Interview-Analyzer

Interview-Analyzer is a tiny application designed to help you analyze and improve your job interview performance. It leverages AI to transcribe and analyze your interview recordings, providing actionable feedback.

Features

• AI-Powered Analysis: Automatically evaluates your interview performance using GPT-4o via LangChain.
• Transcription: Seamlessly converts audio recordings into text using OpenAI Whisper.
• CV Management: Upload and manage CVs (PDF) with automatic text extraction for cross-referencing during analysis.
• Historical Analysis: Keeps a record of your past interviews and analyses for tracking progress.
• Re-analyze: Re-analyze interviews with different prompts or updated CVs.
• Secure Access: Username/password authentication with Redis-backed rate limiting.

Tech Stack

• Streamlit: Interactive web interface.
• Django ORM: Database models and data access layer.
• LangChain: LLM orchestration and analysis logic.
• PostgreSQL: Persistent storage of transcripts, analyses, and CVs.
• Redis: Cache and authentication rate limiting.
• Docker: Consistent environment and easy deployment.
• Poetry: Dependency management.
• Ruff: Linting and formatting.

Getting Started

Prerequisites

• Docker and Docker Compose installed on your machine.
• An OpenAI API Key.

Installation

1. Clone the repository:

   git clone <repository_url>
   cd interview-analyzer

2. Configure environment variables:

   cp .env.dist .env

   Open .env and fill in the required values:

   • OPENAI_API_KEY: Your OpenAI API key.
   • LOGIN_USER, LOGIN_PASSWORD: Credentials to log in to the app (defaults: admin / admin).

3. Build and install:

   make install

4. Start the application:

   make start

Run make help to see all available commands.

Usage

1. Open your browser and navigate to http://localhost:8501.
2. Log in using the credentials defined in .env.
3. Analyze New Interview: Go to the Interview Analyzer page, upload an audio file (MP3, WAV, M4A, MP4), optionally attach a CV, and click Analyze. The system will transcribe and analyze it with step-by-step progress.
4. View History: Use the sidebar to browse past interviews and review the AI's feedback.
5. Manage CVs: Go to the Curriculum Vitae page to upload, view, edit, or delete CVs.

Database Management

The project includes Adminer for easy database management.

• Access Adminer at http://localhost:8080.
• System: PostgreSQL.
• Server: db.
• Username/Password/Database: As defined in your .env file.