Azure · Copilot · Jan 12, 2026 · Jan 13, 2026 · Jan 13, 2026
@@ -43,7 +43,9 @@ BROWSER_AUTOMATION_PROJECT_CONNECTION_ID=
 OPENAPI_PROJECT_CONNECTION_ID=
 AI_SEARCH_USER_INPUT=
 SHAREPOINT_USER_INPUT=
-
+FABRIC_SEARCH_USER_INPUT=
+BING_CUSTOM_USER_INPUT=
+A2A_USER_INPUT=
 
 #######################################################################
 #

@@ -25,6 +25,7 @@
     3) BING_CUSTOM_SEARCH_PROJECT_CONNECTION_ID - The Bing Custom Search project connection ID,
        as found in the "Connections" tab in your Microsoft Foundry project.
     4) BING_CUSTOM_SEARCH_INSTANCE_NAME - The Bing Custom Search instance name
+    5) BING_CUSTOM_USER_INPUT - (Optional) The question to ask. If not set, you will be prompted.
 """
 
 import os
@@ -72,7 +73,7 @@
     )
     print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
 
-    user_input = input("Enter your question (e.g., 'Tell me more about foundry agent service'): \n")
+    user_input = os.environ.get("BING_CUSTOM_USER_INPUT") or input("Enter your question: \n")
 
     # Send initial request that will trigger the Bing Custom Search tool
     stream_response = openai_client.responses.create(

@@ -23,6 +23,7 @@
        the "Models + endpoints" tab in your Microsoft Foundry project.
     3) FABRIC_PROJECT_CONNECTION_ID - The Fabric project connection ID,
        as found in the "Connections" tab in your Microsoft Foundry project.
+    4) FABRIC_SEARCH_USER_INPUT - (Optional) The question to ask. If not set, you will be prompted.
 """
 
 import os
@@ -65,7 +66,7 @@
     )
     print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
 
-    user_input = input("Enter your question (e.g., 'Tell me about sales records'): \n")
+    user_input = os.environ.get("FABRIC_SEARCH_USER_INPUT") or input("Enter your question: \n")
 
     response = openai_client.responses.create(
         tool_choice="required",

@@ -24,8 +24,9 @@
        the "Models + endpoints" tab in your Microsoft Foundry project.
     3) A2A_PROJECT_CONNECTION_ID - The A2A project connection ID,
        as found in the "Connections" tab in your Microsoft Foundry project.
-    4) (Optional) A2A_ENDPOINT - If the connection is missing target i.e. if it is of "Custom keys" type, we need to set the A2A
+    4) A2A_ENDPOINT - (Optional) If the connection is missing target i.e. if it is of "Custom keys" type, we need to set the A2A
        endpoint on the tool.
+    5) A2A_USER_INPUT - (Optional) The question to ask. If not set, you will be prompted.
 """
 
 import os
@@ -66,7 +67,7 @@
     )
     print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
 
-    user_input = input("Enter your question (e.g., 'What can the secondary agent do?'): \n")
+    user_input = os.environ.get("A2A_USER_INPUT") or input("Enter your question (e.g., 'What can the secondary agent do?'): \n")
 
     stream_response = openai_client.responses.create(
         stream=True,

@@ -25,6 +25,7 @@
 if not load_dotenv(find_dotenv(), override=True):
     print("Did not find a .env file. Using default environment variable values for tests.")
 
+
 def pytest_collection_modifyitems(items):
     if os.environ.get("AZURE_TEST_RUN_LIVE") == "true":
         return

@@ -64,6 +64,9 @@
     azure_resource_group="sanitized-resource-group",
     ai_search_user_input="What is Azure AI Projects?",
     sharepoint_user_input="What is SharePoint?",
+    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",
     memory_store_chat_model_deployment_name="gpt-4.1-mini",
     memory_store_embedding_model_deployment_name="text-embedding-ada-002",
 )