openai/gpt-image-1/text-to-image

文生图

Openai GPT Image 1 Text-to-Image API by OpenAI

openai/gpt-image-1/text-to-image

Text-to-image

OpenAI GPT Image-1 generates images from text prompts from OpenAI's latest text-to-image model, ideal for creating visual assets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

输入

提示词 *

尺寸

Quality

Output format

Output compression

数量

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 $0.009。$10 可运行约 1111 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": "openai/gpt-image-1/text-to-image",  # Required. model name
    "prompt": "A beautiful landscape with mountains and lake",  # Required. The positive prompt for the generation
    "quality": "medium",  # The quality of the generated image. options: low | medium | high
    "size": "1024x1024",  # The size of the generated media in pixels (widthxheight). options: 1024x1024 | 1024x1536 | 1536x1024
    "output_format": "png",  # Output image format. options: png | jpeg
    "output_compression": 100,  # Compression level for output image. (min: 0, max: 100)
    "n": 1,  # Number of images to generate. (min: 1, max: 10)
    "enable_sync_mode": False,  # If set to true, the function waits for final output before returning
    "enable_base64_output": False,  # If enabled, output can be encoded as BASE64 instead of URL
}

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": "openai/gpt-image-1/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: 9必填: 2可选: 7

modelstringrequired

model name

Default: "openai/gpt-image-1/text-to-image"

promptstringrequired

The positive prompt for the generation.

qualitystring

The quality of the generated image.

Default: "medium"

lowmediumhigh

sizestring

The size of the generated media in pixels (widthxheight).

Default: "1024x1024"

1024x10241024x15361536x1024

output_formatstring

Output image format.

Default: "png"

pngjpeg

output_compressioninteger

Compression level for output image.

Default: 100Min: 0Max: 100

ninteger

Number of images to generate.

Default: 1Min: 1Max: 10

enable_sync_modeboolean

If set to true, the function waits for final output before returning.

Default: false

enable_base64_outputboolean

If enabled, output can be encoded as BASE64 instead of URL.

Default: false

请求体示例

{
  "model": "openai/gpt-image-1/text-to-image",
  "prompt": "A beautiful landscape",
  "quality": "medium",
  "size": "1024x1024",
  "output_format": "png",
  "output_compression": 100,
  "n": 1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}

Output Schema

API 返回包含生成输出 URL 的 prediction 响应。

created_atstring

ISO timestamp of when the request was created.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content (empty 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 300+ 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 300+ 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 300+ 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/result/{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": {
        "type": "object",
        "required": [
          "model",
          "prompt"
        ],
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "openai/gpt-image-1/text-to-image"
          },
          "prompt": {
            "type": "string",
            "minLength": 1,
            "description": "The positive prompt for the generation."
          },
          "quality": {
            "type": "string",
            "default": "medium",
            "description": "The quality of the generated image.",
            "enum": [
              "low",
              "medium",
              "high"
            ]
          },
          "size": {
            "type": "string",
            "default": "1024x1024",
            "description": "The size of the generated media in pixels (widthxheight).",
            "enum": [
              "1024x1024",
              "1024x1536",
              "1536x1024"
            ],
            "x-ui-component": "select width*height"
          },
          "output_format": {
            "type": "string",
            "default": "png",
            "description": "Output image format.",
            "enum": [
              "png",
              "jpeg"
            ]
          },
          "output_compression": {
            "type": "integer",
            "default": 100,
            "minimum": 0,
            "maximum": 100,
            "description": "Compression level for output image."
          },
          "n": {
            "type": "integer",
            "default": 1,
            "minimum": 1,
            "maximum": 10,
            "description": "Number of images to generate."
          },
          "enable_sync_mode": {
            "type": "boolean",
            "default": false,
            "disabled": true,
            "description": "If set to true, the function waits for final output before returning."
          },
          "enable_base64_output": {
            "type": "boolean",
            "default": false,
            "disabled": true,
            "description": "If enabled, output can be encoded as BASE64 instead of URL."
          }
        },
        "x-order-properties": [
          "model",
          "prompt",
          "size",
          "quality",
          "output_format",
          "output_compression",
          "n",
          "enable_sync_mode",
          "enable_base64_output"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "created_at": {
            "type": "string",
            "format": "date-time",
            "description": "ISO timestamp of when the request was created."
          },
          "has_nsfw_contents": {
            "type": "array",
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            }
          },
          "id": {
            "type": "string",
            "description": "Unique identifier for the prediction."
          },
          "model": {
            "type": "string",
            "description": "Model ID used for the prediction."
          },
          "outputs": {
            "type": "array",
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            }
          },
          "status": {
            "type": "string",
            "description": "Status of the task: created, processing, completed, or failed."
          },
          "urls": {
            "type": "object",
            "description": "Object containing related API endpoints."
          }
        }
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  }
}

LLM 友好的提示词模板

# openai/gpt-image-1/text-to-image

> OpenAI GPT Image-1 generates images from text prompts from OpenAI's latest text-to-image model, ideal for creating visual assets. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.


## 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**: `openai/gpt-image-1/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: `"openai/gpt-image-1/text-to-image"`

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation.

- **`size`** (`string`, _optional_):
  The size of the generated media in pixels (widthxheight).
  - Default: `"1024x1024"`
  - Options: "1024x1024", "1024x1536", "1536x1024"

- **`quality`** (`string`, _optional_):
  The quality of the generated image.
  - Default: `"medium"`
  - Options: "low", "medium", "high"

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

- **`output_compression`** (`integer`, _optional_):
  Compression level for output image.
  - Default: `100`
  - Min: 0
  - Max: 100

- **`n`** (`integer`, _optional_):
  Number of images to generate.
  - Default: `1`
  - Min: 1
  - Max: 10

- **`enable_sync_mode`** (`boolean`, _optional_):
  If set to true, the function waits for final output before returning.
  - Default: `false`

- **`enable_base64_output`** (`boolean`, _optional_):
  If enabled, output can be encoded as BASE64 instead of URL.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "openai/gpt-image-1/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "openai/gpt-image-1/text-to-image",
  "prompt": "",
  "size": "1024x1024",
  "quality": "medium",
  "output_format": "png",
  "output_compression": 100,
  "n": 1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

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

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

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty 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
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "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": "openai/gpt-image-1/text-to-image",
  "prompt": "",
  "size": "1024x1024",
  "quality": "medium",
  "output_format": "png",
  "output_compression": 100,
  "n": 1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}'

# 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/openai/gpt-image-1/text-to-image)

暂无可用示例

加载中...

OpenAI GPT Image 1

GPT Image 1 is OpenAI’s latest multimodal image generation model, built to understand both text and image inputs and produce visually coherent, high-quality image outputs. It combines the reasoning power of GPT-4-Turbo with DALL·E-class visual synthesis, allowing for creative, controllable, and context-aware generation across illustration, photography, design, and visualization tasks.

🧠 Key Features

Multimodal Understanding
Accepts both text and image inputs, enabling style transfer, editing, or contextual composition.
Flexible Styles
Produces photorealistic renders, stylized artwork, concept art, infographics, and 3D-style illustrations.
High Visual Fidelity
Maintains object relationships, lighting consistency, and color balance with strong adherence to prompts.
Accurate Text Rendering
Capable of generating clean typography, ideal for posters, memes, comics, and branding visuals.
Knowledge-Grounded Creativity
Uses GPT-4’s world knowledge to generate factual, contextually appropriate visuals.

⚙️ Parameters

Parameter	Description
`prompt`	Required text description of the desired image
`size`	Supports `1024×1024`, `1024×1536`, and `1536×1024`
`quality`	Choose between `low`, `medium`, and `high`

💡 Tips for Best Results

Write prompts that specify style, subject, composition, and lighting.
Example:

A small robot exploring an abandoned city, cartoon style, bright colors.
Use high quality for detailed or large-format outputs.
Prefer landscape (1536×1024) for cinematic or wide compositions.
Prefer portrait (1024×1536) for characters or vertical art.

📝 Notes

All generated content follows OpenAI’s safety and content policies.
If a prompt triggers moderation, rephrase or simplify it.
This model supports multi-image input via API, enabling creative editing and composition workflows.
For performance- and latency-sensitive cases, use medium quality as the balanced default.

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GPT Image 1 Mini is a cost-efficient multimodal OpenAI model powered by GPT-5 that turns text or image prompts into high-quality images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Openai GPT Image-1 Mini Edit

GPT Image 1 Mini is a cost-efficient, natively multimodal OpenAI model that pairs GPT-5 language understanding with compact image editing and generation from text and image inputs to produce high-quality images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

GPT Image 2 Developer Edit

GPT Image 2 Developer Edit applies natural-language instructions to one or more reference images, with common aspect ratios and 1k, 2k, or supported 4k output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

GPT Image 2 Developer Text-to-Image

GPT Image 2 Developer Text-to-Image generates polished visuals from natural-language prompts, with common aspect ratios and 1k, 2k, or supported 4k output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

MAI-Image-2.5-Flash Text-to-image

Microsoft's fast, cost-optimized text-to-image generation model, creating high-quality images at lower cost using the same diffusion-based architecture as MAI-Image-2.5.

From

$0.03/张