Job Sniffer

Inspiration

Bogged down by hordes of updates to the statuses of many applications, we were inspired to create a web app that uses AI to sift through your emails for you to tell you which are about jobs and a summary of what's going on with them.

What it does

Using Bard we sift through a user's recent emails after they log in to their Google account and give permission, then this is passed to Firebase's Firestore database where its then passed into a Panda dataframe to be presented on the website as a sortable chart.

How we built it

We used Streamlit with Python, and used chunks of JS with HTML/CSS for the FrontEnd. On the bakck end we used Bard for processing emails with a custom made prompt and filtering system to pass appropriate data into the Firestore database.

Challenges we ran into

Figuring out Google Sign-In took a bit as we were all quite new to it. Customizing Bard to work within our parameters took some trial and error.

Accomplishments that we're proud of

For most of us it was our first time using AI in a project, first time using Python and by proxy, Streamlit, and our first time using Firestore.

What we learned

Many different technologies flow very well together as long as you pay attention to how they work and research well.

What's next for Job Sniffer

The ability to hold multiple users concurrently is possible and very in our reach, UI improvements and minor code cleaning.

Built With

• css3
• html5
• javascript
• python
• streamlit