Open Matching Engine (OME)

Overview

The Open Matching Engine (OME) is a flexible, domain-agnostic framework designed to solve complex requirements-to-capabilities matching problems across various domains. The system matches requirements (what needs to be done) with capabilities (what can be done) to create viable solutions.

Quick Start for Developers

Installation

# Clone the repository
git clone https://github.com/helpfulengineering/supply-graph-ai.git
cd supply-graph-ai

# Create and activate a virtual environment (recommended)
python -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Documentation

This README provides a quick start guide and basic project information. For comprehensive documentation, please build the documentation locally.

Building Documentation Locally

The OME documentation is built using MkDocs, a simple static site generator for project documentation.

To build and view the documentation locally:

1. Install MkDocs and required plugins:

pip install mkdocs mkdocs-material mkdocs-mermaid2-plugin

2. Start the documentation server:

mkdocs serve

4. Open your browser to http://localhost:8000/

Documentation Structure

Our documentation covers:

• Architecture Guide: System design, components, and data flow

  • System architecture overview
  • Data flow diagrams
  • Component interactions
  • Validation and matching pipelines

• Domain Implementations:

  • Manufacturing domain (OKH/OKW matching)
  • Cooking domain (Recipe/Kitchen matching)
  • Domain extension guidelines

• API Reference:

  • RESTful API endpoints
  • Authentication
  • Request/Response formats
  • Usage examples

• Developer Guide:

  • Setup and installation
  • Contributing guidelines
  • Testing procedures
  • Best practices

Project Structure

open-matching-engine/
├── docs/                   # Documentation files (MkDocs)
├── src/                    # Source code
│   ├── core/               # Core framework components
│   │   ├── api/            # API endpoints
│   │   ├── domains/        # Domain implementations
│   │   ├── matching/       # Matching Rules Manager
│   │   ├── models/         # Data models
│   │   ├── registry/       # Domain registry
│   │   ├── services/       # Core services
│   │   ├── storage/        # Storage service for remote file mgmt
│   │   └── utils/          # Utility functions
│   └── config/             # Config management
├── synth/                  # synthetic data for development, remove in prod
├── tests/                  # Test cases
├── mkdocs.yml              # Documentation configuration
├── requirements.txt        # Project dependencies
└── run.py                  # FastAPI server on uvicorn

Running the Application Locally

Note: You may have add a directory called "logs" locally if the command below indicates it can't open the log file!

# Start the FastAPI server
python run.py

# Visit the API documentation at:
http://127.0.0.1:8001/v1/docs