Coder19/interview_system

AI Interview Bot - Backend

A FastAPI-based backend for an AI-powered interview bot with real-time WebSocket communication, speech-to-text, and AI-powered question generation.

Features

• —Real-time interview simulation using WebSockets
• —Speech-to-text conversion
• —AI-powered question generation
• —Resume parsing and analysis
• —Interview feedback and evaluation

Deployment on Hugging Face Spaces

Prerequisites

1. 1.A Hugging Face account
2. 2.Docker installed locally (for testing)
3. 3.Git installed

Deployment Steps

1. 1.Prepare your repository
2. 2.Make sure all the required files are committed to your repository
3. 3.Ensure you have the following files in your root directory:
4. 4.Dockerfile
5. 5.app.py
6. 6.requirements.txt
7. 7..env (for local development, do not commit sensitive data)

1. 1.Create a new Space on Hugging Face
2. 2.Go to Hugging Face Spaces
3. 3.Click "Create new Space"
4. 4.Select "Docker" as the SDK
5. 5.Choose a name and visibility (public/private)
6. 6.Click "Create Space"

1. 1.Configure the Space
2. 2.In your Space settings, go to "Files and versions"
3. 3.Upload all your project files or connect your GitHub repository
4. 4.Set the following environment variables in the "Variables and secrets" section:
5. 5.OPENAI_API_KEY (required for AI functionality)
6. 6.Any other environment variables your app needs

1. 1.Configure Hardware
2. 2.In the "Settings" tab, under "Hardware", select a GPU if your application requires it
3. 3.For this application, a CPU Basic instance should be sufficient for basic functionality

1. 1.Deploy
2. 2.Hugging Face will automatically build and deploy your application
3. 3.Monitor the build logs in the "Logs" tab
4. 4.Once deployed, your application will be available at:

     https://huggingface.co/spaces/<your-username>/<your-space-name>

Local Development

1. 1.Clone the repository
2. 2.Create a virtual environment and activate it
3. 3.Install dependencies:

pip install -r requirements.txt