AI Interview Trainer

Welcome to the AI Interview Trainer project! This server-side application analyzes interview responses to help candidates improve their interview skills by providing feedback on audio, video, and text responses.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• API Endpoints
• Technologies Used
• Contributing
• License

Introduction

The AI Interview Trainer takes in a resume and job description, generates interview questions, and analyzes candidate responses. This project aims to enhance the interview preparation process by providing detailed feedback on audio, video, and text inputs.

Features

• Resume and Job Description Parsing: Generate relevant interview questions.
• Audio Analysis: Evaluate voice quality using AssemblyAI.
• Video Analysis: Analyze body language and expressions using OpenCV and custom CNN models.
• Text Analysis: Detect filler words and overall response quality.
• Relevance Check: Compare candidate responses to AI-generated expected answers.

Installation

1. Clone the repository:

   git clone https://github.com/STSonyThomas/API_FP_v1.git
   cd API_FP_v1

2. Set up Virtual Environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install the required packages:

   pip install -r requirements.txt

Usage

1. Run the server:

   flask run

2. Use Tools like Postman or curl to interact with the API:

API Endpoints

• GET /questions: Retrieve generated interview questions.
• POST /analyze/audio: Submit audio for analysis.
• POST /analyze/video: Submit video for analysis.
• POST /analyze/text: Submit text responses for analysis.

Technologies Used

• Flask: For the server-side logic.
• AssemblyAI: For audio analysis.
• OpenCV & CNN: For video analysis.
• Natural Language Processing: For text analysis.
• FFmpeg: For audio extraction.

Contributing

We welcome contributions! Please fork the repository and create a pull request with your changes. Ensure your code follows the project's coding standards and is well-documented.

License

This project is licensed under the MIT License. See the LICENSE file for more details.