mtg/essentia-bpm:b3045c35 – Run with an API on Replicate

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mtg /essentia-bpm:b3045c35

Playground API

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=mtg/essentia-bpm

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run mtg/essentia-bpm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mtg/essentia-bpm:b3045c359817fea53678791886d50aa3e3a995dc4796fe74db0de156d5074a43",
  {
    input: {
      url: "https://www.youtube.com/watch?v=5-XfBN3olvE",
      algo_type: "deepsquare-k16"
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run mtg/essentia-bpm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mtg/essentia-bpm:b3045c359817fea53678791886d50aa3e3a995dc4796fe74db0de156d5074a43",
    input={
        "url": "https://www.youtube.com/watch?v=5-XfBN3olvE",
        "algo_type": "deepsquare-k16"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run mtg/essentia-bpm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "b3045c359817fea53678791886d50aa3e3a995dc4796fe74db0de156d5074a43",
    "input": {
      "url": "https://www.youtube.com/watch?v=5-XfBN3olvE",
      "algo_type": "deepsquare-k16"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Rendering markdown...

{
  "completed_at": "2023-11-30T10:58:18.095332Z",
  "created_at": "2023-11-30T10:58:07.874800Z",
  "data_removed": false,
  "error": null,
  "id": "xmdbg2rbdv6u2vd2zlynkq73uu",
  "input": {
    "url": "https://www.youtube.com/watch?v=5-XfBN3olvE",
    "algo_type": "deepsquare-k16"
  },
  "logs": "[youtube] 5-XfBN3olvE: Downloading webpage\n[youtube] 5-XfBN3olvE: Downloading player 5753e790\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmpv7ejeaw3/audio.webm\n[download]   0.0% of ~4.95MiB at  6.94KiB/s ETA 12:10\n[download]   0.1% of ~4.95MiB at 20.79KiB/s ETA 04:03\n[download]   0.1% of ~4.95MiB at 48.42KiB/s ETA 01:44\n[download]   0.3% of ~4.95MiB at 103.49KiB/s ETA 00:48\n[download]   0.6% of ~4.95MiB at 201.98KiB/s ETA 00:24\n[download]   1.2% of ~4.95MiB at 388.21KiB/s ETA 00:12\n[download]   2.5% of ~4.95MiB at 738.33KiB/s ETA 00:06\n[download]   5.0% of ~4.95MiB at  1.37MiB/s ETA 00:03\n[download]  10.1% of ~4.95MiB at  2.59MiB/s ETA 00:01\n[download]  20.2% of ~4.95MiB at  4.92MiB/s ETA 00:00\n[download]  40.4% of ~4.95MiB at  9.35MiB/s ETA 00:00\n[download]  80.8% of ~4.95MiB at 17.58MiB/s ETA 00:00\n[download] 100.0% of ~4.95MiB at 21.41MiB/s ETA 00:00\n[download] 100.0% of ~4.95MiB at 21.36MiB/s ETA 00:00\n[download] 100% of 4.95MiB in 00:00\n[ffmpeg] Destination: /tmp/tmpv7ejeaw3/audio.wav\nDeleting original file /tmp/tmpv7ejeaw3/audio.webm (pass -k to keep)\nloading audio...\nrunning analysis algorithm...\nDEBUG size before resample 14819841\nDEBUG size after resample 3704961\nDEBUG [0. 0. 0. ... 0. 0. 0.]\n2023-11-30 10:58:17.387081: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\ndone!",
  "metrics": {
    "predict_time": 8.331015,
    "total_time": 10.220532
  },
  "output": "https://replicate.delivery/pbxt/jitCG30GoS6LPVBbIxsLJVmc4k25bDZgFSc7KPIA2fmk5weRA/out.md",
  "started_at": "2023-11-30T10:58:09.764317Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/xmdbg2rbdv6u2vd2zlynkq73uu",
    "cancel": "https://api.replicate.com/v1/predictions/xmdbg2rbdv6u2vd2zlynkq73uu/cancel"
  },
  "version": "b3045c359817fea53678791886d50aa3e3a995dc4796fe74db0de156d5074a43"
}

Generated in

8.3 seconds

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