Pistology-WAIS

An intelligent, collaborative Warehouse AI System (WAIS) for document processing and warehouse management using multiple AI agents.

Features

• Multi-agent AI system with specialized agents:
  • Inventory Agent (DeepSeek)
  • Operations Agent (Gemini)
  • Supervisor Agent (Gemini)
• Document processing with LangChain
• Real-time system monitoring
• Interactive chat interface
• Secure API key management

Prerequisites

• Python 3.12+
• pip (Python package manager)

Installation

1. Clone the repository:

git clone https://github.com/nezpik/Pistology-WAIS.git
cd Pistology-WAIS

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

cp .env.example .env

4. Edit the .env file and add your API keys:

• DEEPSEEK_API_KEY
• GEMINI_API_KEY
• GEMINI_OPERATIONS_KEY
• GEMINI_SUPERVISOR_KEY
• GEMINI_INVENTORY_KEY

Security Notes

• Never commit the .env file to version control
• Keep your API keys secure and never share them
• Regularly rotate your API keys
• The .gitignore file is set up to exclude sensitive files
• All API keys are loaded from environment variables for security

Running the Application

Start the FastAPI server:

python main.py

The server will start on http://localhost:8000

API Endpoints

• POST /query: Send queries to specific agents
• GET /status: Get current state of all agents

Example Usage

import requests

# Query the inventory agent
response = requests.post("http://localhost:8000/query", 
    json={
        "query": "Check stock levels for item A123",
        "agent_type": "inventory"
    }
)

# Get system status
status = requests.get("http://localhost:8000/status")

Architecture

• Each agent inherits from BaseAgent class
• TensorFlow integration available for machine learning tasks
• Supervisor agent validates decisions made by other agents
• FastAPI provides REST API interface