google/veo3.1-lite/start-end-frame-to-video

圖生影片

Veo 3.1 Lite Start-End Frame-to-Video API by Google

google/veo3.1-lite/start-end-frame-to-video

Start-end-frame-to-video

Veo 3.1 Lite start-end frame to video: generate motion between a first and last frame with audio. Lightweight, developer-oriented option with 8s duration and 720p/1080p. Does not support 4K outputs or Extension.

輸入

提示詞 *

圖片 *

可拖曳檔案至此，或點擊上傳

MAX:1

尾幀圖片 *

可拖曳檔案至此，或點擊上傳

MAX:1

寬高比

時長

解析度

種子

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 $0.05。$10 可執行約 200 次。

你可以繼續：

Seedance 2.0 Kling v3 Vidu Wan2.7

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": "google/veo3.1-lite/start-end-frame-to-video",  # Required. model name
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. Text description for the video between the first and last frames
    "image": "example_value",  # Required. First frame of the video (instance image)
    "last_image": "example_value",  # Required. Final frame for interpolation (config lastFrame)
    "aspect_ratio": "16:9",  # The aspect ratio of the generated video. options: 16:9 | 9:16
    "duration": 8,  # Length of the generated video in seconds (durationSeconds). options: 4 | 6 | 8
    "resolution": "720p",  # Output resolution. options: 720p | 1080p
    "seed": -1,  # Random seed
}

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

安裝所需的相依套件。

pip install requests

驗證

所有 API 請求都需要透過 API Key 進行認證。您可以在 Atlas Cloud 控制台取得 API Key。

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

HTTP 標頭

import os

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

保護好您的 API Key

切勿在客戶端程式碼或公開儲存庫中暴露您的 API Key。請使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

提交一個非同步生成請求。API 會傳回一個 prediction ID，您可以用它來檢查狀態與取得結果。

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": "google/veo3.1-lite/start-end-frame-to-video",
    "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['data']['id']}")
print(f"Status: {result['data']['status']}")

回應

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

檢查狀態

輪詢 prediction 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，輸出可用。

succeeded生成成功，輸出可用。

failed生成失敗，請檢查 error 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

將檔案上傳到 Atlas Cloud 儲存空間，取得可在 API 請求中使用的 URL。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
  }
}

Input Schema

以下參數在請求主體中被接受。

總計: 8必填: 4選填: 4

modelstringrequired

model name

Default: "google/veo3.1-lite/start-end-frame-to-video"

promptstringrequired

Text description for the video between the first and last frames. Supports audio cues per Veo prompt guidance.

imagestringrequired

First frame of the video (instance image). Must be used together with last_image (lastFrame in the API). Accepts a public image URL, a data URL, or raw base64-encoded image bytes. Input image up to 8MB per Veo 3.1 Lite limits.

last_imagestringrequired

Final frame for interpolation (config lastFrame). Must be used together with image. Accepts a public image URL, a data URL, or raw base64-encoded image bytes. Input image up to 8MB per Veo 3.1 Lite limits.

aspect_ratiostring

The aspect ratio of the generated video

Default: "16:9"

16:99:16

durationinteger

Length of the generated video in seconds (durationSeconds).

Default: 8

468

resolutionstring

Output resolution. 1080p only supports 8s duration. Veo 3.1 Lite does not support 4K.

Default: "720p"

720p1080p

seedinteger

Random seed. Does not guarantee determinism but may improve repeatability. -1 means a random seed will be used.

Default: -1

範例請求主體

{
  "model": "google/veo3.1-lite/start-end-frame-to-video",
  "prompt": "A beautiful landscape",
  "image": "example_image",
  "last_image": "example_last_image",
  "aspect_ratio": "16:9",
  "duration": 8,
  "resolution": "720p",
  "seed": -1
}

Output Schema

API 傳回包含生成輸出 URL 的 prediction 回應。

created_atstring

ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

idstring

Unique identifier for the prediction, the ID of the prediction to get.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content (empty when status is not completed).

statusstring

Status of the task: created, processing, completed, or failed.

範例回應

{
  "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 400+ AI 模型直接整合到您的 AI 程式碼助手中。一條命令安裝，即可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

npx skills add AtlasCloudAI/atlas-cloud-skills

設定 API Key

從 Atlas Cloud 控制台取得 API Key，並將其設定為環境變數。

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生影片工作流程。

MCP Server

Atlas Cloud MCP Server 透過 Model Context Protocol 將您的 IDE 與 400+ AI 模型連接。支援任何相容 MCP 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

npx -y atlascloud-mcp

設定

將以下設定新增到您的 IDE 的 MCP 設定檔中。

{
  "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 400+ 可用 AI 模型。

atlas_quick_generate一步式內容創建，自動選擇最佳模型。

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

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "google/veo3.1-lite/start-end-frame-to-video"
          },
          "prompt": {
            "description": "Text description for the video between the first and last frames. Supports audio cues per Veo prompt guidance.",
            "type": "string"
          },
          "image": {
            "description": "First frame of the video (instance image). Must be used together with last_image (lastFrame in the API). Accepts a public image URL, a data URL, or raw base64-encoded image bytes. Input image up to 8MB per Veo 3.1 Lite limits.",
            "type": "string",
            "x-ui-component": "uploader"
          },
          "last_image": {
            "description": "Final frame for interpolation (config lastFrame). Must be used together with image. Accepts a public image URL, a data URL, or raw base64-encoded image bytes. Input image up to 8MB per Veo 3.1 Lite limits.",
            "type": "string",
            "x-ui-component": "uploader"
          },
          "aspect_ratio": {
            "default": "16:9",
            "description": "The aspect ratio of the generated video",
            "enum": [
              "16:9",
              "9:16"
            ],
            "type": "string",
            "x-ui-component": "select"
          },
          "duration": {
            "default": 8,
            "description": "Length of the generated video in seconds (durationSeconds).",
            "enum": [
              4,
              6,
              8
            ],
            "type": "integer",
            "x-ui-component": "select"
          },
          "resolution": {
            "default": "720p",
            "description": "Output resolution. 1080p only supports 8s duration. Veo 3.1 Lite does not support 4K.",
            "enum": [
              "720p",
              "1080p"
            ],
            "type": "string",
            "x-ui-component": "select"
          },
          "seed": {
            "default": -1,
            "description": "Random seed. Does not guarantee determinism but may improve repeatability. -1 means a random seed will be used.",
            "type": "integer"
          }
        },
        "required": [
          "model",
          "prompt",
          "image",
          "last_image"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "image",
          "last_image",
          "aspect_ratio",
          "duration",
          "resolution",
          "seed"
        ],
        "allOf": [
          {
            "description": "When resolution is 1080p, duration must be 8 (seconds).",
            "if": {
              "properties": {
                "resolution": {
                  "enum": [
                    "1080p"
                  ]
                }
              },
              "required": [
                "resolution"
              ]
            },
            "then": {
              "properties": {
                "duration": {
                  "enum": [
                    8
                  ]
                }
              }
            }
          }
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction, the ID of the prediction to get.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM 友善的提示詞範本

# google/veo3.1-lite/start-end-frame-to-video

> Veo 3.1 Lite start-end frame to video: generate motion between a first and last frame with audio. Lightweight, developer-oriented option with 8s duration and 720p/1080p. Does not support 4K outputs or Extension.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `google/veo3.1-lite/start-end-frame-to-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"google/veo3.1-lite/start-end-frame-to-video"`

- **`prompt`** (`string`, _required_):
  Text description for the video between the first and last frames. Supports audio cues per Veo prompt guidance.

- **`image`** (`string`, _required_):
  First frame of the video (instance image). Must be used together with last_image (lastFrame in the API). Accepts a public image URL, a data URL, or raw base64-encoded image bytes. Input image up to 8MB per Veo 3.1 Lite limits.

- **`last_image`** (`string`, _required_):
  Final frame for interpolation (config lastFrame). Must be used together with image. Accepts a public image URL, a data URL, or raw base64-encoded image bytes. Input image up to 8MB per Veo 3.1 Lite limits.

- **`aspect_ratio`** (`string`, _optional_):
  The aspect ratio of the generated video
  - Default: `"16:9"`
  - Options: "16:9", "9:16"

- **`duration`** (`integer`, _optional_):
  Length of the generated video in seconds (durationSeconds).
  - Default: `8`
  - Options: 4, 6, 8

- **`resolution`** (`string`, _optional_):
  Output resolution. 1080p only supports 8s duration. Veo 3.1 Lite does not support 4K.
  - Default: `"720p"`
  - Options: "720p", "1080p"

- **`seed`** (`integer`, _optional_):
  Random seed. Does not guarantee determinism but may improve repeatability. -1 means a random seed will be used.
  - Default: `-1`



**Required Parameters Example**:

```json
{
  "model": "google/veo3.1-lite/start-end-frame-to-video",
  "prompt": "",
  "image": "",
  "last_image": ""
}
```


**Full Example**:

```json
{
  "model": "google/veo3.1-lite/start-end-frame-to-video",
  "prompt": "",
  "image": "",
  "last_image": "",
  "aspect_ratio": "16:9",
  "duration": 8,
  "resolution": "720p",
  "seed": -1
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty when status is not completed).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "google/veo3.1-lite/start-end-frame-to-video",
  "prompt": "",
  "image": "",
  "last_image": "",
  "aspect_ratio": "16:9",
  "duration": 8,
  "resolution": "720p",
  "seed": -1
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/google/veo3.1-lite/start-end-frame-to-video)

A supercar executes a breathtaking high-speed drift across the asphalt track, massive tire smoke swirling behind, glowing brake discs, motion blur emphasizing extreme speed, low-angle cinematic camera following the slide, ultra-realistic, high-energy racing scene.

載入中...

Google Veo 3.1 Lite — Start–End Frame to Video

Veo 3.1 Lite Preview (veo-3.1-lite-generate-preview) is Google's high-efficiency video model for creators and enterprises that need a programmable, scalable path from still frames to motion. It inherits Veo 3.1–class fidelity and control while emphasizing developer-first integration and competitive pricing at scale. Output is video with audio. The model page notes that Veo 3.1 Lite Preview does not support 4K outputs or Extension; see Video generation for broader capability coverage.

Overview

Generate videos by animating between a first and last frame using Google's Veo 3.1 Lite model.

A lightweight, cost-effective variant of Veo 3.1 that always generates video with audio.

Supported options

The model supports:

Input images up to 8MB in size
720p or 1080p output resolution
8 second duration
16:9 or 9:16 aspect ratio
Audio is always generated
Safety filters are applied to both input images and generated content

Veo 3.1 Lite Start-End Frame-to-Video API by Google

輸入

輸出

參數

程式碼範例

安裝

驗證

HTTP 標頭

提交請求

提交請求

請求主體

回應

檢查狀態

輪詢範例

狀態值

完成回應

上傳檔案

上傳範例

回應

Input Schema

範例請求主體

Output Schema

範例回應

Atlas Cloud Skills

支援的客戶端

安裝

設定 API Key

功能

MCP Server

支援的客戶端

安裝

設定

可用工具

API Schema

LLM 友善的提示詞範本

Google Veo 3.1 Lite — Start–End Frame to Video

Overview

Supported options

Reference

探索類似模型

Gemini Omni Flash Reference-to-Video

Gemini Omni Flash Image-to-Video

Gemini Omni Flash Video Edit

Gemini Omni Flash Text-to-Video

Gemini Omni Flash Reference-to-Video Developer

Gemini Omni Flash Image-to-Video Developer

Gemini Omni Flash Text-to-Video Developer

Veo 3.1 Lite Text-to-video

Veo 3.1 Lite Image-to-video

Veo3.1 Fast Image-to-video

Veo3.1 Fast Text-to-video

Veo3.1 Image-to-video

Veo3.1 Reference-to-video

Veo3.1 Text-to-video

Sync.so Lipsync v3

VEED Lipsync

一個 API，暢享全模態 AI。

Join our Discord community

輸入

輸出

參數

程式碼範例

安裝

驗證

HTTP 標頭

提交請求

提交請求

請求主體

回應

檢查狀態

輪詢範例

狀態值

完成回應

上傳檔案

上傳範例

回應

Input Schema

範例請求主體

Output Schema

範例回應