Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible.
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："Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
1. codex plugin install runapi-mcp@agents
2. 重启 Codex
3. 粘贴这个 prompt：生成一张图像："Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
1. npx @runapi.ai/mcp init cursor
2. 重启 Cursor
3. 粘贴这个 prompt：生成一张图像："Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
1. npx @runapi.ai/mcp init windsurf
2. 重启 Windsurf
3. 粘贴这个 prompt：生成一张图像："Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
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": "Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
}
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": "Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
});
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: "Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible."
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"model\":\"gpt-image-2\",\"prompt\":\"Food specimen dissected like a museum natural history discovery: one half showing the natural exterior surface, the other half precisely cut to reveal the core structure. Pure black velvet background. Handwritten serif annotations pointing to each layer with thin leader lines. Audubon naturalist illustration meets Caravaggio dramatic lighting. Every material rendered with true physical texture — seeds, juice, cellular structure visible.\"}")
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