Facilis - Effortless API Interoperability with AI

Facilis is an AI-powered solution designed to streamline API integration by extracting structured specifications from natural language descriptions. Now powered by CrewAI, Facilis ensures a more efficient and modular approach to handling API documentation and interoperability.

How to pronounce Facilis: [ˈfäkɪlʲɪs̠]

🚀 Motivation

Managing API integrations can be complex and error-prone. Facilis simplifies this process by leveraging AI to extract and validate API details, ensuring compliance with OpenAPI standards and facilitating seamless interoperability.

🛠️ How It Works

Facilis processes user-provided API descriptions, extracting key details such as endpoints, HTTP methods, parameters, authentication, and more. It then structures the extracted information into OpenAPI-compliant JSON and exports it to InterSystems IRIS for interoperability. The workflow consists of multiple AI agents, orchestrated by CrewAI, handling:

• Extraction: Identifies and structures API specifications from natural language.
• Interaction: Requests missing details from the user.
• Validation: Ensures API compliance and consistency.
• Transformation: Converts structured API details into OpenAPI JSON.
• Review: Verifies OpenAPI compliance before finalization.
• Integration: Connects with Facilis API on InterSystems IRIS. Handles deployment configurations, creating the production, Business Services, Business Operations, and everything else

📋 Prerequisites

• Python 3.10+
• Docker & Docker Compose
• An API key from your preferred LLM provider (OpenAI, Azure OpenAI, Google Gemini, or Claude)

🛠️ Installation

1️⃣ Clone the Repository

git clone https://github.com/musketeers-br/dc-facilis
cd dc-facilis

2️⃣ Set Up Environment Variables

Facilis requires two .env files, one in the root directory and another in python/facilis/.

Create .env files based on the provided samples

cp env_sample .env
cp python/facilis/env_sample python/facilis/.env

Edit .env and python/facilis/.env with your settings

# AI Engine selection (choose one: openai, azureopenai, googleGemini, claude, ollama)
AI_ENGINE=openai  
LLM Model Name
LLM_MODEL_NAME=gpt-4o-mini
API Key for the selected AI provider
OPENAI_API_KEY=your-api-key-here

3️⃣ Run with Docker Compose

# Build the container
docker-compose build --no-cache --progress=plain
Start the application
docker-compose up -d
Stop and remove containers
docker-compose down --rmi all

💡 How to Use

1. Describe Your APIs

Simply describe your API endpoints in natural language. For example:

I want to retrieve all users from api.example.com/users using GET method and also create a new user POST api.example.com/users

This will be automatically converted into proper API specifications for:

• GET /users - Retrieve all users
• POST /users - Create a new user

2. Provide Production Details

• Enter your production name
• Specify the namespace

Facilis will handle the rest!

🚧 Limitations

• Accuracy of extracted API details depends on the quality of user input.
• LLM-based processing may introduce minor inconsistencies requiring manual review.
• Currently optimized for OpenAPI 3.0.

🎖️ Credits

Facilis is developed with ❤️ by the Musketeers Team

• José Roberto Pereira
• Henry Pereira
• Henrique Dias