The OpenAI Agents SDK provides a powerful framework for building intelligent AI assistants with specialised capabilities. In this blog post, I'll demonstrate how to integrate Azure OpenAI Service and...
great share hieunhu! hopefully, agents sdk will soon imports AsyncAzureOpenAI module. I did a streamlit demo using Agents SDK + Azure AI Agents and it's phenomenal!! :)
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The OpenAI Agents SDK provides a powerful framework for building intelligent AI assistants with specialised capabilities. In this blog post, I'll demonstrate how to integrate Azure OpenAI Service and...","body@stringLength":"13858","rawBody":"
The OpenAI Agents SDK provides a powerful framework for building intelligent AI assistants with specialised capabilities. In this blog post, I'll demonstrate how to integrate Azure OpenAI Service and Azure API Management (APIM) with the OpenAI Agents SDK to create a banking assistant system with specialised agents.
\n
Key Takeaways:\n
\n
Learn how to connect the OpenAI Agents SDK to Azure OpenAI Service
\n
Understand the differences between direct Azure OpenAI integration and using Azure API Management
\n
Implement tracing with the OpenAI Agents SDK for monitoring and debugging
\n
Create a practical banking application with specialized agents and handoff capabilities
\n
\n
\n
The OpenAI Agents SDK
\n
The OpenAI Agents SDK is a powerful toolkit that enables developers to create AI agents with specialised capabilities, tools, and the ability to work together through handoffs. It's designed to work seamlessly with OpenAI's models, but can be integrated with Azure services for enterprise-grade deployments.
\n
Setting Up Your Environment
\n
To get started with the OpenAI Agents SDK and Azure, you'll need to install the necessary packages:
\n
pip install openai openai-agents python-dotenv
\n
You'll also need to set up your environment variables. Create a `.env` file with your Azure OpenAI or APIM credentials:
\n
For Direct Azure OpenAI Connection:
\n
\n# .env file for Azure OpenAI\nAZURE_OPENAI_API_KEY=your_api_key\nAZURE_OPENAI_API_VERSION=2024-08-01-preview\nAZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/\nAZURE_OPENAI_DEPLOYMENT=your-deployment-name\n
For Azure API Management (APIM) Connection:
\n
\n# .env file for Azure APIM\nAZURE_APIM_OPENAI_SUBSCRIPTION_KEY=your_subscription_key\nAZURE_APIM_OPENAI_API_VERSION=2024-08-01-preview\nAZURE_APIM_OPENAI_ENDPOINT=https://your-apim-name.azure-api.net/\nAZURE_APIM_OPENAI_DEPLOYMENT=your-deployment-name\n
\n
Connecting to Azure OpenAI Service
\n
The OpenAI Agents SDK can be integrated with Azure OpenAI Service in two ways: direct connection or through Azure API Management (APIM).
\n
Option 1: Direct Azure OpenAI Connection
\n
\nfrom openai import AsyncAzureOpenAI\nfrom agents import set_default_openai_client\nfrom dotenv import load_dotenv\nimport os\n\n# Load environment variables\nload_dotenv()\n\n# Create OpenAI client using Azure OpenAI\nopenai_client = AsyncAzureOpenAI(\n api_key=os.getenv(\"AZURE_OPENAI_API_KEY\"),\n api_version=os.getenv(\"AZURE_OPENAI_API_VERSION\"),\n azure_endpoint=os.getenv(\"AZURE_OPENAI_ENDPOINT\"),\n azure_deployment=os.getenv(\"AZURE_OPENAI_DEPLOYMENT\")\n)\n\n# Set the default OpenAI client for the Agents SDK\nset_default_openai_client(openai_client)\n
\n
Option 2: Azure API Management (APIM) Connection
\nfrom openai import AsyncAzureOpenAI\nfrom agents import set_default_openai_client\nfrom dotenv import load_dotenv\nimport os\n\n# Load environment variables\nload_dotenv()\n\n# Create OpenAI client using Azure APIM\nopenai_client = AsyncAzureOpenAI(\n api_key=os.getenv(\"AZURE_APIM_OPENAI_SUBSCRIPTION_KEY\"), # Note: Using subscription key\n api_version=os.getenv(\"AZURE_APIM_OPENAI_API_VERSION\"),\n azure_endpoint=os.getenv(\"AZURE_APIM_OPENAI_ENDPOINT\"),\n azure_deployment=os.getenv(\"AZURE_APIM_OPENAI_DEPLOYMENT\")\n)\n\n# Set the default OpenAI client for the Agents SDK\nset_default_openai_client(openai_client)\n
\n
\n
Key Difference: When using Azure API Management, you use a subscription key instead of an API key. This provides an additional layer of management, security, and monitoring for your OpenAI API access.
\n
\n
Creating Agents with the OpenAI Agents SDK
\n
Once you've set up your Azure OpenAI or APIM connection, you can create agents using the OpenAI Agents SDK:
\n
\nfrom agents import Agent\nfrom openai.types.chat import ChatCompletionMessageParam\n\n# Create a banking assistant agent\nbanking_assistant = Agent(\n name=\"Banking Assistant\",\n instructions=\"You are a helpful banking assistant. Be concise and professional.\",\n model=\"gpt-4o\", # This will use the deployment specified in your Azure OpenAI/APIM client\n tools=[check_account_balance] # A function tool defined elsewhere\n)\n
\n
The OpenAI Agents SDK automatically uses the Azure OpenAI or APIM client you've configured, making it seamless to switch between different Azure environments or configurations.
\n
Implementing Tracing with Azure OpenAI
\n
The OpenAI Agents SDK includes powerful tracing capabilities that can help you monitor and debug your agents. When using Azure OpenAI or APIM, you can implement two types of tracing:
\n
\n\n
1. Console Tracing for Development
\n
Console logging is rather verbose, if you would like to explore the Spans then enable do it like below:
Tracing is particularly valuable when working with Azure deployments, as it helps you monitor usage, performance, and behavior across different environments.
\n
Note that at the time of writing this article, there is a ongoing bug where OpenAI Agent SDK is fetching the old input_tokens, output_tokens instead of the new prompt_tokens & completion_tokens returned by newer ChatCompletion APIs.
To run your agents with Azure OpenAI or APIM, use the Runner class from the OpenAI Agents SDK:
\n
\nfrom agents import Runner\nimport asyncio\n\nasync def main():\n # Run the banking assistant\n result = await Runner.run(\n banking_assistant, \n input=\"Hi, I'd like to check my account balance.\"\n )\n \n print(f\"Response: {result.response.content}\")\n\nif __name__ == \"__main__\":\n asyncio.run(main())\n
\n
Practical Example: Banking Agents System
\n
Let's look at how we can use Azure OpenAI or APIM with the OpenAI Agents SDK to create a banking system with specialized agents and handoff capabilities.
\n
1. Define Specialized Banking Agents
\n
We'll create several specialized agents:
\n
\n
General Banking Assistant: Handles basic inquiries and account information
\n
Loan Specialist: Focuses on loan options and payment calculations
\n
Investment Specialist: Provides guidance on investment options
\n
Customer Service Agent: Routes inquiries to specialists
\n
\n
2. Implement Handoff Between Agents
\n
\nfrom agents import handoff, HandoffInputData\nfrom agents.extensions import handoff_filters\n\n# Define a filter for handoff messages\ndef banking_handoff_message_filter(handoff_message_data: HandoffInputData) -> HandoffInputData:\n # Remove any tool-related messages from the message history\n handoff_message_data = handoff_filters.remove_all_tools(handoff_message_data)\n return handoff_message_data\n\n# Create customer service agent with handoffs\ncustomer_service_agent = Agent(\n name=\"Customer Service Agent\",\n instructions=\"\"\"You are a customer service agent at a bank.\n Help customers with general inquiries and direct them to specialists when needed.\n If the customer asks about loans or mortgages, handoff to the Loan Specialist.\n If the customer asks about investments or portfolio management, handoff to the Investment Specialist.\"\"\",\n handoffs=[\n handoff(loan_specialist_agent, input_filter=banking_handoff_message_filter),\n handoff(investment_specialist_agent, input_filter=banking_handoff_message_filter),\n ],\n tools=[check_account_balance],\n)\n
\n
\n
3. Trace the Conversation Flow
\n
\nfrom agents import trace\n\nasync def main():\n # Trace the entire run as a single workflow\n with trace(workflow_name=\"Banking Assistant Demo\"):\n # Run the customer service agent\n result = await Runner.run(\n customer_service_agent,\n input=\"I'm interested in taking out a mortgage loan. Can you help me understand my options?\"\n )\n \n print(f\"Response: {result.response.content}\")\n\nif __name__ == \"__main__\":\n asyncio.run(main())\n
\n
Benefits of Using Azure OpenAI/APIM with the OpenAI Agents SDK
\n
Integrating Azure OpenAI or APIM with the OpenAI Agents SDK offers several advantages:
The OpenAI Agents SDK combined with Azure OpenAI Service or Azure API Management provides a powerful foundation for building intelligent, specialized AI assistants. By leveraging Azure's enterprise features and the OpenAI Agents SDK's capabilities, you can create robust, scalable, and secure AI applications for production environments.
\n
Whether you choose direct Azure OpenAI integration or Azure API Management depends on your specific needs for API management, security, and monitoring. Both approaches work seamlessly with the OpenAI Agents SDK, making it easy to build sophisticated agent-based applications.
","kudosSumWeight":6,"postTime":"2025-03-12T12:10:02.140-07:00","images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkyNTM3LTM5MFh0TQ?revision=9\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkyNTM3LWl5eVJpNw?revision=9\"}"}}],"totalCount":2,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"attachments":{"__typename":"AttachmentConnection","pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null},"edges":[]},"tags":{"__typename":"TagConnection","pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null},"edges":[{"__typename":"TagEdge","cursor":"MjUuMXwyLjF8b3wxMHxfTlZffDE","node":{"__typename":"Tag","id":"tag:azure ai services","text":"azure ai services","time":"2017-08-22T12:28:03.122-07:00","lastActivityTime":null,"messagesCount":null,"followersCount":null}},{"__typename":"TagEdge","cursor":"MjUuMXwyLjF8b3wxMHxfTlZffDI","node":{"__typename":"Tag","id":"tag:azure openai service","text":"azure openai service","time":"2022-12-14T08:49:09.396-08:00","lastActivityTime":null,"messagesCount":null,"followersCount":null}}]},"timeToRead":5,"rawTeaser":"","introduction":"","coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""},"currentRevision":{"__ref":"Revision:revision:4392537_9"},"latestVersion":{"__typename":"FriendlyVersion","major":"9","minor":"0"},"metrics":{"__typename":"MessageMetrics","views":7548},"visibilityScope":"PUBLIC","canonicalUrl":"","seoTitle":"","seoDescription":null,"placeholder":false,"originalMessageForPlaceholder":null,"contributors":{"__typename":"UserConnection","edges":[]},"nonCoAuthorContributors":{"__typename":"UserConnection","edges":[]},"coAuthors":{"__typename":"UserConnection","edges":[]},"blogMessagePolicies":{"__typename":"BlogMessagePolicies","canDoAuthoringActionsOnBlog":{"__typename":"PolicyResult","failureReason":{"__typename":"FailureReason","message":"error.lithium.policies.blog.action_can_do_authoring_action.accessDenied","key":"error.lithium.policies.blog.action_can_do_authoring_action.accessDenied","args":[]}}},"archivalData":null,"customFields":[],"revisions({\"constraints\":{\"isPublished\":{\"eq\":true}},\"first\":1})":{"__typename":"RevisionConnection","totalCount":9},"body":"
The OpenAI Agents SDK provides a powerful framework for building intelligent AI assistants with specialised capabilities. In this blog post, I'll demonstrate how to integrate Azure OpenAI Service and Azure API Management (APIM) with the OpenAI Agents SDK to create a banking assistant system with specialised agents.
\n
Key Takeaways:\n
\n
Learn how to connect the OpenAI Agents SDK to Azure OpenAI Service
\n
Understand the differences between direct Azure OpenAI integration and using Azure API Management
\n
Implement tracing with the OpenAI Agents SDK for monitoring and debugging
\n
Create a practical banking application with specialized agents and handoff capabilities
\n
\n
\n
The OpenAI Agents SDK
\n
The OpenAI Agents SDK is a powerful toolkit that enables developers to create AI agents with specialised capabilities, tools, and the ability to work together through handoffs. It's designed to work seamlessly with OpenAI's models, but can be integrated with Azure services for enterprise-grade deployments.
\n
Setting Up Your Environment
\n
To get started with the OpenAI Agents SDK and Azure, you'll need to install the necessary packages:
\n
pip install openai openai-agents python-dotenv
\n
You'll also need to set up your environment variables. Create a `.env` file with your Azure OpenAI or APIM credentials:
\n
For Direct Azure OpenAI Connection:
\n
\n
# .env file for Azure OpenAI\nAZURE_OPENAI_API_KEY=your_api_key\nAZURE_OPENAI_API_VERSION=2024-08-01-preview\nAZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/\nAZURE_OPENAI_DEPLOYMENT=your-deployment-name
\n
For Azure API Management (APIM) Connection:
\n
\n
# .env file for Azure APIM\nAZURE_APIM_OPENAI_SUBSCRIPTION_KEY=your_subscription_key\nAZURE_APIM_OPENAI_API_VERSION=2024-08-01-preview\nAZURE_APIM_OPENAI_ENDPOINT=https://your-apim-name.azure-api.net/\nAZURE_APIM_OPENAI_DEPLOYMENT=your-deployment-name
\n
\n
Connecting to Azure OpenAI Service
\n
The OpenAI Agents SDK can be integrated with Azure OpenAI Service in two ways: direct connection or through Azure API Management (APIM).
\n
Option 1: Direct Azure OpenAI Connection
\n
\n
from openai import AsyncAzureOpenAI\nfrom agents import set_default_openai_client\nfrom dotenv import load_dotenv\nimport os\n\n# Load environment variables\nload_dotenv()\n\n# Create OpenAI client using Azure OpenAI\nopenai_client = AsyncAzureOpenAI(\n api_key=os.getenv(\"AZURE_OPENAI_API_KEY\"),\n api_version=os.getenv(\"AZURE_OPENAI_API_VERSION\"),\n azure_endpoint=os.getenv(\"AZURE_OPENAI_ENDPOINT\"),\n azure_deployment=os.getenv(\"AZURE_OPENAI_DEPLOYMENT\")\n)\n\n# Set the default OpenAI client for the Agents SDK\nset_default_openai_client(openai_client)
\n
\n
Option 2: Azure API Management (APIM) Connection
\n
from openai import AsyncAzureOpenAI\nfrom agents import set_default_openai_client\nfrom dotenv import load_dotenv\nimport os\n\n# Load environment variables\nload_dotenv()\n\n# Create OpenAI client using Azure APIM\nopenai_client = AsyncAzureOpenAI(\n api_key=os.getenv(\"AZURE_APIM_OPENAI_SUBSCRIPTION_KEY\"), # Note: Using subscription key\n api_version=os.getenv(\"AZURE_APIM_OPENAI_API_VERSION\"),\n azure_endpoint=os.getenv(\"AZURE_APIM_OPENAI_ENDPOINT\"),\n azure_deployment=os.getenv(\"AZURE_APIM_OPENAI_DEPLOYMENT\")\n)\n\n# Set the default OpenAI client for the Agents SDK\nset_default_openai_client(openai_client)
\n
\n
\n
Key Difference: When using Azure API Management, you use a subscription key instead of an API key. This provides an additional layer of management, security, and monitoring for your OpenAI API access.
\n
\n
Creating Agents with the OpenAI Agents SDK
\n
Once you've set up your Azure OpenAI or APIM connection, you can create agents using the OpenAI Agents SDK:
\n
\n
from agents import Agent\nfrom openai.types.chat import ChatCompletionMessageParam\n\n# Create a banking assistant agent\nbanking_assistant = Agent(\n name=\"Banking Assistant\",\n instructions=\"You are a helpful banking assistant. Be concise and professional.\",\n model=\"gpt-4o\", # This will use the deployment specified in your Azure OpenAI/APIM client\n tools=[check_account_balance] # A function tool defined elsewhere\n)
\n
\n
The OpenAI Agents SDK automatically uses the Azure OpenAI or APIM client you've configured, making it seamless to switch between different Azure environments or configurations.
\n
Implementing Tracing with Azure OpenAI
\n
The OpenAI Agents SDK includes powerful tracing capabilities that can help you monitor and debug your agents. When using Azure OpenAI or APIM, you can implement two types of tracing:
\n
\n\n
1. Console Tracing for Development
\n
Console logging is rather verbose, if you would like to explore the Spans then enable do it like below:
\n
from agents import Agent, HandoffInputData, Runner, function_tool, handoff, trace, set_default_openai_client, set_tracing_disabled, OpenAIChatCompletionsModel, set_tracing_export_api_key, add_trace_processor\nfrom agents.tracing.processors import ConsoleSpanExporter, BatchTraceProcessor\n\n# Set up console tracing\nconsole_exporter = ConsoleSpanExporter()\nconsole_processor = BatchTraceProcessor(exporter=console_exporter)\nadd_trace_processor(console_processor)
Tracing is particularly valuable when working with Azure deployments, as it helps you monitor usage, performance, and behavior across different environments.
\n
Note that at the time of writing this article, there is a ongoing bug where OpenAI Agent SDK is fetching the old input_tokens, output_tokens instead of the new prompt_tokens & completion_tokens returned by newer ChatCompletion APIs.
To run your agents with Azure OpenAI or APIM, use the Runner class from the OpenAI Agents SDK:
\n
\n
from agents import Runner\nimport asyncio\n\nasync def main():\n # Run the banking assistant\n result = await Runner.run(\n banking_assistant, \n input=\"Hi, I'd like to check my account balance.\"\n )\n \n print(f\"Response: {result.response.content}\")\n\nif __name__ == \"__main__\":\n asyncio.run(main())
\n
\n
Practical Example: Banking Agents System
\n
Let's look at how we can use Azure OpenAI or APIM with the OpenAI Agents SDK to create a banking system with specialized agents and handoff capabilities.
\n
1. Define Specialized Banking Agents
\n
We'll create several specialized agents:
\n
\n
General Banking Assistant: Handles basic inquiries and account information
\n
Loan Specialist: Focuses on loan options and payment calculations
\n
Investment Specialist: Provides guidance on investment options
\n
Customer Service Agent: Routes inquiries to specialists
\n
\n
2. Implement Handoff Between Agents
\n
\n
from agents import handoff, HandoffInputData\nfrom agents.extensions import handoff_filters\n\n# Define a filter for handoff messages\ndef banking_handoff_message_filter(handoff_message_data: HandoffInputData) -> HandoffInputData:\n # Remove any tool-related messages from the message history\n handoff_message_data = handoff_filters.remove_all_tools(handoff_message_data)\n return handoff_message_data\n\n# Create customer service agent with handoffs\ncustomer_service_agent = Agent(\n name=\"Customer Service Agent\",\n instructions=\"\"\"You are a customer service agent at a bank.\n Help customers with general inquiries and direct them to specialists when needed.\n If the customer asks about loans or mortgages, handoff to the Loan Specialist.\n If the customer asks about investments or portfolio management, handoff to the Investment Specialist.\"\"\",\n handoffs=[\n handoff(loan_specialist_agent, input_filter=banking_handoff_message_filter),\n handoff(investment_specialist_agent, input_filter=banking_handoff_message_filter),\n ],\n tools=[check_account_balance],\n)
\n
\n
\n
3. Trace the Conversation Flow
\n
\n
from agents import trace\n\nasync def main():\n # Trace the entire run as a single workflow\n with trace(workflow_name=\"Banking Assistant Demo\"):\n # Run the customer service agent\n result = await Runner.run(\n customer_service_agent,\n input=\"I'm interested in taking out a mortgage loan. Can you help me understand my options?\"\n )\n \n print(f\"Response: {result.response.content}\")\n\nif __name__ == \"__main__\":\n asyncio.run(main())
\n
\n
Benefits of Using Azure OpenAI/APIM with the OpenAI Agents SDK
\n
Integrating Azure OpenAI or APIM with the OpenAI Agents SDK offers several advantages:
The OpenAI Agents SDK combined with Azure OpenAI Service or Azure API Management provides a powerful foundation for building intelligent, specialized AI assistants. By leveraging Azure's enterprise features and the OpenAI Agents SDK's capabilities, you can create robust, scalable, and secure AI applications for production environments.
\n
Whether you choose direct Azure OpenAI integration or Azure API Management depends on your specific needs for API management, security, and monitoring. Both approaches work seamlessly with the OpenAI Agents SDK, making it easy to build sophisticated agent-based applications.
"},"Conversation:conversation:4392537":{"__typename":"Conversation","id":"conversation:4392537","solved":false,"topic":{"__ref":"BlogTopicMessage:message:4392537"},"lastPostingActivityTime":"2025-05-03T20:50:37.332-07:00","lastPostTime":"2025-05-03T20:50:37.332-07:00","unreadReplyCount":12,"isSubscribed":false},"ModerationData:moderation_data:4392537":{"__typename":"ModerationData","id":"moderation_data:4392537","status":"APPROVED","rejectReason":null,"isReportedAbuse":false,"rejectUser":null,"rejectTime":null,"rejectActorType":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkyNTM3LTM5MFh0TQ?revision=9\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkyNTM3LTM5MFh0TQ?revision=9","title":"image.png","associationType":"BODY","width":1986,"height":1700,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkyNTM3LWl5eVJpNw?revision=9\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkyNTM3LWl5eVJpNw?revision=9","title":"clipboard_image-1-1742199564240.png","associationType":"BODY","width":750,"height":331,"altText":""},"Revision:revision:4392537_9":{"__typename":"Revision","id":"revision:4392537_9","lastEditTime":"2025-03-17T01:19:42.741-07:00"},"BlogReplyMessage:message:4392624":{"__typename":"BlogReplyMessage","id":"message:4392624","conversation":{"__ref":"Conversation:conversation:4392537"},"author":{"__ref":"User:user:2618628"},"revisionNum":1,"uid":4392624,"depth":1,"hasGivenKudo":false,"subscribed":false,"board":{"__ref":"Blog:board:Azure-AI-Services-blog"},"subject":"Re: Use Azure OpenAI and APIM with the OpenAI Agents SDK","readOnly":false,"editFrozen":false,"moderationData":{"__ref":"ModerationData:moderation_data:4392624"},"parent":{"__ref":"BlogTopicMessage:message:4392537"},"body":"
great share hieunhu! hopefully, agents sdk will soon imports AsyncAzureOpenAI module. I did a streamlit demo using Agents SDK + Azure AI Agents and it's phenomenal!! :)
","body@stringLength":"364","rawBody":"
great share ! hopefully, agents sdk will soon imports AsyncAzureOpenAI module. I did a streamlit demo using Agents SDK + Azure AI Agents and it's phenomenal!! :)
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Microsoft
