MiniMax H3

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'minimax:h3@0',
  positivePrompt: 'Create a polished six-second living team portrait for a mountain ski patrol recruitment campaign. Single continuous landscape shot outside an alpine rescue hut at blue hour after fresh snowfall. Eight adult ski patrollers stand shoulder-to-shoulder facing the camera in practical red rescue jackets, dark snow pants, helmets, radios and avalanche gear; varied ages and appearances, relaxed but professional, no visible logos. Skis and a rescue toboggan rest neatly beside the timber equipment bay. Warm amber light spills from the hut against cool cobalt snow and a pale mountain sky.\n\nTemporal progression: begin with the complete patrol lineup holding a formal group-photo pose while one deliberate gap remains near the center. After about one second, a lively black-and-white avalanche rescue dog runs in from the right foreground, kicking up soft powder. The patrollers notice it, smile naturally and shift just enough to open the gap. The dog reaches the center, turns toward camera and sits proudly between two patrollers. One patroller briefly lowers a gloved hand to steady the dog. By the final two seconds, everyone is composed and looking into the lens as a cohesive team portrait, with the dog\'s breath faintly visible in the cold air and its tail making one final wag.\n\nCamera: eye-level medium-wide group framing, symmetrical but natural composition, all eight people visible head to boot, dog fully visible, mountain ridge retained above them. Locked tripod with an almost imperceptible slow push-in; no cuts, no reframing, no handheld shake. Preserve consistent faces, clothing, body count and equipment throughout. Premium documentary realism with subtle 1970s alpine tourism color influence, fine film grain, crisp winter air, restrained rescue-red, amber and deep-blue palette. Natural synchronized sound only: soft boots shifting in snow, the dog\'s paws and collar, a light mountain breeze and one quiet shared chuckle. No dialogue, captions, titles, signage, watermarks or added graphics.',
  width: 1344,
  height: 768,
  duration: 6
})

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": "minimax:h3@0",
            "positivePrompt": "Create a polished six-second living team portrait for a mountain ski patrol recruitment campaign. Single continuous landscape shot outside an alpine rescue hut at blue hour after fresh snowfall. Eight adult ski patrollers stand shoulder-to-shoulder facing the camera in practical red rescue jackets, dark snow pants, helmets, radios and avalanche gear; varied ages and appearances, relaxed but professional, no visible logos. Skis and a rescue toboggan rest neatly beside the timber equipment bay. Warm amber light spills from the hut against cool cobalt snow and a pale mountain sky.\n\nTemporal progression: begin with the complete patrol lineup holding a formal group-photo pose while one deliberate gap remains near the center. After about one second, a lively black-and-white avalanche rescue dog runs in from the right foreground, kicking up soft powder. The patrollers notice it, smile naturally and shift just enough to open the gap. The dog reaches the center, turns toward camera and sits proudly between two patrollers. One patroller briefly lowers a gloved hand to steady the dog. By the final two seconds, everyone is composed and looking into the lens as a cohesive team portrait, with the dog's breath faintly visible in the cold air and its tail making one final wag.\n\nCamera: eye-level medium-wide group framing, symmetrical but natural composition, all eight people visible head to boot, dog fully visible, mountain ridge retained above them. Locked tripod with an almost imperceptible slow push-in; no cuts, no reframing, no handheld shake. Preserve consistent faces, clothing, body count and equipment throughout. Premium documentary realism with subtle 1970s alpine tourism color influence, fine film grain, crisp winter air, restrained rescue-red, amber and deep-blue palette. Natural synchronized sound only: soft boots shifting in snow, the dog's paws and collar, a light mountain breeze and one quiet shared chuckle. No dialogue, captions, titles, signage, watermarks or added graphics.",
            "width": 1344,
            "height": 768,
            "duration": 6
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "6592f33b-6e7e-4bcb-8973-836bfc3c92ff",
      "model": "minimax:h3@0",
      "positivePrompt": "Create a polished six-second living team portrait for a mountain ski patrol recruitment campaign. Single continuous landscape shot outside an alpine rescue hut at blue hour after fresh snowfall. Eight adult ski patrollers stand shoulder-to-shoulder facing the camera in practical red rescue jackets, dark snow pants, helmets, radios and avalanche gear; varied ages and appearances, relaxed but professional, no visible logos. Skis and a rescue toboggan rest neatly beside the timber equipment bay. Warm amber light spills from the hut against cool cobalt snow and a pale mountain sky.\n\nTemporal progression: begin with the complete patrol lineup holding a formal group-photo pose while one deliberate gap remains near the center. After about one second, a lively black-and-white avalanche rescue dog runs in from the right foreground, kicking up soft powder. The patrollers notice it, smile naturally and shift just enough to open the gap. The dog reaches the center, turns toward camera and sits proudly between two patrollers. One patroller briefly lowers a gloved hand to steady the dog. By the final two seconds, everyone is composed and looking into the lens as a cohesive team portrait, with the dog's breath faintly visible in the cold air and its tail making one final wag.\n\nCamera: eye-level medium-wide group framing, symmetrical but natural composition, all eight people visible head to boot, dog fully visible, mountain ridge retained above them. Locked tripod with an almost imperceptible slow push-in; no cuts, no reframing, no handheld shake. Preserve consistent faces, clothing, body count and equipment throughout. Premium documentary realism with subtle 1970s alpine tourism color influence, fine film grain, crisp winter air, restrained rescue-red, amber and deep-blue palette. Natural synchronized sound only: soft boots shifting in snow, the dog's paws and collar, a light mountain breeze and one quiet shared chuckle. No dialogue, captions, titles, signage, watermarks or added graphics.",
      "width": 1344,
      "height": 768,
      "duration": 6
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Create a polished six-second living team portrait for a mountain ski patrol recruitment campaign. Single continuous landscape shot outside an alpine rescue hut at blue hour after fresh snowfall. Eight adult ski patrollers stand shoulder-to-shoulder facing the camera in practical red rescue jackets, dark snow pants, helmets, radios and avalanche gear; varied ages and appearances, relaxed but professional, no visible logos. Skis and a rescue toboggan rest neatly beside the timber equipment bay. Warm amber light spills from the hut against cool cobalt snow and a pale mountain sky.

Temporal progression: begin with the complete patrol lineup holding a formal group-photo pose while one deliberate gap remains near the center. After about one second, a lively black-and-white avalanche rescue dog runs in from the right foreground, kicking up soft powder. The patrollers notice it, smile naturally and shift just enough to open the gap. The dog reaches the center, turns toward camera and sits proudly between two patrollers. One patroller briefly lowers a gloved hand to steady the dog. By the final two seconds, everyone is composed and looking into the lens as a cohesive team portrait, with the dog's breath faintly visible in the cold air and its tail making one final wag.

Camera: eye-level medium-wide group framing, symmetrical but natural composition, all eight people visible head to boot, dog fully visible, mountain ridge retained above them. Locked tripod with an almost imperceptible slow push-in; no cuts, no reframing, no handheld shake. Preserve consistent faces, clothing, body count and equipment throughout. Premium documentary realism with subtle 1970s alpine tourism color influence, fine film grain, crisp winter air, restrained rescue-red, amber and deep-blue palette. Natural synchronized sound only: soft boots shifting in snow, the dog's paws and collar, a light mountain breeze and one quiet shared chuckle. No dialogue, captions, titles, signage, watermarks or added graphics." \
  width=1344 \
  height=768 \
  duration=6

{
  "taskType": "videoInference",
  "taskUUID": "6592f33b-6e7e-4bcb-8973-836bfc3c92ff",
  "model": "minimax:h3@0",
  "positivePrompt": "Create a polished six-second living team portrait for a mountain ski patrol recruitment campaign. Single continuous landscape shot outside an alpine rescue hut at blue hour after fresh snowfall. Eight adult ski patrollers stand shoulder-to-shoulder facing the camera in practical red rescue jackets, dark snow pants, helmets, radios and avalanche gear; varied ages and appearances, relaxed but professional, no visible logos. Skis and a rescue toboggan rest neatly beside the timber equipment bay. Warm amber light spills from the hut against cool cobalt snow and a pale mountain sky.\n\nTemporal progression: begin with the complete patrol lineup holding a formal group-photo pose while one deliberate gap remains near the center. After about one second, a lively black-and-white avalanche rescue dog runs in from the right foreground, kicking up soft powder. The patrollers notice it, smile naturally and shift just enough to open the gap. The dog reaches the center, turns toward camera and sits proudly between two patrollers. One patroller briefly lowers a gloved hand to steady the dog. By the final two seconds, everyone is composed and looking into the lens as a cohesive team portrait, with the dog's breath faintly visible in the cold air and its tail making one final wag.\n\nCamera: eye-level medium-wide group framing, symmetrical but natural composition, all eight people visible head to boot, dog fully visible, mountain ridge retained above them. Locked tripod with an almost imperceptible slow push-in; no cuts, no reframing, no handheld shake. Preserve consistent faces, clothing, body count and equipment throughout. Premium documentary realism with subtle 1970s alpine tourism color influence, fine film grain, crisp winter air, restrained rescue-red, amber and deep-blue palette. Natural synchronized sound only: soft boots shifting in snow, the dog's paws and collar, a light mountain breeze and one quiet shared chuckle. No dialogue, captions, titles, signage, watermarks or added graphics.",
  "width": 1344,
  "height": 768,
  "duration": 6
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'minimax:h3@0',
  positivePrompt: 'The scene continues naturally from the supplied first frame as a single uninterrupted eight-second stock-footage shot inside an indoor wasabi farm. The worker slowly loosens the wet gravel around the plant with one hand, then lifts the mature wasabi root smoothly into view, revealing its knobbly pale-green rhizome and fine dangling roots. Small pebbles tumble back into the shallow bed, droplets fall from the root, and nearby heart-shaped leaves sway gently from the movement and circulating greenhouse air. The camera performs a restrained, steady slider move forward and slightly to the right while maintaining the root and gloved hands as the focal point; realistic parallax develops across the receding crop rows. Finish with the freshly harvested rhizome held clearly in the foreground for useful editorial coverage. Photorealistic premium agricultural documentary b-roll, controlled natural motion, authentic horticultural handling, shallow depth of field, soft diffused skylight, cool humid atmosphere, rich emerald greens and muted silver-gray infrastructure, crisp water droplets, subtle filmic contrast. No cuts, no time lapse, no talking, no eye contact, no signage, no logos, no captions, no on-screen text. Natural synchronized ambience only: low irrigation trickle, faint ventilation hum, soft leaf rustle, gravel shifting, and droplets landing.',
  resolution: '768p',
  duration: 8,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/93bc5eb1-8f3d-4c56-9232-06f3da7dce28.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": "minimax:h3@0",
            "positivePrompt": "The scene continues naturally from the supplied first frame as a single uninterrupted eight-second stock-footage shot inside an indoor wasabi farm. The worker slowly loosens the wet gravel around the plant with one hand, then lifts the mature wasabi root smoothly into view, revealing its knobbly pale-green rhizome and fine dangling roots. Small pebbles tumble back into the shallow bed, droplets fall from the root, and nearby heart-shaped leaves sway gently from the movement and circulating greenhouse air. The camera performs a restrained, steady slider move forward and slightly to the right while maintaining the root and gloved hands as the focal point; realistic parallax develops across the receding crop rows. Finish with the freshly harvested rhizome held clearly in the foreground for useful editorial coverage. Photorealistic premium agricultural documentary b-roll, controlled natural motion, authentic horticultural handling, shallow depth of field, soft diffused skylight, cool humid atmosphere, rich emerald greens and muted silver-gray infrastructure, crisp water droplets, subtle filmic contrast. No cuts, no time lapse, no talking, no eye contact, no signage, no logos, no captions, no on-screen text. Natural synchronized ambience only: low irrigation trickle, faint ventilation hum, soft leaf rustle, gravel shifting, and droplets landing.",
            "resolution": "768p",
            "duration": 8,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/93bc5eb1-8f3d-4c56-9232-06f3da7dce28.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": "3cd47883-fa01-412f-8263-b4c3725aea6e",
      "model": "minimax:h3@0",
      "positivePrompt": "The scene continues naturally from the supplied first frame as a single uninterrupted eight-second stock-footage shot inside an indoor wasabi farm. The worker slowly loosens the wet gravel around the plant with one hand, then lifts the mature wasabi root smoothly into view, revealing its knobbly pale-green rhizome and fine dangling roots. Small pebbles tumble back into the shallow bed, droplets fall from the root, and nearby heart-shaped leaves sway gently from the movement and circulating greenhouse air. The camera performs a restrained, steady slider move forward and slightly to the right while maintaining the root and gloved hands as the focal point; realistic parallax develops across the receding crop rows. Finish with the freshly harvested rhizome held clearly in the foreground for useful editorial coverage. Photorealistic premium agricultural documentary b-roll, controlled natural motion, authentic horticultural handling, shallow depth of field, soft diffused skylight, cool humid atmosphere, rich emerald greens and muted silver-gray infrastructure, crisp water droplets, subtle filmic contrast. No cuts, no time lapse, no talking, no eye contact, no signage, no logos, no captions, no on-screen text. Natural synchronized ambience only: low irrigation trickle, faint ventilation hum, soft leaf rustle, gravel shifting, and droplets landing.",
      "resolution": "768p",
      "duration": 8,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/93bc5eb1-8f3d-4c56-9232-06f3da7dce28.jpg",
            "frame": "first"
          }
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="The scene continues naturally from the supplied first frame as a single uninterrupted eight-second stock-footage shot inside an indoor wasabi farm. The worker slowly loosens the wet gravel around the plant with one hand, then lifts the mature wasabi root smoothly into view, revealing its knobbly pale-green rhizome and fine dangling roots. Small pebbles tumble back into the shallow bed, droplets fall from the root, and nearby heart-shaped leaves sway gently from the movement and circulating greenhouse air. The camera performs a restrained, steady slider move forward and slightly to the right while maintaining the root and gloved hands as the focal point; realistic parallax develops across the receding crop rows. Finish with the freshly harvested rhizome held clearly in the foreground for useful editorial coverage. Photorealistic premium agricultural documentary b-roll, controlled natural motion, authentic horticultural handling, shallow depth of field, soft diffused skylight, cool humid atmosphere, rich emerald greens and muted silver-gray infrastructure, crisp water droplets, subtle filmic contrast. No cuts, no time lapse, no talking, no eye contact, no signage, no logos, no captions, no on-screen text. Natural synchronized ambience only: low irrigation trickle, faint ventilation hum, soft leaf rustle, gravel shifting, and droplets landing." \
  resolution=768p \
  duration=8 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/93bc5eb1-8f3d-4c56-9232-06f3da7dce28.jpg \
  inputs.frameImages.0.frame=first

{
  "taskType": "videoInference",
  "taskUUID": "3cd47883-fa01-412f-8263-b4c3725aea6e",
  "model": "minimax:h3@0",
  "positivePrompt": "The scene continues naturally from the supplied first frame as a single uninterrupted eight-second stock-footage shot inside an indoor wasabi farm. The worker slowly loosens the wet gravel around the plant with one hand, then lifts the mature wasabi root smoothly into view, revealing its knobbly pale-green rhizome and fine dangling roots. Small pebbles tumble back into the shallow bed, droplets fall from the root, and nearby heart-shaped leaves sway gently from the movement and circulating greenhouse air. The camera performs a restrained, steady slider move forward and slightly to the right while maintaining the root and gloved hands as the focal point; realistic parallax develops across the receding crop rows. Finish with the freshly harvested rhizome held clearly in the foreground for useful editorial coverage. Photorealistic premium agricultural documentary b-roll, controlled natural motion, authentic horticultural handling, shallow depth of field, soft diffused skylight, cool humid atmosphere, rich emerald greens and muted silver-gray infrastructure, crisp water droplets, subtle filmic contrast. No cuts, no time lapse, no talking, no eye contact, no signage, no logos, no captions, no on-screen text. Natural synchronized ambience only: low irrigation trickle, faint ventilation hum, soft leaf rustle, gravel shifting, and droplets landing.",
  "resolution": "768p",
  "duration": 8,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/93bc5eb1-8f3d-4c56-9232-06f3da7dce28.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: 'minimax:h3@0',
  positivePrompt: 'Create a polished single-shot colorway reveal for a professional diver propulsion vehicle, transitioning coherently from the supplied first frame to the supplied last frame. Begin with the rescue-orange scooter perfectly still on its wet black-basalt plinth. Hold the opening composition briefly, then send a narrow band of refracted cyan light slowly across the product from left to right. As the light passes, only the orange outer shell changes progressively into deep kelp green, with a convincing premium factory finish and tiny beads of water catching the light. Preserve the scooter\'s exact silhouette, dimensions, seams, fasteners, control module, black handles, ducted propeller, orientation, and position throughout; this is a product recolor, not a redesign or transformation. Keep the camera locked at the same eye-level three-quarter angle with no zoom, cuts, or reframing. Add restrained motion only in the environment: drifting microbubbles, gently moving aquatic caustic reflections, and a faint curl of cool mist along the plinth. Finish cleanly on the supplied kelp-green endpoint image and hold long enough to inspect the completed colorway. Photorealistic high-end industrial product cinematography, crisp materials, dark cyan expedition-lab atmosphere, controlled cool rim light, realistic reflections, no people, no logos, no lettering, no packaging, no extra objects. Synchronized sound: subtle underwater pressure ambience, delicate bubbles, and one soft low-frequency sweep following the moving light band; no voice and no music.',
  resolution: '1440p',
  duration: 10,
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/5910fd92-f212-4f8f-b55b-d07d91486788.jpg',
        frame: 'first'
      },
      {
        image: 'https://assets.runware.ai/assets/inputs/7aa2c02b-988f-4012-882a-dc7172d2e571.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": "minimax:h3@0",
            "positivePrompt": "Create a polished single-shot colorway reveal for a professional diver propulsion vehicle, transitioning coherently from the supplied first frame to the supplied last frame. Begin with the rescue-orange scooter perfectly still on its wet black-basalt plinth. Hold the opening composition briefly, then send a narrow band of refracted cyan light slowly across the product from left to right. As the light passes, only the orange outer shell changes progressively into deep kelp green, with a convincing premium factory finish and tiny beads of water catching the light. Preserve the scooter's exact silhouette, dimensions, seams, fasteners, control module, black handles, ducted propeller, orientation, and position throughout; this is a product recolor, not a redesign or transformation. Keep the camera locked at the same eye-level three-quarter angle with no zoom, cuts, or reframing. Add restrained motion only in the environment: drifting microbubbles, gently moving aquatic caustic reflections, and a faint curl of cool mist along the plinth. Finish cleanly on the supplied kelp-green endpoint image and hold long enough to inspect the completed colorway. Photorealistic high-end industrial product cinematography, crisp materials, dark cyan expedition-lab atmosphere, controlled cool rim light, realistic reflections, no people, no logos, no lettering, no packaging, no extra objects. Synchronized sound: subtle underwater pressure ambience, delicate bubbles, and one soft low-frequency sweep following the moving light band; no voice and no music.",
            "resolution": "1440p",
            "duration": 10,
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/5910fd92-f212-4f8f-b55b-d07d91486788.jpg",
                        "frame": "first"
                    },
                    {
                        "image": "https://assets.runware.ai/assets/inputs/7aa2c02b-988f-4012-882a-dc7172d2e571.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": "d9a4a833-4f42-4561-b503-236bb89f2c02",
      "model": "minimax:h3@0",
      "positivePrompt": "Create a polished single-shot colorway reveal for a professional diver propulsion vehicle, transitioning coherently from the supplied first frame to the supplied last frame. Begin with the rescue-orange scooter perfectly still on its wet black-basalt plinth. Hold the opening composition briefly, then send a narrow band of refracted cyan light slowly across the product from left to right. As the light passes, only the orange outer shell changes progressively into deep kelp green, with a convincing premium factory finish and tiny beads of water catching the light. Preserve the scooter's exact silhouette, dimensions, seams, fasteners, control module, black handles, ducted propeller, orientation, and position throughout; this is a product recolor, not a redesign or transformation. Keep the camera locked at the same eye-level three-quarter angle with no zoom, cuts, or reframing. Add restrained motion only in the environment: drifting microbubbles, gently moving aquatic caustic reflections, and a faint curl of cool mist along the plinth. Finish cleanly on the supplied kelp-green endpoint image and hold long enough to inspect the completed colorway. Photorealistic high-end industrial product cinematography, crisp materials, dark cyan expedition-lab atmosphere, controlled cool rim light, realistic reflections, no people, no logos, no lettering, no packaging, no extra objects. Synchronized sound: subtle underwater pressure ambience, delicate bubbles, and one soft low-frequency sweep following the moving light band; no voice and no music.",
      "resolution": "1440p",
      "duration": 10,
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/5910fd92-f212-4f8f-b55b-d07d91486788.jpg",
            "frame": "first"
          },
          {
            "image": "https://assets.runware.ai/assets/inputs/7aa2c02b-988f-4012-882a-dc7172d2e571.jpg",
            "frame": "last"
          }
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Create a polished single-shot colorway reveal for a professional diver propulsion vehicle, transitioning coherently from the supplied first frame to the supplied last frame. Begin with the rescue-orange scooter perfectly still on its wet black-basalt plinth. Hold the opening composition briefly, then send a narrow band of refracted cyan light slowly across the product from left to right. As the light passes, only the orange outer shell changes progressively into deep kelp green, with a convincing premium factory finish and tiny beads of water catching the light. Preserve the scooter's exact silhouette, dimensions, seams, fasteners, control module, black handles, ducted propeller, orientation, and position throughout; this is a product recolor, not a redesign or transformation. Keep the camera locked at the same eye-level three-quarter angle with no zoom, cuts, or reframing. Add restrained motion only in the environment: drifting microbubbles, gently moving aquatic caustic reflections, and a faint curl of cool mist along the plinth. Finish cleanly on the supplied kelp-green endpoint image and hold long enough to inspect the completed colorway. Photorealistic high-end industrial product cinematography, crisp materials, dark cyan expedition-lab atmosphere, controlled cool rim light, realistic reflections, no people, no logos, no lettering, no packaging, no extra objects. Synchronized sound: subtle underwater pressure ambience, delicate bubbles, and one soft low-frequency sweep following the moving light band; no voice and no music." \
  resolution=1440p \
  duration=10 \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/5910fd92-f212-4f8f-b55b-d07d91486788.jpg \
  inputs.frameImages.0.frame=first \
  inputs.frameImages.1.image=https://assets.runware.ai/assets/inputs/7aa2c02b-988f-4012-882a-dc7172d2e571.jpg \
  inputs.frameImages.1.frame=last

{
  "taskType": "videoInference",
  "taskUUID": "d9a4a833-4f42-4561-b503-236bb89f2c02",
  "model": "minimax:h3@0",
  "positivePrompt": "Create a polished single-shot colorway reveal for a professional diver propulsion vehicle, transitioning coherently from the supplied first frame to the supplied last frame. Begin with the rescue-orange scooter perfectly still on its wet black-basalt plinth. Hold the opening composition briefly, then send a narrow band of refracted cyan light slowly across the product from left to right. As the light passes, only the orange outer shell changes progressively into deep kelp green, with a convincing premium factory finish and tiny beads of water catching the light. Preserve the scooter's exact silhouette, dimensions, seams, fasteners, control module, black handles, ducted propeller, orientation, and position throughout; this is a product recolor, not a redesign or transformation. Keep the camera locked at the same eye-level three-quarter angle with no zoom, cuts, or reframing. Add restrained motion only in the environment: drifting microbubbles, gently moving aquatic caustic reflections, and a faint curl of cool mist along the plinth. Finish cleanly on the supplied kelp-green endpoint image and hold long enough to inspect the completed colorway. Photorealistic high-end industrial product cinematography, crisp materials, dark cyan expedition-lab atmosphere, controlled cool rim light, realistic reflections, no people, no logos, no lettering, no packaging, no extra objects. Synchronized sound: subtle underwater pressure ambience, delicate bubbles, and one soft low-frequency sweep following the moving light band; no voice and no music.",
  "resolution": "1440p",
  "duration": 10,
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/5910fd92-f212-4f8f-b55b-d07d91486788.jpg",
        "frame": "first"
      },
      {
        "image": "https://assets.runware.ai/assets/inputs/7aa2c02b-988f-4012-882a-dc7172d2e571.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: 'minimax:h3@0',
  positivePrompt: 'Create a polished 12-second municipal public-health talking-head video in a cinematic documentary style. The presenter is the wastewater scientist shown in the reference image: preserve her facial identity, short natural curls, warm brown skin, clear safety glasses, navy utility coverall, teal gloves, and approachable professional presence. Place her at a clean stainless-steel testing bench in the same modern wastewater laboratory, with softly defocused sample bottles and turquoise-lit utility pipes behind her. Use the reference image as the primary guide for subject identity, wardrobe, laboratory design, cyan-and-amber palette, and lighting.\n\nUse the reference video as guidance for framing and performance: one uninterrupted eye-level medium shot, presenter centered slightly left with modest negative space, restrained documentary camera language, and a very slow subtle push-in. Match its natural posture, direct eye contact, realistic blinking, small open-hand emphasis gesture, and reassuring finishing nod. Avoid exaggerated gesturing or commercial-presenter energy.\n\nUse the reference audio as the exact spoken performance and synchronize the presenter’s mouth, facial articulation, pauses, breath, gesture timing, and final nod precisely to it. Preserve a credible adult female voice and clean speech intelligibility. Add only subtle, realistic laboratory room tone underneath—soft ventilation and distant water-system hum—with no music and no competing machinery noise.\n\nThe mood is practical, trustworthy, and quietly urgent rather than alarming. Keep skin texture, hands, safety glasses, lip motion, and eye movement photorealistic. Maintain continuity throughout with no cuts, no additional people, no logos, no captions, no lower thirds, no visible brand names, and no on-screen text.',
  resolution: '768p',
  duration: 12,
  inputs: {
    referenceImages: [
      'https://assets.runware.ai/assets/inputs/40514195-8f31-4c96-90c2-745681242642.jpg'
    ],
    referenceVideos: [
      'https://assets.runware.ai/assets/inputs/2979c59c-60b2-4eb5-b38b-ef5e2f115ed3.mp4'
    ],
    referenceAudios: [
      'https://assets.runware.ai/assets/inputs/4723fc05-9966-41c2-b7e8-40ef4cc59920.mp3'
    ]
  }
})

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": "minimax:h3@0",
            "positivePrompt": "Create a polished 12-second municipal public-health talking-head video in a cinematic documentary style. The presenter is the wastewater scientist shown in the reference image: preserve her facial identity, short natural curls, warm brown skin, clear safety glasses, navy utility coverall, teal gloves, and approachable professional presence. Place her at a clean stainless-steel testing bench in the same modern wastewater laboratory, with softly defocused sample bottles and turquoise-lit utility pipes behind her. Use the reference image as the primary guide for subject identity, wardrobe, laboratory design, cyan-and-amber palette, and lighting.\n\nUse the reference video as guidance for framing and performance: one uninterrupted eye-level medium shot, presenter centered slightly left with modest negative space, restrained documentary camera language, and a very slow subtle push-in. Match its natural posture, direct eye contact, realistic blinking, small open-hand emphasis gesture, and reassuring finishing nod. Avoid exaggerated gesturing or commercial-presenter energy.\n\nUse the reference audio as the exact spoken performance and synchronize the presenter’s mouth, facial articulation, pauses, breath, gesture timing, and final nod precisely to it. Preserve a credible adult female voice and clean speech intelligibility. Add only subtle, realistic laboratory room tone underneath—soft ventilation and distant water-system hum—with no music and no competing machinery noise.\n\nThe mood is practical, trustworthy, and quietly urgent rather than alarming. Keep skin texture, hands, safety glasses, lip motion, and eye movement photorealistic. Maintain continuity throughout with no cuts, no additional people, no logos, no captions, no lower thirds, no visible brand names, and no on-screen text.",
            "resolution": "768p",
            "duration": 12,
            "inputs": {
                "referenceImages": [
                    "https://assets.runware.ai/assets/inputs/40514195-8f31-4c96-90c2-745681242642.jpg"
                ],
                "referenceVideos": [
                    "https://assets.runware.ai/assets/inputs/2979c59c-60b2-4eb5-b38b-ef5e2f115ed3.mp4"
                ],
                "referenceAudios": [
                    "https://assets.runware.ai/assets/inputs/4723fc05-9966-41c2-b7e8-40ef4cc59920.mp3"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "50c2c534-6240-4f75-a203-70dcbddc2b5b",
      "model": "minimax:h3@0",
      "positivePrompt": "Create a polished 12-second municipal public-health talking-head video in a cinematic documentary style. The presenter is the wastewater scientist shown in the reference image: preserve her facial identity, short natural curls, warm brown skin, clear safety glasses, navy utility coverall, teal gloves, and approachable professional presence. Place her at a clean stainless-steel testing bench in the same modern wastewater laboratory, with softly defocused sample bottles and turquoise-lit utility pipes behind her. Use the reference image as the primary guide for subject identity, wardrobe, laboratory design, cyan-and-amber palette, and lighting.\n\nUse the reference video as guidance for framing and performance: one uninterrupted eye-level medium shot, presenter centered slightly left with modest negative space, restrained documentary camera language, and a very slow subtle push-in. Match its natural posture, direct eye contact, realistic blinking, small open-hand emphasis gesture, and reassuring finishing nod. Avoid exaggerated gesturing or commercial-presenter energy.\n\nUse the reference audio as the exact spoken performance and synchronize the presenter’s mouth, facial articulation, pauses, breath, gesture timing, and final nod precisely to it. Preserve a credible adult female voice and clean speech intelligibility. Add only subtle, realistic laboratory room tone underneath—soft ventilation and distant water-system hum—with no music and no competing machinery noise.\n\nThe mood is practical, trustworthy, and quietly urgent rather than alarming. Keep skin texture, hands, safety glasses, lip motion, and eye movement photorealistic. Maintain continuity throughout with no cuts, no additional people, no logos, no captions, no lower thirds, no visible brand names, and no on-screen text.",
      "resolution": "768p",
      "duration": 12,
      "inputs": {
        "referenceImages": [
          "https://assets.runware.ai/assets/inputs/40514195-8f31-4c96-90c2-745681242642.jpg"
        ],
        "referenceVideos": [
          "https://assets.runware.ai/assets/inputs/2979c59c-60b2-4eb5-b38b-ef5e2f115ed3.mp4"
        ],
        "referenceAudios": [
          "https://assets.runware.ai/assets/inputs/4723fc05-9966-41c2-b7e8-40ef4cc59920.mp3"
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Create a polished 12-second municipal public-health talking-head video in a cinematic documentary style. The presenter is the wastewater scientist shown in the reference image: preserve her facial identity, short natural curls, warm brown skin, clear safety glasses, navy utility coverall, teal gloves, and approachable professional presence. Place her at a clean stainless-steel testing bench in the same modern wastewater laboratory, with softly defocused sample bottles and turquoise-lit utility pipes behind her. Use the reference image as the primary guide for subject identity, wardrobe, laboratory design, cyan-and-amber palette, and lighting.

Use the reference video as guidance for framing and performance: one uninterrupted eye-level medium shot, presenter centered slightly left with modest negative space, restrained documentary camera language, and a very slow subtle push-in. Match its natural posture, direct eye contact, realistic blinking, small open-hand emphasis gesture, and reassuring finishing nod. Avoid exaggerated gesturing or commercial-presenter energy.

Use the reference audio as the exact spoken performance and synchronize the presenter’s mouth, facial articulation, pauses, breath, gesture timing, and final nod precisely to it. Preserve a credible adult female voice and clean speech intelligibility. Add only subtle, realistic laboratory room tone underneath—soft ventilation and distant water-system hum—with no music and no competing machinery noise.

The mood is practical, trustworthy, and quietly urgent rather than alarming. Keep skin texture, hands, safety glasses, lip motion, and eye movement photorealistic. Maintain continuity throughout with no cuts, no additional people, no logos, no captions, no lower thirds, no visible brand names, and no on-screen text." \
  resolution=768p \
  duration=12 \
  inputs.referenceImages.0=https://assets.runware.ai/assets/inputs/40514195-8f31-4c96-90c2-745681242642.jpg \
  inputs.referenceVideos.0=https://assets.runware.ai/assets/inputs/2979c59c-60b2-4eb5-b38b-ef5e2f115ed3.mp4 \
  inputs.referenceAudios.0=https://assets.runware.ai/assets/inputs/4723fc05-9966-41c2-b7e8-40ef4cc59920.mp3

{
  "taskType": "videoInference",
  "taskUUID": "50c2c534-6240-4f75-a203-70dcbddc2b5b",
  "model": "minimax:h3@0",
  "positivePrompt": "Create a polished 12-second municipal public-health talking-head video in a cinematic documentary style. The presenter is the wastewater scientist shown in the reference image: preserve her facial identity, short natural curls, warm brown skin, clear safety glasses, navy utility coverall, teal gloves, and approachable professional presence. Place her at a clean stainless-steel testing bench in the same modern wastewater laboratory, with softly defocused sample bottles and turquoise-lit utility pipes behind her. Use the reference image as the primary guide for subject identity, wardrobe, laboratory design, cyan-and-amber palette, and lighting.\n\nUse the reference video as guidance for framing and performance: one uninterrupted eye-level medium shot, presenter centered slightly left with modest negative space, restrained documentary camera language, and a very slow subtle push-in. Match its natural posture, direct eye contact, realistic blinking, small open-hand emphasis gesture, and reassuring finishing nod. Avoid exaggerated gesturing or commercial-presenter energy.\n\nUse the reference audio as the exact spoken performance and synchronize the presenter’s mouth, facial articulation, pauses, breath, gesture timing, and final nod precisely to it. Preserve a credible adult female voice and clean speech intelligibility. Add only subtle, realistic laboratory room tone underneath—soft ventilation and distant water-system hum—with no music and no competing machinery noise.\n\nThe mood is practical, trustworthy, and quietly urgent rather than alarming. Keep skin texture, hands, safety glasses, lip motion, and eye movement photorealistic. Maintain continuity throughout with no cuts, no additional people, no logos, no captions, no lower thirds, no visible brand names, and no on-screen text.",
  "resolution": "768p",
  "duration": 12,
  "inputs": {
    "referenceImages": [
      "https://assets.runware.ai/assets/inputs/40514195-8f31-4c96-90c2-745681242642.jpg"
    ],
    "referenceVideos": [
      "https://assets.runware.ai/assets/inputs/2979c59c-60b2-4eb5-b38b-ef5e2f115ed3.mp4"
    ],
    "referenceAudios": [
      "https://assets.runware.ai/assets/inputs/4723fc05-9966-41c2-b7e8-40ef4cc59920.mp3"
    ]
  }
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'minimax:h3@0',
  positivePrompt: 'Create a polished 15-second cinematic title teaser for a prestige investigative documentary about seed patents and control of the global food supply. Begin exactly from the supplied macro seed evidence frame. Hold in tense stillness, then make a slow, precise push toward the seed as the light table flickers. The seed’s internal veins illuminate like an X-ray and extend outward as fine root systems; these roots transform into patent-diagram lines, fingerprint ridges, legal redaction bars, and geometric field boundaries seen from directly overhead. Use elegant match cuts and restrained optical transitions rather than flashy effects. Let the image progressively darken until the diagram lines contract into the letterforms of the supplied final title card, ending exactly on that frame with “OWNED EARTH” sharp and fully legible for the final two seconds. Art direction: forensic botanical archive, oxidized amber, acidic chlorophyll green, bone ivory, dense blacks, tactile paper and glass textures, anamorphic highlights, subtle 35mm grain, controlled camera movement, ominous but intellectually rigorous mood. Native synchronized sound design: low fluorescent hum, glass scrape, distant seed rattle, dry paper friction, a rising sub-bass pulse, then one muted soil impact as the title resolves. No narration, no people, no logos, no additional readable text.',
  duration: 15,
  seed: 248071936,
  settings: {
    aigcWatermark: false
  },
  inputs: {
    frameImages: [
      {
        image: 'https://assets.runware.ai/assets/inputs/514f9aef-94fe-4bcf-a178-45b32780d6a8.jpg',
        frame: 'first'
      },
      {
        image: 'https://assets.runware.ai/assets/inputs/9e457e0b-615f-4fb4-a7a0-b82eff98508c.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": "minimax:h3@0",
            "positivePrompt": "Create a polished 15-second cinematic title teaser for a prestige investigative documentary about seed patents and control of the global food supply. Begin exactly from the supplied macro seed evidence frame. Hold in tense stillness, then make a slow, precise push toward the seed as the light table flickers. The seed’s internal veins illuminate like an X-ray and extend outward as fine root systems; these roots transform into patent-diagram lines, fingerprint ridges, legal redaction bars, and geometric field boundaries seen from directly overhead. Use elegant match cuts and restrained optical transitions rather than flashy effects. Let the image progressively darken until the diagram lines contract into the letterforms of the supplied final title card, ending exactly on that frame with “OWNED EARTH” sharp and fully legible for the final two seconds. Art direction: forensic botanical archive, oxidized amber, acidic chlorophyll green, bone ivory, dense blacks, tactile paper and glass textures, anamorphic highlights, subtle 35mm grain, controlled camera movement, ominous but intellectually rigorous mood. Native synchronized sound design: low fluorescent hum, glass scrape, distant seed rattle, dry paper friction, a rising sub-bass pulse, then one muted soil impact as the title resolves. No narration, no people, no logos, no additional readable text.",
            "duration": 15,
            "seed": 248071936,
            "settings": {
                "aigcWatermark": False
            },
            "inputs": {
                "frameImages": [
                    {
                        "image": "https://assets.runware.ai/assets/inputs/514f9aef-94fe-4bcf-a178-45b32780d6a8.jpg",
                        "frame": "first"
                    },
                    {
                        "image": "https://assets.runware.ai/assets/inputs/9e457e0b-615f-4fb4-a7a0-b82eff98508c.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": "055ede1f-2f0d-44a3-9557-e77376f775be",
      "model": "minimax:h3@0",
      "positivePrompt": "Create a polished 15-second cinematic title teaser for a prestige investigative documentary about seed patents and control of the global food supply. Begin exactly from the supplied macro seed evidence frame. Hold in tense stillness, then make a slow, precise push toward the seed as the light table flickers. The seed’s internal veins illuminate like an X-ray and extend outward as fine root systems; these roots transform into patent-diagram lines, fingerprint ridges, legal redaction bars, and geometric field boundaries seen from directly overhead. Use elegant match cuts and restrained optical transitions rather than flashy effects. Let the image progressively darken until the diagram lines contract into the letterforms of the supplied final title card, ending exactly on that frame with “OWNED EARTH” sharp and fully legible for the final two seconds. Art direction: forensic botanical archive, oxidized amber, acidic chlorophyll green, bone ivory, dense blacks, tactile paper and glass textures, anamorphic highlights, subtle 35mm grain, controlled camera movement, ominous but intellectually rigorous mood. Native synchronized sound design: low fluorescent hum, glass scrape, distant seed rattle, dry paper friction, a rising sub-bass pulse, then one muted soil impact as the title resolves. No narration, no people, no logos, no additional readable text.",
      "duration": 15,
      "seed": 248071936,
      "settings": {
        "aigcWatermark": false
      },
      "inputs": {
        "frameImages": [
          {
            "image": "https://assets.runware.ai/assets/inputs/514f9aef-94fe-4bcf-a178-45b32780d6a8.jpg",
            "frame": "first"
          },
          {
            "image": "https://assets.runware.ai/assets/inputs/9e457e0b-615f-4fb4-a7a0-b82eff98508c.jpg",
            "frame": "last"
          }
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Create a polished 15-second cinematic title teaser for a prestige investigative documentary about seed patents and control of the global food supply. Begin exactly from the supplied macro seed evidence frame. Hold in tense stillness, then make a slow, precise push toward the seed as the light table flickers. The seed’s internal veins illuminate like an X-ray and extend outward as fine root systems; these roots transform into patent-diagram lines, fingerprint ridges, legal redaction bars, and geometric field boundaries seen from directly overhead. Use elegant match cuts and restrained optical transitions rather than flashy effects. Let the image progressively darken until the diagram lines contract into the letterforms of the supplied final title card, ending exactly on that frame with “OWNED EARTH” sharp and fully legible for the final two seconds. Art direction: forensic botanical archive, oxidized amber, acidic chlorophyll green, bone ivory, dense blacks, tactile paper and glass textures, anamorphic highlights, subtle 35mm grain, controlled camera movement, ominous but intellectually rigorous mood. Native synchronized sound design: low fluorescent hum, glass scrape, distant seed rattle, dry paper friction, a rising sub-bass pulse, then one muted soil impact as the title resolves. No narration, no people, no logos, no additional readable text." \
  duration=15 \
  seed=248071936 \
  settings.aigcWatermark=false \
  inputs.frameImages.0.image=https://assets.runware.ai/assets/inputs/514f9aef-94fe-4bcf-a178-45b32780d6a8.jpg \
  inputs.frameImages.0.frame=first \
  inputs.frameImages.1.image=https://assets.runware.ai/assets/inputs/9e457e0b-615f-4fb4-a7a0-b82eff98508c.jpg \
  inputs.frameImages.1.frame=last

{
  "taskType": "videoInference",
  "taskUUID": "055ede1f-2f0d-44a3-9557-e77376f775be",
  "model": "minimax:h3@0",
  "positivePrompt": "Create a polished 15-second cinematic title teaser for a prestige investigative documentary about seed patents and control of the global food supply. Begin exactly from the supplied macro seed evidence frame. Hold in tense stillness, then make a slow, precise push toward the seed as the light table flickers. The seed’s internal veins illuminate like an X-ray and extend outward as fine root systems; these roots transform into patent-diagram lines, fingerprint ridges, legal redaction bars, and geometric field boundaries seen from directly overhead. Use elegant match cuts and restrained optical transitions rather than flashy effects. Let the image progressively darken until the diagram lines contract into the letterforms of the supplied final title card, ending exactly on that frame with “OWNED EARTH” sharp and fully legible for the final two seconds. Art direction: forensic botanical archive, oxidized amber, acidic chlorophyll green, bone ivory, dense blacks, tactile paper and glass textures, anamorphic highlights, subtle 35mm grain, controlled camera movement, ominous but intellectually rigorous mood. Native synchronized sound design: low fluorescent hum, glass scrape, distant seed rattle, dry paper friction, a rising sub-bass pulse, then one muted soil impact as the title resolves. No narration, no people, no logos, no additional readable text.",
  "duration": 15,
  "seed": 248071936,
  "settings": {
    "aigcWatermark": false
  },
  "inputs": {
    "frameImages": [
      {
        "image": "https://assets.runware.ai/assets/inputs/514f9aef-94fe-4bcf-a178-45b32780d6a8.jpg",
        "frame": "first"
      },
      {
        "image": "https://assets.runware.ai/assets/inputs/9e457e0b-615f-4fb4-a7a0-b82eff98508c.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: 'minimax:h3@0',
  positivePrompt: 'Replace only the green-screen studio and floor with a photorealistic 1880s wooden shipwreck on the cold North Atlantic seabed. Preserve the diver exactly: same copper helmet, canvas suit, proportions, walking performance, timing, pose, and framing. The diver crosses a silty seabed beside broken timber ribs, scattered ceramic cargo, rope, and sparse kelp. Soft blue-green daylight filters down through deep water; suspended particles drift naturally and silt lifts subtly beneath each boot. Add physically accurate underwater light falloff, contact shadows, reflections on the copper helmet, and environmental color spill so the subject belongs convincingly in the scene. Keep the camera locked in a wide documentary composition with restrained, historically credible production design. Synchronized sound: muffled underwater ambience, slow bubbles from the helmet, subtle suit creaks, and heavy footfalls disturbing gravel. No modern debris, fantasy creatures, text, logos, borders, or visible studio elements.',
  width: 2560,
  height: 1440,
  duration: 10,
  seed: 1849032716,
  settings: {
    aigcWatermark: false
  },
  inputs: {
    referenceVideos: [
      'https://assets.runware.ai/assets/inputs/84a14a42-2ef6-4e31-9726-b8cc2cb433db.mp4'
    ]
  }
})

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": "minimax:h3@0",
            "positivePrompt": "Replace only the green-screen studio and floor with a photorealistic 1880s wooden shipwreck on the cold North Atlantic seabed. Preserve the diver exactly: same copper helmet, canvas suit, proportions, walking performance, timing, pose, and framing. The diver crosses a silty seabed beside broken timber ribs, scattered ceramic cargo, rope, and sparse kelp. Soft blue-green daylight filters down through deep water; suspended particles drift naturally and silt lifts subtly beneath each boot. Add physically accurate underwater light falloff, contact shadows, reflections on the copper helmet, and environmental color spill so the subject belongs convincingly in the scene. Keep the camera locked in a wide documentary composition with restrained, historically credible production design. Synchronized sound: muffled underwater ambience, slow bubbles from the helmet, subtle suit creaks, and heavy footfalls disturbing gravel. No modern debris, fantasy creatures, text, logos, borders, or visible studio elements.",
            "width": 2560,
            "height": 1440,
            "duration": 10,
            "seed": 1849032716,
            "settings": {
                "aigcWatermark": False
            },
            "inputs": {
                "referenceVideos": [
                    "https://assets.runware.ai/assets/inputs/84a14a42-2ef6-4e31-9726-b8cc2cb433db.mp4"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "6a134275-978d-49ce-935f-2491835c97f0",
      "model": "minimax:h3@0",
      "positivePrompt": "Replace only the green-screen studio and floor with a photorealistic 1880s wooden shipwreck on the cold North Atlantic seabed. Preserve the diver exactly: same copper helmet, canvas suit, proportions, walking performance, timing, pose, and framing. The diver crosses a silty seabed beside broken timber ribs, scattered ceramic cargo, rope, and sparse kelp. Soft blue-green daylight filters down through deep water; suspended particles drift naturally and silt lifts subtly beneath each boot. Add physically accurate underwater light falloff, contact shadows, reflections on the copper helmet, and environmental color spill so the subject belongs convincingly in the scene. Keep the camera locked in a wide documentary composition with restrained, historically credible production design. Synchronized sound: muffled underwater ambience, slow bubbles from the helmet, subtle suit creaks, and heavy footfalls disturbing gravel. No modern debris, fantasy creatures, text, logos, borders, or visible studio elements.",
      "width": 2560,
      "height": 1440,
      "duration": 10,
      "seed": 1849032716,
      "settings": {
        "aigcWatermark": false
      },
      "inputs": {
        "referenceVideos": [
          "https://assets.runware.ai/assets/inputs/84a14a42-2ef6-4e31-9726-b8cc2cb433db.mp4"
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Replace only the green-screen studio and floor with a photorealistic 1880s wooden shipwreck on the cold North Atlantic seabed. Preserve the diver exactly: same copper helmet, canvas suit, proportions, walking performance, timing, pose, and framing. The diver crosses a silty seabed beside broken timber ribs, scattered ceramic cargo, rope, and sparse kelp. Soft blue-green daylight filters down through deep water; suspended particles drift naturally and silt lifts subtly beneath each boot. Add physically accurate underwater light falloff, contact shadows, reflections on the copper helmet, and environmental color spill so the subject belongs convincingly in the scene. Keep the camera locked in a wide documentary composition with restrained, historically credible production design. Synchronized sound: muffled underwater ambience, slow bubbles from the helmet, subtle suit creaks, and heavy footfalls disturbing gravel. No modern debris, fantasy creatures, text, logos, borders, or visible studio elements." \
  width=2560 \
  height=1440 \
  duration=10 \
  seed=1849032716 \
  settings.aigcWatermark=false \
  inputs.referenceVideos.0=https://assets.runware.ai/assets/inputs/84a14a42-2ef6-4e31-9726-b8cc2cb433db.mp4

{
  "taskType": "videoInference",
  "taskUUID": "6a134275-978d-49ce-935f-2491835c97f0",
  "model": "minimax:h3@0",
  "positivePrompt": "Replace only the green-screen studio and floor with a photorealistic 1880s wooden shipwreck on the cold North Atlantic seabed. Preserve the diver exactly: same copper helmet, canvas suit, proportions, walking performance, timing, pose, and framing. The diver crosses a silty seabed beside broken timber ribs, scattered ceramic cargo, rope, and sparse kelp. Soft blue-green daylight filters down through deep water; suspended particles drift naturally and silt lifts subtly beneath each boot. Add physically accurate underwater light falloff, contact shadows, reflections on the copper helmet, and environmental color spill so the subject belongs convincingly in the scene. Keep the camera locked in a wide documentary composition with restrained, historically credible production design. Synchronized sound: muffled underwater ambience, slow bubbles from the helmet, subtle suit creaks, and heavy footfalls disturbing gravel. No modern debris, fantasy creatures, text, logos, borders, or visible studio elements.",
  "width": 2560,
  "height": 1440,
  "duration": 10,
  "seed": 1849032716,
  "settings": {
    "aigcWatermark": false
  },
  "inputs": {
    "referenceVideos": [
      "https://assets.runware.ai/assets/inputs/84a14a42-2ef6-4e31-9726-b8cc2cb433db.mp4"
    ]
  }
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'minimax:h3@0',
  positivePrompt: 'Create a seamless eight-second animated awards portrait from the three reference images. Preserve the original robotics team group shot, workshop, robot, camera angle, lighting and every existing person without changing their faces, clothing, body positions or relative scale. Add the student captain from reference images 2 and 3 into the open space at the front-left of the group, seated in her matte-black manual wheelchair and aligned naturally with the team. Match her facial identity, short black hair, round glasses and charcoal jacket precisely. Reproduce realistic wheelchair geometry, floor contact, perspective, cyan edge light, warm facial illumination, shadows and subtle reflections. She belongs in the original photograph rather than appearing pasted in; nearby teammates subtly lean toward her as a cohesive team. Animate only restrained portrait motion: natural blinking, breathing, tiny posture shifts, faint jacket movement, softly flickering workshop practicals and a slow, stable camera push-in. Keep all eight students and the robot visible throughout. Professional collegiate awards-film aesthetic, crisp documentary photography, cyan and amber palette, proud and optimistic mood, no text, no logos, no added people, no face morphing, no warped hands, no wheelchair distortion, no cuts.',
  width: 1920,
  height: 1440,
  duration: 8,
  seed: 18472639,
  settings: {
    aigcWatermark: false
  },
  inputs: {
    referenceImages: [
      'https://assets.runware.ai/assets/inputs/9125e8e8-2d21-4cdc-885f-42a692c07ceb.jpg',
      'https://assets.runware.ai/assets/inputs/2961405a-c61e-473f-8448-1afc076f1efa.jpg',
      'https://assets.runware.ai/assets/inputs/bce576d5-3cad-4f38-b489-1a02ada5e75d.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": "minimax:h3@0",
            "positivePrompt": "Create a seamless eight-second animated awards portrait from the three reference images. Preserve the original robotics team group shot, workshop, robot, camera angle, lighting and every existing person without changing their faces, clothing, body positions or relative scale. Add the student captain from reference images 2 and 3 into the open space at the front-left of the group, seated in her matte-black manual wheelchair and aligned naturally with the team. Match her facial identity, short black hair, round glasses and charcoal jacket precisely. Reproduce realistic wheelchair geometry, floor contact, perspective, cyan edge light, warm facial illumination, shadows and subtle reflections. She belongs in the original photograph rather than appearing pasted in; nearby teammates subtly lean toward her as a cohesive team. Animate only restrained portrait motion: natural blinking, breathing, tiny posture shifts, faint jacket movement, softly flickering workshop practicals and a slow, stable camera push-in. Keep all eight students and the robot visible throughout. Professional collegiate awards-film aesthetic, crisp documentary photography, cyan and amber palette, proud and optimistic mood, no text, no logos, no added people, no face morphing, no warped hands, no wheelchair distortion, no cuts.",
            "width": 1920,
            "height": 1440,
            "duration": 8,
            "seed": 18472639,
            "settings": {
                "aigcWatermark": False
            },
            "inputs": {
                "referenceImages": [
                    "https://assets.runware.ai/assets/inputs/9125e8e8-2d21-4cdc-885f-42a692c07ceb.jpg",
                    "https://assets.runware.ai/assets/inputs/2961405a-c61e-473f-8448-1afc076f1efa.jpg",
                    "https://assets.runware.ai/assets/inputs/bce576d5-3cad-4f38-b489-1a02ada5e75d.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": "d9064278-51df-412a-8876-55a6cc0767bd",
      "model": "minimax:h3@0",
      "positivePrompt": "Create a seamless eight-second animated awards portrait from the three reference images. Preserve the original robotics team group shot, workshop, robot, camera angle, lighting and every existing person without changing their faces, clothing, body positions or relative scale. Add the student captain from reference images 2 and 3 into the open space at the front-left of the group, seated in her matte-black manual wheelchair and aligned naturally with the team. Match her facial identity, short black hair, round glasses and charcoal jacket precisely. Reproduce realistic wheelchair geometry, floor contact, perspective, cyan edge light, warm facial illumination, shadows and subtle reflections. She belongs in the original photograph rather than appearing pasted in; nearby teammates subtly lean toward her as a cohesive team. Animate only restrained portrait motion: natural blinking, breathing, tiny posture shifts, faint jacket movement, softly flickering workshop practicals and a slow, stable camera push-in. Keep all eight students and the robot visible throughout. Professional collegiate awards-film aesthetic, crisp documentary photography, cyan and amber palette, proud and optimistic mood, no text, no logos, no added people, no face morphing, no warped hands, no wheelchair distortion, no cuts.",
      "width": 1920,
      "height": 1440,
      "duration": 8,
      "seed": 18472639,
      "settings": {
        "aigcWatermark": false
      },
      "inputs": {
        "referenceImages": [
          "https://assets.runware.ai/assets/inputs/9125e8e8-2d21-4cdc-885f-42a692c07ceb.jpg",
          "https://assets.runware.ai/assets/inputs/2961405a-c61e-473f-8448-1afc076f1efa.jpg",
          "https://assets.runware.ai/assets/inputs/bce576d5-3cad-4f38-b489-1a02ada5e75d.jpg"
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Create a seamless eight-second animated awards portrait from the three reference images. Preserve the original robotics team group shot, workshop, robot, camera angle, lighting and every existing person without changing their faces, clothing, body positions or relative scale. Add the student captain from reference images 2 and 3 into the open space at the front-left of the group, seated in her matte-black manual wheelchair and aligned naturally with the team. Match her facial identity, short black hair, round glasses and charcoal jacket precisely. Reproduce realistic wheelchair geometry, floor contact, perspective, cyan edge light, warm facial illumination, shadows and subtle reflections. She belongs in the original photograph rather than appearing pasted in; nearby teammates subtly lean toward her as a cohesive team. Animate only restrained portrait motion: natural blinking, breathing, tiny posture shifts, faint jacket movement, softly flickering workshop practicals and a slow, stable camera push-in. Keep all eight students and the robot visible throughout. Professional collegiate awards-film aesthetic, crisp documentary photography, cyan and amber palette, proud and optimistic mood, no text, no logos, no added people, no face morphing, no warped hands, no wheelchair distortion, no cuts." \
  width=1920 \
  height=1440 \
  duration=8 \
  seed=18472639 \
  settings.aigcWatermark=false \
  inputs.referenceImages.0=https://assets.runware.ai/assets/inputs/9125e8e8-2d21-4cdc-885f-42a692c07ceb.jpg \
  inputs.referenceImages.1=https://assets.runware.ai/assets/inputs/2961405a-c61e-473f-8448-1afc076f1efa.jpg \
  inputs.referenceImages.2=https://assets.runware.ai/assets/inputs/bce576d5-3cad-4f38-b489-1a02ada5e75d.jpg

{
  "taskType": "videoInference",
  "taskUUID": "d9064278-51df-412a-8876-55a6cc0767bd",
  "model": "minimax:h3@0",
  "positivePrompt": "Create a seamless eight-second animated awards portrait from the three reference images. Preserve the original robotics team group shot, workshop, robot, camera angle, lighting and every existing person without changing their faces, clothing, body positions or relative scale. Add the student captain from reference images 2 and 3 into the open space at the front-left of the group, seated in her matte-black manual wheelchair and aligned naturally with the team. Match her facial identity, short black hair, round glasses and charcoal jacket precisely. Reproduce realistic wheelchair geometry, floor contact, perspective, cyan edge light, warm facial illumination, shadows and subtle reflections. She belongs in the original photograph rather than appearing pasted in; nearby teammates subtly lean toward her as a cohesive team. Animate only restrained portrait motion: natural blinking, breathing, tiny posture shifts, faint jacket movement, softly flickering workshop practicals and a slow, stable camera push-in. Keep all eight students and the robot visible throughout. Professional collegiate awards-film aesthetic, crisp documentary photography, cyan and amber palette, proud and optimistic mood, no text, no logos, no added people, no face morphing, no warped hands, no wheelchair distortion, no cuts.",
  "width": 1920,
  "height": 1440,
  "duration": 8,
  "seed": 18472639,
  "settings": {
    "aigcWatermark": false
  },
  "inputs": {
    "referenceImages": [
      "https://assets.runware.ai/assets/inputs/9125e8e8-2d21-4cdc-885f-42a692c07ceb.jpg",
      "https://assets.runware.ai/assets/inputs/2961405a-c61e-473f-8448-1afc076f1efa.jpg",
      "https://assets.runware.ai/assets/inputs/bce576d5-3cad-4f38-b489-1a02ada5e75d.jpg"
    ]
  }
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'minimax:h3@0',
  positivePrompt: 'Restore this archival film excerpt for a museum exhibition while preserving the original performance, timing, facial identity, sign-language hand movements, camera position, 4:3 composition, and period authenticity. Remove dust, scratches, flicker, gate weave, torn-frame artifacts, exposure pulsing, and chemical stains. Stabilize the frame, recover natural detail without plastic skin or modern digital sharpening, and retain a subtle, consistent 16mm grain structure. Apply restrained historically plausible colorization: warm cream workshop walls, muted rust and ochre 1970s clothing, natural skin tones, gray-brown clay, dark metal pottery wheel, and soft daylight from high windows. Do not invent objects, alter gestures, crop the frame, or modernize the scene. Preserve and gently clarify the original soundtrack without changing synchronization.',
  duration: 10,
  seed: 1976,
  settings: {
    aigcWatermark: false
  },
  inputs: {
    referenceVideos: [
      'https://assets.runware.ai/assets/inputs/6df70e4c-6515-4999-886e-6162d02fc132.mp4'
    ]
  }
})

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": "minimax:h3@0",
            "positivePrompt": "Restore this archival film excerpt for a museum exhibition while preserving the original performance, timing, facial identity, sign-language hand movements, camera position, 4:3 composition, and period authenticity. Remove dust, scratches, flicker, gate weave, torn-frame artifacts, exposure pulsing, and chemical stains. Stabilize the frame, recover natural detail without plastic skin or modern digital sharpening, and retain a subtle, consistent 16mm grain structure. Apply restrained historically plausible colorization: warm cream workshop walls, muted rust and ochre 1970s clothing, natural skin tones, gray-brown clay, dark metal pottery wheel, and soft daylight from high windows. Do not invent objects, alter gestures, crop the frame, or modernize the scene. Preserve and gently clarify the original soundtrack without changing synchronization.",
            "duration": 10,
            "seed": 1976,
            "settings": {
                "aigcWatermark": False
            },
            "inputs": {
                "referenceVideos": [
                    "https://assets.runware.ai/assets/inputs/6df70e4c-6515-4999-886e-6162d02fc132.mp4"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "videoInference",
      "taskUUID": "eb7227f7-5971-40a0-a85d-836238e9975d",
      "model": "minimax:h3@0",
      "positivePrompt": "Restore this archival film excerpt for a museum exhibition while preserving the original performance, timing, facial identity, sign-language hand movements, camera position, 4:3 composition, and period authenticity. Remove dust, scratches, flicker, gate weave, torn-frame artifacts, exposure pulsing, and chemical stains. Stabilize the frame, recover natural detail without plastic skin or modern digital sharpening, and retain a subtle, consistent 16mm grain structure. Apply restrained historically plausible colorization: warm cream workshop walls, muted rust and ochre 1970s clothing, natural skin tones, gray-brown clay, dark metal pottery wheel, and soft daylight from high windows. Do not invent objects, alter gestures, crop the frame, or modernize the scene. Preserve and gently clarify the original soundtrack without changing synchronization.",
      "duration": 10,
      "seed": 1976,
      "settings": {
        "aigcWatermark": false
      },
      "inputs": {
        "referenceVideos": [
          "https://assets.runware.ai/assets/inputs/6df70e4c-6515-4999-886e-6162d02fc132.mp4"
        ]
      }
    }
  ]'

runware run minimax:h3@0 \
  positivePrompt="Restore this archival film excerpt for a museum exhibition while preserving the original performance, timing, facial identity, sign-language hand movements, camera position, 4:3 composition, and period authenticity. Remove dust, scratches, flicker, gate weave, torn-frame artifacts, exposure pulsing, and chemical stains. Stabilize the frame, recover natural detail without plastic skin or modern digital sharpening, and retain a subtle, consistent 16mm grain structure. Apply restrained historically plausible colorization: warm cream workshop walls, muted rust and ochre 1970s clothing, natural skin tones, gray-brown clay, dark metal pottery wheel, and soft daylight from high windows. Do not invent objects, alter gestures, crop the frame, or modernize the scene. Preserve and gently clarify the original soundtrack without changing synchronization." \
  duration=10 \
  seed=1976 \
  settings.aigcWatermark=false \
  inputs.referenceVideos.0=https://assets.runware.ai/assets/inputs/6df70e4c-6515-4999-886e-6162d02fc132.mp4

{
  "taskType": "videoInference",
  "taskUUID": "eb7227f7-5971-40a0-a85d-836238e9975d",
  "model": "minimax:h3@0",
  "positivePrompt": "Restore this archival film excerpt for a museum exhibition while preserving the original performance, timing, facial identity, sign-language hand movements, camera position, 4:3 composition, and period authenticity. Remove dust, scratches, flicker, gate weave, torn-frame artifacts, exposure pulsing, and chemical stains. Stabilize the frame, recover natural detail without plastic skin or modern digital sharpening, and retain a subtle, consistent 16mm grain structure. Apply restrained historically plausible colorization: warm cream workshop walls, muted rust and ochre 1970s clothing, natural skin tones, gray-brown clay, dark metal pottery wheel, and soft daylight from high windows. Do not invent objects, alter gestures, crop the frame, or modernize the scene. Preserve and gently clarify the original soundtrack without changing synchronization.",
  "duration": 10,
  "seed": 1976,
  "settings": {
    "aigcWatermark": false
  },
  "inputs": {
    "referenceVideos": [
      "https://assets.runware.ai/assets/inputs/6df70e4c-6515-4999-886e-6162d02fc132.mp4"
    ]
  }
}