Claudio Ortolina
204 lines
6.1 KiB
Markdown
204 lines
6.1 KiB
Markdown
# Music Library
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<!--toc:start-->
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- [Music Library](#music-library)
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- [Features](#features)
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- [Screenshots](#screenshots)
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- [Stats dashboard](#stats-dashboard)
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- [Collection](#collection)
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- [Searching for a record to add](#searching-for-a-record-to-add)
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- [Record details](#record-details)
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- [Record releases](#record-releases)
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- [Record chat](#record-chat)
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- [Artist details](#artist-details)
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- [Wishlist record details](#wishlist-record-details)
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- [Record sets](#record-sets)
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- [Scrobble rules](#scrobble-rules)
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- [New scrobble rule](#new-scrobble-rule)
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- [Universal search](#universal-search)
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- [Setup](#setup)
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- [Environment configuration](#environment-configuration)
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- [Running the application](#running-the-application)
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- [Auditing Scrobble Data Quality](#auditing-scrobble-data-quality)
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- [Deployment](#deployment)
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- [CI](#ci)
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- [Architecture](#architecture)
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- [Favicons](#favicons)
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<!--toc:end-->
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## Features
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- Add records from MusicBrainz, with optional override of specific pieces of data
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- Manage a collection and a wishlist of records, with ways to quickly search
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and filter based on records' metadata
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- Browse record releases and select a collected release
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- AI-powered chat for records and artists, with web search
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- Artist details with biography, discography, and similar artists
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- Wishlist with links to online stores for purchasing
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- Curate record sets (e.g. "best live albums")
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- Universal search across collection, wishlist, artists, and record sets
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- Integration with Last.fm:
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- display latest scrobbles, and where possible
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connect them with records in the collection or wishlist
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- scrobble a record
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- store a local copy of the complete scrobble history, and setup rules to fix its data as needed
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- audit scrobble data quality and identify tracks with missing MusicBrainz IDs
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- Similarity search via OpenAI embeddings
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- Barcode scanning for quick imports
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- Stats dashboard with collection overview, top artists, top albums, and records on this day
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- All data stored in SQLite databases for portability and ease of backup/restore
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## Screenshots
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### Stats dashboard
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### Collection
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### Searching for a record to add
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### Record details
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### Record releases
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### Record chat
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### Artist details
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### Wishlist record details
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### Record sets
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### Scrobble rules
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### New scrobble rule
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### Universal search
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## Setup
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The project is managed and configured via [mise-en-place](https://mise.jdx.dev):
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- `mise install` will pull the correct Erlang, Elixir and Node.js versions
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- `mise run dev:setup` will setup dependencies and database structure
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> [!IMPORTANT]
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> The project uses [Fluxon UI](https://fluxonui.com/), so it requires a valid
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> set of credentials. See the `env` section in `mise.toml` for the required
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> environment variables.
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It's recommended to use the git hooks included in the project. Install with:
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`mise generate git-pre-commit --write --task=dev:precommit`
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## Environment configuration
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Required environment variables for development are listed in `mise.toml`.
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You can create a `mise.local.toml` with the required variables (sample values
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are included at the top of `mise.toml`).
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For production, please see `compose.yaml` for a list of required variables.
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## Running the application
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Start the Phoenix endpoint with `mise run console` (along with an attached IEx session).
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## Auditing Scrobble Data Quality
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The application includes a Mix task to audit scrobbled tracks and identify data quality issues such as missing MusicBrainz IDs for artists and albums.
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### Running the Audit
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```bash
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# Audit all tracks
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mix scrobble.audit
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# Audit with detailed output including sample tracks
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mix scrobble.audit --verbose
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# Audit only artist issues
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mix scrobble.audit --type artist
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# Audit only album issues
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mix scrobble.audit --type album
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# Output as JSON for processing
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mix scrobble.audit --format json
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```
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### Understanding the Audit Report
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The audit report shows:
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- Total number of scrobbled tracks
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- Artists with missing MusicBrainz IDs (grouped by artist name)
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- Albums with missing MusicBrainz IDs (grouped by album title and artist)
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- Track counts for each issue
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### Fixing Data Quality Issues
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After identifying issues, you can:
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1. **Create Scrobble Rules**: Navigate to the Scrobble Rules page in the web interface and add rules to map artist or album names to their correct MusicBrainz IDs.
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2. **Apply Rules**: Use the "Apply Rules" button in the Scrobble Rules page to update existing tracks, or run in IEx:
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```elixir
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MusicLibrary.ScrobbleRules.apply_all_rules()
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```
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3. **Re-audit**: Run the audit again to verify the fixes worked.
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The application also provides helper functions in the `MusicLibrary.ScrobbleActivity` context:
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- `count_tracks_missing_artist_musicbrainz_id/0`
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- `count_tracks_missing_album_musicbrainz_id/0`
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- `get_artists_missing_musicbrainz_id/1`
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- `get_albums_missing_musicbrainz_id/1`
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## Deployment
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The application is deployed via Coolify, using a Docker Compose strategy.
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## CI
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See the `.github` folder.
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## Architecture
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See the `docs` folder.
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## Favicons
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This favicon was generated using the following graphics from Twitter Twemoji:
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- Graphics Title: 1f4bd.svg
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- Graphics Author: Copyright 2020 Twitter, Inc and other contributors (<https://github.com/twitter/twemoji>)
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- Graphics Source: <https://github.com/twitter/twemoji/blob/master/assets/svg/1f4bd.svg>
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- Graphics License: CC-BY 4.0 (<https://creativecommons.org/licenses/by/4.0/>)
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