Spaces:
Sleeping
Sleeping
| title: AI Procurement Agent Demo | |
| emoji: π€ | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: streamlit | |
| sdk_version: 1.29.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # π€ AI Procurement Agent Demo | |
| An intelligent procurement agent that leverages reinforcement learning (PPO) for optimal supplier selection and allocation decisions. | |
| ## Features | |
| π― **Smart Supplier Selection**: Uses PPO (Proximal Policy Optimization) to make optimal allocation decisions | |
| π **Real-time Market Analysis**: Considers volatility, demand changes, and price fluctuations | |
| π **Multi-criteria Optimization**: Balances cost, quality, delivery performance, financial risk, and ESG factors | |
| π€ **Autonomous Decision Making**: End-to-end procurement process automation | |
| π **Interactive Visualization**: Real-time dashboards and performance metrics | |
| ## How It Works | |
| 1. **Market Analysis**: Analyzes current market conditions and volatility | |
| 2. **Supplier Evaluation**: Assesses suppliers across multiple dimensions | |
| 3. **AI Recommendation**: Uses trained PPO model for optimal allocation | |
| 4. **PO Generation**: Automatically creates purchase orders | |
| 5. **SAP Integration**: (Mocked) Integration with enterprise systems | |
| ## Technology Stack | |
| - **Reinforcement Learning**: Stable-Baselines3 PPO | |
| - **Agent Framework**: SmolagentS for tool orchestration | |
| - **Visualization**: Plotly for interactive charts | |
| - **Backend**: Python with NumPy/Pandas | |
| - **Frontend**: Streamlit for web interface | |
| ## Usage | |
| 1. Adjust market parameters (volatility, demand, pricing) | |
| 2. Configure supplier settings | |
| 3. Click "Run Procurement Agent" | |
| 4. View AI recommendations and generated purchase orders | |
| Perfect for demonstrating AI-driven procurement automation and intelligent supply chain management! | |