Azure · dargilco · Dec 5, 2025 · Dec 4, 2025 · Dec 4, 2025 · Dec 4, 2025
@@ -65,9 +65,6 @@ AZURE_AI_PROJECTS_TESTS_AI_SEARCH_PROJECT_CONNECTION_ID=
 AZURE_AI_PROJECTS_TESTS_AI_SEARCH_INDEX_NAME=
 AZURE_AI_PROJECTS_TESTS_MCP_PROJECT_CONNECTION_ID=
 
-# Used in Image generation agent tools tests
-AZURE_AI_PROJECTS_TESTS_IMAGE_MODEL_DEPLOYMENT_NAME=
-
 # Used in Fine-tuning tests
 AZURE_AI_PROJECTS_TESTS_COMPLETED_OAI_MODEL_SFT_FINE_TUNING_JOB_ID=
 AZURE_AI_PROJECTS_TESTS_COMPLETED_OAI_MODEL_RFT_FINE_TUNING_JOB_ID=

@@ -259,7 +259,7 @@ Generate images based on text prompts with customizable resolution, quality, and
 <!-- SNIPPET:sample_agent_image_generation.tool_declaration -->
 
 ```python
-tool = ImageGenTool(quality="low", size="1024x1024")
+tool = ImageGenTool(model="gpt-image-1-mini", quality="low", size="1024x1024")  # type: ignore
 ```
 
 <!-- END SNIPPET -->

@@ -2,5 +2,5 @@
   "AssetsRepo": "Azure/azure-sdk-assets",
   "AssetsRepoPrefixPath": "python",
   "TagPrefix": "python/ai/azure-ai-projects",
-  "Tag": "python/ai/azure-ai-projects_9e7a9707f6"
+  "Tag": "python/ai/azure-ai-projects_3c34f28cdc"
 }
@@ -31,9 +31,10 @@
        used by the agent for understanding and responding to prompts. This is NOT the image generation model.
 
     NOTE:
-    - Image generation requires a separate "gpt-image-1" deployment which is specified in the
-      x-ms-oai-image-generation-deployment header when creating the response.
-    - AZURE_AI_MODEL_DEPLOYMENT_NAME should be set to your chat model (e.g., gpt-4o), NOT "gpt-image-1".
+    - Image generation requires a separate "gpt-image-1-mini" deployment which is specified when constructing
+      the `ImageGenTool`, as well as providing it in the `x-ms-oai-image-generation-deployment` header when
+      calling `.responses.create`.
+    - AZURE_AI_MODEL_DEPLOYMENT_NAME should be set to your chat model (e.g., gpt-4o), NOT "gpt-image-1-mini".
     - The generated image will be saved as "microsoft.png" in the current directory.
 """
 
@@ -56,7 +57,7 @@
 ):
 
     # [START tool_declaration]
-    tool = ImageGenTool(quality="low", size="1024x1024")
+    tool = ImageGenTool(model="gpt-image-1-mini", quality="low", size="1024x1024")  # type: ignore
     # [END tool_declaration]
 
     agent = project_client.agents.create_version(
@@ -73,7 +74,7 @@
     response = openai_client.responses.create(
         input="Generate an image of Microsoft logo.",
         extra_headers={
-            "x-ms-oai-image-generation-deployment": "gpt-image-1"
+            "x-ms-oai-image-generation-deployment": "gpt-image-1-mini"
         },  # this is required at the moment for image generation
         extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
     )

@@ -30,8 +30,11 @@
        the "Models + endpoints" tab in your Microsoft Foundry project.
 
     NOTE:
-    - Image generation must have "gpt-image-1" deployment specified in the header when creating response at this moment
-    - The generated image will be saved as "microsoft.png" in the current directory
+    - Image generation requires a separate "gpt-image-1-mini" deployment which is specified when constructing
+      the `ImageGenTool`, as well as providing it in the `x-ms-oai-image-generation-deployment` header when
+      calling `.responses.create`.
+    - AZURE_AI_MODEL_DEPLOYMENT_NAME should be set to your chat model (e.g., gpt-4o), NOT "gpt-image-1-mini".
+    - The generated image will be saved as "microsoft.png" in the current directory.
 """
 
 import asyncio
@@ -58,7 +61,7 @@ async def main():
             definition=PromptAgentDefinition(
                 model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
                 instructions="Generate images based on user prompts",
-                tools=[ImageGenTool(quality="low", size="1024x1024")],
+                tools=[ImageGenTool(model="gpt-image-1-mini", quality="low", size="1024x1024")],  # type: ignore
             ),
             description="Agent for image generation.",
         )
@@ -67,7 +70,7 @@ async def main():
         response = await openai_client.responses.create(
             input="Generate an image of Microsoft logo.",
             extra_headers={
-                "x-ms-oai-image-generation-deployment": "gpt-image-1"
+                "x-ms-oai-image-generation-deployment": "gpt-image-1-mini"
             },  # this is required at the moment for image generation
             extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
         )

@@ -13,6 +13,8 @@
 
 class TestAgentCrud(TestBase):
 
+    # To run this test:
+    # pytest tests\agents\test_agents_crud.py::TestAgentCrud::test_agents_crud -s
     @servicePreparer()
     @recorded_by_proxy()
     def test_agents_crud(self, **kwargs):

@@ -9,18 +9,15 @@
 import base64
 import pytest
 from test_base import TestBase, servicePreparer
-from devtools_testutils import is_live_and_not_recording
+from devtools_testutils import recorded_by_proxy, RecordedTransport
 from azure.ai.projects.models import PromptAgentDefinition, ImageGenTool
 from azure.core.exceptions import ResourceNotFoundError
 
 
 class TestAgentImageGeneration(TestBase):
 
     @servicePreparer()
-    @pytest.mark.skipif(
-        condition=(not is_live_and_not_recording()),
-        reason="Skipped because we cannot record network calls with OpenAI client",
-    )
+    @recorded_by_proxy(RecordedTransport.AZURE_CORE, RecordedTransport.HTTPX)
     def test_agent_image_generation(self, **kwargs):
         """
         Test agent with Image Generation tool.
@@ -44,57 +41,49 @@ def test_agent_image_generation(self, **kwargs):
         DELETE /agents/{agent_name}/versions/{agent_version} project_client.agents.delete_version()
         """
 
-        # Get the image model deployment name from environment variable
-        image_model_deployment = os.environ.get(
-            "AZURE_AI_PROJECTS_TESTS_IMAGE_MODEL_DEPLOYMENT_NAME", "gpt-image-1-mini"
-        )
-
         model = self.test_agents_params["model_deployment_name"]
+        image_model = self.test_agents_tools_params["image_generation_model_deployment_name"]
+        agent_name = "image-gen-agent"
 
         with (
             self.create_client(operation_group="agents", **kwargs) as project_client,
             project_client.get_openai_client() as openai_client,
         ):
             # Check if the image model deployment exists in the project
             try:
-                deployment = project_client.deployments.get(image_model_deployment)
+                deployment = project_client.deployments.get(image_model)
                 print(f"Image model deployment found: {deployment.name}")
             except ResourceNotFoundError:
-                pytest.skip(f"Image generation model '{image_model_deployment}' not available in this project")
+                pytest.fail(f"Image generation model '{image_model}' not available in this project")
             except Exception as e:
-                pytest.skip(f"Unable to verify image model deployment: {e}")
+                pytest.fail(f"Unable to verify image model deployment: {e}")
 
             # Disable retries for faster failure when service returns 500
             openai_client.max_retries = 0
 
             # Create agent with image generation tool
             agent = project_client.agents.create_version(
-                agent_name="image-gen-agent",
+                agent_name=agent_name,
                 definition=PromptAgentDefinition(
                     model=model,
                     instructions="Generate images based on user prompts",
-                    tools=[ImageGenTool(quality="low", size="1024x1024")],
+                    tools=[ImageGenTool(model=image_model, quality="low", size="1024x1024")],  # type: ignore
                 ),
                 description="Agent for testing image generation.",
             )
-            print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
-            assert agent.id is not None
-            assert agent.name == "image-gen-agent"
-            assert agent.version is not None
+            self._validate_agent_version(agent, expected_name=agent_name)
 
             # Request image generation
             print("\nAsking agent to generate an image of a simple geometric shape...")
 
             response = openai_client.responses.create(
                 input="Generate an image of a blue circle on a white background.",
-                extra_headers={
-                    "x-ms-oai-image-generation-deployment": image_model_deployment
-                },  # Required for image generation
+                extra_headers={"x-ms-oai-image-generation-deployment": image_model},  # Required for image generation
                 extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
             )
 
             print(f"Response created (id: {response.id})")
-            assert response.id is not None
+            assert response.id
             assert response.output is not None
             assert len(response.output) > 0
 
@@ -127,6 +116,12 @@ def test_agent_image_generation(self, **kwargs):
 
             print("\n✓ Agent successfully generated and returned a valid image")
 
+            # Save the image to a file in the .assets directory (which is .gitignored)
+            os.makedirs(".assets", exist_ok=True)
+            with open(".assets/generated_image_sync.png", "wb") as f:
+                f.write(image_bytes)
+            print("✓ Image saved to .assets/generated_image_sync.png")
+
             # Teardown
             project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
             print("Agent deleted")
@@ -0,0 +1,108 @@
+# pylint: disable=too-many-lines,line-too-long,useless-suppression
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+# cSpell:disable
+
+import os
+import base64
+import pytest
+from test_base import TestBase, servicePreparer
+from devtools_testutils.aio import recorded_by_proxy_async
+from devtools_testutils import RecordedTransport
+from azure.ai.projects.models import PromptAgentDefinition, ImageGenTool
+from azure.core.exceptions import ResourceNotFoundError
+
+
+class TestAgentImageGenerationAsync(TestBase):
+
+    @servicePreparer()
+    @recorded_by_proxy_async(RecordedTransport.AZURE_CORE, RecordedTransport.HTTPX)
+    async def test_agent_image_generation_async(self, **kwargs):
+
+        model = self.test_agents_params["model_deployment_name"]
+        image_model = self.test_agents_tools_params["image_generation_model_deployment_name"]
+        agent_name = "image-gen-agent"
+
+        async with (
+            self.create_async_client(operation_group="agents", **kwargs) as project_client,
+            project_client.get_openai_client() as openai_client,
+        ):
+            # Check if the image model deployment exists in the project
+            try:
+                deployment = await project_client.deployments.get(image_model)
+                print(f"Image model deployment found: {deployment.name}")
+            except ResourceNotFoundError:
+                pytest.fail(f"Image generation model '{image_model}' not available in this project")
+            except Exception as e:
+                pytest.fail(f"Unable to verify image model deployment: {e}")
+
+            # Disable retries for faster failure when service returns 500
+            openai_client.max_retries = 0
+
+            # Create agent with image generation tool
+            agent = await project_client.agents.create_version(
+                agent_name=agent_name,
+                definition=PromptAgentDefinition(
+                    model=model,
+                    instructions="Generate images based on user prompts",
+                    tools=[ImageGenTool(model=image_model, quality="low", size="1024x1024")],  # type: ignore
+                ),
+                description="Agent for testing image generation.",
+            )
+            print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
+            self._validate_agent_version(agent, expected_name=agent_name)
+
+            # Request image generation
+            print("\nAsking agent to generate an image of a simple geometric shape...")
+
+            response = await openai_client.responses.create(
+                input="Generate an image of a blue circle on a white background.",
+                extra_headers={"x-ms-oai-image-generation-deployment": image_model},  # Required for image generation
+                extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
+            )
+
+            print(f"Response created (id: {response.id})")
+            assert response.id
+            assert response.output is not None
+            assert len(response.output) > 0
+
+            # Extract image data from response
+            image_data = [output.result for output in response.output if output.type == "image_generation_call"]
+
+            # Verify image was generated
+            assert len(image_data) > 0, "Expected at least one image to be generated"
+            assert image_data[0], "Expected image data to be non-empty"
+
+            print(f"✓ Image data received ({len(image_data[0])} base64 characters)")
+
+            # Decode the base64 image
+            image_bytes = b""
+            try:
+                image_bytes = base64.b64decode(image_data[0])
+                assert len(image_bytes) > 0, "Decoded image should have content"
+                print(f"✓ Image decoded successfully ({len(image_bytes)} bytes)")
+            except Exception as e:
+                pytest.fail(f"Failed to decode base64 image data: {e}")
+
+            # Verify it's a PNG image (check magic bytes)
+            # PNG files start with: 89 50 4E 47 (‰PNG)
+            assert image_bytes[:4] == b"\x89PNG", "Image does not appear to be a valid PNG"
+            print("✓ Image is a valid PNG")
+
+            # Verify reasonable image size (should be > 1KB for a 1024x1024 image)
+            assert len(image_bytes) > 1024, f"Image seems too small ({len(image_bytes)} bytes)"
+            print(f"✓ Image size is reasonable ({len(image_bytes):,} bytes)")
+
+            print("\n✓ Agent successfully generated and returned a valid image")
+
+            # Save the image to a file in the .assets directory (which is .gitignored)
+            os.makedirs(".assets", exist_ok=True)
+            with open(".assets/generated_image_async.png", "wb") as f:
+                f.write(image_bytes)
+            print("✓ Image saved to .assets/generated_image_async.png")
+
+            # Teardown
+            await project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+            print("Agent deleted")
@@ -66,7 +66,6 @@
     azure_ai_projects_tests_ai_search_project_connection_id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/sanitized-resource-group/providers/Microsoft.CognitiveServices/accounts/sanitized-account/projects/sanitized-project/connections/sanitized-ai-search-connection",
     azure_ai_projects_tests_ai_search_index_name="sanitized-index-name",
     azure_ai_projects_tests_mcp_project_connection_id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/sanitized-resource-group/providers/Microsoft.CognitiveServices/accounts/sanitized-account/projects/sanitized-project/connections/sanitized-mcp-connection",
-    azure_ai_projects_tests_image_model_deployment_name="gpt-image-1-mini",
 )
 
 # Fine-tuning job type constants
@@ -105,6 +104,10 @@ class TestBase(AzureRecordedTestCase):
         "agent_name": "agent-for-python-projects-sdk-testing",
     }
 
+    test_agents_tools_params = {
+        "image_generation_model_deployment_name": "gpt-image-1-mini",
+    }
+
     test_inference_params = {
         "connection_name_api_key_auth": "connection1",
         "connection_name_entra_id_auth": "connection2",
@@ -386,23 +389,31 @@ def _validate_agent_version(
     ) -> None:
         assert agent is not None
         assert isinstance(agent, AgentVersionDetails)
-        assert agent.id is not None
+        assert agent.id
         if expected_name:
             assert agent.name == expected_name
+        else:
+            assert agent.name
         if expected_version:
             assert agent.version == expected_version
+        else:
+            assert agent.version
         print(f"Agent version validated (id: {agent.id}, name: {agent.name}, version: {agent.version})")
 
     def _validate_agent(
         self, agent: AgentDetails, expected_name: Optional[str] = None, expected_latest_version: Optional[str] = None
     ) -> None:
         assert agent is not None
         assert isinstance(agent, AgentDetails)
-        assert agent.id is not None
+        assert agent.id
         if expected_name:
             assert agent.name == expected_name
+        else:
+            assert agent.name
         if expected_latest_version:
             assert agent.versions.latest.version == expected_latest_version
+        else:
+            assert agent.versions.latest.version
         print(f"Agent validated (id: {agent.id}, name: {agent.name}, latest version: {agent.versions.latest.version})")
 
     def _validate_conversation_item(