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enmarcha

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The ENMARCHA libraries are the company's own libraries that are used in the development of the different projects. These libraries are mostly developed in C#, currently with .NET 8 and .NET Standard 2.1.

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# ENMARCHA — Your package to accelerate .NET projects

[![dotnet-ci-nuget](https://github.com/Encamina/enmarcha/actions/workflows/main.yml/badge.svg)](https://github.com/Encamina/enmarcha/actions/workflows/main.yml) [![CodeQL](https://github.com/Encamina/enmarcha/actions/workflows/codeql.yml/badge.svg)](https://github.com/Encamina/enmarcha/actions/workflows/codeql.yml)

> :warning: **This project is still under development.** We're working hard to release the first version of ENMARCHA as soon as possible. Stay tuned! Documentation and code examples will be available soon.

ENMARCHA aims to speed up the development of various .NET applications by leveraging robust modules that integrate with popular services and frameworks.

## Overview

## Key Features

ENMARCHA is a collection of modules that can be used to accelerate the development of various .NET applications. Each module is designed to integrate with popular services and frameworks, and can be used independently or in combination with other modules.

In terms of Generative AI, ENMARCHA implement ENGENIA as a core component to help with the develop of Generative AI applications in .NET. ENGENIA is based on the Microsoft Semantic Kernel and it's based of differente modules to help implement all the stacks of a Copilot application.

![ENGENIA stack](https://raw.githubusercontent.com/wiki/Encamina/enmarcha/assets/engenia-stack.png)

## 🚀 Core Components from ENGENIA

### [Your data](./wiki/YourData)

ENGENIA help to process your data and make it available for your applications. The approach is to use RAG (Retrieval Augmented Generation) to help with the data processing and the data augmentation.

### [Foundation models](./wiki/FoundationModels)

ENGENIA help using different LLM and implemente tools to help understand performance and help with the inference.

### [AI Orchestration](./wiki/AIOrchestration)

ENGENIA help with the orchestration of the different AI models and the different AI stacks. The idea is to use the Semantic Kernel to help with the orchestration of the different AI models.

### [Your Copilots](./wiki/YourCopilots)

ENGENIA help with the implementation of the different Copilots. The idea is to use the AI Orchestration to help with the orchestration of the different AI models and connect with Your Data to help with the data processing and the data augmentation.

### [Plugin Extensibility](./wiki/PluginExtensibility)

ENGENIA help with the extensibility of the different modules. The idea is to use the Plugin Extensibility to help with the extensibility of the different modules.

## 📖 Documentation
For detailed documentation on each module, see our official documentation.

## 🙏 Contributing
We welcome contributions from the community. For guidelines on how to contribute, see our [contribution FAQ](./CONTRIBUTING.md).

### Contributor Wall of Fame

[![ENMARCHA contributors](https://contrib.rocks/image?repo=encamina/enmarcha)](https://github.com/encamina/enmarcha/graphs/contributors)

## Code of Conduct

More information about our [Code of Conduct](./CODE_OF_CONDUCT.md).

## 📄 License

This project is licensed under the [Apache License 2.0](./LICENSE)

## 🛠 Getting Started

1. **Prerequisites**:
   - [.NET SDK](link_to_download)
   - ... (any other prerequisites)

2. **Installation**:

3. **Usage**:
Provide a basic example of how to use the modules, or link to a USAGE.md or your documentation for detailed guidance.

enmarcha

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