Jammin' is a project created for SENG 401 by Group 11 - Software Architecture that uses ChatGPT to parse a user’s Spotify analytics and match them with people with similar music taste. Matches are made based on both user’s top artists, songs and genres, combining to generate a compatibility score between both parties.
The Hosted Version can be found at this link: https://jammin-app.vercel.app/
If you wanted to remove your spotify account or add a new user to Jammin' you can use the logout button to remove your Spotify account and logout your Jammin' profile. This allows you to sign in or sign up with a different account, making Jammin' usable on one device.
If you wish to sign-up and not use your own spotify accounts, we have made 2 for you to login to when making "Jammin'" accounts, please contact us if theres any issues (because spotify developer apps that don't have specific approval from spotify need to manually add users that are able to register with their app). If there are any issues, please reach out.
Note, the below are SPOTIFY ACCOUNTS that need to be used when Signing Up through Jammin Username: sam.photolibrary4@gmail.com Password: SENG401project
Username: hexdpizza@gmail.com Password: SENG401project
You can scroll through people's profile, seeing their compatibility score with you, description of why they received that match score and more Spotify data of your matched user. Data visible includes top songs, top artists and top genres for each user.
You can see your own Spotify data and personal Jammin' data on the Profile page. On the public profile tab, you can see your Spotify name, top songs and top artists, as well as additional prompts to add to your public profile. On the Jammin' profile tab, you see the data associated with your Jammin' profile. This includes name, email, password, along with personal profile data like age, gender, bio, school, occupation, and what you are looking for on Jammin'.
After matching with users, you can see who you matched with on the Matches page. If both of you matched with each other, you can see that persons profile name, match score and date you matched on. If you drop down that menu, you can see the Jammin' data associated with that user. This allows you to see the more personal data of the people you matched with, and get to know that person better.
- Frontend: Vercel, React + Vite
- Backend: Flask
- Database: MySQL (Local), PostgreSQL (Hosted), Supabase
- Testing: Mockito
To use Jammin' online, you simply visit Jammin' and create an account. In the login/signup process, you must link your Spotify account and authorize Spotify access for Jammin'. From there, you can simply browse Jammin', where you can create matches and update our account throughout the app!
Jammin' allows for expansion in various ways, some of which we already have planned out. Messaging was a big plan for our development cycle, where we wanted matched users to be able to message each other over Jammin' and actually talk about their music interests. We also wanted to add additional data to the account, such as prompts to display on the users profile to customize your account more. We were also looking into adding photos to your public profile, further personalizing the data users see when matching together.
Our source code can be found in this repository. Also it can be observed that we attempted to use proper git techniques such as making pull requests when merging branches and putting tags in our commit messages. One thing to be noted is towards the end, we were making many commits directly to main as we were evaluating and updating our hosted version which was automatically updated by making commits to main.
TEAM 11: Samiul Haque, Keeryn Johnson, Elias Poitras-Whitecalf, Petr Dubovsky, Ryan Graham, Evan Mann
Our frontend pages and many components were designed on Figma where we used tools such as 'Builder.io' which uses AI to convert these to visually established jsx files. Additionally, AI tools such as ChatGPT, DeepSeek, and Builder.io were used to brainstorm and find solutions to functionalities, bug-fixes, and best-practices implemented in parts of code. The use of AI still required us to make many modifications to returned code to serve our specific purposes or simply function as intended when the AI provided solution provided a starting point that did not work. This helped us simplify redundant tasks and organize our code better. Some challenges we encountered include: correcting incorrect/inapplicable code provided by AI, AI not having up-to-date/relevant solutions, inaccurate results/hallucinations. To overcome these challenges we would get high-level solutions that would allow us to apply our own knowledge and understanding towards obtaining a solution and using other -more up-to-date- resources like stackOverflow, various video tutorials