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Azure AI Studio Updates at Build 2024
I wrote “Azure AI Studio Updates at Build 2024” to share practical, production-minded guidance on this topic.
What’s New in Azure AI Studio
1. Unified Experience
Azure AI Studio now provides a single pane of glass for:
- Model catalog browsing
- Prompt engineering
- Fine-tuning
- Evaluation
- Deployment
- Monitoring
2. Model Catalog Expansion
Available Models:
├── OpenAI (GPT-4o, GPT-4, GPT-3.5)
├── Microsoft (Phi-3 family)
├── Meta (Llama 3)
├── Mistral (Mistral, Mixtral)
├── Cohere (Command R+)
└── Stability AI (SDXL)
Getting Started with AI Studio
Project Setup
from azure.ai.projects import AIProjectClient
from azure.identity import DefaultAzureCredential
# Connect to AI Studio project
credential = DefaultAzureCredential()
client = AIProjectClient(
credential=credential,
subscription_id="your-subscription-id",
resource_group_name="your-resource-group",
project_name="your-ai-project"
)
# List available models
models = client.models.list()
for model in models:
print(f"{model.name}: {model.version}")
Model Deployment
from azure.ai.projects.models import ModelDeployment
# Deploy a model
deployment = client.deployments.create(
name="gpt4o-production",
model="gpt-4o",
sku="Standard",
capacity=10 # TPM in thousands
)
print(f"Deployment created: {deployment.name}")
print(f"Endpoint: {deployment.endpoint}")
Prompt Flow Updates
Visual Flow Builder
# prompt_flow.yaml
$schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
query:
type: string
description: User question
context:
type: string
description: Retrieved documents
nodes:
- name: search
type: python
source:
type: code
path: search.py
inputs:
query: ${inputs.query}
- name: generate
type: llm
source:
type: code
path: generate.prompty
inputs:
context: ${search.output}
query: ${inputs.query}
outputs:
answer:
type: string
reference: ${generate.output}
Prompty Files
# generate.prompty\n\n## Takeaways\n\n*Add a concise, personal takeaway and recommended next steps here.*\n