[feature] Add command for track predictions

[AntonVanAssche]

Description:

This feature would introduce a new command: predict which would accept the playlist_id as argument. The goal is to predict and recommend songs for a given playlist based on its audio characteristics and the user’s playlist.

Command Syntax:

• Base command: jamjar predict <playlist_id>
• Options:
  • amount: jamjar predict <playlist_id> --amount 5

Functionality:

1. Analyze the audio features of tracks within the specified playlist using Spotify’s /audio-features/ endpoint.

{
  "acousticness": 0.00242,
  "analysis_url": "https://api.spotify.com/v1/audio-analysis/2takcwOaAZWiXQijPHIx7B",
  "danceability": 0.585,
  "duration_ms": 237040,
  "energy": 0.842,
  "id": "2takcwOaAZWiXQijPHIx7B",
  "instrumentalness": 0.00686,
  "key": 9,
  "liveness": 0.0866,
  "loudness": -5.883,
  "mode": 0,
  "speechiness": 0.0556,
  "tempo": 118.211,
  "time_signature": 4,
  "track_href": "https://api.spotify.com/v1/tracks/2takcwOaAZWiXQijPHIx7B",
  "type": "audio_features",
  "uri": "spotify:track:2takcwOaAZWiXQijPHIx7B",
  "valence": 0.428
}

2. Generate a set of recommended tracks based on similarities in audio characteristics (e.g., danceability, energy, valence) or patterns in the user’s playlist history.
3. Output the results in JSON format, suitable for further processing or visualization.

Example Output:

{
  "predictions": [
    {
      "track_name": "New Track 1",
      "track_url": "https://spotify.com",
      "artist_name": "Artist A",
      "likelihood": 0.92,
      "audio_features": {
        "danceability": 0.85,
        "energy": 0.88,
        "valence": 0.7,
        "tempo": 120
      }
    },
    {
      "track_name": "New Track 2",
      "track_url": "https://spotify.com",
      "artist_name": "Artist B",
      "likelihood": 0.85,
      "audio_features": {
        "danceability": 0.65,
        "energy": 0.75,
        "valence": 0.8,
        "tempo": 105
      }
    }
  ]
}

Require Changes:

1. Integration with Spotify’s /audio-features/ endpoint.
2. Database: Update the tracks table to store the required audio features. This may require a migration script.
3. Algorithm for recommendations.
4. Command logic.