Feels: Translating Your Spotify Soundtrack into Real Outdoor Places with Local AI and SerpApi

Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Submission 🌿

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

Like many developers, I spend hours locked in a sensory bubble at my desk with noise-canceling headphones on, cycling through music while deep in code. Over time, I noticed something undeniable about my daily Spotify queue: my listening history serves as an unfiltered mirror of my mental state and fatigue. When hunting subtle bugs or sprinting against deadlines, my queue naturally shifts to driving, high-tempo electronica. When unwinding after a long refactoring session or mapping system architecture, it settles into minimalist acoustic or atmospheric ambient soundscapes:

Session Window (Last 10 Tracks): - M83: Midnight City -> 105 BPM, expansive synth wave, high kinetic momentum - Justice: Genesis -> 117 BPM, distorted analog bass, aggressive forward drive - The xx: Intro -> 100 BPM, minimalist reverberation, steady contemplative pace - The Prodigy: Breathe -> 130 BPM, breakbeat rhythm, peak adrenaline burst - Woodkid: Run Boy Run -> 132 BPM, marching orchestral drums, surging forward drive Enter fullscreen mode Exit fullscreen mode Streaming algorithms take this behavioral data and use it to feed more screen addiction, building autoplay queues engineered to keep you in your chair. The moment you push your commits, you close your editor only to open social feeds or video streams instead of getting fresh air.

I built Feels to turn that dynamic around: using your soundtrack as a natural bridge to step away from your desk and reconnect with the outdoors.

Feels is a web application that takes your recent Spotify listening session and interprets its acoustic cadence, energy density, and emotional texture using an open-weight model running locally on your hardware. Rather than trapping you in a conversational chatbot loop, it acts as an environmental scout. It maps your sonic state to geographic search intents, then uses SerpApi's Google Maps engine to find three verified real-world outdoor destinations - such as elevated ridgeline trails, shaded forest loops, or tranquil lakeside parks. Each spot includes verified user ratings, review counts, photos, a grounded explanation of why it fits your current soundtrack, and one-click Google Maps directions.

To ensure the screen stays the shortest part of the experience, the application enforces a strict cap of 15 refreshes per day. You check your curated spots, pick a trail, shut the laptop, and head outside.

Here is a walkthrough of Feels in action, showing the Spotify authorization, the live four-stage processing indicator, and the resulting outdoor trail cards:

Turn your music into a reason to get outside.

An open-weight, privacy-first web application that translates your recent Spotify listening history into curated outdoor destinations using on-device AI and real-time map discovery.

Live Demo • Architecture • Configuration • Deployment

Most streaming apps use your listening history to feed more screen time, generating algorithmic queues engineered to keep you in your chair.

Instead of another chatbot or infinite playlist, Feels treats your recent soundtrack as an unfiltered mirror of your mental headspace. It reads your 10 most recent tracks once per day, runs an open-weight model ( Qwen 2.5 Coder 7B ) locally on your machine to analyze tempo, energy density, and emotional cadence, and grounds that mood in real-world outdoor spaces using SerpApi's Google Maps engine.

You get three curated physical destinations - elevated ridge trails, shaded forest loops, or…