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Getting Started with Pharia Applications

Before diving into the process of developing and deploying a Pharia AI Application, it's essential to understand what a Pharia AI Application is. For a comprehensive overview, refer to What is a Pharia AI Application?.

If you're looking for a more hands-on approach, start with our Quick Start Guide to get your Pharia AI Application up and running quickly.

Developing and deploying a Pharia AI Application follows an iterative process similar to other software development workflows. While the phases below are presented sequentially, you can adapt and revisit them as needed based on your application's requirements. This section provides an overview of the key development phases and points you to detailed documentation for each step.

1. Infrastructure pre-requisites​

To get started with Pharia AI Applications, ensure that you have installed Pharia AI with the following core components enabled:

  • Pharia Kernel - For building and deploying skills
  • Pharia Assistant - For rendering your application UI
  • Pharia OS Manager - For deployment and management of your application
  • Pharia Data Platform - For data management utilities such as file management, file transformation, etc.
  • Inference API - For model serving and inference
  • Document Index - For creating document collections

2. Data setup, processing and management​

When building a Pharia AI Application you will need to setup and process some data whether its for model training, creation of collections for document search, or experimentation during development of your skills and Applications. We provide Pharia Data Platform to help you setup and process data for your application, including file ingestion for dataset creation, other file transformations, and more.

We also provide a Vector Database, called Document Index, to support Retrieval Augmented Generation (RAG) setups. With Document Index, you can create collections with metadata and leverage powerful semantic and hybrid search functionality to retrieve relevant documents and contexts for your AI applications.

You can take a look at our How to Setup Collections guide to learn more about how to use the Document Index api to create collections.

3. Skill Development and Deployment​

Pharia Kernel is designed to facilitate the development and deployment of your skills. For detailed information on the API Specs, refer to the Pharia Kernel documentation here. To explore the integration of a skill into a Pharia AI Application, follow the steps outlined in the Quick Start Guide. to create a base Pharia AI Application that includes a skill.

4. Development and Deployment of the Application Service and UI​

To initiate the development and deployment of your first Pharia AI Application, refer to our Quick Start Guide for a streamlined process. This guide provides a comprehensive walkthrough to get you started efficiently.

5. Tracing, Debugging and Evaluation of the Application and Skills​

You can do tracing, debugging, and evaluation of your skills and application service during development and also in production by using Pharia Studio. We provide a user interface and an SDK to help you do this. To get started, refer to our Pharia Studio Introduction.

Troubleshooting Guide​

For any issues you encounter during the development and deployment process, refer to our Troubleshooting Guide for common error solutions and best practices.

Next Steps​

Pharia AI Application is still evolving. Your feedback is invaluable. If you have suggestions or comments, please reach out to us via Aleph Alpha Support Portal.