Python: Fix for AzureAIAgent streaming func call invocations. Other fixes/improvements for tool call content types, and logging.

python/pyproject.toml

@@ -23,6 +23,9 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
+    # azure agents
+    "azure-ai-projects >= 1.0.0b11",
+    "azure-ai-agents >= 1.0.0",
     "aiohttp ~= 3.8",
     "cloudevents ~=1.0",
     "pydantic >=2.0,!=2.10.0,!=2.10.1,!=2.10.2,!=2.10.3,<2.12",
@@ -67,10 +70,7 @@ autogen = [
 aws = [
     "boto3>=1.36.4,<1.39.0",
 ]
-# This is temporary to get the PR reviewed, and will be replaced when their new version is public.
 azure = [
-    "azure-ai-projects >= 1.0.0b11",
-    "azure-ai-agents >= 1.0.0",
     "azure-ai-inference >= 1.0.0b6",
     "azure-core-tracing-opentelemetry >= 1.0.0b11",
     "azure-search-documents >= 11.6.0b4",
@@ -132,7 +132,7 @@ qdrant = [
     "qdrant-client ~= 1.9"
 ]
 redis = [
-    "redis[hiredis] >= 5,< 7",
+    "redis[hiredis] >= 5,< 6",
     "types-redis ~= 4.6.0.20240425",
     "redisvl ~= 0.4"
 ]

python/samples/concepts/agents/azure_ai_agent/azure_ai_agent_bing_grounding.py

@@ -6,7 +6,12 @@
 from azure.identity.aio import DefaultAzureCredential
 
 from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings, AzureAIAgentThread
-from semantic_kernel.contents import AnnotationContent
+from semantic_kernel.contents import (
+    AnnotationContent,
+    ChatMessageContent,
+    FunctionCallContent,
+    FunctionResultContent,
+)
 
 """
 The following sample demonstrates how to create an Azure AI agent that
@@ -20,13 +25,23 @@
 TASK = "Which team won the 2025 NCAA basketball championship?"
 
 
+async def handle_intermediate_steps(message: ChatMessageContent) -> None:
+    for item in message.items or []:
+        if isinstance(item, FunctionResultContent):
+            print(f"Function Result:> {item.result} for function: {item.name}")
+        elif isinstance(item, FunctionCallContent):
+            print(f"Function Call:> {item.name} with arguments: {item.arguments}")
+        else:
+            print(f"{item}")
+
+
 async def main() -> None:
     async with (
         DefaultAzureCredential() as creds,
         AzureAIAgent.create_client(credential=creds) as client,
     ):
         # 1. Enter your Bing Grounding Connection Name
-        bing_connection = await client.connections.get(connection_name="<your-bing-grounding-connection-name>")
+        bing_connection = await client.connections.get(name="<your-bing-grounding-connection-name>")
         conn_id = bing_connection.id
 
         # 2. Initialize agent bing tool and add the connection id
@@ -54,7 +69,9 @@ async def main() -> None:
         try:
             print(f"# User: '{TASK}'")
             # 6. Invoke the agent for the specified thread for response
-            async for response in agent.invoke(messages=TASK, thread=thread):
+            async for response in agent.invoke(
+                messages=TASK, thread=thread, on_intermediate_message=handle_intermediate_steps
+            ):
                 print(f"# {response.name}: {response}")
                 thread = response.thread
 
@@ -75,10 +92,17 @@ async def main() -> None:
         Sample Output:
 
         # User: 'Which team won the 2025 NCAA basketball championship?'
-        # BingGroundingAgent: The Florida Gators won the 2025 NCAA basketball championship, defeating the Houston Cougars 65-63 in the final to secure their third national title【3:5†source】【3:6†source】【3:9†source】.
-        Annotation :> https://www.usatoday.com/story/sports/ncaab/2025/04/07/houston-florida-live-updates-national-championship-score/82982004007/, source=【3:5†source】, with start_index=147 and end_index=159
-        Annotation :> https://bleacherreport.com/articles/25182096-winners-and-losers-2025-mens-ncaa-tournament, source=【3:6†source】, with start_index=159 and end_index=171
-        Annotation :> https://wtop.com/ncaa-basketball/2025/04/ncaa-basketball-champions/, source=【3:9†source】, with start_index=171 and end_index=183
+        Function Call:> bing_grounding with arguments: 
+            {
+                'requesturl': 'https://api.bing.microsoft.com/v7.0/search?q=search(query:2025 NCAA basketball championship winner)', 
+                'response_metadata': "{'market': 'en-US', 'num_docs_retrieved': 5, 'num_docs_actually_used': 5}"
+            }
+        # BingGroundingAgent: The team that won the 2025 NCAA men's basketball championship was the Florida Gators. They defeated the Houston Cougars with a final score of 65-63. 
+            The championship game took place in San Antonio, Texas, and the Florida team was coached by Todd Golden. This victory made Florida the national champion for the 2024-25 
+            NCAA Division I men's basketball season【3:0†source】【3:1†source】【3:2†source】.
+        Annotation :> https://en.wikipedia.org/wiki/2025_NCAA_Division_I_men%27s_basketball_championship_game, source=【3:0†source】, with start_index=357 and end_index=369
+        Annotation :> https://www.ncaa.com/history/basketball-men/d1, source=【3:1†source】, with start_index=369 and end_index=381
+        Annotation :> https://sports.yahoo.com/article/won-march-madness-2025-ncaa-100551421.html, source=【3:2†source】, with start_index=381 and end_index=393
         """  # noqa: E501
 
 

python/samples/concepts/agents/azure_ai_agent/azure_ai_agent_bing_grounding_streaming_with_message_callback.py

@@ -1,7 +1,6 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
-from functools import reduce
 
 from azure.ai.agents.models import BingGroundingTool
 from azure.identity.aio import DefaultAzureCredential
@@ -10,8 +9,8 @@
 from semantic_kernel.contents import (
     ChatMessageContent,
     FunctionCallContent,
+    FunctionResultContent,
     StreamingAnnotationContent,
-    StreamingChatMessageContent,
 )
 
 """
@@ -32,7 +31,13 @@
 
 
 async def handle_streaming_intermediate_steps(message: ChatMessageContent) -> None:
-    intermediate_steps.append(message)
+    for item in message.items or []:
+        if isinstance(item, FunctionResultContent):
+            print(f"Function Result:> {item.result} for function: {item.name}")
+        elif isinstance(item, FunctionCallContent):
+            print(f"Function Call:> {item.name} with arguments: {item.arguments}")
+        else:
+            print(f"{item}")
 
 
 async def main() -> None:
@@ -41,8 +46,7 @@ async def main() -> None:
         AzureAIAgent.create_client(credential=creds) as client,
     ):
         # 1. Enter your Bing Grounding Connection Name
-        # <your-bing-grounding-connection-name>
-        bing_connection = await client.connections.get(connection_name="skbinggrounding")
+        bing_connection = await client.connections.get(name="<your-bing-grounding-connection-name>")
         conn_id = bing_connection.id
 
         # 2. Initialize agent bing tool and add the connection id
@@ -94,41 +98,18 @@ async def main() -> None:
             await thread.delete() if thread else None
             await client.agents.delete_agent(agent.id)
 
-        print("====================================================")
-        print("\nResponse complete:\n")
-        # Combine the intermediate `StreamingChatMessageContent` chunks into a single message
-        filtered_steps = [step for step in intermediate_steps if isinstance(step, StreamingChatMessageContent)]
-        streaming_full_completion: StreamingChatMessageContent = reduce(lambda x, y: x + y, filtered_steps)
-        # Grab the other messages that are not `StreamingChatMessageContent`
-        other_steps = [s for s in intermediate_steps if not isinstance(s, StreamingChatMessageContent)]
-        final_msgs = [streaming_full_completion] + other_steps
-        for msg in final_msgs:
-            if any(isinstance(item, FunctionCallContent) for item in msg.items):
-                for item in msg.items:
-                    if isinstance(item, FunctionCallContent):
-                        # Note: the AI Projects SDK is not returning a `requesturl` for streaming events
-                        # The issue was raised with the AI Projects team
-                        print(f"Function call: {item.function_name} with arguments: {item.arguments}")
-
-            print(f"{msg.content}")
-
         """
         Sample Output:
 
         # User: 'Which team won the 2025 NCAA basketball championship?'
-        # BingGroundingAgent: The Florida Gators won the 2025 NCAA men's basketball championship, defeating the Houston Cougars 65-63. It marked Florida's third national title and their first since back-to-back wins in 2006-2007【5:0†source】
-        Annotation :> https://www.usatoday.com/story/sports/ncaab/2025/04/07/houston-florida-live-updates-national-championship-score/82982004007/, source=Florida vs Houston final score: Gators win 2025 NCAA championship, with start_index=198 and end_index=210
-        【5:5†source】
-        Annotation :> https://www.nbcsports.com/mens-college-basketball/live/florida-vs-houston-live-score-updates-game-news-stats-highlights-for-2025-ncaa-march-madness-mens-national-championship, source=Houston vs. Florida RECAP: Highlights, stats, box score, results as ..., with start_index=210 and end_index=222
-        .
-        ====================================================
-
-        Response complete:
-
-        Function call: bing_grounding with arguments: None
-        Function call: bing_grounding with arguments: None
-
-        The Florida Gators won the 2025 NCAA men's basketball championship, defeating the Houston Cougars 65-63. It marked Florida's third national title and their first since back-to-back wins in 2006-2007【5:0†source】【5:5†source】.
+        Function Call:> bing_grounding with arguments: {'requesturl': 'https://api.bing.microsoft.com/v7.0/search?q=search(query: 2025 NCAA basketball championship winner)'}
+        Function Call:> bing_grounding with arguments: {'response_metadata': "{'market': 'en-US', 'num_docs_retrieved': 5, 'num_docs_actually_used': 5}"}
+        # BingGroundingAgent: The Florida Gators won the 2025 NCAA men's basketball championship. They defeated the Houston Cougars with a close score of 65-63 in the championship game held in San Antonio, Texas. This victory marked their third national title. Florida overcame a 12-point deficit during the game to claim the championship【3:0†source】
+        Annotation :> https://en.wikipedia.org/wiki/2025_NCAA_Division_I_men%27s_basketball_championship_game, source=None, with start_index=308 and end_index=320
+        【3:1†source】
+        Annotation :> https://www.ncaa.com/history/basketball-men/d1, source=None, with start_index=320 and end_index=332
+        【3:2†source】
+        Annotation :> https://sports.yahoo.com/article/florida-gators-win-2025-ncaa-034021303.html, source=None, with start_index=332 and end_index=344.
         """  # noqa: E501
 
 

python/samples/concepts/agents/azure_ai_agent/azure_ai_agent_message_callback_streaming.py

@@ -1,13 +1,14 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
+import logging
 from typing import Annotated
 
 from azure.identity.aio import DefaultAzureCredential
 
 from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings, AzureAIAgentThread
-from semantic_kernel.contents import FunctionCallContent, FunctionResultContent
-from semantic_kernel.contents.chat_message_content import ChatMessageContent
+from semantic_kernel.contents import ChatMessageContent, FunctionCallContent, FunctionResultContent
+from semantic_kernel.core_plugins import MathPlugin
 from semantic_kernel.functions import kernel_function
 
 """
@@ -22,6 +23,8 @@
 while assistant replies stream back incrementally through the main response loop.
 """
 
+logging.basicConfig(level=logging.DEBUG)
+
 
 # Define a sample plugin for the sample
 class MenuPlugin:
@@ -67,14 +70,14 @@ async def main() -> None:
         agent_definition = await client.agents.create_agent(
             model=ai_agent_settings.model_deployment_name,
             name="Host",
-            instructions="Answer questions about the menu.",
+            instructions="Answer questions from the user using your provided functions. You must invoke multiple functions to answer the user's questions. ",  # noqa: E501
         )
 
         # Create the AzureAI Agent
         agent = AzureAIAgent(
             client=client,
             definition=agent_definition,
-            plugins=[MenuPlugin()],  # add the sample plugin to the agent
+            plugins=[MenuPlugin(), MathPlugin()],
         )
 
         # Create a thread for the agent
@@ -83,10 +86,7 @@ async def main() -> None:
         thread: AzureAIAgentThread = None
 
         user_inputs = [
-            "Hello",
-            "What is the special soup?",
-            "How much does that cost?",
-            "Thank you",
+            "What is the price of the special drink and the special food item added together?",
         ]
 
         try:
@@ -112,23 +112,21 @@ async def main() -> None:
         """
         Sample Output:
 
-        # User: 'Hello'
-        # AuthorRole.ASSISTANT: Hello! How can I assist you today?
-        # User: 'What is the special soup?'
+        # User: 'What is the price of the special drink and then special food item added together?'
         Function Call:> MenuPlugin-get_specials with arguments: {}
         Function Result:> 
                 Special Soup: Clam Chowder
                 Special Salad: Cobb Salad
                 Special Drink: Chai Tea
                 for function: MenuPlugin-get_specials
-        # AuthorRole.ASSISTANT: The special soup is Clam Chowder. Would you like to know more about it or anything 
-            else from the menu?
-        # User: 'How much does that cost?'
-        Function Call:> MenuPlugin-get_item_price with arguments: {"menu_item":"Clam Chowder"}
+        Function Call:> MenuPlugin-get_item_price with arguments: {"menu_item": "Chai Tea"}
+        Function Call:> MenuPlugin-get_item_price with arguments: {"menu_item": "Clam Chowder"}
+        Function Result:> $9.99 for function: MenuPlugin-get_item_price
         Function Result:> $9.99 for function: MenuPlugin-get_item_price
-        # AuthorRole.ASSISTANT: The Clam Chowder costs $9.99. Would you like to order it?
-        # User: 'Thank you'
-        # AuthorRole.ASSISTANT: You're welcome! Let me know if you need anything else. Enjoy your day! 😊
+        Function Call:> MathPlugin-Add with arguments: {"input":9.99,"amount":9.99}
+        Function Result:> 19.98 for function: MathPlugin-Add
+        # AuthorRole.ASSISTANT: The price of the special drink, Chai Tea, is $9.99 and the price of the special food 
+            item, Clam Chowder, is $9.99. Added together, the total price is $19.98.
         """
 
 

python/samples/getting_started_with_agents/azure_ai_agent/README.md

@@ -7,7 +7,7 @@ To set up the required resources, follow the "Quickstart: Create a new agent" gu
 You will need to install the optional Semantic Kernel `azure` dependencies if you haven't already via:
 
 ```bash
-pip install semantic-kernel[azure]
+pip install semantic-kernel
 ```
 
 Before running an Azure AI Agent, modify your .env file to include:

python/samples/getting_started_with_agents/azure_ai_agent/step6_azure_ai_agent_openapi.py

@@ -8,7 +8,7 @@
 from azure.identity.aio import DefaultAzureCredential
 
 from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings, AzureAIAgentThread
-from semantic_kernel.contents import AuthorRole
+from semantic_kernel.contents import ChatMessageContent, FunctionCallContent, FunctionResultContent
 
 """
 The following sample demonstrates how to create a simple, Azure AI agent that
@@ -23,6 +23,16 @@
 ]
 
 
+async def handle_streaming_intermediate_steps(message: ChatMessageContent) -> None:
+    for item in message.items or []:
+        if isinstance(item, FunctionResultContent):
+            print(f"Function Result:> {item.result} for function: {item.name}")
+        elif isinstance(item, FunctionCallContent):
+            print(f"Function Call:> {item.name} with arguments: {item.arguments}")
+        else:
+            print(f"{item}")
+
+
 async def main() -> None:
     async with (
         DefaultAzureCredential() as creds,
@@ -76,12 +86,11 @@ async def main() -> None:
                 print(f"# User: '{user_input}'")
                 # 7. Invoke the agent for the specified thread for response
                 async for response in agent.invoke(messages=user_input, thread=thread):
-                    if response.role != AuthorRole.TOOL:
-                        print(f"# Agent: {response}")
+                    print(f"# Agent: {response}")
                     thread = response.thread
         finally:
             # 8. Cleanup: Delete the thread and agent
-            await client.agents.threads.delete(thread.id)
+            await client.agents.threads.delete(thread.id) if thread else None
             await client.agents.delete_agent(agent.id)
 
         """

python/samples/getting_started_with_agents/azure_ai_agent/step7_azure_ai_agent_retrieval.py

@@ -5,6 +5,7 @@
 from azure.identity.aio import DefaultAzureCredential
 
 from semantic_kernel.agents import AzureAIAgent, AzureAIAgentThread
+from semantic_kernel.contents import ChatMessageContent, FunctionCallContent, FunctionResultContent
 
 """
 The following sample demonstrates how to use an already existing
@@ -16,10 +17,20 @@
 
 # Simulate a conversation with the agent
 USER_INPUTS = [
-    "Why is the sky blue?",
+    "Using the provided doc, tell me about the evolution of RAG.",
 ]
 
 
+async def handle_streaming_intermediate_steps(message: ChatMessageContent) -> None:
+    for item in message.items or []:
+        if isinstance(item, FunctionResultContent):
+            print(f"Function Result:> {item.result} for function: {item.name}")
+        elif isinstance(item, FunctionCallContent):
+            print(f"Function Call:> {item.name} with arguments: {item.arguments}")
+        else:
+            print(f"{item}")
+
+
 async def main() -> None:
     async with (
         DefaultAzureCredential() as creds,
@@ -29,7 +40,7 @@ async def main() -> None:
         # Replace the "your-agent-id" with the actual agent ID
         # you want to use.
         agent_definition = await client.agents.get_agent(
-            agent_id="your-agent-id",
+            agent_id="<your-agent-id>",
         )
 
         # 2. Create a Semantic Kernel agent for the Azure AI agent
@@ -47,8 +58,15 @@ async def main() -> None:
             for user_input in USER_INPUTS:
                 print(f"# User: '{user_input}'")
                 # 4. Invoke the agent for the specified thread for response
-                response = await agent.get_response(messages=user_input, thread=thread)
-                print(f"# {response.name}: {response}")
+                async for response in agent.invoke_stream(
+                    messages=user_input,
+                    thread=thread,
+                    on_intermediate_message=handle_streaming_intermediate_steps,
+                ):
+                    # Print the agent's response
+                    print(f"{response}", end="", flush=True)
+                    # Update the thread for subsequent messages
+                    thread = response.thread
         finally:
             # 5. Cleanup: Delete the thread and agent
             await thread.delete() if thread else None