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Kwaivgi Kling V1 Ai Multi Shot

Kwaivgi Kling V1 Ai Multi Shot

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Kling V1 AI Multi-Shot delivers top-tier image-to-image generation with cinematic visuals, accurate prompt adherence, and multi-shot consistency for ready-to-share images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Kling V1 AI Multi-Shot

Kling V1 AI Multi-Shot automatically generates multiple dynamic camera angles and perspectives from a single image. Upload one photo and the model creates a professional multi-shot video sequence with cinematic camera movements, smooth transitions, and consistent visual quality across all shots.

Why Choose This?

  • One image, multiple shots Automatically generates varied camera angles and perspectives from a single input.

  • Cinematic camera movements Professional-grade pans, zooms, and transitions between shots.

  • Visual consistency Maintains lighting, composition, and character identity across all generated shots.

  • Zero configuration No complex parameters — just upload an image and run.

  • Ready-to-use output Generated sequences are ready for immediate use in projects.

Parameters

ParameterRequiredDescription
imageYesSource image to generate multi-shot video from (URL or upload)

Input Requirements

  • Supported formats: JPG, JPEG, PNG
  • Maximum file size: 10MB
  • Minimum dimensions: 300px (width and height)
  • Aspect ratio range: 1:2.5 to 2.5:1

How to Use

  1. Upload your image — provide a source image meeting the input requirements.
  2. Run — the model automatically generates optimal multi-shot sequences.
  3. Download — receive multiple shot variations with different camera angles.

Pricing

OutputCost
Per generation$0.07

Best Use Cases

  • Product Videos — Multiple viewing angles from a single product photo.
  • Character Showcases — Dynamic perspectives for character presentations.
  • Real Estate — Virtual tour-style sequences from property images.
  • E-commerce — Professional product demonstrations with varied angles.
  • Marketing & Social Media — Cinematic content from still imagery.

Pro Tips

  • Use high-resolution source images for best quality across all shots.
  • Images with clear subjects produce more varied and dynamic shot compositions.
  • Ensure the source image meets the aspect ratio range (1:2.5 to 2.5:1).
  • Works best with portraits, product images, and scenes with clear focal points.

Notes

  • Only image is required — no additional parameters needed.
  • The model automatically determines camera angles and shot compositions.
  • Ensure uploaded image URLs are publicly accessible.

Related Models

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v1/ai-multi-shot" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "enable_base64_output": false
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-Supported image formats:.jpg /.jpeg /.png The size of the image file should not exceed 10MB, the width and height of the image should be no less than 300px, and the aspect ratio of the image should be between 1:2.5 and 2.5:1
enable_base64_outputbooleanNofalse-If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray of URLs to the generated content (empty when status is not completed).
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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