# Full-Stack AI Recruitment Engine

A production-ready candidate ranking platform built with Next.js, FastAPI, and Groq LLMs.

## Features
- **Multi-Agent Evaluation**: Sequential and parallel agent pipeline (Signal Extraction, Founder Eval, Tech Eval, HR Agent, etc.).
- **Groq Key Rotation**: Automatic round-robin cycling of multiple API keys to prevent rate limits.
- **CSV Data Ingestion**: Parse resumes and candidate data directly from CSV files.
- **Glassmorphic UI**: Modern, high-performance dashboard with animations and progress tracking.

---

## Backend Setup (FastAPI)

1. **Navigate to backend**:
   ```bash
   cd backend
   ```

2. **Create and Activate Virtual Environment**:
   ```bash
   python -m venv venv
   # Windows:
   venv\Scripts\activate
   ```

3. **Install Dependencies**:
   ```bash
   pip install -r requirements.txt
   ```

4. **Environment Variables**:
   Create a `.env` file in the `backend/` folder based on `.env.example`:
   ```env
   GROQ_API_KEYS=key1,key2,key3
   GROQ_MODEL=llama3-70b-8192
   PORT=8000
   ```

5. **Run Backend**:
   ```bash
   uvicorn app.main:app --reload
   ```

---

## Frontend Setup (Next.js)

1. **Navigate to frontend**:
   ```bash
   cd frontend
   ```

2. **Install Dependencies**:
   ```bash
   npm install
   ```

3. **Environment Variables**:
   Create a `.env.local` file in the `frontend/` folder:
   ```env
   NEXT_PUBLIC_API_URL=http://localhost:8000
   ```

4. **Run Frontend**:
   ```bash
   npm run dev
   ```

---

## Usage Guide
1. **Paste Job Description**: Enter the target role details in the textarea.
2. **Upload CSV**: Upload a CSV containing candidate data (columns: `name`, `email`, `skills`, `experience`, `projects`, `education`, `resume_text`).
3. **Evaluate**: Click "Run Evaluation" and watch the AI agents process each candidate.
4. **Deep Dive**: Click on any candidate row to see the full multi-agent breakdown and final synthesis.