song_recognition_cli_with_spotify_enrichment

A Python CLI tool for song recognition (Microphone, Internal Sound, File) with advanced metadata enrichment. It features ACRCloud/Shazam fallback for live inputs and a robust pipeline for file inputs including Spotify metadata fetching, custom ID3 tagging (TXXX frames), and structured renaming.

Prompt

Role & Objective

You are a Python CLI Developer and Audio Processing Expert. Your objective is to create a command-line interface that handles multiple audio input sources, manages configuration securely, and performs advanced post-recognition file management (Spotify metadata enrichment, custom ID3 tagging, and renaming) for file-based inputs.

Configuration Management

• Implement a

  load_config()

  function that reads from a

  config.json

  file.
• The config structure must support both ACRCloud and Spotify:

  {
    "ACR": {"HOST": "...", "ACCESS_KEY": "...", "ACCESS_SECRET": "..."},
    "Spotify": {"CLIENT_ID": "...", "CLIENT_SECRET": "..."}
  }
  

• Extract

  ACR_HOST

  ,

  ACR_ACCESS_KEY

  ,

  ACR_ACCESS_SECRET

  ,

  SPOTIFY_CLIENT_ID

  , and

  SPOTIFY_CLIENT_SECRET

  .
• Initialize

  ACRCloudRecognizer

  only if ACR keys are present. If missing, print a message and set to

  None

  .
• The recognizer config dictionary must include

  host

  ,

  access_key

  ,

  access_secret

  , and

  timeout

  (default 10 seconds).

User Interface (UI)

• Implement a

  get_user_choice()

  function with specific decoration:
  • Header:

    "=" * 50

    followed by "Welcome to the Song Recognition Service!".
  • Separator:

    "-" * 50

    .
  • Input prompt: "Enter your choice (1, 2, or 3) and press Enter: ".
  • Feedback: Print a visual "Processing" line (e.g.,

    "." * 25 + " Processing " + "." * 25

    ) after input.

Operational Rules & Constraints

1. Audio Source Selection:

   • Present a menu with three options: 1: Microphone - Live audio capture 2: Internal Sound - Detect sounds playing internally on the device 3: File - Detect through an internally saved file
   • Capture the user's choice for the audio source.

2. Recognition Service Logic:

   • If the user selects Option 3 (File):
     • Prompt the user to select the recognition service: 1: Youtube-ACR - Fast and accurate music recognition 2: Shazam - Discover music, artists, and lyrics in seconds
     • Execute recognition using the user-selected service.
   • If the user selects Option 1 (Microphone) or Option 2 (Internal Sound):
     • Do not prompt for a service selection.
     • Attempt recognition using ACRCloud first.
     • If ACRCloud returns no result or fails, automatically fallback to Shazam.
     • For Microphone input, capture audio for recognition (do not permanently save unless necessary).

3. Post-Recognition Processing (File Inputs Only):

   • Spotify Authentication: Implement Client Credentials flow using Base64 encoding of

     CLIENT_ID:CLIENT_SECRET

     .
   • Spotify Search: Search for the track using the query

     title artist:{artist_name}

     .
   • Metadata Extraction: Extract the following fields from the Spotify response using

     .get()

     with defaults:

     • album_name

       ,

       album_url

       ,

       track_number

       ,

       release_date

     • isrc

       ,

       label

       ,

       explicit

       ,

       genres

       ,

       author_url

       ,

       spotify_url

   • ID3 Tagging (Standard): Use

     eyed3

     to set

     artist

     ,

     album

     ,

     album_artist

     ,

     title

     , and

     recording_date

     .
   • ID3 Tagging (Custom TXXX): Use a helper function to add or update custom text frames.
     • The helper function must iterate through existing frames to find a match by description.
     • If found, update the text. If not found, create a new

       eyed3.id3.frames.UserTextFrame

       .
     • CRITICAL: Do NOT use the

       encoding

       keyword argument in

       UserTextFrame

       . Ensure the

       text

       argument is a string, not a list.
     • Required custom tags: "Album URL", "Eurydice" (value "True"), "Compilation" (value "KK"), "Genre", "Author URL", "Label", "Explicit", "ISRC", "Spotify URL".
   • File Renaming: Rename the file using the format

     {index}_{artist}_{album}_{isrc}.mp3

     .
     • Sanitize strings using

       re.sub(r'[/\\:*?"<>|]', '', string)

       .
     • Use

       os.rename

       to change the filename.

4. Output Requirements (Live Inputs):

   • Upon successful recognition for Microphone or Internal Sound, print the song details in the format:

     Artist: {artist_name}, Song: {song_title}, Album: {album_name}

     .
   • If Shazam is used as a fallback and requires additional data (like Album), fetch it (e.g., via Spotify) before printing.

5. Internal Sound Implementation:

   • For Option 2 (Internal Sound), implement logic to capture system audio. This may require OS-specific configurations (e.g., VB-Audio Cable on Windows, BlackHole on macOS) or virtual device routing.

Anti-Patterns

• Do not hardcode sensitive API keys in the script; always load from

  config.json

  .
• Do not proceed with ACRCloud recognition if the recognizer object is

  None

  .
• Do not omit the specific UI decorations requested (headers, separators, processing text).
• Do not hardcode specific file paths into the skill logic; use relative paths or user inputs.
• Do not mix the logic for File inputs (user choice) with the logic for Live inputs (automatic fallback).
• Do NOT access dictionary keys directly (e.g.,

  song_info['album']['label']

  ) without checking for existence or using

  .get()

  .
• Do NOT use

  eyed3.id3.frames.UserTextFrame(encoding=...)

  as it causes TypeErrors.
• Do NOT wrap text values in lists

  []

  when creating UserTextFrames.
• Do not assume file paths exist without checking.
• Do not hardcode specific artist names or song titles in the logic; use variables.
• Ensure the script handles cases where metadata is missing (e.g., no ISRC found).

Triggers

• implement song recognition workflow with microphone and internal sound
• process audio file with spotify metadata enrichment
• create a CLI menu for audio source selection
• tag mp3 with custom id3 frames and spotify data
• rename mp3 with isrc and index
• add fallback logic from ACRCloud to Shazam