Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain
/api/v1/runapi/text_to_image
RUN DETAILS
Model
Provider
Runapi
Service
Runapi
Endpoint
Text To Image
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate an image: "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate an image: "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate an image: "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate an image: "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
curl -X POST https://runapi.ai/api/v1/runapi/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"prompt": "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
}
JSON
import { RunapiClient } from "@runapi.ai/runapi";
const client = new RunapiClient({
apiKey: process.env.RUNAPI_API_KEY,
});
const result = await client.textToImage.run({
"prompt": "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
});
console.log(result.id);
require "runapi/runapi"
client = RunApi::Runapi::Client.new
result = client.text_to_image.run(
prompt: "Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain"
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"prompt\":\"Five friends in their thirties gathered around a large wooden dining table after dinner — wine glasses, burned-down candles, half-eaten plates — all laughing mid-conversation, candlelight plus warm pendant lamp creating golden ambient light, documentary photography style with slight motion blur on gesturing hands, shot with 24mm wide-angle lens showing the full table scene, subtle film grain\"}")
req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/runapi/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)
}
Close-up of a weathered explorer in their 50s with intense blue eyes, silver-streaked dark hair, worn leather jacket, dramatic side lighting, shallow depth of field, 85mm lens, golden hour, photorealistic portrait photography
curl -X POST https://runapi.ai/api/v1/runapi/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"prompt": "Close-up of a weathered explorer in their 50s with intense blue eyes, silver-streaked dark hair, worn leather jacket, dramatic side lighting, shallow depth of field, 85mm lens, golden hour, photorealistic portrait photography"
}
JSON
Mid-thirties woman standing in the doorway of a worn brick building, late afternoon window light streaming from the left, wearing a natural linen shirt with reading glasses pushed up on forehead, shallow depth of field, warm ochres and muted greens color palette, documentary street portraiture style, shot with 35mm lens
curl -X POST https://runapi.ai/api/v1/runapi/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"prompt": "Mid-thirties woman standing in the doorway of a worn brick building, late afternoon window light streaming from the left, wearing a natural linen shirt with reading glasses pushed up on forehead, shallow depth of field, warm ochres and muted greens color palette, documentary street portraiture style, shot with 35mm lens"
}
JSON
Close-up studio portrait of a man in his fifties with grey hair, dark charcoal seamless backdrop, single softbox positioned at 45 degrees, rim light on right shoulder, dark turtleneck, medium format film look with cool desaturated tones, sharp focus on eyes
curl -X POST https://runapi.ai/api/v1/runapi/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"prompt": "Close-up studio portrait of a man in his fifties with grey hair, dark charcoal seamless backdrop, single softbox positioned at 45 degrees, rim light on right shoulder, dark turtleneck, medium format film look with cool desaturated tones, sharp focus on eyes"
}
JSON
Full-length shot of an early-twenties man standing in a wheat field at golden hour, warm backlight creating a golden halo around curly hair, weathered denim jacket, looking slightly away from camera, foreground wheat stalks blurred, amber and pale blue color palette, lifestyle photography, 85mm wide aperture lens
curl -X POST https://runapi.ai/api/v1/runapi/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"prompt": "Full-length shot of an early-twenties man standing in a wheat field at golden hour, warm backlight creating a golden halo around curly hair, weathered denim jacket, looking slightly away from camera, foreground wheat stalks blurred, amber and pale blue color palette, lifestyle photography, 85mm wide aperture lens"
}
JSON
35mm film photography portrait, harsh convenience store fluorescent lighting mixed with colorful neon signs from outside, high contrast, cinematic street editorial mood, late-night atmosphere, young woman wearing oversized white shirt and black mini skirt, messy high ponytail, seductive urban portrait energy, shot on analog film with visible grain
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": "35mm film photography portrait, harsh convenience store fluorescent lighting mixed with colorful neon signs from outside, high contrast, cinematic street editorial mood, late-night atmosphere, young woman wearing oversized white shirt and black mini skirt, messy high ponytail, seductive urban portrait energy, shot on analog film with visible grain"
}
JSON
A fluffy white Persian cat with bright blue eyes sitting gracefully on a sunlit windowsill, soft morning light streaming through lace curtains creating gentle dappled shadows, warm golden tones, shallow depth of field with sharp focus on the cat's face, photorealistic, shot on medium format camera
curl -X POST https://runapi.ai/api/v1/imagen_4/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "imagen-4",
"prompt": "A fluffy white Persian cat with bright blue eyes sitting gracefully on a sunlit windowsill, soft morning light streaming through lace curtains creating gentle dappled shadows, warm golden tones, shallow depth of field with sharp focus on the cat's face, photorealistic, shot on medium format camera"
}
JSON
FAQ
Using this prompt
How do I copy this prompt safely?
Use the copy button beside the full prompt block. It copies only the prompt text, not surrounding page labels, so you can paste it into an agent instruction, a JSON request body, or your own prompt library.
Why does the detail page show parameters?
Some prompts were collected with saved generation settings such as aspect ratio, duration, or voice controls. When parameters exist, the page lists them separately so you can reuse the prompt text and the structured settings together.
Which endpoint should I call?
Use the endpoint path shown in the API code block. The path is generated from the prompt's RunAPI service and endpoint name, then rendered as the public API URL used by curl and SDK examples.
Can I use this prompt in an agent instead of code?
Yes. Pick Claude Code, Codex, Cursor, or Windsurf in the tab switcher, install the RunAPI MCP Server, and paste the generated instruction. The instruction includes the full prompt text.