HappyHorse 1.0 Image To Video

curl -X POST https://api.vibetool.ai/v1/videos/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "happyhorse-1.0-image-to-video",
    "image_url": "https://example.com/input.png",
    "prompt": "a horse galloping across a meadow, cinematic lighting",
    "duration": 4
  }'

import requests

url = "https://api.vibetool.ai/v1/videos/generations"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "model": "happyhorse-1.0-image-to-video",
    "image_url": "https://example.com/input.png",
    "prompt": "a horse galloping across a meadow, cinematic lighting",
    "duration": 4
}

r = requests.post(url, json=payload, headers=headers, timeout=60)
print(r.status_code, r.json())

const response = await fetch("https://api.vibetool.ai/v1/videos/generations", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "happyhorse-1.0-image-to-video",
    image_url: "https://example.com/input.png",
    prompt: "a horse galloping across a meadow, cinematic lighting",
    duration: 4
  })
});
const data = await response.json();
console.log(data);

package main

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

func main() {
	payload := map[string]interface{}{
		"model":     "happyhorse-1.0-image-to-video",
		"image_url": "https://example.com/input.png",
		"prompt":    "a horse galloping across a meadow, cinematic lighting",
		"duration":  4,
	}
	b, _ := json.Marshal(payload)

	req, _ := http.NewRequest("POST", "https://api.vibetool.ai/v1/videos/generations", bytes.NewReader(b))
	req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
	req.Header.Set("Content-Type", "application/json")

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

	var result map[string]interface{}
	json.NewDecoder(resp.Body).Decode(&result)
	fmt.Println(result)
}

{
  "id": "gen_vid_xyz789",
  "object": "video.generation",
  "model": "happyhorse-1.0-image-to-video",
  "created_at": 1767072426,
  "status": "pending",
  "task_id": "vid_202512261557_b4fcbb08"
}

{
  "error": {
    "message": "Invalid image URL or unsupported image format.",
    "type": "invalid_request_error",
    "param": "image_url",
    "code": 400
  }
}

POST

videos

generations

curl -X POST https://api.vibetool.ai/v1/videos/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "happyhorse-1.0-image-to-video",
    "image_url": "https://example.com/input.png",
    "prompt": "a horse galloping across a meadow, cinematic lighting",
    "duration": 4
  }'

import requests

url = "https://api.vibetool.ai/v1/videos/generations"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "model": "happyhorse-1.0-image-to-video",
    "image_url": "https://example.com/input.png",
    "prompt": "a horse galloping across a meadow, cinematic lighting",
    "duration": 4
}

r = requests.post(url, json=payload, headers=headers, timeout=60)
print(r.status_code, r.json())

const response = await fetch("https://api.vibetool.ai/v1/videos/generations", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "happyhorse-1.0-image-to-video",
    image_url: "https://example.com/input.png",
    prompt: "a horse galloping across a meadow, cinematic lighting",
    duration: 4
  })
});
const data = await response.json();
console.log(data);

package main

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

func main() {
	payload := map[string]interface{}{
		"model":     "happyhorse-1.0-image-to-video",
		"image_url": "https://example.com/input.png",
		"prompt":    "a horse galloping across a meadow, cinematic lighting",
		"duration":  4,
	}
	b, _ := json.Marshal(payload)

	req, _ := http.NewRequest("POST", "https://api.vibetool.ai/v1/videos/generations", bytes.NewReader(b))
	req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
	req.Header.Set("Content-Type", "application/json")

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

	var result map[string]interface{}
	json.NewDecoder(resp.Body).Decode(&result)
	fmt.Println(result)
}

{
  "id": "gen_vid_xyz789",
  "object": "video.generation",
  "model": "happyhorse-1.0-image-to-video",
  "created_at": 1767072426,
  "status": "pending",
  "task_id": "vid_202512261557_b4fcbb08"
}

{
  "error": {
    "message": "Invalid image URL or unsupported image format.",
    "type": "invalid_request_error",
    "param": "image_url",
    "code": 400
  }
}

Pricing: See vibetool.ai/pricing for current rates.

HappyHorse 1.0 is a top-ranked image‑to‑video model that generates high‑resolution videos (720p or 1080p) from a reference image and optional text prompt. It supports realistic motion, dynamic scenes, and per‑second billing via Vibetool’s asynchronous API.

Input Modalities

Image – a still image to animate (JPEG or PNG)
Text – (optional) a prompt describing the desired motion, scene, or style

Output Modality

Video – an MP4 file at 720p or 1080p resolution (duration configurable)

Authorization

string

required

All APIs require Bearer Token authentication. Format: Bearer YOUR_API_KEY

Request Body

string

required

The model identifier. Use "happyhorse-1.0-image-to-video".

string

required

A publicly accessible URL to the input image (JPEG or PNG). The image should be at least 256x256 pixels and no larger than 2048x2048.

string

Optional text description of the desired video content (e.g., “a horse galloping across a meadow, cinematic lighting”).

number

Requested video duration in seconds (defaults to 4, maximum 10). The model may adjust to match its capabilities.

Response Schema

string

required

Unique identifier for the generation task.

string

required

Type of object, always "video.generation".

string

required

The model used, e.g., "happyhorse-1.0-image-to-video".

integer

required

Unix timestamp (seconds) of task creation.

string

required

Initial status: "pending" or "processing". Use the Get Video Status endpoint to poll for completion.

string

required

The task ID to query in the status endpoint.

curl -X POST https://api.vibetool.ai/v1/videos/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "happyhorse-1.0-image-to-video",
    "image_url": "https://example.com/input.png",
    "prompt": "a horse galloping across a meadow, cinematic lighting",
    "duration": 4
  }'

import requests

url = "https://api.vibetool.ai/v1/videos/generations"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "model": "happyhorse-1.0-image-to-video",
    "image_url": "https://example.com/input.png",
    "prompt": "a horse galloping across a meadow, cinematic lighting",
    "duration": 4
}

r = requests.post(url, json=payload, headers=headers, timeout=60)
print(r.status_code, r.json())

const response = await fetch("https://api.vibetool.ai/v1/videos/generations", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "happyhorse-1.0-image-to-video",
    image_url: "https://example.com/input.png",
    prompt: "a horse galloping across a meadow, cinematic lighting",
    duration: 4
  })
});
const data = await response.json();
console.log(data);

package main

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

func main() {
	payload := map[string]interface{}{
		"model":     "happyhorse-1.0-image-to-video",
		"image_url": "https://example.com/input.png",
		"prompt":    "a horse galloping across a meadow, cinematic lighting",
		"duration":  4,
	}
	b, _ := json.Marshal(payload)

	req, _ := http.NewRequest("POST", "https://api.vibetool.ai/v1/videos/generations", bytes.NewReader(b))
	req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
	req.Header.Set("Content-Type", "application/json")

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

	var result map[string]interface{}
	json.NewDecoder(resp.Body).Decode(&result)
	fmt.Println(result)
}

{
  "id": "gen_vid_xyz789",
  "object": "video.generation",
  "model": "happyhorse-1.0-image-to-video",
  "created_at": 1767072426,
  "status": "pending",
  "task_id": "vid_202512261557_b4fcbb08"
}

{
  "error": {
    "message": "Invalid image URL or unsupported image format.",
    "type": "invalid_request_error",
    "param": "image_url",
    "code": 400
  }
}

Once the task is created, use the Get Video Status endpoint to poll for the generated video URL.

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

model

enum<string>

required

Use happyhorse-1.0-image-to-video.

Available options:

happyhorse-1.0-image-to-video

image_url

string<uri>

required

Input image used as the starting frame

prompt

string

Optional motion description

duration

number

Duration in seconds

Response

Task created

string

Unique identifier for the generation task

object

string

Example:

"video.generation"

model

string

created_at

integer

Unix timestamp (seconds)

status

enum<string>

Initial task status

Available options:

pending,

processing

task_id

string

Task ID for the status polling endpoint

Getting Started

Text Generation

Image Generation

Video Generation

HappyHorse 1.0 Image To Video

Input Modalities

Output Modality

Authorization

Request Body

Response Schema

Authorizations

Body

Response

​Input Modalities

​Output Modality

​Authorization

​Request Body

​Response Schema

Authorizations

Body

Response

Input Modalities

Output Modality

Authorization

Request Body

Response Schema