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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 smooth motion, cinematic visuals, accurate prompt adherence, and native audio for ready-to-share clips. Ready-to-use REST inference API, best performance, no cold starts, 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 input. Create professional multi-shot sequences with cinematic camera movements, smooth transitions, and consistent visual quality across all generated shots.

Model Highlights

  • Automatic multi-angle shot generation from a single image
  • Cinematic camera movements and transitions
  • Consistent lighting and composition across all shots
  • Professional-grade visual quality
  • Ready-to-use output for immediate deployment

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

Use Cases

  • Product videos with multiple viewing angles
  • Character showcases with dynamic perspectives
  • Real estate virtual tours
  • E-commerce product demonstrations
  • Marketing videos with professional camera work
  • Social media content with cinematic quality

Price

  • Per generation$0.70

How to Use

  1. Prepare your source image meeting the input requirements
  2. Submit the image via REST API endpoint
  3. Receive multiple shot variations with different camera angles
  4. Use the generated multi-shot sequence in your projects

API Integration

Simple REST API integration with straightforward image input. No complex parameters needed – the model automatically generates optimal multi-shot sequences based on your input image.

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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