[AI] [Projects] Add Fabric sample (#40116)

* [AI] [Projects] add fabric sample

* update README and sample

* use agent_id param in sample

* review feedback

* more review feedback

* Even more feedback

* run snippet updater

Author: glharper

sdk/ai/azure-ai-projects/README.md

@@ -46,6 +46,7 @@ To report an issue with the client library, or request additional features, plea
       - [Function call](#create-agent-with-function-call)
       - [Azure Function Call](#create-agent-with-azure-function-call)
       - [OpenAPI](#create-agent-with-openapi)
+      - [Fabric data](#create-an-agent-with-fabric)
     - [Create thread](#create-thread) with
       - [Tool resource](#create-thread-with-tool-resource)
     - [Create message](#create-message) with:
@@ -810,6 +811,37 @@ with project_client:
 
 <!-- END SNIPPET -->
 
+#### Create an Agent with Fabric
+
+To enable your Agent to answer queries using Fabric data, use `FabricTool` along with a connection to the Fabric resource.
+
+Here is an example:
+
+<!-- SNIPPET:sample_agents_fabric.create_agent_with_fabric_tool -->
+
+```python
+fabric_connection = project_client.connections.get(connection_name=os.environ["FABRIC_CONNECTION_NAME"])
+conn_id = fabric_connection.id
+
+print(conn_id)
+
+# Initialize an Agent Fabric tool and add the connection id
+fabric = FabricTool(connection_id=conn_id)
+
+# Create an Agent with the Fabric tool and process an Agent run
+with project_client:
+    agent = project_client.agents.create_agent(
+        model=os.environ["MODEL_DEPLOYMENT_NAME"],
+        name="my-agent",
+        instructions="You are a helpful agent",
+        tools=fabric.definitions,
+        headers={"x-ms-enable-preview": "true"},
+    )
+```
+
+<!-- END SNIPPET -->
+
+
 #### Create Thread
 
 For each session or conversation, a thread is required.   Here is an example:

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
+
+project_client = AIProjectClient.from_connection_string(
+    credential=DefaultAzureCredential(),
+    conn_str=os.environ["PROJECT_CONNECTION_STRING"],
+)
+
+# [START create_agent_with_fabric_tool]
+fabric_connection = project_client.connections.get(connection_name=os.environ["FABRIC_CONNECTION_NAME"])
+conn_id = fabric_connection.id
+
+print(conn_id)
+
+# Initialize an Agent Fabric tool and add the connection id
+fabric = FabricTool(connection_id=conn_id)
+
+# Create an Agent with the Fabric tool and process an Agent run
+with project_client:
+    agent = project_client.agents.create_agent(
+        model=os.environ["MODEL_DEPLOYMENT_NAME"],
+        name="my-agent",
+        instructions="You are a helpful agent",
+        tools=fabric.definitions,
+        headers={"x-ms-enable-preview": "true"},
+    )
+    # [END create_agent_with_fabric_tool]
+    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="<User query against Fabric resource>",
+    )
+    print(f"Created message, ID: {message.id}")
+
+    # Create and process an Agent run in thread with tools
+    run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
+    print(f"Run finished with status: {run.status}")
+
+    if run.status == "failed":
+        print(f"Run failed: {run.last_error}")
+
+    # Delete the Agent 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}")