Examples for using flux-2-pro-text-to-image through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate an image: "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate an image: "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate an image: "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate an image: "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
curl -X POST https://runapi.ai/api/v1/flux_2/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "flux-2-pro-text-to-image",
"prompt": "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
}
JSON
import { Flux2Client } from "@runapi.ai/flux-2";
const client = new Flux2Client({
apiKey: process.env.RUNAPI_API_KEY,
});
const result = await client.textToImage.run({
"model": "flux-2-pro-text-to-image",
"prompt": "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
});
console.log(result.id);
require "runapi/flux_2"
client = RunApi::Flux2::Client.new
result = client.text_to_image.run(
model: "flux-2-pro-text-to-image",
prompt: "Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial."
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"model\":\"flux-2-pro-text-to-image\",\"prompt\":\"Photorealistic interior photograph of a Scandinavian living room with double-height ceilings and floor-to-ceiling windows overlooking a pine forest. Light oak flooring, a cream boucle sofa with linen cushions, a round walnut coffee table, and a single dried eucalyptus stem in a ceramic vase. Late afternoon golden hour light casting long soft shadows across the floor. Like an architectural magazine editorial.\"}")
req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/flux_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)
}
flux-2-pro-text-to-image/api/v1/flux_2/text_to_imageGet API Key
Professional headshot photo, 30 year old woman in navy business attire, confident natural smile, neutral grey seamless background, studio lighting with large softbox, shallow depth of field with beautiful bokeh, shot with 85mm f/1.8 lens, photorealistic, high quality, 8k, professional corporate photography
curl -X POST https://runapi.ai/api/v1/flux_2/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "flux-2-pro-text-to-image",
"prompt": "Professional headshot photo, 30 year old woman in navy business attire, confident natural smile, neutral grey seamless background, studio lighting with large softbox, shallow depth of field with beautiful bokeh, shot with 85mm f/1.8 lens, photorealistic, high quality, 8k, professional corporate photography"
}
JSON
FAQ
Using flux-2-pro-text-to-image prompts
What is %{model}?
%{model} is available through RunAPI as part of the unified model catalog. These prompts show practical input patterns that agents and backend services can reuse.
How do I use these prompts?
Copy any prompt and paste it into Claude Code, Codex, Cursor, or Windsurf after installing the RunAPI MCP Server. Developers can also copy the API example and send the prompt directly.
Do these prompts cost money to browse?
Browsing and copying prompt examples is free. Generation requests only cost money when you call a RunAPI model with your API key.
Can I adapt the prompts for production?
Yes. Treat each prompt as a starting point, then add your brand rules, output dimensions, safety constraints, and application-specific context before using it in production.