KlingAI 1.6 Pro

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  positivePrompt: 'A polished five-second talking-head public information clip featuring a charismatic woman in her early 50s, the curator of a municipal seed library. She stands inside a beautifully ordered seed archive with matte cobalt-blue specimen drawers, pale oak shelving, glass jars of beans and grains, and a few dried native grasses. She wears a mustard-yellow work jacket over a cream shirt, with a small seed packet held naturally at chest level. Medium close-up, centered square composition, direct eye contact. She speaks warmly to the viewer, visibly articulating one concise sentence: “Drought-tolerant seeds are now ready at every neighborhood library.” Natural mouth movement, subtle eyebrow emphasis, one gentle nod, relaxed shoulders, authentic blinking and restrained hand movement. The camera makes a very slow, stable push-in while maintaining eye level. Soft window light from camera left and warm practical archive lighting create a fresh cobalt, mustard, cream, and botanical-brown palette. Contemporary civic documentary style, credible real person, crisp facial detail, calm optimistic mood, continuous single take, no cuts, no captions, no logos, no visible writing, no interface elements.',
  width: 1080,
  height: 1080,
  duration: 5
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "positivePrompt": "A polished five-second talking-head public information clip featuring a charismatic woman in her early 50s, the curator of a municipal seed library. She stands inside a beautifully ordered seed archive with matte cobalt-blue specimen drawers, pale oak shelving, glass jars of beans and grains, and a few dried native grasses. She wears a mustard-yellow work jacket over a cream shirt, with a small seed packet held naturally at chest level. Medium close-up, centered square composition, direct eye contact. She speaks warmly to the viewer, visibly articulating one concise sentence: “Drought-tolerant seeds are now ready at every neighborhood library.” Natural mouth movement, subtle eyebrow emphasis, one gentle nod, relaxed shoulders, authentic blinking and restrained hand movement. The camera makes a very slow, stable push-in while maintaining eye level. Soft window light from camera left and warm practical archive lighting create a fresh cobalt, mustard, cream, and botanical-brown palette. Contemporary civic documentary style, credible real person, crisp facial detail, calm optimistic mood, continuous single take, no cuts, no captions, no logos, no visible writing, no interface elements.",
            "width": 1080,
            "height": 1080,
            "duration": 5
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "4e56cea0-f4a3-4fb9-a6da-acb54de639e0",
      "model": "klingai:3@2",
      "positivePrompt": "A polished five-second talking-head public information clip featuring a charismatic woman in her early 50s, the curator of a municipal seed library. She stands inside a beautifully ordered seed archive with matte cobalt-blue specimen drawers, pale oak shelving, glass jars of beans and grains, and a few dried native grasses. She wears a mustard-yellow work jacket over a cream shirt, with a small seed packet held naturally at chest level. Medium close-up, centered square composition, direct eye contact. She speaks warmly to the viewer, visibly articulating one concise sentence: “Drought-tolerant seeds are now ready at every neighborhood library.” Natural mouth movement, subtle eyebrow emphasis, one gentle nod, relaxed shoulders, authentic blinking and restrained hand movement. The camera makes a very slow, stable push-in while maintaining eye level. Soft window light from camera left and warm practical archive lighting create a fresh cobalt, mustard, cream, and botanical-brown palette. Contemporary civic documentary style, credible real person, crisp facial detail, calm optimistic mood, continuous single take, no cuts, no captions, no logos, no visible writing, no interface elements.",
      "width": 1080,
      "height": 1080,
      "duration": 5
    }
  ]'

runware run klingai:3@2 \
  positivePrompt="A polished five-second talking-head public information clip featuring a charismatic woman in her early 50s, the curator of a municipal seed library. She stands inside a beautifully ordered seed archive with matte cobalt-blue specimen drawers, pale oak shelving, glass jars of beans and grains, and a few dried native grasses. She wears a mustard-yellow work jacket over a cream shirt, with a small seed packet held naturally at chest level. Medium close-up, centered square composition, direct eye contact. She speaks warmly to the viewer, visibly articulating one concise sentence: “Drought-tolerant seeds are now ready at every neighborhood library.” Natural mouth movement, subtle eyebrow emphasis, one gentle nod, relaxed shoulders, authentic blinking and restrained hand movement. The camera makes a very slow, stable push-in while maintaining eye level. Soft window light from camera left and warm practical archive lighting create a fresh cobalt, mustard, cream, and botanical-brown palette. Contemporary civic documentary style, credible real person, crisp facial detail, calm optimistic mood, continuous single take, no cuts, no captions, no logos, no visible writing, no interface elements." \
  width=1080 \
  height=1080 \
  duration=5

{
  "taskType": "videoInference",
  "taskUUID": "4e56cea0-f4a3-4fb9-a6da-acb54de639e0",
  "model": "klingai:3@2",
  "positivePrompt": "A polished five-second talking-head public information clip featuring a charismatic woman in her early 50s, the curator of a municipal seed library. She stands inside a beautifully ordered seed archive with matte cobalt-blue specimen drawers, pale oak shelving, glass jars of beans and grains, and a few dried native grasses. She wears a mustard-yellow work jacket over a cream shirt, with a small seed packet held naturally at chest level. Medium close-up, centered square composition, direct eye contact. She speaks warmly to the viewer, visibly articulating one concise sentence: “Drought-tolerant seeds are now ready at every neighborhood library.” Natural mouth movement, subtle eyebrow emphasis, one gentle nod, relaxed shoulders, authentic blinking and restrained hand movement. The camera makes a very slow, stable push-in while maintaining eye level. Soft window light from camera left and warm practical archive lighting create a fresh cobalt, mustard, cream, and botanical-brown palette. Contemporary civic documentary style, credible real person, crisp facial detail, calm optimistic mood, continuous single take, no cuts, no captions, no logos, no visible writing, no interface elements.",
  "width": 1080,
  "height": 1080,
  "duration": 5
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  positivePrompt: 'A confident Black British aerospace risk analyst in her late 30s presents a concise orbital-safety update directly to camera from a contemporary satellite operations studio. Chest-up square composition, centered with comfortable headroom. She wears a tailored graphite blazer over a muted saffron blouse and a small silver satellite-shaped lapel pin. During the five-second clip, she speaks naturally with precise mouth movement, maintains reassuring eye contact, gives one restrained open-hand gesture, then settles into a calm professional expression. Behind her, softly defocused wall displays show elegant amber orbital arcs and tiny satellite markers on a deep charcoal field, with no readable text, logos, interface panels, or warning labels. Cinematic corporate documentary style, warm key light across her face, subtle amber rim light, realistic skin texture, restrained graphite-and-saffron palette. Single continuous shot with a very slow, stable camera push-in; natural blinking and breathing, accurate hands, consistent facial identity, no cuts, no captions, no on-screen graphics.',
  width: 1080,
  height: 1080,
  duration: 5
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "positivePrompt": "A confident Black British aerospace risk analyst in her late 30s presents a concise orbital-safety update directly to camera from a contemporary satellite operations studio. Chest-up square composition, centered with comfortable headroom. She wears a tailored graphite blazer over a muted saffron blouse and a small silver satellite-shaped lapel pin. During the five-second clip, she speaks naturally with precise mouth movement, maintains reassuring eye contact, gives one restrained open-hand gesture, then settles into a calm professional expression. Behind her, softly defocused wall displays show elegant amber orbital arcs and tiny satellite markers on a deep charcoal field, with no readable text, logos, interface panels, or warning labels. Cinematic corporate documentary style, warm key light across her face, subtle amber rim light, realistic skin texture, restrained graphite-and-saffron palette. Single continuous shot with a very slow, stable camera push-in; natural blinking and breathing, accurate hands, consistent facial identity, no cuts, no captions, no on-screen graphics.",
            "width": 1080,
            "height": 1080,
            "duration": 5
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "4a88c236-b6c5-496c-86c0-5bf4afe8cc22",
      "model": "klingai:3@2",
      "positivePrompt": "A confident Black British aerospace risk analyst in her late 30s presents a concise orbital-safety update directly to camera from a contemporary satellite operations studio. Chest-up square composition, centered with comfortable headroom. She wears a tailored graphite blazer over a muted saffron blouse and a small silver satellite-shaped lapel pin. During the five-second clip, she speaks naturally with precise mouth movement, maintains reassuring eye contact, gives one restrained open-hand gesture, then settles into a calm professional expression. Behind her, softly defocused wall displays show elegant amber orbital arcs and tiny satellite markers on a deep charcoal field, with no readable text, logos, interface panels, or warning labels. Cinematic corporate documentary style, warm key light across her face, subtle amber rim light, realistic skin texture, restrained graphite-and-saffron palette. Single continuous shot with a very slow, stable camera push-in; natural blinking and breathing, accurate hands, consistent facial identity, no cuts, no captions, no on-screen graphics.",
      "width": 1080,
      "height": 1080,
      "duration": 5
    }
  ]'

runware run klingai:3@2 \
  positivePrompt="A confident Black British aerospace risk analyst in her late 30s presents a concise orbital-safety update directly to camera from a contemporary satellite operations studio. Chest-up square composition, centered with comfortable headroom. She wears a tailored graphite blazer over a muted saffron blouse and a small silver satellite-shaped lapel pin. During the five-second clip, she speaks naturally with precise mouth movement, maintains reassuring eye contact, gives one restrained open-hand gesture, then settles into a calm professional expression. Behind her, softly defocused wall displays show elegant amber orbital arcs and tiny satellite markers on a deep charcoal field, with no readable text, logos, interface panels, or warning labels. Cinematic corporate documentary style, warm key light across her face, subtle amber rim light, realistic skin texture, restrained graphite-and-saffron palette. Single continuous shot with a very slow, stable camera push-in; natural blinking and breathing, accurate hands, consistent facial identity, no cuts, no captions, no on-screen graphics." \
  width=1080 \
  height=1080 \
  duration=5

{
  "taskType": "videoInference",
  "taskUUID": "4a88c236-b6c5-496c-86c0-5bf4afe8cc22",
  "model": "klingai:3@2",
  "positivePrompt": "A confident Black British aerospace risk analyst in her late 30s presents a concise orbital-safety update directly to camera from a contemporary satellite operations studio. Chest-up square composition, centered with comfortable headroom. She wears a tailored graphite blazer over a muted saffron blouse and a small silver satellite-shaped lapel pin. During the five-second clip, she speaks naturally with precise mouth movement, maintains reassuring eye contact, gives one restrained open-hand gesture, then settles into a calm professional expression. Behind her, softly defocused wall displays show elegant amber orbital arcs and tiny satellite markers on a deep charcoal field, with no readable text, logos, interface panels, or warning labels. Cinematic corporate documentary style, warm key light across her face, subtle amber rim light, realistic skin texture, restrained graphite-and-saffron palette. Single continuous shot with a very slow, stable camera push-in; natural blinking and breathing, accurate hands, consistent facial identity, no cuts, no captions, no on-screen graphics.",
  "width": 1080,
  "height": 1080,
  "duration": 5
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  positivePrompt: 'Continue directly from the supplied first frame as a polished five-second luxury fashion showcase. The model takes one measured step forward and turns her torso slightly toward camera, revealing the suit\'s sculptural shoulder quilting, articulated pockets, amber piping, and tailored side profile. Her translucent veil lifts and settles naturally in the ventilation breeze while a loose waist tab and trouser fabric respond with subtle, physically accurate motion. She maintains a calm, assured editorial expression and briefly meets the lens. The camera performs a smooth, restrained dolly-in with a gentle arc from her left toward center, preserving a full-to-three-quarter view and keeping the entire garment readable. Warm reflections travel softly across the stainless-steel extractor; golden light flickers through the honeycomb frames as a few bees drift through the distant background. Preserve the exact model, garment construction, colors, room layout, and premium photorealistic texture from the source image. Elegant pacing, stable anatomy, natural fabric physics, crisp product detail, shallow cinematic depth of field, no cuts, no text, no logos, no added accessories, no garment morphing.',
  width: 1920,
  height: 1080,
  duration: 5,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/6057f9ab-ee6d-4cc0-b3c8-95cf085e409b.jpg',
        frame: 'first'
      }
    ]
  }
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "positivePrompt": "Continue directly from the supplied first frame as a polished five-second luxury fashion showcase. The model takes one measured step forward and turns her torso slightly toward camera, revealing the suit's sculptural shoulder quilting, articulated pockets, amber piping, and tailored side profile. Her translucent veil lifts and settles naturally in the ventilation breeze while a loose waist tab and trouser fabric respond with subtle, physically accurate motion. She maintains a calm, assured editorial expression and briefly meets the lens. The camera performs a smooth, restrained dolly-in with a gentle arc from her left toward center, preserving a full-to-three-quarter view and keeping the entire garment readable. Warm reflections travel softly across the stainless-steel extractor; golden light flickers through the honeycomb frames as a few bees drift through the distant background. Preserve the exact model, garment construction, colors, room layout, and premium photorealistic texture from the source image. Elegant pacing, stable anatomy, natural fabric physics, crisp product detail, shallow cinematic depth of field, no cuts, no text, no logos, no added accessories, no garment morphing.",
            "width": 1920,
            "height": 1080,
            "duration": 5,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/6057f9ab-ee6d-4cc0-b3c8-95cf085e409b.jpg",
                        "frame": "first"
                    }
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "2db5656c-2d1c-432e-9705-46cce4555306",
      "model": "klingai:3@2",
      "positivePrompt": "Continue directly from the supplied first frame as a polished five-second luxury fashion showcase. The model takes one measured step forward and turns her torso slightly toward camera, revealing the suit's sculptural shoulder quilting, articulated pockets, amber piping, and tailored side profile. Her translucent veil lifts and settles naturally in the ventilation breeze while a loose waist tab and trouser fabric respond with subtle, physically accurate motion. She maintains a calm, assured editorial expression and briefly meets the lens. The camera performs a smooth, restrained dolly-in with a gentle arc from her left toward center, preserving a full-to-three-quarter view and keeping the entire garment readable. Warm reflections travel softly across the stainless-steel extractor; golden light flickers through the honeycomb frames as a few bees drift through the distant background. Preserve the exact model, garment construction, colors, room layout, and premium photorealistic texture from the source image. Elegant pacing, stable anatomy, natural fabric physics, crisp product detail, shallow cinematic depth of field, no cuts, no text, no logos, no added accessories, no garment morphing.",
      "width": 1920,
      "height": 1080,
      "duration": 5,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/6057f9ab-ee6d-4cc0-b3c8-95cf085e409b.jpg",
            "frame": "first"
          }
        ]
      }
    }
  ]'

runware run klingai:3@2 \
  positivePrompt="Continue directly from the supplied first frame as a polished five-second luxury fashion showcase. The model takes one measured step forward and turns her torso slightly toward camera, revealing the suit's sculptural shoulder quilting, articulated pockets, amber piping, and tailored side profile. Her translucent veil lifts and settles naturally in the ventilation breeze while a loose waist tab and trouser fabric respond with subtle, physically accurate motion. She maintains a calm, assured editorial expression and briefly meets the lens. The camera performs a smooth, restrained dolly-in with a gentle arc from her left toward center, preserving a full-to-three-quarter view and keeping the entire garment readable. Warm reflections travel softly across the stainless-steel extractor; golden light flickers through the honeycomb frames as a few bees drift through the distant background. Preserve the exact model, garment construction, colors, room layout, and premium photorealistic texture from the source image. Elegant pacing, stable anatomy, natural fabric physics, crisp product detail, shallow cinematic depth of field, no cuts, no text, no logos, no added accessories, no garment morphing." \
  width=1920 \
  height=1080 \
  duration=5 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/6057f9ab-ee6d-4cc0-b3c8-95cf085e409b.jpg \
  inputs.frameImages.0.frame=first

{
  "taskType": "videoInference",
  "taskUUID": "2db5656c-2d1c-432e-9705-46cce4555306",
  "model": "klingai:3@2",
  "positivePrompt": "Continue directly from the supplied first frame as a polished five-second luxury fashion showcase. The model takes one measured step forward and turns her torso slightly toward camera, revealing the suit's sculptural shoulder quilting, articulated pockets, amber piping, and tailored side profile. Her translucent veil lifts and settles naturally in the ventilation breeze while a loose waist tab and trouser fabric respond with subtle, physically accurate motion. She maintains a calm, assured editorial expression and briefly meets the lens. The camera performs a smooth, restrained dolly-in with a gentle arc from her left toward center, preserving a full-to-three-quarter view and keeping the entire garment readable. Warm reflections travel softly across the stainless-steel extractor; golden light flickers through the honeycomb frames as a few bees drift through the distant background. Preserve the exact model, garment construction, colors, room layout, and premium photorealistic texture from the source image. Elegant pacing, stable anatomy, natural fabric physics, crisp product detail, shallow cinematic depth of field, no cuts, no text, no logos, no added accessories, no garment morphing.",
  "width": 1920,
  "height": 1080,
  "duration": 5,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/6057f9ab-ee6d-4cc0-b3c8-95cf085e409b.jpg",
        "frame": "first"
      }
    ]
  }
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  positivePrompt: 'Create a single continuous 10-second vertical product demonstration connecting the supplied endpoint frames. Keep the camera completely locked and preserve the mannequin, backpack design, jacket, laboratory, framing, proportions, and lighting. Begin with the avalanche airbag fully stowed and the orange trigger cable taut. The cable snaps downward and pulls the handle; the backpack\'s top seam opens mechanically. Signal-red airbag fabric emerges from the shoulder compartment, rapidly but physically inflates, and expands upward and outward into a protective horseshoe around the mannequin\'s head and shoulders. Show realistic staged inflation: fabric unfolding first, then chambers filling with pressure, wrinkles smoothing, seams becoming taut, and the final shape settling with one subtle rebound. A brief controlled puff of cold white test vapor escapes near the shoulder vents and dissipates naturally. The mannequin remains rigid and stable while jacket fabric reacts slightly to the airflow. Emphasize accurate product mechanics, technical fabric texture, crisp industrial detail, and a clear before-to-after explanation. No cuts, camera movement, morphing, extra equipment, people, text, logos, overlays, sparks, fire, or explosive shockwave.',
  width: 1080,
  height: 1920,
  duration: 10,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/28a2d08a-1326-469d-94d4-5a0ea28fa2ae.jpg',
        frame: 'first'
      },
      {
        image: 'https://assets.runware.ai/assets/inputs/72b7dfe2-6cd6-4206-a5cb-c5cd188eeb35.jpg',
        frame: 'last'
      }
    ]
  }
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "positivePrompt": "Create a single continuous 10-second vertical product demonstration connecting the supplied endpoint frames. Keep the camera completely locked and preserve the mannequin, backpack design, jacket, laboratory, framing, proportions, and lighting. Begin with the avalanche airbag fully stowed and the orange trigger cable taut. The cable snaps downward and pulls the handle; the backpack's top seam opens mechanically. Signal-red airbag fabric emerges from the shoulder compartment, rapidly but physically inflates, and expands upward and outward into a protective horseshoe around the mannequin's head and shoulders. Show realistic staged inflation: fabric unfolding first, then chambers filling with pressure, wrinkles smoothing, seams becoming taut, and the final shape settling with one subtle rebound. A brief controlled puff of cold white test vapor escapes near the shoulder vents and dissipates naturally. The mannequin remains rigid and stable while jacket fabric reacts slightly to the airflow. Emphasize accurate product mechanics, technical fabric texture, crisp industrial detail, and a clear before-to-after explanation. No cuts, camera movement, morphing, extra equipment, people, text, logos, overlays, sparks, fire, or explosive shockwave.",
            "width": 1080,
            "height": 1920,
            "duration": 10,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/28a2d08a-1326-469d-94d4-5a0ea28fa2ae.jpg",
                        "frame": "first"
                    },
                    {
                        "image": "https://assets.runware.ai/assets/inputs/72b7dfe2-6cd6-4206-a5cb-c5cd188eeb35.jpg",
                        "frame": "last"
                    }
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "6ec75ef8-244b-4f79-99e2-bf7da935352e",
      "model": "klingai:3@2",
      "positivePrompt": "Create a single continuous 10-second vertical product demonstration connecting the supplied endpoint frames. Keep the camera completely locked and preserve the mannequin, backpack design, jacket, laboratory, framing, proportions, and lighting. Begin with the avalanche airbag fully stowed and the orange trigger cable taut. The cable snaps downward and pulls the handle; the backpack's top seam opens mechanically. Signal-red airbag fabric emerges from the shoulder compartment, rapidly but physically inflates, and expands upward and outward into a protective horseshoe around the mannequin's head and shoulders. Show realistic staged inflation: fabric unfolding first, then chambers filling with pressure, wrinkles smoothing, seams becoming taut, and the final shape settling with one subtle rebound. A brief controlled puff of cold white test vapor escapes near the shoulder vents and dissipates naturally. The mannequin remains rigid and stable while jacket fabric reacts slightly to the airflow. Emphasize accurate product mechanics, technical fabric texture, crisp industrial detail, and a clear before-to-after explanation. No cuts, camera movement, morphing, extra equipment, people, text, logos, overlays, sparks, fire, or explosive shockwave.",
      "width": 1080,
      "height": 1920,
      "duration": 10,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/28a2d08a-1326-469d-94d4-5a0ea28fa2ae.jpg",
            "frame": "first"
          },
          {
            "image": "https://assets.runware.ai/assets/inputs/72b7dfe2-6cd6-4206-a5cb-c5cd188eeb35.jpg",
            "frame": "last"
          }
        ]
      }
    }
  ]'

runware run klingai:3@2 \
  positivePrompt="Create a single continuous 10-second vertical product demonstration connecting the supplied endpoint frames. Keep the camera completely locked and preserve the mannequin, backpack design, jacket, laboratory, framing, proportions, and lighting. Begin with the avalanche airbag fully stowed and the orange trigger cable taut. The cable snaps downward and pulls the handle; the backpack's top seam opens mechanically. Signal-red airbag fabric emerges from the shoulder compartment, rapidly but physically inflates, and expands upward and outward into a protective horseshoe around the mannequin's head and shoulders. Show realistic staged inflation: fabric unfolding first, then chambers filling with pressure, wrinkles smoothing, seams becoming taut, and the final shape settling with one subtle rebound. A brief controlled puff of cold white test vapor escapes near the shoulder vents and dissipates naturally. The mannequin remains rigid and stable while jacket fabric reacts slightly to the airflow. Emphasize accurate product mechanics, technical fabric texture, crisp industrial detail, and a clear before-to-after explanation. No cuts, camera movement, morphing, extra equipment, people, text, logos, overlays, sparks, fire, or explosive shockwave." \
  width=1080 \
  height=1920 \
  duration=10 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/28a2d08a-1326-469d-94d4-5a0ea28fa2ae.jpg \
  inputs.frameImages.0.frame=first \
  inputs.frameImages.1.image=https://assets.runware.ai/assets/inputs/72b7dfe2-6cd6-4206-a5cb-c5cd188eeb35.jpg \
  inputs.frameImages.1.frame=last

{
  "taskType": "videoInference",
  "taskUUID": "6ec75ef8-244b-4f79-99e2-bf7da935352e",
  "model": "klingai:3@2",
  "positivePrompt": "Create a single continuous 10-second vertical product demonstration connecting the supplied endpoint frames. Keep the camera completely locked and preserve the mannequin, backpack design, jacket, laboratory, framing, proportions, and lighting. Begin with the avalanche airbag fully stowed and the orange trigger cable taut. The cable snaps downward and pulls the handle; the backpack's top seam opens mechanically. Signal-red airbag fabric emerges from the shoulder compartment, rapidly but physically inflates, and expands upward and outward into a protective horseshoe around the mannequin's head and shoulders. Show realistic staged inflation: fabric unfolding first, then chambers filling with pressure, wrinkles smoothing, seams becoming taut, and the final shape settling with one subtle rebound. A brief controlled puff of cold white test vapor escapes near the shoulder vents and dissipates naturally. The mannequin remains rigid and stable while jacket fabric reacts slightly to the airflow. Emphasize accurate product mechanics, technical fabric texture, crisp industrial detail, and a clear before-to-after explanation. No cuts, camera movement, morphing, extra equipment, people, text, logos, overlays, sparks, fire, or explosive shockwave.",
  "width": 1080,
  "height": 1920,
  "duration": 10,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/28a2d08a-1326-469d-94d4-5a0ea28fa2ae.jpg",
        "frame": "first"
      },
      {
        "image": "https://assets.runware.ai/assets/inputs/72b7dfe2-6cd6-4206-a5cb-c5cd188eeb35.jpg",
        "frame": "last"
      }
    ]
  }
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  width: 1920,
  height: 1080,
  duration: 5,
  CFGScale: 0.61,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/85565701-0333-49ed-acc8-5ff05d7dab46.jpg',
        frame: 'first'
      },
      {
        image: 'https://assets.runware.ai/assets/inputs/626775ac-612c-4283-93db-ad050ad47c7a.jpg',
        frame: 'last'
      }
    ]
  }
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "width": 1920,
            "height": 1080,
            "duration": 5,
            "CFGScale": 0.61,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/85565701-0333-49ed-acc8-5ff05d7dab46.jpg",
                        "frame": "first"
                    },
                    {
                        "image": "https://assets.runware.ai/assets/inputs/626775ac-612c-4283-93db-ad050ad47c7a.jpg",
                        "frame": "last"
                    }
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "574ec329-6440-4eb8-aaad-857b4866c16f",
      "model": "klingai:3@2",
      "width": 1920,
      "height": 1080,
      "duration": 5,
      "CFGScale": 0.61,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/85565701-0333-49ed-acc8-5ff05d7dab46.jpg",
            "frame": "first"
          },
          {
            "image": "https://assets.runware.ai/assets/inputs/626775ac-612c-4283-93db-ad050ad47c7a.jpg",
            "frame": "last"
          }
        ]
      }
    }
  ]'

runware run klingai:3@2 \
  width=1920 \
  height=1080 \
  duration=5 \
  CFGScale=0.61 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/85565701-0333-49ed-acc8-5ff05d7dab46.jpg \
  inputs.frameImages.0.frame=first \
  inputs.frameImages.1.image=https://assets.runware.ai/assets/inputs/626775ac-612c-4283-93db-ad050ad47c7a.jpg \
  inputs.frameImages.1.frame=last

{
  "taskType": "videoInference",
  "taskUUID": "574ec329-6440-4eb8-aaad-857b4866c16f",
  "model": "klingai:3@2",
  "width": 1920,
  "height": 1080,
  "duration": 5,
  "CFGScale": 0.61,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/85565701-0333-49ed-acc8-5ff05d7dab46.jpg",
        "frame": "first"
      },
      {
        "image": "https://assets.runware.ai/assets/inputs/626775ac-612c-4283-93db-ad050ad47c7a.jpg",
        "frame": "last"
      }
    ]
  }
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  width: 1920,
  height: 1080,
  duration: 5,
  CFGScale: 0.63,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/13b3128c-1388-4ef0-a381-e6636865ae4d.jpg',
        frame: 'first'
      },
      {
        image: 'https://assets.runware.ai/assets/inputs/2af37daf-00dd-44cc-90de-ddeb77cab964.jpg',
        frame: 'last'
      }
    ]
  }
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "width": 1920,
            "height": 1080,
            "duration": 5,
            "CFGScale": 0.63,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/13b3128c-1388-4ef0-a381-e6636865ae4d.jpg",
                        "frame": "first"
                    },
                    {
                        "image": "https://assets.runware.ai/assets/inputs/2af37daf-00dd-44cc-90de-ddeb77cab964.jpg",
                        "frame": "last"
                    }
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "06c38629-89c8-4af9-94e3-ee1a0729000c",
      "model": "klingai:3@2",
      "width": 1920,
      "height": 1080,
      "duration": 5,
      "CFGScale": 0.63,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/13b3128c-1388-4ef0-a381-e6636865ae4d.jpg",
            "frame": "first"
          },
          {
            "image": "https://assets.runware.ai/assets/inputs/2af37daf-00dd-44cc-90de-ddeb77cab964.jpg",
            "frame": "last"
          }
        ]
      }
    }
  ]'

runware run klingai:3@2 \
  width=1920 \
  height=1080 \
  duration=5 \
  CFGScale=0.63 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/13b3128c-1388-4ef0-a381-e6636865ae4d.jpg \
  inputs.frameImages.0.frame=first \
  inputs.frameImages.1.image=https://assets.runware.ai/assets/inputs/2af37daf-00dd-44cc-90de-ddeb77cab964.jpg \
  inputs.frameImages.1.frame=last

{
  "taskType": "videoInference",
  "taskUUID": "06c38629-89c8-4af9-94e3-ee1a0729000c",
  "model": "klingai:3@2",
  "width": 1920,
  "height": 1080,
  "duration": 5,
  "CFGScale": 0.63,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/13b3128c-1388-4ef0-a381-e6636865ae4d.jpg",
        "frame": "first"
      },
      {
        "image": "https://assets.runware.ai/assets/inputs/2af37daf-00dd-44cc-90de-ddeb77cab964.jpg",
        "frame": "last"
      }
    ]
  }
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  width: 1920,
  height: 1080,
  duration: 5,
  CFGScale: 0.7,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/98d8ef45-0ed2-48d7-a85c-0643d31c1f2e.jpg',
        frame: 'first'
      },
      {
        image: 'https://assets.runware.ai/assets/inputs/4ce163a9-b621-4437-a91a-83818bea60dc.jpg',
        frame: 'last'
      }
    ]
  }
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "width": 1920,
            "height": 1080,
            "duration": 5,
            "CFGScale": 0.7,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/98d8ef45-0ed2-48d7-a85c-0643d31c1f2e.jpg",
                        "frame": "first"
                    },
                    {
                        "image": "https://assets.runware.ai/assets/inputs/4ce163a9-b621-4437-a91a-83818bea60dc.jpg",
                        "frame": "last"
                    }
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "0a594031-6e45-4ed5-a3c9-5f696ecae3e4",
      "model": "klingai:3@2",
      "width": 1920,
      "height": 1080,
      "duration": 5,
      "CFGScale": 0.7,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/98d8ef45-0ed2-48d7-a85c-0643d31c1f2e.jpg",
            "frame": "first"
          },
          {
            "image": "https://assets.runware.ai/assets/inputs/4ce163a9-b621-4437-a91a-83818bea60dc.jpg",
            "frame": "last"
          }
        ]
      }
    }
  ]'

runware run klingai:3@2 \
  width=1920 \
  height=1080 \
  duration=5 \
  CFGScale=0.7 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/98d8ef45-0ed2-48d7-a85c-0643d31c1f2e.jpg \
  inputs.frameImages.0.frame=first \
  inputs.frameImages.1.image=https://assets.runware.ai/assets/inputs/4ce163a9-b621-4437-a91a-83818bea60dc.jpg \
  inputs.frameImages.1.frame=last

{
  "taskType": "videoInference",
  "taskUUID": "0a594031-6e45-4ed5-a3c9-5f696ecae3e4",
  "model": "klingai:3@2",
  "width": 1920,
  "height": 1080,
  "duration": 5,
  "CFGScale": 0.7,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/98d8ef45-0ed2-48d7-a85c-0643d31c1f2e.jpg",
        "frame": "first"
      },
      {
        "image": "https://assets.runware.ai/assets/inputs/4ce163a9-b621-4437-a91a-83818bea60dc.jpg",
        "frame": "last"
      }
    ]
  }
}

import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'klingai:3@2',
  width: 1920,
  height: 1080,
  duration: 5,
  CFGScale: 0.5,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/707c859d-8043-4584-a364-f59500a9f687.jpg'
      }
    ]
  }
})

import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "klingai:3@2",
            "width": 1920,
            "height": 1080,
            "duration": 5,
            "CFGScale": 0.5,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/707c859d-8043-4584-a364-f59500a9f687.jpg"
                    }
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "1c7d3789-92b8-4174-bc3f-0329d200f93d",
      "model": "klingai:3@2",
      "width": 1920,
      "height": 1080,
      "duration": 5,
      "CFGScale": 0.5,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/707c859d-8043-4584-a364-f59500a9f687.jpg"
          }
        ]
      }
    }
  ]'

runware run klingai:3@2 \
  width=1920 \
  height=1080 \
  duration=5 \
  CFGScale=0.5 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/707c859d-8043-4584-a364-f59500a9f687.jpg

{
  "taskType": "videoInference",
  "taskUUID": "1c7d3789-92b8-4174-bc3f-0329d200f93d",
  "model": "klingai:3@2",
  "width": 1920,
  "height": 1080,
  "duration": 5,
  "CFGScale": 0.5,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/707c859d-8043-4584-a364-f59500a9f687.jpg"
      }
    ]
  }
}