Unlocking Spotify's Audio DNA with n8n and AI
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Automate the retrieval and in-depth analysis of your Spotify track data using n8n. This workflow leverages AI to extract rich audio features and structure them for deeper insights.
About This Workflow
This n8n workflow orchestrates a powerful data pipeline to extract detailed information about your Spotify music library. It begins by fetching your playlists and their tracks, then efficiently gathers essential track metadata. Crucially, it interacts with the Spotify API to retrieve advanced audio features for your songs, such as danceability, energy, and valence. Finally, it employs an AI model (Anthropic Chat) to process and structure this complex audio data into a clean, usable format, ready for further analysis or integration into other applications. This allows for a deeper understanding of your musical preferences and the characteristics of your favorite songs.
Key Features
- Automated Spotify Data Retrieval: Seamlessly pull your playlists and track information.
- In-depth Audio Feature Analysis: Access granular audio characteristics like danceability, energy, and more from the Spotify API.
- AI-Powered Data Structuring: Utilize an AI model to organize and refine complex audio feature data.
- Batch Processing: Efficiently handles large volumes of data for scalable automation.
- Customizable Metadata Extraction: Precisely define the information you want to capture about each track.
How To Use
- Connect your Spotify Account: Authenticate n8n with your Spotify account using the
Spotify OAuth2 APIcredential. - Retrieve User Playlists: Use the
Get Playlistnode to fetch all your Spotify playlists. - Filter Your Playlists: Configure the
Filter my playlistnode to select playlists owned by you (e.g., bydisplay_name). - Extract Playlist Information: Use the
Playlists informationsnode to structure key playlist details. - Get Library Tracks: Employ the
Get Tracksnode to retrieve all tracks within your saved library. - Extract Track Details: Use the
Retrieve relevant infonode to gather essential track metadata like name, artist, album, and Spotify URI. - Prepare for Audio Features: The
Batch preparationnode groups track Spotify IDs into manageable batches for the API request. - Fetch Audio Features: The
Get Track detailsnode makes API calls to Spotify to retrieve audio features for each batch of track IDs. - Split Audio Features: The
Split Outnode separates theaudio_featuresarray for individual processing. - Structure AI Input: The
Batch preparation1node prepares the structured playlist and track data for the AI model, handling potential batching of track URIs. - AI Analysis: Configure the
Anthropic Chat Modelnode with a prompt that instructs the AI to parse the provided structured data, referencing the JSON schema for expected output. Ensure theStructured Output Parseris set up with the correct schema to guide the AI's response format. - Merge Data: Use the
Mergenode to combine the extracted playlist and track information with the AI-processed audio features.
Apps Used
Workflow JSON
{
"id": "22425f08-eb2d-473b-a224-4020751ea373",
"name": "Unlocking Spotify's Audio DNA with n8n and AI",
"nodes": 10,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 22425f08-eb2d...
About the Author
SaaS_Connector
Integration Guru
Connecting CRM, Notion, and Slack to automate your life.
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