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An organizational AI system to build a suite of AI assistants leveraging ontologies as a unifying field that connect data, AI models, workflows, analytics, and external systems. Star and follow to stay updated [Beta]

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ABI

Agent Based Intelligence

Overview

The ABI (Agent Based Intelligence) project is a Python-based backend framework designed to serve as the core infrastructure for building an Agentic AI Ontology Engine. This system empowers organizations to integrate, manage, and scale AI-driven operations with a focus on ontology, agent-driven workflows, and analytics. Designed for flexibility and scalability, ABI provides a customizable framework suitable for organizations aiming to create intelligent, automated systems tailored to their needs.

Why ABI?

The ABI project aims to provide a open alternative to Palantir by offering a flexible and scalable framework for building intelligent systems using ontology. Unlike Palantir, which is often seen as a monolithic solution, ABI emphasizes modularity and customization, allowing organizations to tailor their AI-driven operations to specific needs. Combined with the Naas.ai ecosystem, ABI can be used to build the brain of your organization's agentic AI applications.

Key Features

  • Agents: Configurable AI agents (also named agents) to handle specific organizational tasks and interact with users.
  • Ontology Management: Define and manage data relationships, structures, and semantic elements.
  • Integrations: Seamlessly connect to external data sources and APIs for unified data access.
  • Pipelines: Define data processing pipelines to handle and transform data efficiently into the ontological layer.
  • Workflows: Automate complex business processes and manage end-to-end workflows.
  • Analytics: Access insights through integrated analytics and real-time data processing.
  • Data: Handle diverse datasets and manage schema, versioning, deduplication, and change data capture.

Quick Start

Step 1: Clone the repository

git clone https://github.com/jupyter-naas/abi.git

Step 2: Setup environment variables

cp .env.example .env

Step 3: Run the project

make

This will run the supervisor agent and the agentic engine.

For specific agents, you can run them directly with the following command:

make chat-[name]-agent

Step 4: Build and run the API

You need to build the API before running it. Find out more about the API in the API documentation.

make api

Contributing

We welcome contributions! Please read the contributing guidelines for more information.

License

ABI Framework is open-source and available for use under the MIT license. Professionals and enterprises are encouraged to contact our support for custom services as this project evolves rapidly at [email protected]

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An organizational AI system to build a suite of AI assistants leveraging ontologies as a unifying field that connect data, AI models, workflows, analytics, and external systems. Star and follow to stay updated [Beta]

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