AIcruiter - AI-Powered Recruitment Platform

An intelligent multi-agent recruitment system that automates candidate discovery, evaluation, and outreach using AI.

Features

• Hybrid Candidate Search - Combines LinkedIn API with MongoDB for efficient candidate discovery
• AI Evaluation - GPT-powered candidate scoring with relevance grading (A/B/C/D)
• Smart Filtering - Location-based and skill-based candidate relevance matching
• Multi-Channel Outreach - LinkedIn and email campaign management
• REST API - Full API for integration with external systems

Quick Start

Installation

# Clone and setup
git clone <repository-url>
cd Recruitment-agent

# Create virtual environment
python -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your credentials

Configuration

Create a .env file with:

# OpenAI
OPENAI_API_KEY=sk-...
OPENAI_MODEL=gpt-4

# MongoDB
MONGO_URI=mongodb+srv://...
MONGO_DATABASE=AIcruiter

# LinkedIn (Unipile)
UNIPILE_API_KEY=...
UNIPILE_ACCOUNT_ID=...

Running

Start API Server:

python main.py api --port 8000

Access:

• API Docs: http://localhost:8000/docs
• Health Check: http://localhost:8000/health

API Usage

Search Candidates

curl -X POST "http://localhost:8000/api/search/candidates" \
  -H "Content-Type: application/json" \
  -d '{
    "project_id": "1234567890",
    "search_criteria": {
      "keywords": ["Developer", "Python"],
      "location": "Netherlands",
      "job_title": "Software Engineer"
    },
    "target_count": 50
  }'

Get Project Candidates

curl "http://localhost:8000/api/search/candidates/{project_id}"

Evaluate Candidates

curl -X POST "http://localhost:8000/api/evaluation/evaluate" \
  -H "Content-Type: application/json" \
  -d '{
    "project_id": "1234567890",
    "candidate_ids": ["candidate_1", "candidate_2"]
  }'

Project Structure

Recruitment-agent/
├── main.py                 # Application entry point
├── agents/                 # Core agents
│   ├── database_agent.py   # Database operations
│   ├── recruitment_executive.py
│   └── sourcing_manager_unified.py
├── sub_agents/             # Specialized agents
│   ├── candidate_serching_agent.py
│   ├── candidate_evaluation_agent.py
│   └── profile_scraping_agent.py
├── src/
│   ├── application/        # Use cases & orchestrators
│   ├── domain/             # Domain models
│   ├── infrastructure/     # External services
│   └── presentation/       # API routes & CLI
├── tools/                  # LinkedIn & database tools
├── config/                 # Configuration
└── test/                   # Test suite

Architecture

┌─────────────────────────────────────────────────┐
│              REST API / CLI                      │
└─────────────────────┬───────────────────────────┘
                      │
┌─────────────────────▼───────────────────────────┐
│         RecruitmentExecutiveAgent               │
│         (Main Orchestrator)                      │
└─────────────────────┬───────────────────────────┘
                      │
        ┌─────────────┼─────────────┐
        ▼             ▼             ▼
┌───────────┐  ┌───────────┐  ┌───────────┐
│ Sourcing  │  │Evaluation │  │ Outreach  │
│ Manager   │  │  Agent    │  │ Manager   │
└─────┬─────┘  └───────────┘  └───────────┘
      │
      ▼
┌───────────────────────────────────────────────┐
│         CandidateSearchingAgent               │
│   (Hybrid: MongoDB + LinkedIn Search)         │
└─────────────────────┬─────────────────────────┘
                      │
        ┌─────────────┴─────────────┐
        ▼                           ▼
┌───────────────┐          ┌───────────────┐
│   MongoDB     │          │  LinkedIn API │
│  (prospects)  │          │   (Unipile)   │
└───────────────┘          └───────────────┘

Relevance Scoring

Candidates are scored (0-100) based on:

Factor	Points	Description
Location	40	Match with target location
Job Title	30	Keywords in title/headline
Skills	20	Matching required skills
Profile	10	Profile completeness

Grades:

• A (90+): Excellent match
• B (70-89): Good match
• C (50-69): Moderate match
• D (30-49): Low match
• F (<30): Filtered out

Development

Run Tests

pytest test/ -v

Code Style

# Format
black .

# Lint
flake8 .

Tech Stack

• Python 3.11+
• FastAPI - REST API framework
• MongoDB - Database
• LangChain - AI agent framework
• OpenAI GPT - Language model
• Unipile - LinkedIn API provider

License

MIT