https://github.com/sayantanmpaul/cv-compass-client
Accelerate talent match, find right talents, amplify quality.
https://github.com/sayantanmpaul/cv-compass-client
ai-resume-analyzer ai-resume-optimizer cv-optimization huggingface llama-index llama3 resume-parser resume-screening
Last synced: 2 months ago
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Accelerate talent match, find right talents, amplify quality.
- Host: GitHub
- URL: https://github.com/sayantanmpaul/cv-compass-client
- Owner: SayantanmPaul
- License: apache-2.0
- Created: 2025-01-16T21:04:16.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-04-04T10:52:24.000Z (3 months ago)
- Last Synced: 2025-04-15T18:20:05.116Z (2 months ago)
- Topics: ai-resume-analyzer, ai-resume-optimizer, cv-optimization, huggingface, llama-index, llama3, resume-parser, resume-screening
- Language: TypeScript
- Homepage: https://cvcompass.sayantanpaul.com/
- Size: 6.2 MB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CVCompass: LLM-Powered Resume Review for Hiring Teams & Job Seekers
#### This project aims to address the limitations of traditional ATS (Applicant Tracking System) scanners while providing a more intelligent, user-centric solution for job seekers and hiring teams.
### Checkout the demo : [YouTube](https://youtu.be/D5ZdgJj3WhA?si=igRR-B_5ue_4jcpn)
### How CVCompass will help?
It compares the candidate's resume with the specific job requirements and background fit needs and provides a more accurate analysis of the candidate's strengths and relevancy with the job requirement.
## Some Quick Features (Beta Launch):
**Different options for LLM:** Our application relies on different large language models (currently: Llama3, DeepSeek r1) to review and score the candidate's strengths.
**No Login Flow:** Breaking the extra barrier between the user and the application. Get started instantly; no sign-up hassle.
**Local Processing:** As there's no user-centric database, most of your data is stored and managed from your cached memory.
**Interactive Charts:** Dynamic, interactive charts to visualize the candidate's strengths, weaknesses, and key insights to make quick decisions.
**Personalized Feedback:** Job description-specific feedback and recommendations to improve the candidate's performance.
## Design System of the product:
### Backend Server Files : [Click here](https://github.com/SayantanmPaul/cv-compass-server)
## Run your local development enviornment
Run the following command to build and start the application using Docker Compose:
```bash
docker-compose up --build
```
This will:
- Build the Docker image using the Dockerfile
- Install dependencies
- Start the application inside a container
#### Access the Application
Once the container is up and running, the application will be accessible at:
```bash
http://localhost:3000
```
#### Stopping the Application
To stop the running containers, use:
```bash
docker-compose down
```
## Support the Project
If you find this project helpful, please consider giving it a star on GitHub! ✨