Seedance 系列

curl --request POST \
  --url https://api.qingbo.ai/v1/tasks \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "<string>",
  "action": "<string>",
  "prompt": "<string>",
  "duration": 123,
  "resolution": "<string>",
  "aspect_ratio": "<string>",
  "n": 123,
  "seed": 123,
  "first_frame_image": "<string>",
  "last_frame_image": "<string>",
  "image_urls": [
    "<string>"
  ],
  "video_urls": [
    "<string>"
  ],
  "audio_urls": [
    "<string>"
  ],
  "generate_audio": true,
  "watermark": true,
  "image_with_roles": [
    {}
  ],
  "camerafixed": true,
  "return_last_frame": true,
  "tools": [
    {}
  ],
  "output_format": "<string>",
  "omni_reference_task_type": "<string>"
}
'

import requests

url = "https://api.qingbo.ai/v1/tasks"

payload = {
    "model": "<string>",
    "action": "<string>",
    "prompt": "<string>",
    "duration": 123,
    "resolution": "<string>",
    "aspect_ratio": "<string>",
    "n": 123,
    "seed": 123,
    "first_frame_image": "<string>",
    "last_frame_image": "<string>",
    "image_urls": ["<string>"],
    "video_urls": ["<string>"],
    "audio_urls": ["<string>"],
    "generate_audio": True,
    "watermark": True,
    "image_with_roles": [{}],
    "camerafixed": True,
    "return_last_frame": True,
    "tools": [{}],
    "output_format": "<string>",
    "omni_reference_task_type": "<string>"
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: '<string>',
    action: '<string>',
    prompt: '<string>',
    duration: 123,
    resolution: '<string>',
    aspect_ratio: '<string>',
    n: 123,
    seed: 123,
    first_frame_image: '<string>',
    last_frame_image: '<string>',
    image_urls: ['<string>'],
    video_urls: ['<string>'],
    audio_urls: ['<string>'],
    generate_audio: true,
    watermark: true,
    image_with_roles: [{}],
    camerafixed: true,
    return_last_frame: true,
    tools: [{}],
    output_format: '<string>',
    omni_reference_task_type: '<string>'
  })
};

fetch('https://api.qingbo.ai/v1/tasks', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.qingbo.ai/v1/tasks"

	payload := strings.NewReader("{\n  \"model\": \"<string>\",\n  \"action\": \"<string>\",\n  \"prompt\": \"<string>\",\n  \"duration\": 123,\n  \"resolution\": \"<string>\",\n  \"aspect_ratio\": \"<string>\",\n  \"n\": 123,\n  \"seed\": 123,\n  \"first_frame_image\": \"<string>\",\n  \"last_frame_image\": \"<string>\",\n  \"image_urls\": [\n    \"<string>\"\n  ],\n  \"video_urls\": [\n    \"<string>\"\n  ],\n  \"audio_urls\": [\n    \"<string>\"\n  ],\n  \"generate_audio\": true,\n  \"watermark\": true,\n  \"image_with_roles\": [\n    {}\n  ],\n  \"camerafixed\": true,\n  \"return_last_frame\": true,\n  \"tools\": [\n    {}\n  ],\n  \"output_format\": \"<string>\",\n  \"omni_reference_task_type\": \"<string>\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.qingbo.ai/v1/tasks")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"<string>\",\n  \"action\": \"<string>\",\n  \"prompt\": \"<string>\",\n  \"duration\": 123,\n  \"resolution\": \"<string>\",\n  \"aspect_ratio\": \"<string>\",\n  \"n\": 123,\n  \"seed\": 123,\n  \"first_frame_image\": \"<string>\",\n  \"last_frame_image\": \"<string>\",\n  \"image_urls\": [\n    \"<string>\"\n  ],\n  \"video_urls\": [\n    \"<string>\"\n  ],\n  \"audio_urls\": [\n    \"<string>\"\n  ],\n  \"generate_audio\": true,\n  \"watermark\": true,\n  \"image_with_roles\": [\n    {}\n  ],\n  \"camerafixed\": true,\n  \"return_last_frame\": true,\n  \"tools\": [\n    {}\n  ],\n  \"output_format\": \"<string>\",\n  \"omni_reference_task_type\": \"<string>\"\n}")
  .asString();