metadata

title: RAG Interview Agent
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: streamlit
app_file: app.py
pinned: true

RAG-Powered AI Interview Agent

An intelligent interview assistant that evaluates candidates using pure Retrieval-Augmented Generation (RAG) architecture.

🚀 Features

CV Screening: Automatic qualification check using semantic similarity
Smart Interviews: Context-aware questions generated from job requirements
Fair Evaluation: Answers scored against knowledge base
Detailed Reports: PDF transcripts with scores and feedback

🛠️ Tech Stack

Component	Technology Used
LLM	Meta Llama-3-8B
Vector Store	FAISS
Embeddings	Sentence-Transformers
UI Framework	Streamlit
CV Parsing	PyPDF2, python-docx

interview-agent/ ├── app.py # Main application ├── utils/ │ ├── cv_processor.py # CV parsing and evaluation │ ├── rag_agent.py # Core RAG implementation │ ├── evaluator.py # Scoring logic │ └── report_generator.py# PDF report creation ├── data/ # Job requirements and interviews └── requirements.txt # Python dependencies

📦 Installation

# Clone the repository
git clone https://huggingface.co/spaces/Jekyll2000/interview_agent
cd your-space-name

# Install dependencies
pip install -r requirements.txt

# Set Hugging Face token
export HUGGINGFACEHUB_API_TOKEN='your-api-token'

# Launch the app
streamlit run app.py