kwaivgi/kling-video-o3-std/reference-to-video

圖生影片

Kling Omni Video O3 (Standard) Reference-to-Video generates creative videos using character, prop, or scene references. Supports up to 7 reference images and optional video input.

輸入

正在載入參數設定...

輸出

閒置

生成的影片將在這裡顯示

設定參數後點擊執行開始生成

每次執行將花費 0.071。$10 可執行約 140 次。

你可以繼續：

影片超分影片延展

參數

程式碼範例
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "kwaivgi/kling-video-o3-std/reference-to-video",
    "prompt": "A beautiful sunset over the ocean with gentle waves",
    "width": 512,
    "height": 512,
    "duration": 3,
    "fps": 24,
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

安裝

為您的程式語言安裝所需的套件。

bash

pip install requests

驗證

所有 API 請求都需要透過 API 金鑰進行驗證。您可以從 Atlas Cloud 儀表板取得 API 金鑰。

bash

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP 標頭

python

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

請妥善保管您的 API 金鑰

切勿在客戶端程式碼或公開儲存庫中暴露您的 API 金鑰。請改用環境變數或後端代理。

提交請求

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

提交請求

提交非同步生成請求。API 會傳回一個預測 ID，您可以用它來檢查狀態並取得結果。

POST/api/v1/model/generateVideo

請求主體

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "kwaivgi/kling-video-o3-std/reference-to-video",
    "input": {
        "prompt": "A beautiful sunset over the ocean with gentle waves"
    }
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")

回應

{
  "id": "pred_abc123",
  "status": "processing",
  "model": "model-name",
  "created_at": "2025-01-01T00:00:00Z"
}

檢查狀態

輪詢預測端點以檢查請求的當前狀態。

GET/api/v1/model/prediction/{prediction_id}

輪詢範例

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

狀態值

processing請求仍在處理中。

completed生成完成。輸出已可取得。

succeeded生成成功。輸出已可取得。

failed生成失敗。請檢查錯誤欄位。

完成回應

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

上傳檔案

上傳檔案至 Atlas Cloud 儲存空間並取得 URL，可用於您的 API 請求。使用 multipart/form-data 上傳。

POST/api/v1/model/uploadMedia

上傳範例

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

回應

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

輸入 Schema

以下參數可在請求主體中使用。

總計: 0必填: 0選填: 0

無可用參數。

範例請求主體

json

{
  "model": "kwaivgi/kling-video-o3-std/reference-to-video"
}

輸出 Schema

API 傳回包含生成輸出 URL 的預測回應。

idstringrequired

Unique identifier for the prediction.

statusstringrequired

Current status of the prediction.

processingcompletedsucceededfailed

modelstringrequired

The model used for generation.

outputsarray[string]

Array of output URLs. Available when status is "completed".

errorstring

Error message if status is "failed".

metricsobject

Performance metrics.

predict_timenumber

Time taken for video generation in seconds.

created_atstringrequired

ISO 8601 timestamp when the prediction was created.

Format: date-time

completed_atstring

ISO 8601 timestamp when the prediction was completed.

Format: date-time

範例回應

json

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills 將 300 多個 AI 模型直接整合至您的 AI 程式碼助手。一鍵安裝，即可使用自然語言生成圖片、影片，以及與 LLM 對話。

支援的客戶端

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ 支援的客戶端

安裝

bash

npx skills add AtlasCloudAI/atlas-cloud-skills

設定 API 金鑰

從 Atlas Cloud 儀表板取得 API 金鑰，並設為環境變數。

bash

export ATLASCLOUD_API_KEY="your-api-key-here"

功能

安裝完成後，您可以在 AI 助手中使用自然語言存取所有 Atlas Cloud 模型。

圖片生成使用 Nano Banana 2、Z-Image 等模型生成圖片。

影片創作使用 Kling、Vidu、Veo 等從文字或圖片創建影片。

LLM 對話與 Qwen、DeepSeek 及其他大型語言模型對話。

媒體上傳上傳本機檔案，用於圖片編輯和圖片轉影片工作流程。

MCP Server

Atlas Cloud MCP Server 透過 Model Context Protocol 將您的 IDE 與 300 多個 AI 模型連接。支援任何 MCP 相容的客戶端。

支援的客戶端

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ 支援的客戶端

安裝

bash

npx -y atlascloud-mcp

設定

將以下設定新增至您 IDE 的 MCP 設定檔中。

json

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

可用工具

atlas_generate_image根據文字提示生成圖片。

atlas_generate_video從文字或圖片創建影片。

atlas_chat與大型語言模型對話。

atlas_list_models瀏覽 300 多個可用的 AI 模型。

atlas_quick_generate一步完成內容創建，自動選擇模型。

atlas_upload_media上傳本機檔案用於 API 工作流程。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

Schema 不可用

請登入以檢視請求歷史

您需要登入才能存取模型請求歷史記錄。

登入

Kling Video O3 Std Reference-to-Video

Kling Video O3 Standard Reference-to-Video generates new videos guided by reference images and an optional reference video, maintaining consistent characters, styles, and scenes. Describe a scenario involving the people or elements in your reference images — the model brings them together in a coherent, natural video. Supports flexible duration, aspect ratio control, and optional sound generation.

Why Choose This?

Character-consistent generation Upload reference images of specific people or elements, and the model preserves their identity throughout the generated video.

Multi-reference support Provide multiple reference images to combine different characters, styles, or elements in one scene.

Optional reference video Supply a reference video for motion guidance, style transfer, or scene continuity.

Sound options Keep original audio from a reference video, or generate new synchronized sound effects.

Flexible output Multiple aspect ratios (16:9, 9:16, 1:1, etc.) and duration from 3 to 15 seconds.

Parameters

Parameter	Required	Description
prompt	Yes	Text description of the desired scene and action
video	No	Reference video for motion or style guidance
images	No	Reference images of characters, elements, or styles
keep_original_sound	No	Keep the original sound from the reference video (default: enabled)
sound	No	Generate synchronized audio for the video (default: disabled)
aspect_ratio	No	Video aspect ratio (default: 16:9)
duration	No	Video length: 3–15 seconds (default: 5)

How to Use

Run — submit and download your video.
Set sound preference — keep original audio from the reference video, or enable generated sound.
Set duration — choose any length from 3 to 15 seconds.
Choose aspect ratio — select the format that fits your platform.
Add reference video (optional) — provide a video for motion or style guidance.
Add reference images — upload images of the characters, objects, or styles you want in the video.
Write your prompt — describe the scene, referencing the characters or elements in your images (e.g., "The man in Figure 2 is walking with the woman in Figure 1 in the park.").

Best Use Cases

Style Transfer — Use a reference video to guide the motion and visual style of new content.
Creative Concepting — Combine multiple characters or elements into new scenarios for rapid ideation.
Marketing & Ads — Generate brand ambassador or spokesperson videos from still photos.
Social Media Content — Produce personalized short-form videos with consistent character identity.
Character-Driven Storytelling — Create scenes starring specific characters from your reference images.

Pro Tips

Match aspect ratio to your target platform: 16:9 for YouTube, 9:16 for TikTok/Reels.
Use shorter durations (3–5 s) for testing character consistency before generating longer clips.
Adding a reference video significantly enhances motion quality.
Use "Figure 1", "Figure 2" etc. in your prompt to refer to specific reference images in order.
Reference images with clear faces and distinct features produce the best character consistency.

Notes

Ensure uploaded URLs are publicly accessible.
Duration supports any value from 3 to 15 seconds.
Prompt is the only required field, but reference images are recommended for best results.

Kling Video O3 Std Video Edit — Edit existing videos with natural-language instructions.
Kling Video O3 Std Text-to-Video — Generate videos from text prompts at Standard pricing.
Kling Video O3 Std Image-to-Video — Animate a single image into video at Standard pricing.
Kling Video O3 Pro Reference-to-Video — Maximum quality reference-to-video with O3 Pro tier.