What problem does it solve?
This Skill documents how to manage Azure AI Foundry project resources from Java, removing uncertainty about client patterns, authentication, and common operations so developers can programmatically enumerate and manage connections, datasets, indexes, deployments, and evaluations.
Core Features & Use Cases
- Client builder guidance: use AIProjectClientBuilder with environment-based credentials to produce multiple sub-clients efficiently.
- Resource management: examples for listing and retrieving connections, creating and updating datasets and indexes, and enumerating deployments.
- Evaluations and integrations: guidance for accessing the OpenAI evaluation client through the evaluations sub-client, async usage patterns, and error handling best practices.
- Use Case: ingest documents into a dataset, create or update a search index, deploy a model, and run automated evaluations for continuous validation.
Quick Start
Initialize the AIProjectClientBuilder using your PROJECT_ENDPOINT environment variable and DefaultAzureCredential then build the sub-clients you need to list connections and datasets.
