🤖 AI Video Interviewer

An immersive, AI-powered mock interview platform that simulates a real-time video call experience. This application helps users practice for job interviews by providing dynamic, job-specific questions, transcribing spoken answers, and delivering the AI’s responses with audible speech.

(Replace this with a demo GIF showing your app in action)

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✨ Features

• 🧠 Dynamic AI-powered interview questions using Hugging Face (ahmedatk/ai_interviewer)
• 🎙️ Speech Recognition with SpeechRecognition
• 🔊 Text-to-Speech via gTTS and pydub (requires FFmpeg)
• 💬 Interactive chat UI with separate bubbles for user and interviewer
• 📁 Upload resume and job description for personalized sessions
• ⚙️ Built with Python/Flask backend and HTML/CSS/JavaScript frontend

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🛠️ Tech Stack

Layer	Technology Used
Backend	Python, Flask, Flask-Cors
Frontend	HTML5, CSS3, JavaScript
AI Integration	Hugging Face Spaces, gradio_client
Speech-to-Text	SpeechRecognition
Text-to-Speech	gTTS, pydub, FFmpeg

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🔧 Setup Instructions

Prerequisites

• Python 3.8+
• FFmpeg (audio processing)

FFmpeg Installation

• Windows: Download here → extract → add bin/ to system PATH
• macOS: brew install ffmpeg
• Linux: sudo apt-get install ffmpeg

To verify:

ffmpeg -version

Installation Steps

# Clone the repository
git clone https://github.com/your-username/ai-video-interviewer.git
cd ai-video-interviewer

# Create a virtual environment
python -m venv venv

# Activate it
source venv/bin/activate        # macOS/Linux
.\venv\Scripts\activate         # Windows

# Install Python dependencies
pip install Flask Flask-Cors gradio_client gTTS SpeechRecognition pydub

# Run the Flask app
python app.py

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📋 How to Use

1. Visit http://127.0.0.1:5001 in your browser.
2. Grant permission for webcam and microphone.
3. Upload your resume (PDF) and paste job description.
4. Click Start Interview.
5. The AI will speak a question aloud.
6. Click Record Answer, speak your response, then Stop Recording.
7. Your answer will be transcribed and sent back to the AI.
8. The AI replies and continues the dialogue.

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📁 Project Structure

ai-video-interviewer/
├── app.py                   # Flask backend server
├── templates/
│   └── index.html           # Web interface
├── static/
│   ├── style.css            # CSS styling
│   ├── script.js            # Client-side JavaScript
│   ├── assets/
│   │   └── ai_visual.png    # Visual avatar for AI
│   └── audio/               # Folder for generated speech
├── README.md                # Project documentation
└── requirements.txt         # Python dependencies

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❗ Troubleshooting

• FFmpeg Audio Error:
  If you see Error processing audio. Is FFmpeg correctly installed?, ensure FFmpeg is in your system’s PATH. Verify by running ffmpeg -version.

• API Model Unreachable:
  If Hugging Face returns a connection error, check your internet connection or firewall settings. Retry later if the model is temporarily offline.

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🚀 Future Plans

• Voice tone and clarity analysis for user responses
• Multiple AI personalities and accents
• Save and replay previous interviews
• Generate interview performance reports
• Resume parsing and automatic job-specific questions

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📄 License

This project is licensed under the MIT License.
See LICENSE.md for full terms and conditions.

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🙌 Acknowledgments

• Hugging Face model: ahmedatk/ai_interviewer
• Libraries: Flask, gTTS, SpeechRecognition, pydub, gradio_client
• Audio: FFmpeg for TTS conversion
• Contributors and the open-source community for making this possible.

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🎨 Bonus Branding Tip

Consider adding a branded logo and tagline, such as:

Qedence – “Interview smarter. Speak bolder.”

You can include this at the top of the interface or as the favicon to solidify your project's identity.

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