Project Info
This project did not submit a demo video on Devpost.
Inspiration
There were two main inspirations for this project. Many people suggest that AI tools like ChatGPT are very good at suggesting new music to listen to based on past experiences and genres. There was also another similar project that was ideated in Cal Hacks 9.0 which does music recommendation based on heartbeat rhythms using Zepp OS's watch sensors. This time we decided to do a similar song recommendation system but based on a Journal entry.
What it does
Recommend songs based on your mood as it is presented in your journal entries. Tech Stack Frontend: React, Tailwind, Auth0, SpotifyAPI Backend: Convex, FastAPI, Javascript, Python, OpenAI API, Genius API Database: CockroachDB, Milvus
Challenges we ran into
Getting together.ai to properly clean our lyric texts. Creating a Milvus database without an index. Getting the Spotify API to work properly together with authentication and Convex.
Accomplishments we're proud of
Finishing our app and having a working product that we ourselves would actually use.
What we learned
How to generate and store vector embeddings in a vector database; how to integrate different APIs, such as the Spotify API, into Convex.
What's next
Integrating a user's playlist for personalized recommendation. Ability to pick and choose generated choices. Integrating real-time recording feedback
This repository has no readme, or GitHub could not be reached.
Analysis
View
Metric
- 4
- 1
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- CSSIn code
- HTMLIn code
- JavaScriptIn code
- PythonIn code
- ReactIn code
- Tailwind CSSIn code
- TypeScriptIn code
- FastAPIClaimed
- OpenAIClaimed
7 of 9 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
50 KB
Source files
27
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
pankinkun/rythm-moodify
36 files · 396 KB · @ a83622b
Structure
Interface
6 files · 17%Screens, components and styles rendered to the user.
Application logic
16 files · 44%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- JavaScript54%
- Python23%
- TypeScript16%
- Markdown6%
- HTML1%
- CSS0%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
client/package.json
npm · 17- @auth0/auth0-react
- @xixixao/uploadstuff
- convex
- node-fetch
- react
- react-dom
- +11 more
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This project’s features have not been analysed yet.
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