Project Info
Inspiration
Life is tough and sometimes you don't have time to watch full lectures. Texty Bear allows you to still learn that information in a fraction of a time.
What it does
By submitting a YouTube lecture URL, Texty Bear will automatically look for key points within the lecture and create notes just for you!
How we built it
We utilized the PyTube python package and AssemblyAI to parse YouTube files into notes for our backend. For our front end, we used Flask to incorporate Python scripts into our HTML.
Challenges we ran into
This our our first Hackathon so there are many challenges :). Here are some of our major ones: Git version control Trouble learning the Flask package and how it interacts with HTML Tight deadlines with little project experience(skill issue) It's very cold here... Had to pivot from our original idea as it wasn't feasible to do ##
Accomplishments we're proud of
Cute website aesthetics Learned new packages and libraries Fixed many bugs :) Gaining real-life experiences with working in a team and with tight deadlines ##
What we learned
Learned Flask AI is easier to use than I thought... I finally fixed my Python virtual environments :D ##
What's next
Allow users to upload both media files and YouTube URLs Use and train our own model to take better, more concise notes Continue improving UI/UX of our website Optimize Youtube data parser and API calls
Texty Bear - Flask Application
Welcome to Texty Bear Flask application!
Life is tough and sometimes you don't have time to watch full lectures. Texty Bear allows you to still learn that information in a fraction of a time.
By submitting a YouTube lecture URL, Texty Bear will automatically look for key points within the lecture and create notes just for you!
Installation
- Create Virtual Environment:
Run the following command to create a virtual environment:
cd path/to/your/project
Create a virtual environment named venv:
python -m venv venv
- Activate the Virtual Environment:
On Linux or macOS:
source venv/bin/activate
On Windows (Command Prompt):
venv\Scripts\activate
On Windows (PowerShell):
.\venv\Scripts\Activate.ps1
- Install Dependencies:
While the virtual environment is activated, install the required dependencies from the requirements.txt file:
pip install -r requirements.txt
Run the Flask Application:
python app.py
This will start your Flask application. Visit http://127.0.0.1:5000/ in your browser to access the app.
Analysis
View
Metric
- 21
- 16
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
- PythonIn code
- FlaskClaimed
3 of 4 appear in the indexed code. 1 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
16 KB
Source files
9
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
DenialCant/CruzHack2024
15 files · 295 KB · @ 44a8968
Structure
Interface
3 files · 20%Screens, components and styles rendered to the user.
Application logic
3 files · 20%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
- HTML34%
- CSS32%
- Python27%
- Markdown7%
Share of indexed source by file size. Binary and vendored files are excluded.
This project’s features have not been analysed yet.
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