add fabric tool def and sample

sdk/ai/azure-ai-projects/azure/ai/projects/models/_patch.py

@@ -55,6 +55,7 @@
     MessageTextContent,
     MessageTextFileCitationAnnotation,
     MessageTextFilePathAnnotation,
+    MicrosoftFabricToolDefinition,
     OpenAIPageableListOfThreadMessage,
     RequiredFunctionToolCall,
     RunStep,
@@ -580,6 +581,20 @@ def definitions(self) -> List[ToolDefinition]:
         return [BingGroundingToolDefinition(bing_grounding=ToolConnectionList(connection_list=self.connection_ids))]
 
 
+class FabricTool(ConnectionTool):
+    """
+    A tool that searches for information using Microsoft Fabric.
+    """
+
+    @property
+    def definitions(self) -> List[ToolDefinition]:
+        """
+        Get the Microsoft Fabric tool definitions.
+
+        :rtype: List[ToolDefinition]
+        """
+        return [MicrosoftFabricToolDefinition(fabric_aiskill=ToolConnectionList(connection_list=self.connection_ids))]
+
 class SharepointTool(ConnectionTool):
     """
     A tool that searches for information using Sharepoint.
@@ -1425,6 +1440,7 @@ def get_last_text_message_by_sender(self, sender: str) -> Optional[MessageTextCo
     "FunctionTool",
     "BingGroundingTool",
     "SharepointTool",
+    "FabricTool",
     "AzureAISearchTool",
     "SASTokenCredential",
     "Tool",

sdk/ai/azure-ai-projects/samples/agents/sample_agents_fabric.py

@@ -0,0 +1,80 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+FILE: sample_agents_fabric.py
+
+DESCRIPTION:
+    This sample demonstrates how to use agent operations with the Microsoft Fabric grounding tool from
+    the Azure Agents service using a synchronous client.
+
+USAGE:
+    python sample_agents_fabric.py
+
+    Before running the sample:
+
+    pip install azure-ai-projects azure-identity
+
+    Set this environment variables with your own values:
+    PROJECT_CONNECTION_STRING - the Azure AI Project connection string, as found in your AI Studio Project.
+"""
+
+import os
+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+from azure.ai.projects.models import FabricTool
+
+
+# Create an Azure AI Client from a connection string, copied from your AI Studio project.
+# At the moment, it should be in the format "<HostName>;<AzureSubscriptionId>;<ResourceGroup>;<HubName>"
+# Customer needs to login to Azure subscription via Azure CLI and set the environment variables
+
+project_client = AIProjectClient.from_connection_string(
+    credential=DefaultAzureCredential(),
+    conn_str=os.environ["PROJECT_CONNECTION_STRING"],
+)
+
+conn_id = "your-connection-id"
+
+# Initialize agent fabric tool and add the connection id
+fabric = FabricTool(connection_id=conn_id)
+
+# Create agent with the fabric tool and process assistant run
+with project_client:
+    agent = project_client.agents.create_agent(
+        model="gpt-4o",
+        name="my-assistant",
+        instructions="You are a helpful assistant",
+        tools=fabric.definitions,
+        headers={"x-ms-enable-preview": "true"},
+    )
+    print(f"Created agent, ID: {agent.id}")
+
+    # Create thread for communication
+    thread = project_client.agents.create_thread()
+    print(f"Created thread, ID: {thread.id}")
+
+    # Create message to thread
+    message = project_client.agents.create_message(
+        thread_id=thread.id,
+        role="user",
+        content="How does wikipedia explain Euler's Identity?",
+    )
+    print(f"Created message, ID: {message.id}")
+
+    # Create and process agent run in thread with tools
+    run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
+    print(f"Run finished with status: {run.status}")
+
+    if run.status == "failed":
+        print(f"Run failed: {run.last_error}")
+
+    # Delete the assistant when done
+    project_client.agents.delete_agent(agent.id)
+    print("Deleted agent")
+
+    # Fetch and log all messages
+    messages = project_client.agents.list_messages(thread_id=thread.id)
+    print(f"Messages: {messages}")