MODEL PROMPTS

flux-kontext-max Prompts — 1 curated examples

Examples for using flux-kontext-max through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.

MODELS

flux-kontext-max

Modality
Image
Provider
Black Forest Labs
Endpoint
Text To Image
View model details and pricing →
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate an image: "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate an image: "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate an image: "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate an image: "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
curl -X POST https://runapi.ai/api/v1/flux_kontext/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "flux-kontext-max",
  "prompt": "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
}
JSON
import { FluxKontextClient } from "@runapi.ai/flux-kontext";

const client = new FluxKontextClient({
  apiKey: process.env.RUNAPI_API_KEY,
});

const result = await client.textToImage.run({
  "model": "flux-kontext-max",
  "prompt": "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
});
console.log(result.id);
require "runapi/flux_kontext"

client = RunApi::FluxKontext::Client.new
result = client.text_to_image.run(
  model: "flux-kontext-max",
  prompt: "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
)
puts result.id
package main

import (
  "context"
  "fmt"
  "log"
  "net/http"
  "os"
  "strings"
)

func main() {
  body := strings.NewReader("{\"model\":\"flux-kontext-max\",\"prompt\":\"Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image.\"}")
  req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/flux_kontext/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-kontext-max /api/v1/flux_kontext/text_to_image Get API Key
CATEGORIES All categories product
IM
Image
product flux-kontext-max

E-commerce product photo — wireless earbuds

Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image.

View API Code
curl -X POST https://runapi.ai/api/v1/flux_kontext/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "flux-kontext-max",
  "prompt": "Professional product photography of matte black wireless earbuds resting on a smooth white marble surface. One earbud lies flat, the other stands upright in its open charging case. Soft directional lighting from the upper left creates gentle shadows. The background is a seamless gradient from warm off-white to light gray. Shot at f/2.8, shallow depth of field with the standing earbud in sharp focus. Clean, editorial style suitable for a product listing hero image."
}
JSON
FAQ

Using flux-kontext-max 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.