模型 PROMPTS

runway Prompts — 3 个精选示例

通过 RunAPI 使用 runway 的示例。复制 prompt 后,可在 Claude Code、Codex、Cursor、Windsurf 或后端 API 中使用。

模型

runway

模态
视频
提供方
Runway
Endpoint
Text To Video
查看模型详情和定价 →
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. 重启 Claude Code
3. 粘贴这个 prompt:生成一段视频:"A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
1. codex plugin install runapi-mcp@agents
2. 重启 Codex
3. 粘贴这个 prompt:生成一段视频:"A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
1. npx @runapi.ai/mcp init cursor
2. 重启 Cursor
3. 粘贴这个 prompt:生成一段视频:"A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
1. npx @runapi.ai/mcp init windsurf
2. 重启 Windsurf
3. 粘贴这个 prompt:生成一段视频:"A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
curl -X POST https://runapi.ai/api/v1/runway/text_to_video \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "runway",
  "prompt": "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
}
JSON
import { RunwayClient } from "@runapi.ai/runway";

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

const result = await client.textToVideo.run({
  "model": "runway",
  "prompt": "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
});
console.log(result.id);
require "runapi/runway"

client = RunApi::Runway::Client.new
result = client.text_to_video.run(
  model: "runway",
  prompt: "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
)
puts result.id
package main

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

func main() {
  body := strings.NewReader("{\"model\":\"runway\",\"prompt\":\"A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean.\"}")
  req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/runway/text_to_video", 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)
}
runway /api/v1/runway/text_to_video 获取 API Key
VI
视频
cinematic runway

Hyperspeed timelapse: The camera ascends from street level t...

Hyperspeed timelapse: The camera ascends from street level to a rooftop, showcasing a city's transformation from day to night. Neon signs flicker to life, traffic becomes streams of light, and skyscrapers illuminate against the darkening sky.

查看 API 代码
curl -X POST https://runapi.ai/api/v1/runway/text_to_video \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "runway",
  "prompt": "Hyperspeed timelapse: The camera ascends from street level to a rooftop, showcasing a city's transformation from day to night. Neon signs flicker to life, traffic becomes streams of light, and skyscrapers illuminate against the darkening sky."
}
JSON
VI
视频
cinematic runway

Cinematic dolly — abandoned library

Slow forward dolly shot through an abandoned grand library. The camera glides at waist height between towering bookshelves that stretch to a vaulted ceiling covered in peeling frescoes. Dust motes float in shafts of golden light entering through tall arched windows with broken panes. Books are scattered on the floor, some open with pages curling. Ivy creeps through a crack in the far wall. The movement is perfectly smooth and linear, never deviating from the central aisle. Atmospheric, melancholic mood. Warm color palette with deep shadows in the shelf recesses.

查看 API 代码
curl -X POST https://runapi.ai/api/v1/runway/text_to_video \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "runway",
  "prompt": "Slow forward dolly shot through an abandoned grand library. The camera glides at waist height between towering bookshelves that stretch to a vaulted ceiling covered in peeling frescoes. Dust motes float in shafts of golden light entering through tall arched windows with broken panes. Books are scattered on the floor, some open with pages curling. Ivy creeps through a crack in the far wall. The movement is perfectly smooth and linear, never deviating from the central aisle. Atmospheric, melancholic mood. Warm color palette with deep shadows in the shelf recesses."
}
JSON
常见问题

使用 runway prompts

%{model} 是什么?

%{model} 是 RunAPI 统一模型目录中的模型。这些 prompts 展示了 agent 和后端服务可以复用的实际输入模式。

如何使用这些 prompts?

安装 RunAPI MCP Server 后,复制任意 prompt 并粘贴到 Claude Code、Codex、Cursor 或 Windsurf。开发者也可以复制 API 示例直接调用。

浏览这些 prompts 要付费吗?

浏览和复制 prompt 示例是免费的。只有当你使用 API key 调用 RunAPI 模型生成内容时,才会产生费用。

这些 prompts 可以用于生产环境吗?

可以。把每个 prompt 当作起点,再补充品牌规则、输出尺寸、安全约束和你的业务上下文。