Enola.dev 🕵🏾‍♀️¶

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Enola.dev is an open-source project and community with a three-fold mission:

Build a vibrant community for hands-on learning in the rapidly evolving world of AI. (As Feynman famously said: “What I cannot create, I do not understand.”)
Provide powerful directly useful 🔮 AI-driven 🧙 agents that automate your work. These can be used with several AI tools.
Offer one such AI Tool; the Enola Application.

This Enola application itself is an Agentic AI Tool for Everyone: It enables you to easily create and use your own “No Code” AI 🥷 agents. These agents leverage Large Language Models (LLMs) and can interact with external 🧰 Tools to perform actions, going far beyond simple chat and text generation.

Accessible: It provides both a CLI and a Web UI for interacting with agents.
End-User Focused: It’s designed as a “packaged” tool that’s easy to get started with.
Extensible: While user-friendly, it’s also a full-fledged technical framework that you can use as a library to build your own solutions.
Forward-Looking: We are actively exploring advanced concepts like “multi-agent” scenarios.

Our Vision¶

We believe the future of AI lies in Knowledge Management Platforms benefiting from the synergy between Large Language Models and structured Knowledge Graphs (KG). Our goal is to further explore the fascinating intersection of these fields, particularly with AI Graph RAG (Retrieval-Augmented Generation). By providing agents with a rich, contextual understanding of “IT Infrastructure (or other) as Linked Data” systems through knowledge graphs, we aim to create more powerful, accurate, and intelligent ⛑️ automation (until singularity).

We may also offer our built-in Tools for LLMs as standalone MCP servers for other AI tools to use in the future.

Other Tools¶

Enola includes also a suite of AI unrelated tools:

Resource Abstraction: The fetch command can retrieve resources from diverse sources like HTTP(S), Git repositories, and local files.
Data Transformation (Rosetta): The rosetta command converts between numerous data formats (RDF, JSON, YAML, XML, etc.), and can generate diagrams to visualize your models.
Executable Markdown: The execmd command allows you to embed executable commands within your Markdown documents, enabling dynamic content generation.
Canonicalizing Formatter: The canonicalize command helps maintain consistent formatting across your project files.

BTW: The name “Enola” was originally inspired by the project’s creator having watched the Enola Holmes 🕵🏾‍♀️ detective movie with his daughter. And this is like a detective’s tool!

See You!¶

Come join us and help build the future of open AI-powered knowledge and automation together! 🫶