agent-framework-azure-ai-py

仓库: sickn33/antigravity-awesome-skills
安装量: 74
排名: #10520

安装

npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill agent-framework-azure-ai-py

Agent Framework Azure Hosted Agents Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK. Architecture User Query → AzureAIAgentsProvider → Azure AI Agent Service (Persistent) ↓ Agent.run() / Agent.run_stream() ↓ Tools: Functions | Hosted (Code/Search/Web) | MCP ↓ AgentThread (conversation persistence) Installation

Full framework (recommended)

pip install agent-framework --pre

Or Azure-specific package only

pip install agent-framework-azure-ai --pre Environment Variables export AZURE_AI_PROJECT_ENDPOINT = "https://.services.ai.azure.com/api/projects/" export AZURE_AI_MODEL_DEPLOYMENT_NAME = "gpt-4o-mini" export BING_CONNECTION_ID = "your-bing-connection-id"

For web search

Authentication from azure . identity . aio import AzureCliCredential , DefaultAzureCredential

Development

credential

AzureCliCredential ( )

Production

credential

DefaultAzureCredential
(
)
Core Workflow
Basic Agent
import
asyncio
from
agent_framework
.
azure
import
AzureAIAgentsProvider
from
azure
.
identity
.
aio
import
AzureCliCredential
async
def
main
(
)
:
async
with
(
AzureCliCredential
(
)
as
credential
,
AzureAIAgentsProvider
(
credential
=
credential
)
as
provider
,
)
:
agent
=
await
provider
.
create_agent
(
name
=
"MyAgent"
,
instructions
=
"You are a helpful assistant."
,
)
result
=
await
agent
.
run
(
"Hello!"
)
print
(
result
.
text
)
asyncio
.
run
(
main
(
)
)
Agent with Function Tools
from
typing
import
Annotated
from
pydantic
import
Field
from
agent_framework
.
azure
import
AzureAIAgentsProvider
from
azure
.
identity
.
aio
import
AzureCliCredential
def
get_weather
(
location
:
Annotated
[
str
,
Field
(
description
=
"City name to get weather for"
)
]
,
)
-
>
str
:
"""Get the current weather for a location."""
return
f"Weather in
{
location
}
72°F, sunny" def get_current_time ( ) -

str : """Get the current UTC time.""" from datetime import datetime , timezone return datetime . now ( timezone . utc ) . strftime ( "%Y-%m-%d %H:%M:%S UTC" ) async def main ( ) : async with ( AzureCliCredential ( ) as credential , AzureAIAgentsProvider ( credential = credential ) as provider , ) : agent = await provider . create_agent ( name = "WeatherAgent" , instructions = "You help with weather and time queries." , tools = [ get_weather , get_current_time ] ,

Pass functions directly

) result = await agent . run ( "What's the weather in Seattle?" ) print ( result . text ) Agent with Hosted Tools from agent_framework import ( HostedCodeInterpreterTool , HostedFileSearchTool , HostedWebSearchTool , ) from agent_framework . azure import AzureAIAgentsProvider from azure . identity . aio import AzureCliCredential async def main ( ) : async with ( AzureCliCredential ( ) as credential , AzureAIAgentsProvider ( credential = credential ) as provider , ) : agent = await provider . create_agent ( name = "MultiToolAgent" , instructions = "You can execute code, search files, and search the web." , tools = [ HostedCodeInterpreterTool ( ) , HostedWebSearchTool ( name = "Bing" ) , ] , ) result = await agent . run ( "Calculate the factorial of 20 in Python" ) print ( result . text ) Streaming Responses async def main ( ) : async with ( AzureCliCredential ( ) as credential , AzureAIAgentsProvider ( credential = credential ) as provider , ) : agent = await provider . create_agent ( name = "StreamingAgent" , instructions = "You are a helpful assistant." , ) print ( "Agent: " , end = "" , flush = True ) async for chunk in agent . run_stream ( "Tell me a short story" ) : if chunk . text : print ( chunk . text , end = "" , flush = True ) print ( ) Conversation Threads from agent_framework . azure import AzureAIAgentsProvider from azure . identity . aio import AzureCliCredential async def main ( ) : async with ( AzureCliCredential ( ) as credential , AzureAIAgentsProvider ( credential = credential ) as provider , ) : agent = await provider . create_agent ( name = "ChatAgent" , instructions = "You are a helpful assistant." , tools = [ get_weather ] , )

Create thread for conversation persistence

thread

agent . get_new_thread ( )

First turn

result1

await agent . run ( "What's the weather in Seattle?" , thread = thread ) print ( f"Agent: { result1 . text } " )

Second turn - context is maintained

result2

await agent . run ( "What about Portland?" , thread = thread ) print ( f"Agent: { result2 . text } " )

Save thread ID for later resumption

print
(
f"Conversation ID:
{
thread
.
conversation_id
}
"
)
Structured Outputs
from
pydantic
import
BaseModel
,
ConfigDict
from
agent_framework
.
azure
import
AzureAIAgentsProvider
from
azure
.
identity
.
aio
import
AzureCliCredential
class
WeatherResponse
(
BaseModel
)
:
model_config
=
ConfigDict
(
extra
=
"forbid"
)
location
:
str
temperature
:
float
unit
:
str
conditions
:
str
async
def
main
(
)
:
async
with
(
AzureCliCredential
(
)
as
credential
,
AzureAIAgentsProvider
(
credential
=
credential
)
as
provider
,
)
:
agent
=
await
provider
.
create_agent
(
name
=
"StructuredAgent"
,
instructions
=
"Provide weather information in structured format."
,
response_format
=
WeatherResponse
,
)
result
=
await
agent
.
run
(
"Weather in Seattle?"
)
weather
=
WeatherResponse
.
model_validate_json
(
result
.
text
)
print
(
f"
{
weather
.
location
}
:
{
weather
.
temperature
}
°
{
weather
.
unit
}
"
)
Provider Methods
Method
Description
create_agent()
Create new agent on Azure AI service
get_agent(agent_id)
Retrieve existing agent by ID
as_agent(sdk_agent)
Wrap SDK Agent object (no HTTP call)
Hosted Tools Quick Reference
Tool
Import
Purpose
HostedCodeInterpreterTool
from agent_framework import HostedCodeInterpreterTool
Execute Python code
HostedFileSearchTool
from agent_framework import HostedFileSearchTool
Search vector stores
HostedWebSearchTool
from agent_framework import HostedWebSearchTool
Bing web search
HostedMCPTool
from agent_framework import HostedMCPTool
Service-managed MCP
MCPStreamableHTTPTool
from agent_framework import MCPStreamableHTTPTool
Client-managed MCP
Complete Example
import
asyncio
from
typing
import
Annotated
from
pydantic
import
BaseModel
,
Field
from
agent_framework
import
(
HostedCodeInterpreterTool
,
HostedWebSearchTool
,
MCPStreamableHTTPTool
,
)
from
agent_framework
.
azure
import
AzureAIAgentsProvider
from
azure
.
identity
.
aio
import
AzureCliCredential
def
get_weather
(
location
:
Annotated
[
str
,
Field
(
description
=
"City name"
)
]
,
)
-
>
str
:
"""Get weather for a location."""
return
f"Weather in
{
location
}
72°F, sunny" class AnalysisResult ( BaseModel ) : summary : str key_findings : list [ str ] confidence : float async def main ( ) : async with ( AzureCliCredential ( ) as credential , MCPStreamableHTTPTool ( name = "Docs MCP" , url = "https://learn.microsoft.com/api/mcp" , ) as mcp_tool , AzureAIAgentsProvider ( credential = credential ) as provider , ) : agent = await provider . create_agent ( name = "ResearchAssistant" , instructions = "You are a research assistant with multiple capabilities." , tools = [ get_weather , HostedCodeInterpreterTool ( ) , HostedWebSearchTool ( name = "Bing" ) , mcp_tool , ] , ) thread = agent . get_new_thread ( )

Non-streaming

result

await agent . run ( "Search for Python best practices and summarize" , thread = thread , ) print ( f"Response: { result . text } " )

Streaming

print ( "\nStreaming: " , end = "" ) async for chunk in agent . run_stream ( "Continue with examples" , thread = thread ) : if chunk . text : print ( chunk . text , end = "" , flush = True ) print ( )

Structured output

result

await agent . run ( "Analyze findings" , thread = thread , response_format = AnalysisResult , ) analysis = AnalysisResult . model_validate_json ( result . text ) print ( f"\nConfidence: { analysis . confidence } " ) if name == "main" : asyncio . run ( main ( ) ) Conventions Always use async context managers: async with provider: Pass functions directly to tools= parameter (auto-converted to AIFunction) Use Annotated[type, Field(description=...)] for function parameters Use get_new_thread() for multi-turn conversations Prefer HostedMCPTool for service-managed MCP, MCPStreamableHTTPTool for client-managed Reference Files references/tools.md: Detailed hosted tool patterns references/mcp.md: MCP integration (hosted + local) references/threads.md: Thread and conversation management references/advanced.md: OpenAPI, citations, structured outputs When to Use This skill is applicable to execute the workflow or actions described in the overview.

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