
abi
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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README:
Agent Based Intelligence
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.
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.
- Assistants: Configurable AI assistants (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.
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
Step 5: Build your own module
make build-module
This will build the agent and save it in the /src/custom/modules
directory.
We welcome contributions! Please read the contributing guidelines for more information.
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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