Add samples for Fabric IQ agent with synchronous and asynchronous cli…

sdk/ai/azure-ai-projects/assets.json

@@ -2,5 +2,5 @@
   "AssetsRepo": "Azure/azure-sdk-assets",
   "AssetsRepoPrefixPath": "python",
   "TagPrefix": "python/ai/azure-ai-projects",
-  "Tag": "python/ai/azure-ai-projects_5642dfc4d2"
+  "Tag": "python/ai/azure-ai-projects_b13a910d61"
 }

sdk/ai/azure-ai-projects/samples/agents/tools/sample_agent_fabric_iq.py

@@ -0,0 +1,69 @@
+# pylint: disable=line-too-long,useless-suppression
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    This sample demonstrates how to run a Prompt Agent that uses the
+    Fabric IQ preview tool with a synchronous client.
+
+USAGE:
+    python sample_agent_fabric_iq.py
+
+    Before running the sample:
+
+    pip install "azure-ai-projects>=2.2.0" python-dotenv
+
+    Set these environment variables with your own values:
+    1) FOUNDRY_PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
+       page of your Microsoft Foundry portal.
+    2) FOUNDRY_MODEL_NAME - The deployment name of the AI model, as found under the "Name" column in
+       the "Models + endpoints" tab in your Microsoft Foundry project.
+    3) FABRIC_IQ_PROJECT_CONNECTION_ID - The fully-qualified resource id of the Fabric IQ project connection.
+    4) FABRIC_IQ_USER_INPUT - The natural-language question to send to the agent.
+"""
+
+import os
+from dotenv import load_dotenv
+from azure.identity import DefaultAzureCredential
+from azure.ai.projects import AIProjectClient
+from azure.ai.projects.models import PromptAgentDefinition, FabricIQPreviewTool
+
+load_dotenv()
+
+endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
+
+with (
+    DefaultAzureCredential() as credential,
+    AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
+    project_client.get_openai_client() as openai_client,
+):
+    tool_payload = FabricIQPreviewTool(
+        project_connection_id=os.environ["FABRIC_IQ_PROJECT_CONNECTION_ID"],
+        require_approval="never",
+    )
+
+    agent = project_client.agents.create_version(
+        agent_name="MyAgent",
+        definition=PromptAgentDefinition(
+            model=os.environ["FOUNDRY_MODEL_NAME"],
+            instructions="Use the available Fabric IQ tools to answer questions and perform tasks.",
+            tools=[tool_payload],
+        ),
+    )
+    print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
+
+    user_input = os.environ.get("FABRIC_IQ_USER_INPUT") or input("Enter your question:\n")
+
+    response = openai_client.responses.create(
+        input=user_input,
+        extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
+    )
+
+    print(f"Agent response: {response.output_text}")
+
+    # Clean up the agent version so unused versions don't accumulate in the project.
+    project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+    print("Agent deleted")

sdk/ai/azure-ai-projects/samples/agents/tools/sample_agent_fabric_iq_async.py

@@ -0,0 +1,76 @@
+# pylint: disable=line-too-long,useless-suppression
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    This sample demonstrates how to run a Prompt Agent that uses the
+    Fabric IQ preview tool with an asynchronous client.
+
+USAGE:
+    python sample_agent_fabric_iq_async.py
+
+    Before running the sample:
+
+    pip install "azure-ai-projects>=2.2.0" python-dotenv aiohttp
+
+    Set these environment variables with your own values:
+    1) FOUNDRY_PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
+       page of your Microsoft Foundry portal.
+    2) FOUNDRY_MODEL_NAME - The deployment name of the AI model, as found under the "Name" column in
+       the "Models + endpoints" tab in your Microsoft Foundry project.
+    3) FABRIC_IQ_PROJECT_CONNECTION_ID - The fully-qualified resource id of the Fabric IQ project connection.
+    4) FABRIC_IQ_USER_INPUT - The natural-language question to send to the agent.
+"""
+
+import os
+import asyncio
+from dotenv import load_dotenv
+from azure.identity.aio import DefaultAzureCredential
+from azure.ai.projects.aio import AIProjectClient
+from azure.ai.projects.models import PromptAgentDefinition, FabricIQPreviewTool
+
+load_dotenv()
+
+endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
+
+
+async def main():
+    async with (
+        DefaultAzureCredential() as credential,
+        AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
+        project_client.get_openai_client() as openai_client,
+    ):
+        tool_payload = FabricIQPreviewTool(
+            project_connection_id=os.environ["FABRIC_IQ_PROJECT_CONNECTION_ID"],
+            require_approval="never",
+        )
+
+        agent = await project_client.agents.create_version(
+            agent_name="MyAgent",
+            definition=PromptAgentDefinition(
+                model=os.environ["FOUNDRY_MODEL_NAME"],
+                instructions="Use the available Fabric IQ tools to answer questions and perform tasks.",
+                tools=[tool_payload],
+            ),
+        )
+        print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
+
+        user_input = os.environ.get("FABRIC_IQ_USER_INPUT") or input("Enter your question:\n")
+
+        response = await openai_client.responses.create(
+            input=user_input,
+            extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
+        )
+
+        print(f"Agent response: {response.output_text}")
+
+        # Clean up the agent version so unused versions don't accumulate in the project.
+        await project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+        print("Agent deleted")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

sdk/ai/azure-ai-projects/tests/test_base.py

@@ -54,6 +54,7 @@
     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",
     browser_automation_project_connection_id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/sanitized-resource-group/providers/Microsoft.CognitiveServices/accounts/sanitized-account/projects/sanitized-project/connections/sanitized-browser-automation-connection",
     sharepoint_project_connection_id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/sanitized-resource-group/providers/Microsoft.CognitiveServices/accounts/sanitized-account/projects/sanitized-project/connections/sanitized-sharepoint-connection",
+    fabric_iq_project_connection_id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/sanitized-resource-group/providers/Microsoft.CognitiveServices/accounts/sanitized-account/projects/sanitized-project/connections/sanitized-fabric-iq-connection",
     bing_custom_search_instance_name="sanitized-bing-custom-search-instance",
     completed_oai_model_sft_fine_tuning_job_id="sanitized-ftjob-id",
     completed_oai_model_rft_fine_tuning_job_id="sanitized-ftjob-id",
@@ -68,6 +69,7 @@
     fabric_user_input="List all customers!",
     a2a_user_input="What can the secondary agent do?",
     bing_custom_user_input="Tell me more about foundry agent service",
+    fabric_iq_user_input="Tell me weather history in London, Ohio",
     memory_store_chat_model_deployment_name="sanitized-model-deployment-name",
     memory_store_embedding_model_deployment_name="text-embedding-ada-002",
     foundry_agent_container_image="sanitizedregistry.azurecr.io/sanitized/sessions-agent:latest",