Project Info
This project did not submit a demo video on Devpost.
Inspiration
As we are a group of students actively looking for summer internships, we felt that an application to assist in practicing for interviews would be highly impactful. In addition, we felt that there was an opportunity and gap regarding AI and interview prep.
What it does
The app is comprised of two main parts: Interview question generation and video/audio sentiment analysis. The user first requests interview questions based on the job title they are applying for. Then, they film or record themselves answering the questions and submit their answers to be analyzed. The user is given back the 5 highest emotions sensed, which the user can take note of.
How we built it
We built this in Python using Taipy, HumeAi, and OpenAI's ChatGPT API
Challenges we ran into
As this is our first hackathon coordinating our group and utilizing the new software presented many challenges!
Accomplishments we're proud of
Utilizing Taipy and including HumeAI and OpenAI's APIS were great accomplishments for us.
What's next
We have plans to add many features including live video analysis and live question generation.
Analysis
View
Metric
- 3
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
- PythonIn code
- HTMLClaimed
- OpenAIClaimed
2 of 4 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
4.8 KB
Source files
5
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
ferril-s/calPandasCALHACKS
8 files · 194 KB · @ 1fca36d
Structure
Interface
1 file · 13%Screens, components and styles rendered to the user.
Application logic
5 files · 63%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
- Python94%
- CSS4%
- Markdown1%
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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