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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM31928

Interview Preparation Assistant

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM31928

Volume:

8 |

4 |

Apr 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM31928

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SB

SUWANI BOTHRA

VM

VASU MITTAL

YG

YASHIKA GUPTA

AS

ARYAN SHARMA

DRV

DR. RICHA VATS

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Abstract

In an increasingly competitive job market, effective interview preparation is essential for job seekers to showcase their skills and secure their desired positions. This project introduces an AI-powered interview preparation platform that harnesses the power of LLM, Langchain, OpenAI, and other advanced technologies to provide a personalized and effective preparation experience. The platform’s Vue.js front end presents a user-friendly interface where candidates can enter their name and job title. Leveraging the Serp API, the platform retrieves relevant information from the candidate’s LinkedIn profile, including work experience, technology stack, and other pertinent details. Utilizing a combination of LLM, Langchain, and OpenAI technologies, the platform generates personalized interview questions tailored to the candidate’s unique skillset and experience. These questions cover both technical and HR-related aspects, ensuring comprehensive preparation for various interview scenarios. The platform’s Python and Flask-based backend handles user input processing, LinkedIn data retrieval, and interview question generation. It facilitates seamless communication between the front-end and back-end components, providing a smooth user experience. By providing personalized questions, efficient data processing, and a user-friendly interface, this AI-powered interview preparation platform surpasses the limitations of traditional preparation methods. It empowers job seekers to prepare effectively for interviews, enhancing their chances of success in a competitive job market.

KEYWORDS

Large language model LangChain Application Programming Interface.

Cite This Article

SUWANI BOTHRA, VASU MITTAL, YASHIKA GUPTA, ARYAN SHARMA, DR. RICHA VATS, "Interview Preparation Assistant," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 4, Apr 2024. https://doi.org/10.55041/IJSREM31928

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Publication Date

12/31/45414

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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