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Python: Create/Get Agent API for Azure V2 (#3059)

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* Added get_agent method to Azure AI V2

* Small fixes

* Small fix

* Removed AzureAIAgentProvider

* Added create_agent method

* Small fixes

* Fixed code interpreter tool mapping

* Added agent provider for V2 client

* Updated response format handling

* Added provider example

* Fixed errors

* Update python/samples/getting_started/agents/azure_ai/README.md

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Small fix

* Updates from merge

* Resolved comments

* Resolved comments

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
Dmytro Struk
2026-01-14 11:35:01 -08:00
committed by GitHub
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parent f56808b279
commit 99c5718696
35 changed files with 1903 additions and 336 deletions
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python/samples/getting_started/agents/azure_ai/README.md
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@@ -6,8 +6,9 @@ This folder contains examples demonstrating different ways to create and use age
| File | Description |
|------|-------------|
| [`azure_ai_basic.py`](azure_ai_basic.py) | The simplest way to create an agent using `AzureAIClient`. Demonstrates both streaming and non-streaming responses with function tools. Shows automatic agent creation and basic weather functionality. |
| [`azure_ai_use_latest_version.py`](azure_ai_use_latest_version.py) | Demonstrates how to reuse the latest version of an existing agent instead of creating a new agent version on each instantiation using the `use_latest_version=True` parameter. |
| [`azure_ai_basic.py`](azure_ai_basic.py) | The simplest way to create an agent using `AzureAIProjectAgentProvider`. Demonstrates both streaming and non-streaming responses with function tools. Shows automatic agent creation and basic weather functionality. |
| [`azure_ai_provider_methods.py`](azure_ai_provider_methods.py) | Comprehensive guide to `AzureAIProjectAgentProvider` methods: `create_agent()` for creating new agents, `get_agent()` for retrieving existing agents (by name, reference, or details), and `as_agent()` for wrapping SDK objects without HTTP calls. |
| [`azure_ai_use_latest_version.py`](azure_ai_use_latest_version.py) | Demonstrates how to reuse the latest version of an existing agent instead of creating a new agent version on each instantiation by using `provider.get_agent()` to retrieve the latest version. |
| [`azure_ai_with_agent_to_agent.py`](azure_ai_with_agent_to_agent.py) | Shows how to use Agent-to-Agent (A2A) capabilities with Azure AI agents to enable communication with other agents using the A2A protocol. Requires an A2A connection configured in your Azure AI project. |
| [`azure_ai_with_azure_ai_search.py`](azure_ai_with_azure_ai_search.py) | Shows how to use Azure AI Search with Azure AI agents to search through indexed data and answer user questions with proper citations. Requires an Azure AI Search connection and index configured in your Azure AI project. |
| [`azure_ai_with_bing_grounding.py`](azure_ai_with_bing_grounding.py) | Shows how to use Bing Grounding search with Azure AI agents to search the web for current information and provide grounded responses with citations. Requires a Bing connection configured in your Azure AI project. |
python/samples/getting_started/agents/azure_ai/azure_ai_basic.py
+12 -10
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@@ -4,14 +4,14 @@ import asyncio
from random import randint
from typing import Annotated
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
from pydantic import Field
"""
Azure AI Agent Basic Example
This sample demonstrates basic usage of AzureAIClient.
This sample demonstrates basic usage of AzureAIProjectAgentProvider.
Shows both streaming and non-streaming responses with function tools.
"""
@@ -28,17 +28,18 @@ async def non_streaming_example() -> None:
"""Example of non-streaming response (get the complete result at once)."""
print("=== Non-streaming Response Example ===")
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
)
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
@@ -49,17 +50,18 @@ async def streaming_example() -> None:
"""Example of streaming response (get results as they are generated)."""
print("=== Streaming Response Example ===")
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
)
query = "What's the weather like in Tokyo?"
print(f"User: {query}")
print("Agent: ", end="", flush=True)
python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py
+293
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@@ -0,0 +1,293 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import os
from random import randint
from typing import Annotated
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import AgentReference, PromptAgentDefinition
from azure.identity.aio import AzureCliCredential
from pydantic import Field
"""
Azure AI Project Agent Provider Methods Example
This sample demonstrates the three main methods of AzureAIProjectAgentProvider:
1. create_agent() - Create a new agent on the Azure AI service
2. get_agent() - Retrieve an existing agent from the service
3. as_agent() - Wrap an SDK agent version object without making HTTP calls
It also shows how to use a single provider instance to spawn multiple agents
with different configurations, which is efficient for multi-agent scenarios.
Each method returns a ChatAgent that can be used for conversations.
"""
def get_weather(
location: Annotated[str, Field(description="The location to get the weather for.")],
) -> str:
"""Get the weather for a given location."""
conditions = ["sunny", "cloudy", "rainy", "stormy"]
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}C."
async def create_agent_example() -> None:
"""Example of using provider.create_agent() to create a new agent.
This method creates a new agent version on the Azure AI service and returns
a ChatAgent. Use this when you want to create a fresh agent with
specific configuration.
"""
print("=== provider.create_agent() Example ===")
async with (
AzureCliCredential() as credential,
AzureAIProjectAgentProvider(credential=credential) as provider,
):
# Create a new agent with custom configuration
agent = await provider.create_agent(
name="WeatherAssistant",
instructions="You are a helpful weather assistant. Always be concise.",
description="An agent that provides weather information.",
tools=get_weather,
)
print(f"Created agent: {agent.name}")
print(f"Agent ID: {agent.id}")
query = "What's the weather in Paris?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
async def get_agent_by_name_example() -> None:
"""Example of using provider.get_agent(name=...) to retrieve an agent by name.
This method fetches the latest version of an existing agent from the service.
Use this when you know the agent name and want to use the most recent version.
"""
print("=== provider.get_agent(name=...) Example ===")
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
):
# First, create an agent using the SDK directly
created_agent = await project_client.agents.create_version(
agent_name="TestAgentByName",
description="Test agent for get_agent by name example.",
definition=PromptAgentDefinition(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
instructions="You are a helpful assistant. End each response with '- Your Assistant'.",
),
)
try:
# Get the agent using the provider by name (fetches latest version)
provider = AzureAIProjectAgentProvider(project_client=project_client)
agent = await provider.get_agent(name=created_agent.name)
print(f"Retrieved agent: {agent.name}")
query = "Hello!"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
finally:
# Clean up the agent
await project_client.agents.delete_version(
agent_name=created_agent.name, agent_version=created_agent.version
)
async def get_agent_by_reference_example() -> None:
"""Example of using provider.get_agent(reference=...) to retrieve a specific agent version.
This method fetches a specific version of an agent using an AgentReference.
Use this when you need to use a particular version of an agent.
"""
print("=== provider.get_agent(reference=...) Example ===")
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
):
# First, create an agent using the SDK directly
created_agent = await project_client.agents.create_version(
agent_name="TestAgentByReference",
description="Test agent for get_agent by reference example.",
definition=PromptAgentDefinition(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
instructions="You are a helpful assistant. Always respond in uppercase.",
),
)
try:
# Get the agent using an AgentReference with specific version
provider = AzureAIProjectAgentProvider(project_client=project_client)
reference = AgentReference(name=created_agent.name, version=created_agent.version)
agent = await provider.get_agent(reference=reference)
print(f"Retrieved agent: {agent.name} (version via reference)")
query = "Say hello"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
finally:
# Clean up the agent
await project_client.agents.delete_version(
agent_name=created_agent.name, agent_version=created_agent.version
)
async def get_agent_by_details_example() -> None:
"""Example of using provider.get_agent(details=...) with pre-fetched AgentDetails.
This method uses pre-fetched AgentDetails to get the latest version.
Use this when you already have AgentDetails from a previous API call.
"""
print("=== provider.get_agent(details=...) Example ===")
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
):
# First, create an agent using the SDK directly
created_agent = await project_client.agents.create_version(
agent_name="TestAgentByDetails",
description="Test agent for get_agent by details example.",
definition=PromptAgentDefinition(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
instructions="You are a helpful assistant. Always include an emoji in your response.",
),
)
try:
# Fetch AgentDetails separately (simulating a previous API call)
agent_details = await project_client.agents.get(agent_name=created_agent.name)
# Get the agent using the pre-fetched details (sync - no HTTP call)
provider = AzureAIProjectAgentProvider(project_client=project_client)
agent = provider.as_agent(agent_details.versions.latest)
print(f"Retrieved agent: {agent.name} (from pre-fetched details)")
query = "How are you today?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
finally:
# Clean up the agent
await project_client.agents.delete_version(
agent_name=created_agent.name, agent_version=created_agent.version
)
async def multiple_agents_example() -> None:
"""Example of using a single provider to spawn multiple agents.
A single provider instance can create multiple agents with different
configurations.
"""
print("=== Multiple Agents from Single Provider Example ===")
async with (
AzureCliCredential() as credential,
AzureAIProjectAgentProvider(credential=credential) as provider,
):
# Create multiple specialized agents from the same provider
weather_agent = await provider.create_agent(
name="WeatherExpert",
instructions="You are a weather expert. Provide brief weather information.",
tools=get_weather,
)
translator_agent = await provider.create_agent(
name="Translator",
instructions="You are a translator. Translate any text to French. Only output the translation.",
)
poet_agent = await provider.create_agent(
name="Poet",
instructions="You are a poet. Respond to everything with a short haiku.",
)
print(f"Created agents: {weather_agent.name}, {translator_agent.name}, {poet_agent.name}\n")
# Use each agent for its specialty
weather_query = "What's the weather in London?"
print(f"User to WeatherExpert: {weather_query}")
weather_result = await weather_agent.run(weather_query)
print(f"WeatherExpert: {weather_result}\n")
translate_query = "Hello, how are you today?"
print(f"User to Translator: {translate_query}")
translate_result = await translator_agent.run(translate_query)
print(f"Translator: {translate_result}\n")
poet_query = "Tell me about the morning sun"
print(f"User to Poet: {poet_query}")
poet_result = await poet_agent.run(poet_query)
print(f"Poet: {poet_result}\n")
async def as_agent_example() -> None:
"""Example of using provider.as_agent() to wrap an SDK object without HTTP calls.
This method wraps an existing AgentVersionDetails into a ChatAgent without
making additional HTTP calls. Use this when you already have the full
AgentVersionDetails from a previous SDK operation.
"""
print("=== provider.as_agent() Example ===")
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
):
# Create an agent using the SDK directly - this returns AgentVersionDetails
agent_version_details = await project_client.agents.create_version(
agent_name="TestAgentAsAgent",
description="Test agent for as_agent example.",
definition=PromptAgentDefinition(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
instructions="You are a helpful assistant. Keep responses under 20 words.",
),
)
try:
# Wrap the SDK object directly without any HTTP calls
provider = AzureAIProjectAgentProvider(project_client=project_client)
agent = provider.as_agent(agent_version_details)
print(f"Wrapped agent: {agent.name} (no HTTP call needed)")
print(f"Agent version: {agent_version_details.version}")
query = "What can you do?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
finally:
# Clean up the agent
await project_client.agents.delete_version(
agent_name=agent_version_details.name, agent_version=agent_version_details.version
)
async def main() -> None:
print("=== Azure AI Project Agent Provider Methods Example ===\n")
await create_agent_example()
await get_agent_by_name_example()
await get_agent_by_reference_example()
await get_agent_by_details_example()
await as_agent_example()
await multiple_agents_example()
if __name__ == "__main__":
asyncio.run(main())
python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py
+31 -34
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@@ -4,7 +4,7 @@ import asyncio
from random import randint
from typing import Annotated
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
from pydantic import Field
@@ -13,7 +13,7 @@ Azure AI Agent Latest Version Example
This sample demonstrates how to reuse the latest version of an existing agent
instead of creating a new agent version on each instantiation. The first call creates a new agent,
while subsequent calls with `use_latest_version=True` reuse the latest agent version.
while subsequent calls with `get_agent()` reuse the latest agent version.
"""
@@ -28,39 +28,36 @@ def get_weather(
async def main() -> None:
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with AzureCliCredential() as credential:
async with (
AzureAIClient(
credential=credential,
).create_agent(
name="MyWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
# First query will create a new agent
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
async with (
AzureCliCredential() as credential,
AzureAIProjectAgentProvider(credential=credential) as provider,
):
# First call creates a new agent
agent = await provider.create_agent(
name="MyWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
)
# Create a new agent instance
async with (
AzureAIClient(
credential=credential,
# This parameter will allow to re-use latest agent version
# instead of creating a new one
use_latest_version=True,
).create_agent(
name="MyWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
query = "What's the weather like in Tokyo?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result}\n")
# Second call retrieves the existing agent (latest version) instead of creating a new one
# This is useful when you want to reuse an agent that was created earlier
agent2 = await provider.get_agent(
name="MyWeatherAgent",
tools=get_weather, # Tools must be provided for function tools
)
query = "What's the weather like in Tokyo?"
print(f"User: {query}")
result = await agent2.run(query)
print(f"Agent: {result}\n")
print(f"First agent ID with version: {agent.id}")
print(f"Second agent ID with version: {agent2.id}")
if __name__ == "__main__":
python/samples/getting_started/agents/azure_ai/azure_ai_with_agent_to_agent.py
+9 -7
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@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Agent-to-Agent (A2A) Example
This sample demonstrates usage of AzureAIClient with Agent-to-Agent (A2A) capabilities
This sample demonstrates usage of AzureAIProjectAgentProvider with Agent-to-Agent (A2A) capabilities
to enable communication with other agents using the A2A protocol.
Prerequisites:
@@ -26,21 +26,23 @@ async def main() -> None:
"type": "a2a_preview",
"project_connection_id": os.environ["A2A_PROJECT_CONNECTION_ID"],
}
# If the connection is missing a target, we need to set the A2A endpoint URL
if os.environ.get("A2A_ENDPOINT"):
a2a_tool["base_url"] = os.environ["A2A_ENDPOINT"]
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyA2AAgent",
instructions="""You are a helpful assistant that can communicate with other agents.
Use the A2A tool when you need to interact with other agents to complete tasks
or gather information from specialized agents.""",
tools=a2a_tool,
) as agent,
):
)
query = "What can the secondary agent do?"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_azure_ai_search.py
+7 -5
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@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Azure AI Search Example
This sample demonstrates usage of AzureAIClient with Azure AI Search
This sample demonstrates usage of AzureAIProjectAgentProvider with Azure AI Search
to search through indexed data and answer user questions about it.
Prerequisites:
@@ -21,7 +21,9 @@ Prerequisites:
async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MySearchAgent",
instructions="""You are a helpful assistant. You must always provide citations for
answers using the tool and render them as: `[message_idx:search_idx†source]`.""",
@@ -38,8 +40,8 @@ async def main() -> None:
]
},
},
) as agent,
):
)
query = "Tell me about insurance options"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_bing_custom_search.py
+7 -5
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@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Bing Custom Search Example
This sample demonstrates usage of AzureAIClient with Bing Custom Search
This sample demonstrates usage of AzureAIProjectAgentProvider with Bing Custom Search
to search custom search instances and provide responses with relevant results.
Prerequisites:
@@ -21,7 +21,9 @@ Prerequisites:
async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyCustomSearchAgent",
instructions="""You are a helpful agent that can use Bing Custom Search tools to assist users.
Use the available Bing Custom Search tools to answer questions and perform tasks.""",
@@ -36,8 +38,8 @@ async def main() -> None:
]
},
},
) as agent,
):
)
query = "Tell me more about foundry agent service"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_bing_grounding.py
+7 -5
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@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Bing Grounding Example
This sample demonstrates usage of AzureAIClient with Bing Grounding
This sample demonstrates usage of AzureAIProjectAgentProvider with Bing Grounding
to search the web for current information and provide grounded responses.
Prerequisites:
@@ -27,7 +27,9 @@ To get your Bing connection ID:
async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyBingGroundingAgent",
instructions="""You are a helpful assistant that can search the web for current information.
Use the Bing search tool to find up-to-date information and provide accurate, well-sourced answers.
@@ -42,8 +44,8 @@ async def main() -> None:
]
},
},
) as agent,
):
)
query = "What is today's date and weather in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_browser_automation.py
+7 -5
View File
@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Browser Automation Example
This sample demonstrates usage of AzureAIClient with Browser Automation
This sample demonstrates usage of AzureAIProjectAgentProvider with Browser Automation
to perform automated web browsing tasks and provide responses based on web interactions.
Prerequisites:
@@ -21,7 +21,9 @@ Prerequisites:
async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyBrowserAutomationAgent",
instructions="""You are an Agent helping with browser automation tasks.
You can answer questions, provide information, and assist with various tasks
@@ -34,8 +36,8 @@ async def main() -> None:
}
},
},
) as agent,
):
)
query = """Your goal is to report the percent of Microsoft year-to-date stock price change.
To do that, go to the website finance.yahoo.com.
At the top of the page, you will find a search bar.
python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter.py
+8 -6
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@@ -3,7 +3,7 @@
import asyncio
from agent_framework import ChatResponse, HostedCodeInterpreterTool
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
from openai.types.responses.response import Response as OpenAIResponse
from openai.types.responses.response_code_interpreter_tool_call import ResponseCodeInterpreterToolCall
@@ -11,22 +11,24 @@ from openai.types.responses.response_code_interpreter_tool_call import ResponseC
"""
Azure AI Agent Code Interpreter Example
This sample demonstrates using HostedCodeInterpreterTool with AzureAIClient
This sample demonstrates using HostedCodeInterpreterTool with AzureAIProjectAgentProvider
for Python code execution and mathematical problem solving.
"""
async def main() -> None:
"""Example showing how to use the HostedCodeInterpreterTool with AzureAIClient."""
"""Example showing how to use the HostedCodeInterpreterTool with AzureAIProjectAgentProvider."""
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyCodeInterpreterAgent",
instructions="You are a helpful assistant that can write and execute Python code to solve problems.",
tools=HostedCodeInterpreterTool(),
) as agent,
):
)
query = "Use code to get the factorial of 100?"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py
+14 -10
View File
@@ -3,19 +3,19 @@
import asyncio
from agent_framework import (
AgentResponseUpdate,
CitationAnnotation,
HostedCodeInterpreterTool,
HostedFileContent,
TextContent,
)
from agent_framework._agents import AgentResponseUpdate
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI V2 Code Interpreter File Generation Sample
This sample demonstrates how the V2 AzureAIClient handles file annotations
This sample demonstrates how the AzureAIProjectAgentProvider handles file annotations
when code interpreter generates text files. It shows both non-streaming
and streaming approaches to verify file ID extraction.
"""
@@ -32,12 +32,14 @@ async def test_non_streaming() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="V2CodeInterpreterFileAgent",
instructions="You are a helpful assistant that can write and execute Python code to create files.",
tools=HostedCodeInterpreterTool(),
) as agent,
):
)
print(f"User: {QUERY}\n")
result = await agent.run(QUERY)
@@ -66,12 +68,14 @@ async def test_streaming() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="V2CodeInterpreterFileAgentStreaming",
instructions="You are a helpful assistant that can write and execute Python code to create files.",
tools=HostedCodeInterpreterTool(),
) as agent,
):
)
print(f"User: {QUERY}\n")
annotations_found: list[str] = []
text_chunks: list[str] = []
@@ -102,7 +106,7 @@ async def test_streaming() -> None:
async def main() -> None:
print("AzureAIClient Code Interpreter File Generation Test\n")
print("AzureAIProjectAgentProvider Code Interpreter File Generation Test\n")
await test_non_streaming()
await test_streaming()
python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_agent.py
+27 -25
View File
@@ -3,8 +3,7 @@
import asyncio
import os
from agent_framework import ChatAgent
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import PromptAgentDefinition
from azure.identity.aio import AzureCliCredential
@@ -12,19 +11,23 @@ from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Existing Agent Example
This sample demonstrates working with pre-existing Azure AI Agents by providing
agent name and version, showing agent reuse patterns for production scenarios.
This sample demonstrates working with pre-existing Azure AI Agents by using provider.get_agent() method,
showing agent reuse patterns for production scenarios.
"""
async def main() -> None:
async def using_provider_get_agent() -> None:
print("=== Get existing Azure AI agent with provider.get_agent() ===")
# Create the client
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
):
# Create remote agent using SDK directly
azure_ai_agent = await project_client.agents.create_version(
agent_name="MyNewTestAgent",
description="Agent for testing purposes.",
definition=PromptAgentDefinition(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
# Setting specific requirements to verify that this agent is used.
@@ -32,27 +35,22 @@ async def main() -> None:
),
)
chat_client = AzureAIClient(
project_client=project_client,
agent_name=azure_ai_agent.name,
# Property agent_version is required for existing agents.
# If this property is not configured, the client will try to create a new agent using
# provided agent_name.
# It's also possible to leave agent_version empty but set use_latest_version=True.
# This will pull latest available agent version and use that version for operations.
agent_version=azure_ai_agent.version,
)
try:
async with ChatAgent(
chat_client=chat_client,
) as agent:
query = "How are you?"
print(f"User: {query}")
result = await agent.run(query)
# Response that indicates that previously created agent was used:
# "I'm here and ready to help you! How can I assist you today? [END]"
print(f"Agent: {result}\n")
# Get newly created agent as ChatAgent by using provider.get_agent()
provider = AzureAIProjectAgentProvider(project_client=project_client)
agent = await provider.get_agent(name=azure_ai_agent.name)
# Verify agent properties
print(f"Agent ID: {agent.id}")
print(f"Agent name: {agent.name}")
print(f"Agent description: {agent.description}")
query = "How are you?"
print(f"User: {query}")
result = await agent.run(query)
# Response that indicates that previously created agent was used:
# "I'm here and ready to help you! How can I assist you today? [END]"
print(f"Agent: {result}\n")
finally:
# Clean up the agent manually
await project_client.agents.delete_version(
@@ -60,5 +58,9 @@ async def main() -> None:
)
async def main() -> None:
await using_provider_get_agent()
if __name__ == "__main__":
asyncio.run(main())
python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_conversation.py
+24 -23
View File
@@ -4,7 +4,7 @@ import os
from random import randint
from typing import Annotated
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.projects.aio import AIProjectClient
from azure.identity.aio import AzureCliCredential
from pydantic import Field
@@ -12,7 +12,7 @@ from pydantic import Field
"""
Azure AI Agent Existing Conversation Example
This sample demonstrates usage of AzureAIClient with existing conversation created on service side.
This sample demonstrates usage of AzureAIProjectAgentProvider with existing conversation created on service side.
"""
@@ -24,9 +24,9 @@ def get_weather(
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
async def example_with_client() -> None:
"""Example shows how to specify existing conversation ID when initializing Azure AI Client."""
print("=== Azure AI Agent With Existing Conversation and Client ===")
async def example_with_conversation_id() -> None:
"""Example shows how to use existing conversation ID with the provider."""
print("=== Azure AI Agent With Existing Conversation ===")
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
@@ -37,24 +37,23 @@ async def example_with_client() -> None:
conversation_id = conversation.id
print(f"Conversation ID: {conversation_id}")
async with AzureAIClient(
project_client=project_client,
# Specify conversation ID on client level
conversation_id=conversation_id,
).create_agent(
provider = AzureAIProjectAgentProvider(project_client=project_client)
agent = await provider.create_agent(
name="BasicAgent",
instructions="You are a helpful agent.",
tools=get_weather,
) as agent:
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text}\n")
)
query = "What was my last question?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text}\n")
# Pass conversation_id at run level
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query, conversation_id=conversation_id)
print(f"Agent: {result.text}\n")
query = "What was my last question?"
print(f"User: {query}")
result = await agent.run(query, conversation_id=conversation_id)
print(f"Agent: {result.text}\n")
async def example_with_thread() -> None:
@@ -63,12 +62,14 @@ async def example_with_thread() -> None:
async with (
AzureCliCredential() as credential,
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
AzureAIClient(project_client=project_client).create_agent(
):
provider = AzureAIProjectAgentProvider(project_client=project_client)
agent = await provider.create_agent(
name="BasicAgent",
instructions="You are a helpful agent.",
tools=get_weather,
) as agent,
):
)
# Create a conversation using OpenAI client
openai_client = project_client.get_openai_client()
conversation = await openai_client.conversations.create()
@@ -90,7 +91,7 @@ async def example_with_thread() -> None:
async def main() -> None:
await example_with_client()
await example_with_conversation_id()
await example_with_thread()
python/samples/getting_started/agents/azure_ai/azure_ai_with_explicit_settings.py
+11 -12
View File
@@ -5,8 +5,7 @@ import os
from random import randint
from typing import Annotated
from agent_framework import ChatAgent
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
from pydantic import Field
@@ -27,22 +26,22 @@ def get_weather(
async def main() -> None:
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
ChatAgent(
chat_client=AzureAIClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
model_deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
credential=credential,
agent_name="WeatherAgent",
),
AzureAIProjectAgentProvider(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
credential=credential,
) as provider,
):
agent = await provider.create_agent(
name="WeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
)
query = "What's the weather like in New York?"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_file_search.py
+12 -13
View File
@@ -4,8 +4,8 @@ import asyncio
import os
from pathlib import Path
from agent_framework import ChatAgent, HostedFileSearchTool, HostedVectorStoreContent
from agent_framework.azure import AzureAIClient
from agent_framework import HostedFileSearchTool, HostedVectorStoreContent
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.agents.aio import AgentsClient
from azure.ai.agents.models import FileInfo, VectorStore
from azure.identity.aio import AzureCliCredential
@@ -32,7 +32,7 @@ async def main() -> None:
async with (
AzureCliCredential() as credential,
AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
AzureAIClient(credential=credential) as client,
AzureAIProjectAgentProvider(credential=credential) as provider,
):
try:
# 1. Upload file and create vector store
@@ -48,22 +48,21 @@ async def main() -> None:
# 2. Create file search tool with uploaded resources
file_search_tool = HostedFileSearchTool(inputs=[HostedVectorStoreContent(vector_store_id=vector_store.id)])
# 3. Create an agent with file search capabilities
# The tool_resources are automatically extracted from HostedFileSearchTool
async with ChatAgent(
chat_client=client,
# 3. Create an agent with file search capabilities using the provider
agent = await provider.create_agent(
name="EmployeeSearchAgent",
instructions=(
"You are a helpful assistant that can search through uploaded employee files "
"to answer questions about employees."
),
tools=file_search_tool,
) as agent:
# 4. Simulate conversation with the agent
for user_input in USER_INPUTS:
print(f"# User: '{user_input}'")
response = await agent.run(user_input)
print(f"# Agent: {response.text}")
)
# 4. Simulate conversation with the agent
for user_input in USER_INPUTS:
print(f"# User: '{user_input}'")
response = await agent.run(user_input)
print(f"# Agent: {response.text}")
finally:
# 5. Cleanup: Delete the vector store and file in case of earlier failure to prevent orphaned resources.
if vector_store:
python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py
+11 -9
View File
@@ -4,7 +4,7 @@ import asyncio
from typing import Any
from agent_framework import AgentProtocol, AgentResponse, AgentThread, ChatMessage, HostedMCPTool
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
@@ -59,12 +59,13 @@ async def handle_approvals_with_thread(query: str, agent: "AgentProtocol", threa
async def run_hosted_mcp_without_approval() -> None:
"""Example showing MCP Tools without approval."""
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyLearnDocsAgent",
instructions="You are a helpful assistant that can help with Microsoft documentation questions.",
tools=HostedMCPTool(
@@ -72,8 +73,8 @@ async def run_hosted_mcp_without_approval() -> None:
url="https://learn.microsoft.com/api/mcp",
approval_mode="never_require",
),
) as agent,
):
)
query = "How to create an Azure storage account using az cli?"
print(f"User: {query}")
result = await handle_approvals_without_thread(query, agent)
@@ -84,12 +85,13 @@ async def run_hosted_mcp_with_approval_and_thread() -> None:
"""Example showing MCP Tools with approvals using a thread."""
print("=== MCP with approvals and with thread ===")
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyApiSpecsAgent",
instructions="You are a helpful agent that can use MCP tools to assist users.",
tools=HostedMCPTool(
@@ -97,8 +99,8 @@ async def run_hosted_mcp_with_approval_and_thread() -> None:
url="https://gitmcp.io/Azure/azure-rest-api-specs",
approval_mode="always_require",
),
) as agent,
):
)
thread = agent.get_new_thread()
query = "Please summarize the Azure REST API specifications Readme"
print(f"User: {query}")
python/samples/getting_started/agents/azure_ai/azure_ai_with_image_generation.py
+7 -6
View File
@@ -4,13 +4,13 @@ from pathlib import Path
import aiofiles
from agent_framework import DataContent, HostedImageGenerationTool
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Image Generation Example
This sample demonstrates basic usage of AzureAIClient to create an agent
This sample demonstrates basic usage of AzureAIProjectAgentProvider to create an agent
that can generate images based on user requirements.
Pre-requisites:
@@ -20,12 +20,13 @@ Pre-requisites:
async def main() -> None:
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="ImageGenAgent",
instructions="Generate images based on user requirements.",
tools=[
@@ -37,8 +38,8 @@ async def main() -> None:
}
)
],
) as agent,
):
)
query = "Generate an image of Microsoft logo."
print(f"User: {query}")
result = await agent.run(
python/samples/getting_started/agents/azure_ai/azure_ai_with_local_mcp.py
+7 -5
View File
@@ -3,7 +3,7 @@
import asyncio
from agent_framework import MCPStreamableHTTPTool
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
@@ -19,20 +19,22 @@ Pre-requisites:
async def main() -> None:
"""Example showing use of Local MCP Tool with AzureAIClient."""
"""Example showing use of Local MCP Tool with AzureAIProjectAgentProvider."""
print("=== Azure AI Agent with Local MCP Tools Example ===\n")
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="DocsAgent",
instructions="You are a helpful assistant that can help with Microsoft documentation questions.",
tools=MCPStreamableHTTPTool(
name="Microsoft Learn MCP",
url="https://learn.microsoft.com/api/mcp",
),
) as agent,
):
)
# First query
first_query = "How to create an Azure storage account using az cli?"
print(f"User: {first_query}")
python/samples/getting_started/agents/azure_ai/azure_ai_with_memory_search.py
+16 -14
View File
@@ -3,7 +3,7 @@ import asyncio
import os
import uuid
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import MemoryStoreDefaultDefinition, MemoryStoreDefaultOptions
from azure.identity.aio import AzureCliCredential
@@ -11,7 +11,7 @@ from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Memory Search Example
This sample demonstrates usage of AzureAIClient with memory search capabilities
This sample demonstrates usage of AzureAIProjectAgentProvider with memory search capabilities
to retrieve relevant past user messages and maintain conversation context across sessions.
It shows explicit memory store creation using Azure AI Projects client and agent creation
using the Agent Framework.
@@ -46,18 +46,20 @@ async def main() -> None:
)
print(f"Created memory store: {memory_store.name} ({memory_store.id}): {memory_store.description}")
# Then, create the agent using Agent Framework
async with AzureAIClient(credential=credential).create_agent(
name="MyMemoryAgent",
instructions="""You are a helpful assistant that remembers past conversations.
Use the memory search tool to recall relevant information from previous interactions.""",
tools={
"type": "memory_search",
"memory_store_name": memory_store.name,
"scope": "user_123",
"update_delay": 1, # Wait 1 second before updating memories (use higher value in production)
},
) as agent:
# Then, create the agent using Agent Framework provider
async with AzureAIProjectAgentProvider(credential=credential) as provider:
agent = await provider.create_agent(
name="MyMemoryAgent",
instructions="""You are a helpful assistant that remembers past conversations.
Use the memory search tool to recall relevant information from previous interactions.""",
tools={
"type": "memory_search",
"memory_store_name": memory_store.name,
"scope": "user_123",
"update_delay": 1, # Wait 1 second before updating memories (use higher value in production)
},
)
# First interaction - establish some preferences
print("=== First conversation ===")
query1 = "I prefer dark roast coffee"
python/samples/getting_started/agents/azure_ai/azure_ai_with_microsoft_fabric.py
+7 -5
View File
@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with Microsoft Fabric Example
This sample demonstrates usage of AzureAIClient with Microsoft Fabric
This sample demonstrates usage of AzureAIProjectAgentProvider with Microsoft Fabric
to query Fabric data sources and provide responses based on data analysis.
Prerequisites:
@@ -21,7 +21,9 @@ Prerequisites:
async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyFabricAgent",
instructions="You are a helpful assistant.",
tools={
@@ -34,8 +36,8 @@ async def main() -> None:
]
},
},
) as agent,
):
)
query = "Tell me about sales records"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_openapi.py
+7 -5
View File
@@ -4,13 +4,13 @@ import json
from pathlib import Path
import aiofiles
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with OpenAPI Tool Example
This sample demonstrates usage of AzureAIClient with OpenAPI tools
This sample demonstrates usage of AzureAIProjectAgentProvider with OpenAPI tools
to call external APIs defined by OpenAPI specifications.
Prerequisites:
@@ -29,7 +29,9 @@ async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MyOpenAPIAgent",
instructions="""You are a helpful assistant that can use country APIs to provide information.
Use the available OpenAPI tools to answer questions about countries, currencies, and demographics.""",
@@ -42,8 +44,8 @@ async def main() -> None:
"auth": {"type": "anonymous"},
},
},
) as agent,
):
)
query = "What is the name and population of the country that uses currency with abbreviation THB?"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py
+9 -10
View File
@@ -2,14 +2,14 @@
import asyncio
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
from pydantic import BaseModel, ConfigDict
"""
Azure AI Agent Response Format Example
This sample demonstrates basic usage of AzureAIClient with response format,
This sample demonstrates basic usage of AzureAIProjectAgentProvider with response format,
also known as structured outputs.
"""
@@ -24,24 +24,23 @@ class ReleaseBrief(BaseModel):
async def main() -> None:
"""Example of using response_format property."""
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="ProductMarketerAgent",
instructions="Return launch briefs as structured JSON.",
) as agent,
):
query = "Draft a launch brief for the Contoso Note app."
print(f"User: {query}")
result = await agent.run(
query,
# Specify type to use as response
response_format=ReleaseBrief,
)
query = "Draft a launch brief for the Contoso Note app."
print(f"User: {query}")
result = await agent.run(query)
if isinstance(result.value, ReleaseBrief):
release_brief = result.value
print("Agent:")
python/samples/getting_started/agents/azure_ai/azure_ai_with_runtime_json_schema.py
+18 -21
View File
@@ -2,13 +2,13 @@
import asyncio
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent Response Format Example with Runtime JSON Schema
This sample demonstrates basic usage of AzureAIClient with response format,
This sample demonstrates basic usage of AzureAIProjectAgentProvider with response format,
also known as structured outputs.
"""
@@ -29,35 +29,32 @@ runtime_schema = {
async def main() -> None:
"""Example of using response_format property."""
"""Example of using response_format property with a runtime JSON schema."""
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
name="ProductMarketerAgent",
instructions="Return launch briefs as structured JSON.",
) as agent,
AzureAIProjectAgentProvider(credential=credential) as provider,
):
query = "Draft a launch brief for the Contoso Note app."
print(f"User: {query}")
result = await agent.run(
query,
# Specify type to use as response
options={
"response_format": {
"type": "json_schema",
"json_schema": {
"name": runtime_schema["title"],
"strict": True,
"schema": runtime_schema,
},
# Pass response_format at agent creation time using dict schema format
agent = await provider.create_agent(
name="WeatherDigestAgent",
instructions="Return sample weather digest as structured JSON.",
response_format={
"type": "json_schema",
"json_schema": {
"name": runtime_schema["title"],
"strict": True,
"schema": runtime_schema,
},
},
)
query = "Draft a sample weather digest."
print(f"User: {query}")
result = await agent.run(query)
print(result.text)
python/samples/getting_started/agents/azure_ai/azure_ai_with_sharepoint.py
+7 -5
View File
@@ -2,13 +2,13 @@
import asyncio
import os
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent with SharePoint Example
This sample demonstrates usage of AzureAIClient with SharePoint
This sample demonstrates usage of AzureAIProjectAgentProvider with SharePoint
to search through SharePoint content and answer user questions about it.
Prerequisites:
@@ -21,7 +21,9 @@ Prerequisites:
async def main() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="MySharePointAgent",
instructions="""You are a helpful agent that can use SharePoint tools to assist users.
Use the available SharePoint tools to answer questions and perform tasks.""",
@@ -35,8 +37,8 @@ async def main() -> None:
]
},
},
) as agent,
):
)
query = "What is Contoso whistleblower policy?"
print(f"User: {query}")
result = await agent.run(query)
python/samples/getting_started/agents/azure_ai/azure_ai_with_thread.py
+30 -24
View File
@@ -4,7 +4,7 @@ import asyncio
from random import randint
from typing import Annotated
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
from pydantic import Field
@@ -30,12 +30,14 @@ async def example_with_automatic_thread_creation() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
)
# First conversation - no thread provided, will be created automatically
query1 = "What's the weather like in Seattle?"
print(f"User: {query1}")
@@ -59,12 +61,14 @@ async def example_with_thread_persistence_in_memory() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
)
# Create a new thread that will be reused
thread = agent.get_new_thread()
@@ -100,12 +104,14 @@ async def example_with_existing_thread_id() -> None:
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
)
# Start a conversation and get the thread ID
thread = agent.get_new_thread()
@@ -121,21 +127,21 @@ async def example_with_existing_thread_id() -> None:
if existing_thread_id:
print("\n--- Continuing with the same thread ID in a new agent instance ---")
async with (
AzureAIClient(credential=credential).create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
) as agent,
):
# Create a thread with the existing ID
thread = agent.get_new_thread(service_thread_id=existing_thread_id)
# Create a new agent instance from the same provider
agent2 = await provider.create_agent(
name="BasicWeatherAgent",
instructions="You are a helpful weather agent.",
tools=get_weather,
)
query2 = "What was the last city I asked about?"
print(f"User: {query2}")
result2 = await agent.run(query2, thread=thread)
print(f"Agent: {result2.text}")
print("Note: The agent continues the conversation from the previous thread by using thread ID.\n")
# Create a thread with the existing ID
thread = agent2.get_new_thread(service_thread_id=existing_thread_id)
query2 = "What was the last city I asked about?"
print(f"User: {query2}")
result2 = await agent2.run(query2, thread=thread)
print(f"Agent: {result2.text}")
print("Note: The agent continues the conversation from the previous thread by using thread ID.\n")
async def main() -> None:
python/samples/getting_started/agents/azure_ai/azure_ai_with_web_search.py
+7 -6
View File
@@ -3,13 +3,13 @@
import asyncio
from agent_framework import HostedWebSearchTool
from agent_framework.azure import AzureAIClient
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.identity.aio import AzureCliCredential
"""
Azure AI Agent With Web Search
This sample demonstrates basic usage of AzureAIClient to create an agent
This sample demonstrates basic usage of AzureAIProjectAgentProvider to create an agent
that can perform web searches using the HostedWebSearchTool.
Pre-requisites:
@@ -19,17 +19,18 @@ Pre-requisites:
async def main() -> None:
# Since no Agent ID is provided, the agent will be automatically created.
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
async with (
AzureCliCredential() as credential,
AzureAIClient(credential=credential).create_agent(
AzureAIProjectAgentProvider(credential=credential) as provider,
):
agent = await provider.create_agent(
name="WebsearchAgent",
instructions="You are a helpful assistant that can search the web",
tools=[HostedWebSearchTool()],
) as agent,
):
)
query = "What's the weather today in Seattle?"
print(f"User: {query}")
result = await agent.run(query)