Mirelo SFX 1.5

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'mirelo:1@1',
  positivePrompt: 'Self-contained avalanche rescue training sound-effects scene, exactly 6 seconds, no speech and no music. Open with close, heavy boot crunches stopping in dry alpine snow beneath a steady exposed-mountain wind. At 1.2 seconds, a rescuer pulls a probe from a nylon backpack with a short zipper rasp and fabric rustle. From 2.0 to 3.3 seconds, the segmented aluminum probe snaps open in three crisp, clearly separated metallic clicks. At 4.0 seconds, the probe drives into packed snow with a firm granular plunge and compacted-snow squeak. End with one nearby avalanche transceiver chirp at 5.2 seconds while the wind continues. Realistic field-recording fidelity, cold open-air acoustics, tight instructional clarity, moderate intensity, each action distinctly audible.',
  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": "mirelo:1@1",
            "positivePrompt": "Self-contained avalanche rescue training sound-effects scene, exactly 6 seconds, no speech and no music. Open with close, heavy boot crunches stopping in dry alpine snow beneath a steady exposed-mountain wind. At 1.2 seconds, a rescuer pulls a probe from a nylon backpack with a short zipper rasp and fabric rustle. From 2.0 to 3.3 seconds, the segmented aluminum probe snaps open in three crisp, clearly separated metallic clicks. At 4.0 seconds, the probe drives into packed snow with a firm granular plunge and compacted-snow squeak. End with one nearby avalanche transceiver chirp at 5.2 seconds while the wind continues. Realistic field-recording fidelity, cold open-air acoustics, tight instructional clarity, moderate intensity, each action distinctly audible.",
            "duration": 6
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "audioInference",
      "taskUUID": "03047bc8-001e-43a3-821e-a27810bb3099",
      "model": "mirelo:1@1",
      "positivePrompt": "Self-contained avalanche rescue training sound-effects scene, exactly 6 seconds, no speech and no music. Open with close, heavy boot crunches stopping in dry alpine snow beneath a steady exposed-mountain wind. At 1.2 seconds, a rescuer pulls a probe from a nylon backpack with a short zipper rasp and fabric rustle. From 2.0 to 3.3 seconds, the segmented aluminum probe snaps open in three crisp, clearly separated metallic clicks. At 4.0 seconds, the probe drives into packed snow with a firm granular plunge and compacted-snow squeak. End with one nearby avalanche transceiver chirp at 5.2 seconds while the wind continues. Realistic field-recording fidelity, cold open-air acoustics, tight instructional clarity, moderate intensity, each action distinctly audible.",
      "duration": 6
    }
  ]'

runware run mirelo:1@1 \
  positivePrompt="Self-contained avalanche rescue training sound-effects scene, exactly 6 seconds, no speech and no music. Open with close, heavy boot crunches stopping in dry alpine snow beneath a steady exposed-mountain wind. At 1.2 seconds, a rescuer pulls a probe from a nylon backpack with a short zipper rasp and fabric rustle. From 2.0 to 3.3 seconds, the segmented aluminum probe snaps open in three crisp, clearly separated metallic clicks. At 4.0 seconds, the probe drives into packed snow with a firm granular plunge and compacted-snow squeak. End with one nearby avalanche transceiver chirp at 5.2 seconds while the wind continues. Realistic field-recording fidelity, cold open-air acoustics, tight instructional clarity, moderate intensity, each action distinctly audible." \
  duration=6

{
  "taskType": "audioInference",
  "taskUUID": "03047bc8-001e-43a3-821e-a27810bb3099",
  "model": "mirelo:1@1",
  "positivePrompt": "Self-contained avalanche rescue training sound-effects scene, exactly 6 seconds, no speech and no music. Open with close, heavy boot crunches stopping in dry alpine snow beneath a steady exposed-mountain wind. At 1.2 seconds, a rescuer pulls a probe from a nylon backpack with a short zipper rasp and fabric rustle. From 2.0 to 3.3 seconds, the segmented aluminum probe snaps open in three crisp, clearly separated metallic clicks. At 4.0 seconds, the probe drives into packed snow with a firm granular plunge and compacted-snow squeak. End with one nearby avalanche transceiver chirp at 5.2 seconds while the wind continues. Realistic field-recording fidelity, cold open-air acoustics, tight instructional clarity, moderate intensity, each action distinctly audible.",
  "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: 'mirelo:1@1',
  positivePrompt: 'Create a realistic six-second close-miked apiary training soundscape with no speech and no music. 0.0–1.0s: two soft leather smoker-bellows compressions, each releasing a short airy puff. 1.0–2.2s: a wooden hive lid scrapes sideways, then lifts with a muted knock. 2.2–4.5s: the honeybee swarm rises from a gentle background hum to a clearly audible but controlled buzz as one sticky frame loosens with a brief propolis crack and wooden creak. 4.5–6.0s: the frame settles back into its slot with a light wood-on-wood tap while the bees subside. Outdoor rural ambience, faint leaves and distant breeze, intimate documentary detail, moderate intensity, natural stereo space, crisp transients, no threatening swarm, no human vocalization.',
  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": "mirelo:1@1",
            "positivePrompt": "Create a realistic six-second close-miked apiary training soundscape with no speech and no music. 0.0–1.0s: two soft leather smoker-bellows compressions, each releasing a short airy puff. 1.0–2.2s: a wooden hive lid scrapes sideways, then lifts with a muted knock. 2.2–4.5s: the honeybee swarm rises from a gentle background hum to a clearly audible but controlled buzz as one sticky frame loosens with a brief propolis crack and wooden creak. 4.5–6.0s: the frame settles back into its slot with a light wood-on-wood tap while the bees subside. Outdoor rural ambience, faint leaves and distant breeze, intimate documentary detail, moderate intensity, natural stereo space, crisp transients, no threatening swarm, no human vocalization.",
            "duration": 6
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "audioInference",
      "taskUUID": "c99a8d13-7862-40cd-b961-672a90648d70",
      "model": "mirelo:1@1",
      "positivePrompt": "Create a realistic six-second close-miked apiary training soundscape with no speech and no music. 0.0–1.0s: two soft leather smoker-bellows compressions, each releasing a short airy puff. 1.0–2.2s: a wooden hive lid scrapes sideways, then lifts with a muted knock. 2.2–4.5s: the honeybee swarm rises from a gentle background hum to a clearly audible but controlled buzz as one sticky frame loosens with a brief propolis crack and wooden creak. 4.5–6.0s: the frame settles back into its slot with a light wood-on-wood tap while the bees subside. Outdoor rural ambience, faint leaves and distant breeze, intimate documentary detail, moderate intensity, natural stereo space, crisp transients, no threatening swarm, no human vocalization.",
      "duration": 6
    }
  ]'

runware run mirelo:1@1 \
  positivePrompt="Create a realistic six-second close-miked apiary training soundscape with no speech and no music. 0.0–1.0s: two soft leather smoker-bellows compressions, each releasing a short airy puff. 1.0–2.2s: a wooden hive lid scrapes sideways, then lifts with a muted knock. 2.2–4.5s: the honeybee swarm rises from a gentle background hum to a clearly audible but controlled buzz as one sticky frame loosens with a brief propolis crack and wooden creak. 4.5–6.0s: the frame settles back into its slot with a light wood-on-wood tap while the bees subside. Outdoor rural ambience, faint leaves and distant breeze, intimate documentary detail, moderate intensity, natural stereo space, crisp transients, no threatening swarm, no human vocalization." \
  duration=6

{
  "taskType": "audioInference",
  "taskUUID": "c99a8d13-7862-40cd-b961-672a90648d70",
  "model": "mirelo:1@1",
  "positivePrompt": "Create a realistic six-second close-miked apiary training soundscape with no speech and no music. 0.0–1.0s: two soft leather smoker-bellows compressions, each releasing a short airy puff. 1.0–2.2s: a wooden hive lid scrapes sideways, then lifts with a muted knock. 2.2–4.5s: the honeybee swarm rises from a gentle background hum to a clearly audible but controlled buzz as one sticky frame loosens with a brief propolis crack and wooden creak. 4.5–6.0s: the frame settles back into its slot with a light wood-on-wood tap while the bees subside. Outdoor rural ambience, faint leaves and distant breeze, intimate documentary detail, moderate intensity, natural stereo space, crisp transients, no threatening swarm, no human vocalization.",
  "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: 'mirelo:1@1',
  inputs: {
    video: 'https://assets.runware.ai/assets/inputs/ce2fc605-4749-499d-ae43-3448a3f592fa.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": "mirelo:1@1",
            "inputs": {
                "video": "https://assets.runware.ai/assets/inputs/ce2fc605-4749-499d-ae43-3448a3f592fa.mp4"
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "audioInference",
      "taskUUID": "3a6ae4a7-28be-4d4c-8332-563ebee1931f",
      "model": "mirelo:1@1",
      "inputs": {
        "video": "https://assets.runware.ai/assets/inputs/ce2fc605-4749-499d-ae43-3448a3f592fa.mp4"
      }
    }
  ]'

runware run mirelo:1@1 \
  inputs.video=https://assets.runware.ai/assets/inputs/ce2fc605-4749-499d-ae43-3448a3f592fa.mp4

{
  "taskType": "audioInference",
  "taskUUID": "3a6ae4a7-28be-4d4c-8332-563ebee1931f",
  "model": "mirelo:1@1",
  "inputs": {
    "video": "https://assets.runware.ai/assets/inputs/ce2fc605-4749-499d-ae43-3448a3f592fa.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: 'mirelo:1@1',
  inputs: {
    video: 'https://assets.runware.ai/assets/inputs/8c40f870-72dc-4fd9-b129-730d575b06e3.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": "mirelo:1@1",
            "inputs": {
                "video": "https://assets.runware.ai/assets/inputs/8c40f870-72dc-4fd9-b129-730d575b06e3.mp4"
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "audioInference",
      "taskUUID": "8086016c-0620-4ecf-86df-31d920e87212",
      "model": "mirelo:1@1",
      "inputs": {
        "video": "https://assets.runware.ai/assets/inputs/8c40f870-72dc-4fd9-b129-730d575b06e3.mp4"
      }
    }
  ]'

runware run mirelo:1@1 \
  inputs.video=https://assets.runware.ai/assets/inputs/8c40f870-72dc-4fd9-b129-730d575b06e3.mp4

{
  "taskType": "audioInference",
  "taskUUID": "8086016c-0620-4ecf-86df-31d920e87212",
  "model": "mirelo:1@1",
  "inputs": {
    "video": "https://assets.runware.ai/assets/inputs/8c40f870-72dc-4fd9-b129-730d575b06e3.mp4"
  }
}