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---
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 |
## 📦 Installation
```bash
# 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
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
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