diff --git a/guides/fabric_foundry/README.md b/guides/fabric_foundry/README.md
new file mode 100644
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+++ b/guides/fabric_foundry/README.md
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+# Fabric Foundry Integration
+
+This guide demonstrates how to automate the integration between Microsoft Fabric Data Agents and Azure AI Foundry.
+
+## Overview
+
+The automation script performs the following steps:
+
+1. **Upload Notebook**: Uploads the `create_fabric_data_agent.ipynb` notebook to a specified Fabric workspace
+1. **Execute Notebook**: Triggers the notebook to run, which creates a Fabric Data Agent named "data_agent_automation_sample"
+1. **Retrieve Artifact ID**: Gets the artifact ID of the newly created data agent
+1. **Create Connection**: Creates a Connected Resource connection in AI Foundry pointing to the Fabric Data Agent
+1. **Create Agent**: Creates an AI Foundry Agent that uses the Fabric Data Agent as a knowledge source via FabricTool
+
+## Prerequisites
+
+- Azure subscription with access to:
+  - Microsoft Fabric workspace
+  - Azure AI Foundry project (not Hub - must be a Project resource)
+  - AI model deployment in AI Foundry project (e.g., gpt-4o)
+- Fabric workspace must have:
+  - NYC Taxi lakehouse named "NYCTaxi_756" with tables: year_2017, year_2018, year_2019, year_2020
+  - Active capacity (required for notebook execution)
+- Azure CLI or DefaultAzureCredential authentication configured
+- Python 3.12 or higher
+- uv package manager installed
+
+## Setup
+
+1. Install dependencies using uv:
+
+```bash
+cd guides/fabric_foundry
+uv sync
+```
+
+1. Create a `.env` file with required environment variables:
+
+```bash
+# Fabric Configuration
+FABRIC_WORKSPACE_ID=your-fabric-workspace-id
+
+# Azure AI Foundry Configuration
+AI_FOUNDRY_SUBSCRIPTION_ID=your-subscription-id
+AI_FOUNDRY_RESOURCE_GROUP=your-resource-group
+AI_FOUNDRY_ACCOUNT_NAME=your-ai-foundry-account-name
+AI_FOUNDRY_PROJECT_NAME=your-ai-foundry-project-name
+AI_FOUNDRY_MODEL_DEPLOYMENT_NAME=gpt-4o
+```
+
+**Note**: Replace `AI_FOUNDRY_MODEL_DEPLOYMENT_NAME` with your actual model deployment name from the "Models + endpoints" tab in your AI Foundry project.
+
+## Usage
+
+Run the automation script:
+
+```bash
+uv run python automate_fabric_foundry_integration.py
+```
+
+The script will:
+
+- Load configuration from `.env` file
+- Authenticate using DefaultAzureCredential
+- Upload and execute the notebook in Fabric (or reuse existing notebook)
+- Wait for completion (up to 10 minutes)
+- Create the Fabric connection in AI Foundry using ARM REST API
+- Create an AI Foundry Agent with FabricTool using Azure AI Projects SDK
+- Output the created resource IDs
+
+## Implementation Notes
+
+### Connection Creation
+
+- Uses Azure Resource Manager REST API (`Microsoft.CognitiveServices/accounts/projects/connections@2025-06-01`)
+- Connection category: `CustomKeys`
+- Authentication type: `CustomKeys`
+- Stores workspace ID, artifact ID, and type in credentials
+
+### Agent Creation
+
+- Uses Azure AI Projects Python SDK (`azure-ai-projects>=1.0.0b1`)
+- Uses Azure AI Agents SDK (`azure-ai-agents>=1.2.0b6`) for FabricTool
+- FabricTool connects the agent to the Fabric Data Agent as a knowledge source
+- Requires valid model deployment name from AI Foundry project
+
+## Files
+
+- `create_fabric_data_agent.ipynb`: Notebook that creates the Fabric Data Agent (must be run in Fabric)
+- `automate_fabric_foundry_integration.py`: Main automation script
+- `requirements.txt`: Python dependencies
+- `.env`: Environment configuration (not committed to git)
+- `README.md`: This file
+
+## Dependencies
+
+Key Python packages:
+
+- `azure-identity>=1.15.0` - Azure authentication
+- `requests>=2.31.0` - HTTP requests for Fabric and ARM APIs
+- `python-dotenv>=1.0.0` - Environment variable management
+- `azure-ai-projects>=1.0.0b1` - AI Foundry Projects SDK
+- `azure-ai-agents>=1.2.0b6` - AI Agents SDK with FabricTool support
+
+## Troubleshooting
+
+### CapacityNotActive Error
+
+If you get this error when triggering notebook execution, ensure your Fabric workspace has an active capacity assigned.
+
+### 404 Resource Not Found (Agent Creation)
+
+Verify that `AI_FOUNDRY_MODEL_DEPLOYMENT_NAME` matches exactly with a deployment name in your AI Foundry project's "Models + endpoints" tab.
+
+### Import Errors
+
+Make sure you're using the preview version of `azure-ai-agents` (1.2.0b6 or higher) which includes FabricTool:
+
+```bash
+uv pip install --pre --upgrade azure-ai-agents
+```
+
+## Notes
+
+- The Fabric Data Agent SDK can only run inside Microsoft Fabric environments
+- The automation uses the Fabric REST API to upload and trigger notebook execution
+- The script waits up to 10 minutes for notebook completion with 10-second polling intervals
+- Notebooks are reused if they already exist (prevents duplicate creation errors)
+- All resources are created with simple configurations suitable for POC/demo purposes
+- This is a proof-of-concept implementation - keep it simple!
diff --git a/guides/fabric_foundry/automate_fabric_foundry_integration.py b/guides/fabric_foundry/automate_fabric_foundry_integration.py
new file mode 100644
index 00000000..4453b251
--- /dev/null
+++ b/guides/fabric_foundry/automate_fabric_foundry_integration.py
@@ -0,0 +1,427 @@
+#!/usr/bin/env python3
+"""
+Automate connecting AI Foundry to Microsoft Fabric via Fabric Data Agent.
+
+This script:
+1. Uploads the create_fabric_data_agent notebook to a Fabric workspace
+2. Triggers notebook execution to create the data agent
+3. Retrieves the artifact ID of the created data agent
+4. Creates a Connected Resource connection in AI Foundry to Fabric
+5. Creates an AI Foundry Agent using this connection as a knowledge source
+"""
+
+import os
+import sys
+import time
+import base64
+from typing import Optional, Dict, Any
+from azure.identity import DefaultAzureCredential
+from azure.ai.projects import AIProjectClient
+from azure.ai.projects.models import ConnectionType
+import requests
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Constants
+FABRIC_DATA_AGENT_NAME = "data_agent_automation_sample"
+AI_FOUNDRY_API_VERSION = "2025-06-01"
+NOTEBOOK_POLL_INTERVAL = 10
+NOTEBOOK_TIMEOUT = 600
+
+
+class FabricFoundryIntegration:
+    """Handles integration between Microsoft Fabric and Azure AI Foundry."""
+
+    def __init__(
+        self,
+        fabric_workspace_id: str,
+        ai_foundry_subscription_id: str,
+        ai_foundry_resource_group: str,
+        ai_foundry_account_name: str,
+        ai_foundry_project_name: str,
+    ):
+        self.fabric_workspace_id = fabric_workspace_id
+        self.ai_foundry_subscription_id = ai_foundry_subscription_id
+        self.ai_foundry_resource_group = ai_foundry_resource_group
+        self.ai_foundry_account_name = ai_foundry_account_name
+        self.ai_foundry_project_name = ai_foundry_project_name
+        self.credential = DefaultAzureCredential()
+        self._fabric_token = None
+        self._arm_token = None
+
+        # Initialize AI Project Client
+        project_scope = (
+            f"https://{ai_foundry_account_name}.cognitiveservices.azure.com/"
+        )
+        self.ai_client = AIProjectClient(
+            endpoint=project_scope,
+            credential=self.credential
+        )
+
+    # ============================================================================
+    # Authentication Helpers
+    # ============================================================================
+
+    def _get_fabric_token(self) -> str:
+        """Get or refresh authentication token for Fabric APIs."""
+        if not self._fabric_token:
+            token = self.credential.get_token("https://api.fabric.microsoft.com/.default")
+            self._fabric_token = token.token
+        return self._fabric_token
+
+    def _get_arm_token(self) -> str:
+        """Get or refresh authentication token for Azure Resource Manager APIs."""
+        if not self._arm_token:
+            token = self.credential.get_token("https://management.azure.com/.default")
+            self._arm_token = token.token
+        return self._arm_token
+
+    def _get_fabric_headers(self) -> Dict[str, str]:
+        """Get headers for Fabric API requests."""
+        return {
+            "Authorization": f"Bearer {self._get_fabric_token()}",
+            "Content-Type": "application/json",
+        }
+
+    def _get_arm_headers(self) -> Dict[str, str]:
+        """Get headers for ARM API requests."""
+        return {
+            "Authorization": f"Bearer {self._get_arm_token()}",
+            "Content-Type": "application/json",
+        }
+
+    # ============================================================================
+    # Fabric Notebook Operations
+    # ============================================================================
+
+    def _find_existing_notebook(self, notebook_name: str) -> Optional[str]:
+        """Check if notebook with given name already exists in workspace."""
+        try:
+            list_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/items"
+            response = requests.get(list_url, headers=self._get_fabric_headers())
+            response.raise_for_status()
+            items = response.json().get("value", [])
+
+            for item in items:
+                if item.get("displayName") == notebook_name and item.get("type") == "Notebook":
+                    return item["id"]
+            return None
+        except requests.exceptions.RequestException as e:
+            print(f"⚠ Warning: Could not check for existing notebook: {e}")
+            return None
+
+    def _create_notebook(self, notebook_path: str, notebook_name: str) -> str:
+        """Create a new notebook in Fabric workspace."""
+        with open(notebook_path, "rb") as f:
+            notebook_content = base64.b64encode(f.read()).decode("utf-8")
+
+        create_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/items"
+        payload = {
+            "displayName": notebook_name,
+            "type": "Notebook",
+            "definition": {
+                "format": "ipynb",
+                "parts": [
+                    {
+                        "path": "notebook-content.ipynb",
+                        "payload": notebook_content,
+                        "payloadType": "InlineBase64",
+                    }
+                ],
+            },
+        }
+
+        response = requests.post(create_url, headers=self._get_fabric_headers(), json=payload)
+        if not response.ok:
+            raise Exception(f"Failed to create notebook: {response.status_code} - {response.text}")
+
+        response_data = response.json()
+        if not response_data or "id" not in response_data:
+            raise ValueError("Response missing 'id' field")
+
+        return response_data["id"]
+
+    def upload_notebook(self, notebook_path: str, notebook_name: str) -> str:
+        """Upload notebook to Fabric workspace, reusing if it already exists."""
+        # Check if notebook already exists
+        existing_id = self._find_existing_notebook(notebook_name)
+        if existing_id:
+            print(f"✓ Found existing notebook '{notebook_name}' with ID: {existing_id}")
+            return existing_id
+
+        # Create new notebook
+        notebook_id = self._create_notebook(notebook_path, notebook_name)
+        print(f"✓ Uploaded notebook '{notebook_name}' with ID: {notebook_id}")
+        return notebook_id
+
+    def trigger_notebook_run(self, notebook_id: str) -> str:
+        """Trigger notebook execution and return job ID."""
+        run_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/notebooks/{notebook_id}/jobs/instances?jobType=RunNotebook"
+
+        response = requests.post(run_url, headers=self._get_fabric_headers())
+        if not response.ok:
+            raise Exception(f"Failed to trigger notebook: {response.status_code} - {response.text}")
+
+        # Handle 202 Accepted response
+        if response.status_code == 202:
+            location = response.headers.get("Location", "")
+            if location:
+                job_id = location.split("/")[-1]
+                print(f"✓ Triggered notebook run with job ID: {job_id}")
+                return job_id
+
+            # Fallback: query for most recent job
+            print(f"✓ Notebook run triggered (202 Accepted), retrieving job ID...")
+            time.sleep(2)
+            jobs_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/notebooks/{notebook_id}/jobs/instances"
+            jobs_response = requests.get(jobs_url, headers=self._get_fabric_headers())
+            jobs_response.raise_for_status()
+            jobs = jobs_response.json().get("value", [])
+            if jobs:
+                job_id = jobs[0]["id"]
+                print(f"✓ Found running job with ID: {job_id}")
+                return job_id
+            raise ValueError("Notebook run triggered but no job ID found")
+
+        # Normal response with body
+        response_data = response.json()
+        job_id = response_data["id"]
+        print(f"✓ Triggered notebook run with job ID: {job_id}")
+        return job_id
+
+    def wait_for_notebook_completion(self, notebook_id: str, job_id: str) -> bool:
+        """Wait for notebook execution to complete."""
+        status_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/notebooks/{notebook_id}/jobs/instances/{job_id}"
+
+        start_time = time.time()
+        while time.time() - start_time < NOTEBOOK_TIMEOUT:
+            try:
+                response = requests.get(status_url, headers=self._get_fabric_headers())
+                response.raise_for_status()
+                status = response.json()["status"]
+
+                if status == "Completed":
+                    print("✓ Notebook execution completed successfully")
+                    return True
+                elif status in ["Failed", "Cancelled"]:
+                    print(f"✗ Notebook execution {status}")
+                    return False
+
+                print(f"  Notebook status: {status}, waiting...")
+                time.sleep(NOTEBOOK_POLL_INTERVAL)
+            except requests.exceptions.RequestException as e:
+                print(f"⚠ Warning: Error checking notebook status: {e}")
+                time.sleep(NOTEBOOK_POLL_INTERVAL)
+
+        print("✗ Timeout waiting for notebook completion")
+        return False
+
+    # ============================================================================
+    # Fabric Data Agent Operations
+    # ============================================================================
+
+    def get_data_agent_artifact_id(self, data_agent_name: str) -> Optional[str]:
+        """Retrieve the artifact ID of the created Fabric Data Agent."""
+        try:
+            list_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/items"
+            response = requests.get(list_url, headers=self._get_fabric_headers())
+            response.raise_for_status()
+            items = response.json().get("value", [])
+
+            for item in items:
+                if item.get("displayName") == data_agent_name:
+                    item_id = item["id"]
+
+                    # Get full item details
+                    get_item_url = f"https://api.fabric.microsoft.com/v1/workspaces/{self.fabric_workspace_id}/items/{item_id}"
+                    item_response = requests.get(get_item_url, headers=self._get_fabric_headers())
+                    item_response.raise_for_status()
+                    item_details = item_response.json()
+
+                    artifact_id = item_details["id"]
+                    print(f"✓ Found data agent '{data_agent_name}' with artifact ID: {artifact_id}")
+                    return artifact_id
+
+            print(f"✗ Data agent '{data_agent_name}' not found")
+            return None
+        except requests.exceptions.RequestException as e:
+            print(f"✗ Error retrieving data agent: {e}")
+            return None
+
+    # ============================================================================
+    # AI Foundry Operations
+    # ============================================================================
+
+    def _build_connection_url(self, connection_name: str) -> str:
+        """Build the ARM URL for AI Foundry Project connection."""
+        return (
+            f"https://management.azure.com/subscriptions/{self.ai_foundry_subscription_id}"
+            f"/resourceGroups/{self.ai_foundry_resource_group}"
+            f"/providers/Microsoft.CognitiveServices/accounts/{self.ai_foundry_account_name}"
+            f"/projects/{self.ai_foundry_project_name}"
+            f"/connections/{connection_name}"
+            f"?api-version={AI_FOUNDRY_API_VERSION}"
+        )
+
+    # ============================================================================
+    # Fabric Data Agent Operations
+
+    def create_foundry_to_fabric_connection(self, data_agent_artifact_id: str) -> str:
+        """Create a Connected Resource connection in AI Foundry Project to Fabric."""
+        connection_name = "fabric-data-agent-connection"
+        connection_url = self._build_connection_url(connection_name)
+
+        connection_payload = {
+            "properties": {
+                "category": "CustomKeys",
+                "authType": "CustomKeys",
+                "credentials": {
+                    "keys": {
+                        "workspace-id": self.fabric_workspace_id,
+                        "artifact-id": data_agent_artifact_id,
+                        "type": "fabric_dataagent"
+                    }
+                },
+            }
+        }
+
+        response = requests.put(connection_url, headers=self._get_arm_headers(), json=connection_payload)
+        if not response.ok:
+            raise Exception(f"Failed to create connection: {response.status_code} - {response.text}")
+
+        print(f"✓ Created Fabric connection: {connection_name}")
+
+        # Return full connection resource ID for agent creation
+        connection_id = (
+            f"/subscriptions/{self.ai_foundry_subscription_id}"
+            f"/resourceGroups/{self.ai_foundry_resource_group}"
+            f"/providers/Microsoft.CognitiveServices/accounts/{self.ai_foundry_account_name}"
+            f"/projects/{self.ai_foundry_project_name}"
+            f"/connections/{connection_name}"
+        )
+        return connection_id
+
+    def create_ai_foundry_agent(self, connection_id: str, model_deployment_name: str) -> str:
+        """Create an AI Foundry Agent using the Fabric connection as knowledge source."""
+        from azure.ai.agents.models import FabricTool
+
+        print("Available model deployments in the project:")
+        deployments = self.ai_client.deployments.list()  # .deployments is the property for model deployments
+        for d in deployments:
+            print(f"Name: {d.name}, Model: {d.modelName}, Version: {d.modelVersion}, Type: {d.type}")
+
+        # Initialize an Agent Fabric tool and add the connection id
+        fabric = FabricTool(connection_id=connection_id)
+
+        # Create an Agent with the Fabric tool
+        agent = self.ai_client.agents.create_agent(
+            model=model_deployment_name,
+            name="fabric-data-agent",
+            instructions="You are a helpful assistant with access to NYC taxi data through Fabric Data Agent. Help users answer questions about taxi ridership.",
+            tools=fabric.definitions
+        )
+
+        print(f"✓ Created AI Foundry Agent with ID: {agent.id}")
+        return agent.id
+
+
+# ============================================================================
+# Main Execution
+# ============================================================================
+
+def validate_environment() -> Dict[str, str]:
+    """Validate and return required environment variables."""
+    required_vars = {
+        "FABRIC_WORKSPACE_ID": os.getenv("FABRIC_WORKSPACE_ID", ""),
+        "AI_FOUNDRY_SUBSCRIPTION_ID": os.getenv("AI_FOUNDRY_SUBSCRIPTION_ID", ""),
+        "AI_FOUNDRY_RESOURCE_GROUP": os.getenv("AI_FOUNDRY_RESOURCE_GROUP", ""),
+        "AI_FOUNDRY_ACCOUNT_NAME": os.getenv("AI_FOUNDRY_ACCOUNT_NAME", ""),
+        "AI_FOUNDRY_PROJECT_NAME": os.getenv("AI_FOUNDRY_PROJECT_NAME", ""),
+        "AI_FOUNDRY_MODEL_DEPLOYMENT_NAME": os.getenv("AI_FOUNDRY_MODEL_DEPLOYMENT_NAME", "gpt-4o"),
+    }
+
+    missing_vars = [key for key, value in required_vars.items() if not value]
+    if missing_vars:
+        print("✗ Error: Required environment variables not set:")
+        for var in missing_vars:
+            print(f"  - {var}")
+        sys.exit(1)
+
+    return required_vars
+
+
+def main():
+    """Main execution flow."""
+    print("Starting Fabric-Foundry integration automation...")
+    print("=" * 60)
+
+    # Validate environment
+    env_vars = validate_environment()
+
+    # Initialize integration
+    try:
+        integration = FabricFoundryIntegration(
+            fabric_workspace_id=env_vars["FABRIC_WORKSPACE_ID"],
+            ai_foundry_subscription_id=env_vars["AI_FOUNDRY_SUBSCRIPTION_ID"],
+            ai_foundry_resource_group=env_vars["AI_FOUNDRY_RESOURCE_GROUP"],
+            ai_foundry_account_name=env_vars["AI_FOUNDRY_ACCOUNT_NAME"],
+            ai_foundry_project_name=env_vars["AI_FOUNDRY_PROJECT_NAME"],
+        )
+    except Exception as e:
+        print(f"✗ Error initializing integration: {e}")
+        sys.exit(1)
+
+    try:
+        # Step 1: Upload notebook
+        print("\n[Step 1/6] Uploading notebook...")
+        notebook_path = "create_fabric_data_agent.ipynb"
+        notebook_id = integration.upload_notebook(notebook_path, "create_fabric_data_agent")
+
+        # Step 2: Trigger notebook run
+        print("\n[Step 2/6] Triggering notebook execution...")
+        job_id = integration.trigger_notebook_run(notebook_id)
+
+        # Step 3: Wait for completion
+        print("\n[Step 3/6] Waiting for notebook completion...")
+        if not integration.wait_for_notebook_completion(notebook_id, job_id):
+            print("✗ Notebook execution failed, aborting")
+            sys.exit(1)
+
+        # Step 4: Retrieve data agent artifact ID
+        print("\n[Step 4/6] Retrieving data agent artifact ID...")
+        data_agent_artifact_id = integration.get_data_agent_artifact_id(FABRIC_DATA_AGENT_NAME)
+        if not data_agent_artifact_id:
+            print("✗ Could not retrieve data agent artifact ID, aborting")
+            sys.exit(1)
+
+        # Step 5: Create Fabric connection in AI Foundry Project
+        print("\n[Step 5/6] Creating AI Foundry connection")
+        connection_id = integration.create_foundry_to_fabric_connection(data_agent_artifact_id)
+
+        # Step 6: Create AI Foundry Agent
+        print("\n[Step 6/6] Creating AI Foundry agent")
+        agent_id = integration.create_ai_foundry_agent(
+            connection_id,
+            env_vars["AI_FOUNDRY_MODEL_DEPLOYMENT_NAME"]
+        )
+
+        # Success summary
+        print("\n" + "=" * 60)
+        print("✓ Integration complete!")
+        print(f"  - Data Agent Artifact ID: {data_agent_artifact_id}")
+        print(f"  - Connection ID: {connection_id}")
+        print(f"  - Agent ID: {agent_id}")
+        print("=" * 60)
+
+    except KeyboardInterrupt:
+        print("\n\n✗ Process interrupted by user")
+        sys.exit(1)
+    except Exception as e:
+        print(f"\n✗ Unexpected error: {e}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/guides/fabric_foundry/create_fabric_data_agent.ipynb b/guides/fabric_foundry/create_fabric_data_agent.ipynb
new file mode 100644
index 00000000..0bcf3515
--- /dev/null
+++ b/guides/fabric_foundry/create_fabric_data_agent.ipynb
@@ -0,0 +1,77 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2d685538",
+   "metadata": {},
+   "source": [
+    "# Create Fabric Data Agent\n",
+    "Uses NYC taxi data. \n",
+    "Note: Fabric data agent sdk cannot be run outside of Microsoft Fabric."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5e4cee85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install fabric-data-agent-sdk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5fb5751b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fabric.dataagent.client import (\n",
+    "    FabricDataAgentManagement,\n",
+    "    create_data_agent,\n",
+    "    delete_data_agent,\n",
+    ")\n",
+    "\n",
+    "# Hardcoded for now\n",
+    "data_agent_name = \"data_agent_automation_sample\"\n",
+    "lakehouse_name = \"NYCTaxi_756\"\n",
+    "\n",
+    "# create DataAgent\n",
+    "data_agent = create_data_agent(data_agent_name)\n",
+    "\n",
+    "data_agent.update_configuration(\n",
+    "    instructions=\"You are a helpful assistant, help users with their questions\",\n",
+    ")\n",
+    "\n",
+    "# datasource type could be: lakehouse, kqldatabase, warehouse or semanticmodel\n",
+    "data_agent.add_datasource(lakehouse_name, type=\"lakehouse\")\n",
+    "\n",
+    "# Publish\n",
+    "data_agent.publish()\n",
+    "\n",
+    "datasource = data_agent.get_datasources()[0]\n",
+    "\n",
+    "# Add data sources\n",
+    "datasource.select(\"dbo\", \"year_2017\")\n",
+    "datasource.select(\"dbo\", \"year_2018\")\n",
+    "datasource.select(\"dbo\", \"year_2019\")\n",
+    "datasource.select(\"dbo\", \"year_2020\")\n",
+    "\n",
+    "# Add additoinal instructions to the datasource\n",
+    "ds_notes = \"When asked about taxi ridership information use tables in dbo with year_ prefix to retrieve detailed information\"\n",
+    "datasource.update_configuration(instructions=ds_notes)\n",
+    "\n",
+    "# Get configuration\n",
+    "datasource.get_configuration()"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/guides/fabric_foundry/requirements.txt b/guides/fabric_foundry/requirements.txt
new file mode 100644
index 00000000..d9e6b379
--- /dev/null
+++ b/guides/fabric_foundry/requirements.txt
@@ -0,0 +1,5 @@
+azure-identity>=1.15.0
+requests>=2.31.0
+python-dotenv>=1.0.0
+azure-ai-projects>=1.0.0b1
+azure-ai-agents>=1.2.0b6