Veo3.1-Fast - Reference To Video - gptproto

curl --location 'https://gptproto.com/api/v3/google/veo3.1-fast/text-to-video' \
--header 'Authorization: Bearer sk-xxxxxx' \
--header 'Content-Type: application/json' \
--data '{
  "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
  "images": [
    "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
  ],
  "aspect_ratio": "16:9",
  "enhance_prompt": true
}'

import requests
import json

url = "https://gptproto.com/api/v3/google/veo3.1-fast/text-to-video"
headers = {
    "Authorization": "Bearer sk-xxxxxx",
    "Content-Type": "application/json"
}

data = {
    "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
    "images": [
        "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
    ],
    "aspect_ratio": "16:9",
    "enhance_prompt": True
}

response = requests.post(url, headers=headers, json=data)
result = response.json()
print(json.dumps(result, indent=2))

const url = "https://gptproto.com/api/v3/google/veo3.1-fast/text-to-video";
const headers = {
  "Authorization": "Bearer sk-xxxxxx",
  "Content-Type": "application/json"
};

const data = {
  "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
  "images": [
    "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
  ],
  "aspect_ratio": "16:9",
  "enhance_prompt": true
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(data)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error("Error:", error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://gptproto.com/api/v3/google/veo3.1-fast/text-to-video"

    payload := []byte(`{
  "prompt": "A young woman walks alone under a transparent umbrella in a quiet alley during light rain, soft city lights reflecting on the wet pavement. Her pace is calm and thoughtful. The camera follows slowly behind her, occasional droplets hitting the lens. Subtle piano music plays, evoking a melancholic but peaceful mood. Dreamy, cinematic, slightly slow motion.",
  "images": [
    "https://oss.gptproto.com/2025/11/12/d5c2f08479b9452aacbcf9963631ce21.jpeg"
  ],
  "aspect_ratio": "16:9",
  "enhance_prompt": true
}`)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(payload))
    req.Header.Set("Authorization", "Bearer sk-xxxxxx")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}

{
  "error": {
    "message": "Invalid signature",
    "type": "401"
  }
}

{
  "error": {
    "message": "Invalid Token",
    "type": "403"
  }
}

{
  "error": {
    "message": "Insufficient balance",
    "type": "403"
  }
}

{
  "error": {
    "message": "Internal server error",
    "type": "500"
  }
}

{
  "error": {
    "message": "Input may not meet the guidelines. Please adjust and try again.",
    "type": "503"
  }
}