Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension
gpt-image-2/api/v1/gpt_image_2/text_to_image
运行信息
模型
gpt-image-2
提供方
OpenAI
服务
Gpt Image 2
Endpoint
Text To Image
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. 重启 Claude Code
3. 粘贴这个 prompt：生成一张图像："Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
1. codex plugin install runapi-mcp@agents
2. 重启 Codex
3. 粘贴这个 prompt：生成一张图像："Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
1. npx @runapi.ai/mcp init cursor
2. 重启 Cursor
3. 粘贴这个 prompt：生成一张图像："Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
1. npx @runapi.ai/mcp init windsurf
2. 重启 Windsurf
3. 粘贴这个 prompt：生成一张图像："Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "gpt-image-2",
"prompt": "Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
}
JSON
import { GptImage2Client } from "@runapi.ai/gpt-image-2";
const client = new GptImage2Client({
apiKey: process.env.RUNAPI_API_KEY,
});
const result = await client.textToImage.run({
"model": "gpt-image-2",
"prompt": "Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
});
console.log(result.id);
require "runapi/gpt_image_2"
client = RunApi::GptImage2::Client.new
result = client.text_to_image.run(
model: "gpt-image-2",
prompt: "Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension"
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"model\":\"gpt-image-2\",\"prompt\":\"Present a clear, 45° top-down isometric miniature 3D cartoon scene of [STADIUM], with soft refined textures, realistic PBR materials, and gentle lifelike lighting. Use a clean solid [COLOR] background. At the top-center, display the name of this stadium in large bold text, then directly beneath it show its real seating capacity in medium text, and place the official logo associated with this stadium below the capacity. All text must match the background contrast automatically (white or black). Centered layout, square 1080x1080 dimension\"}")
req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/gpt_image_2/text_to_image", body)
if err != nil {
log.Fatal(err)
}
req.Header.Set("Authorization", "Bearer "+os.Getenv("RUNAPI_API_KEY"))
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
log.Fatal(err)
}
defer resp.Body.Close()
fmt.Println(resp.Status)
}
gpt-image-2/api/v1/gpt_image_2/text_to_image获取 API Key
Low-angle fashion campaign photograph of a confident model holding a large [product name] very close to the camera, exaggerated perspective with the hand and product dominating the foreground, full-body pose visible in the background, wide stance, dynamic posture, clean pure white studio background, high-key lighting, sharp focus on product, slight depth of field on the model, bold colorful outfit with strong contrast tones, modern beauty advertising aesthetic, ultra-clean composition, commercial studio photography, glossy packaging detail visible, crisp shadows
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "gpt-image-2",
"prompt": "Low-angle fashion campaign photograph of a confident model holding a large [product name] very close to the camera, exaggerated perspective with the hand and product dominating the foreground, full-body pose visible in the background, wide stance, dynamic posture, clean pure white studio background, high-key lighting, sharp focus on product, slight depth of field on the model, bold colorful outfit with strong contrast tones, modern beauty advertising aesthetic, ultra-clean composition, commercial studio photography, glossy packaging detail visible, crisp shadows"
}
JSON
Create an infographic image of [LANDMARK], combining a real photograph of the landmark with blueprint-style technical annotations and diagrams overlaid on the image. Include the title “[LANDMARK]” in a hand-drawn box in the corner. Add white chalk-style sketches showing key structural data, important measurements, material quantities, internal diagrams, load-flow arrows, cross-sections, floor plans, and notable architectural or engineering features. Style: blueprint aesthetic with white line drawings on the photograph, technical/architectural annotation style, educational infographic feel, with the real environment visible behind the annotations.
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "gpt-image-2",
"prompt": "Create an infographic image of [LANDMARK], combining a real photograph of the landmark with blueprint-style technical annotations and diagrams overlaid on the image. Include the title “[LANDMARK]” in a hand-drawn box in the corner. Add white chalk-style sketches showing key structural data, important measurements, material quantities, internal diagrams, load-flow arrows, cross-sections, floor plans, and notable architectural or engineering features. Style: blueprint aesthetic with white line drawings on the photograph, technical/architectural annotation style, educational infographic feel, with the real environment visible behind the annotations."
}
JSON