best-intern

100x faster internship search

TODOs:

• get a list of a ton of internships
• parse data for each link into txt
• go through each txt and build a data schema for each internship / job
• save them to the database
• build the same general schema for resumes
• use llm/other stuff to combine the most fitting jobs and resumes

1. make internship data schema
2. make resume data schema
3. make resume->internship match algorithm

Progress Tracking

• make resume -> data extraction + upload to db endpoints
• make job description -> data extraction + upload to db endpoints
• make resume data -> job matching algorithm
• config database and test uploading and fetching for resumes and jobs
• write api combining all logic
  • make sure to have protective logic, only 2 pages of all resumes are read, etc.
• connect to frontend
• loc frontend behind login and account logic
  • upload resume
  • runs the api
  • shows the 'best' or 'worst' internship match
  • has the rest of them blurred
  • if user tries to interact, put a login popup
  • once user logs in, save their user data, resume, internships
  • every time they login, it will show the saved data
  • only interaction user will have is the ability to upload a new resume for more jobs
  • can do a lil bit of post processing where llm gives user some advice / give a complement

🛠️ Environment Setup

Make sure Python, ngrok, and uv are installed.

# 1 Navigate to the repository. Install [uv](https://github.com/astral-sh/uv):
pip install uv

# 2. Create a virtual environment at .venv
uv venv

# 3. Activate environment.
source .venv/bin/activate # macOS and Linux
.venv\Scripts\activate # Windows

# 4. Install dependencies
uv pip install -r requirements.txt

# Extra: Save added dependencies
uv pip freeze > requirements.txt