, _optional_):
  Output image format.
  - Default: `"png"`
  - Options: "png", "jpeg"



**Required Parameters Example**:

```json
{
  "model": "krea-2-turbo/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "krea-2-turbo/text-to-image",
  "prompt": "",
  "image_size": "square_hd",
  "num_images": 1,
  "seed": 0,
  "output_format": "png"
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"krea-2-turbo/text-to-image"`

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated images. Null when status is not completed.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "model": "krea-2-turbo/text-to-image",
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "krea-2-turbo/text-to-image",
  "prompt": "",
  "image_size": "square_hd",
  "num_images": 1,
  "seed": 0,
  "output_format": "png"
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/krea-2-turbo/text-to-image)

A colorful alpine meadow blooming beneath towering snow-capped mountains, butterflies dancing among vibrant flowers, crystal stream flowing gently through the valley, cinematic realism, breathtaking scenery

加载中...

Krea 2 Turbo

Krea 2 Turbo is a high-fidelity text-to-image model that generates images from text prompts in seconds. Tuned for speed without sacrificing detail, it delivers crisp, aesthetically strong results with flexible aspect ratios and optional prompt expansion — ideal for rapid creative iteration and production-ready visuals.

🌟 Key Features

✏️ Text-to-Image

Generate high-fidelity images from detailed text prompts with strong semantic understanding and photorealistic quality.

⚡ Turbo Speed

Optimized for fast generation, delivering crisp results in seconds.

📐 Flexible Output Sizes

Choose from six standard presets — square HD, portrait, landscape — or specify custom dimensions to match your layout.

🔁 Reproducible Results

Pin a seed value to reproduce or iterate on a specific generation, enabling systematic prompt refinement.

🖼 Batch Generation

Request up to 4 images per call with num_images to explore multiple variations at once.

⚙️ Parameters

Parameter	Required	Description
`prompt`	✅	Text description of the image to generate.
`image_size`	❌	Output size preset: `square_hd` (default), `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9`. Also accepts custom `WxH` (e.g. `1024x768`).
`num_images`	❌	Number of images to generate (1–4, default: 1).
`seed`	❌	Seed for reproducible output. Omit for a random seed.
`output_format`	❌	Output format: `png` (default) or `jpeg`.

💲 Pricing

Billing Standard	Price
Per megapixel	$0.0088

💡 Prompt Tips

A vintage travel poster for Mars, bold retro typography, warm sunset palette, rocket silhouette, textured paper grain, cinematic composition.

Be specific about subject, environment, lighting, and camera angle for best results.
Fix seed when iterating on a prompt to isolate the effect of each change.
Request multiple images with num_images to explore variations in a single call.

🎯 Use Cases

Creative Illustration — Generate concept art, characters, and environments from descriptive text prompts.
Marketing Visuals — Produce eye-catching posters, banners, and ad creatives quickly.
Social Media Content — Generate scroll-stopping visuals in portrait or square formats for any platform.
Rapid Prototyping — Iterate on creative directions at scale before committing to production assets.
Design Exploration — Batch-generate variations to compare styles, compositions, and color palettes.

📝 Notes

prompt is the only required field (besides model).
image_size accepts either a preset name or a custom WxH string (e.g. 1024x768).
Task status values: created, processing, completed, failed.
Generated image URLs are returned in outputs once status is completed.

Krea 2 Trubo Text-to-Image API

输入

输出

参数

代码示例

安装

认证

HTTP 请求头

提交请求

提交请求

请求体

响应

检查状态

轮询示例

状态值

完成响应

上传文件

上传示例

响应

Input Schema

请求体示例

Output Schema

响应示例

Atlas Cloud Skills

支持的客户端

安装

设置 API Key

功能

MCP Server

支持的客户端

安装

配置

可用工具

API Schema

LLM 友好的提示词模板

Krea 2 Turbo

🌟 Key Features

✏️ Text-to-Image

⚡ Turbo Speed

📐 Flexible Output Sizes

🔁 Reproducible Results

🖼 Batch Generation

⚙️ Parameters

💲 Pricing

💡 Prompt Tips

🎯 Use Cases

📝 Notes

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输入

输出

参数

代码示例

安装

认证

HTTP 请求头

提交请求

提交请求

请求体

响应

检查状态

轮询示例

状态值