Custom Job Interview Simulation

Inspiration

We were inspired by our own interview experiences from trying to find summer internships.

What it does

The app allows you to add custom parameters for an interview (e.g. company, job title, job description, interview type, personal resumé). The AI Chatbot will then conduct a structured interview based on those parameters. Once the interview is finished, a summary and analysis of the interview is released for the user.

How we built it

We built the app in python. The backend uses LangChain for the LLM models, and the frontend is done through tkinter.

Challenges we ran into

The main challenge was getting the ChatBot to develop a structure to its interview, while retaining adaptability to user answers and the freedom to ask specific, personalized questions.

Accomplishments that we're proud of

We're proud of creating a 3-layer ChatBot. The first layer involves creating a structured outline for an interview determined by the parameters. The second layer involves the ChatBot itself, conversing with the user, while proceeding through the interview structure. The final layer is a third-party observer that considers the interview holistically and provides a final analysis.

What we learned

We learned how to use LLM models in practice, in particular the function of agents.

What's next for Custom Job Interview Simulation

Next, we plan on working on adding much greater detail to the interview analysis aspect of the project, making the frontend more user friendly, and adding more features such as a job search tool based on resumé and interview performance.

Built With

• langchain
• openai
• python
• tkinter