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13. References
Glossary
Term Definition
Foundry Hub Shared resource container (AI Search, Storage, Key Vault)
Foundry Project Workspace within a Hub for building AI applications
Agent Service Managed runtime for AI agents with tools and memory
RAG Retrieval-Augmented Generation — ground LLM responses in retrieved data
MCP Model Context Protocol — standardized tool interface
A2A Agent-to-Agent protocol for inter-agent communication
AI Gateway API Management layer for AI models and agents
Foundry IQ Agentic retrieval with intelligent ranking
Cheatsheet
# Python SDK Quick Reference
# 1. Create project client
from azure.ai.projects import AIProjectClient
client = AIProjectClient(subscription_id, resource_group, project_name, credential)
# 2. Create agent
agent = client.agents.create_agent(model="gpt-4o", name="MyAgent", instructions="...")
# 3. Add tools
from azure.ai.projects.models import ToolSet, CodeInterpreterTool, WebSearchTool
toolset = ToolSet()
toolset.add(CodeInterpreterTool())
# 4. Send message
response = client.agents.send_message(agent.id, "Hello")
# 5. Create search index
from azure.search.documents.indexes import SearchIndexClient
index_client = SearchIndexClient(endpoint, credential)
index_client.create_index(index_definition)
# 6. Deploy model (portal or CLI)
# az ml model create --name gpt-4o --type deployment
API Reference
Azure.AI.Projects — Agent lifecycle, tools, memory
Azure.AI.Inference — Chat completions, embeddings
Azure.Search.Documents — Vector + keyword search
Azure.Identity — DefaultAzureCredential, ManagedIdentity
Azure.AI.ContentSafety — PII detection, content filtering
Azure.AI.DocumentIntelligence — Document extraction
Continue Your Journey
Build a production agent with monitoring and guardrails
Contribute to the Foundry SDK on GitHub
Join the Azure AI community discussions
Explore the MAF Fundamentals guide for deeper agent-building skills
📘 Congratulations! You've completed the Microsoft Foundry Fundamentals guide. You now have the knowledge to build, deploy, and manage AI agents at scale using Azure AI Foundry.
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