AI Interview Mocker
Your AI-Powered Interview Coach
Created on 9th February 2025
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AI Interview Mocker
Your AI-Powered Interview Coach
The problem AI Interview Mocker solves
Realistic Simulations:
Users can engage in mock interviews that simulate real-world scenarios, helping them become familiar with the interview process and reducing anxiety.
Personalized Feedback:
The AI analyzes responses and provides tailored feedback on areas for improvement, such as communication style, clarity, and confidence. This helps users refine their answers and presentation.
Convenient and Flexible:
Users can practice anytime, anywhere, without the need for a human interviewer. This flexibility allows for more frequent practice sessions, leading to better preparation.
Diverse Question Bank:
The platform offers a wide range of questions across various industries and roles, ensuring users are well-prepared for different types of interviews.
Skill Development:
By practicing with the AI, users can enhance their critical thinking, problem-solving, and communication skills, which are essential for success in interviews and beyond.
Confidence Building:
Regular practice helps users build confidence in their abilities, making them more likely to perform well in actual interviews.
Safe Learning Environment:
Users can make mistakes and learn from them in a safe, judgment-free environment, allowing for growth and improvement without the pressure of a real interview.
Challenges we ran into
- Integrating the Gemini API for Course Recommendations
Issue: Initially, we faced issues with authenticating and fetching data from the Gemini API. The API would return errors related to permissions, and we were unable to retrieve course recommendations based on job descriptions.
Solution: After debugging the issue, we realized that the authentication tokens were not being passed correctly in the headers. We re-checked the API documentation, updated the authorization flow, and tested the endpoint with proper headers. This allowed us to successfully integrate the API and get the course suggestions. - Fetching Experience Details from LinkedIn API
Issue: When attempting to fetch experience details using the LinkedIn API, we encountered rate limits and restrictions on accessing user data, which caused delays and errors during testing.
Solution: We mitigated this by implementing rate-limiting handling logic in the application, ensuring that requests were spaced out and retry logic was added in case of failure. Additionally, we focused on acquiring necessary permissions from users beforehand to ensure smooth data access. - Building the Interactive Cartoon-Style Avatar
Issue: The Mixamo avatar wasn’t responding smoothly to the speech input. It often got stuck or didn’t sync with the animations properly, especially when trying to implement real-time interview questions.
Solution: We researched different methods for integrating speech animations with Mixamo avatars. We ended up using a combination of JSON animation data and adjusting the timeline to sync the voice with facial expressions. We also added lip-syncing features using third-party libraries like Papagayo to enhance the realism.
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