03.AzureAIFoundry.md

Phi Family in Microsoft Foundry

Microsoft Foundry is a trusted platform that empowers developers to drive innovation and shape the future with AI in a safe, secure, and responsible way.

Microsoft Foundry is designed for developers to:

• Build generative AI applications on an enterprise-grade platform.
• Explore, build, test, and deploy using cutting-edge AI tools and ML models, grounded in responsible AI practices.
• Collaborate with a team for the full life-cycle of application development.

With Microsoft Foundry, you can explore a wide variety of models, services and capabilities, and get to building AI applications that best serve your goals. The Microsoft Foundry platform facilitates scalability for transforming proof of concepts into full-fledged production applications with ease. Continuous monitoring and refinement support long-term success.

In addition to using Azure AOAI Service in Microsoft Foundry, you can also use third-party models in the Microsoft Foundry Model Catalog. This is a good choice if you want to use Microsoft Foundry as your AI solution platform.

We can quickly deploy Phi Family Models through the Model Catalog in Microsoft Foundry

Microsoft Phi Models in Microsoft Foundry Models

Deploy Phi-4 in Microsoft Foundry

Test Phi-4 in Microsoft Foundry Playground

Running Python Code to call Microsoft Foundry Phi-4

import os  
import base64
from openai import AzureOpenAI  
from azure.identity import DefaultAzureCredential, get_bearer_token_provider  
        
endpoint = os.getenv("ENDPOINT_URL", "Your Azure AOAI Service Endpoint")  
deployment = os.getenv("DEPLOYMENT_NAME", "Phi-4")  
      
token_provider = get_bearer_token_provider(  
    DefaultAzureCredential(),  
    "https://cognitiveservices.azure.com/.default"  
)  
  
client = AzureOpenAI(  
    azure_endpoint=endpoint,  
    azure_ad_token_provider=token_provider,  
    api_version="2024-05-01-preview",  
)  
  

chat_prompt = [
    {
        "role": "system",
        "content": "You are an AI assistant that helps people find information."
    },
    {
        "role": "user",
        "content": "can you introduce yourself"
    }
] 
    
# Include speech result if speech is enabled  
messages = chat_prompt 

completion = client.chat.completions.create(  
    model=deployment,  
    messages=messages,
    max_tokens=800,  
    temperature=0.7,  
    top_p=0.95,  
    frequency_penalty=0,  
    presence_penalty=0,
    stop=None,  
    stream=False  
)  
  
print(completion.to_json())