use as* asyncio.gather is used to make function tool calls in paral… (#41311)

* use as* `asyncio.gather` is used to make function tool calls in parallel for `async` scenario.

* Fixed version

* update

Author: howieleung

sdk/ai/azure-ai-agents/CHANGELOG.md

@@ -1,10 +1,12 @@
 # Release History
 
-## 1.1.0b1 (2025-05-20)
+## 1.0.1 (2025-05-20)
 
 ### Bugs Fixed
 
-* Adding instrumentation for create_thread_and_run
+* `asyncio.gather` is used to make function tool calls in parallel for `async` scenario.
+
+* Adding instrumentation for create_thread_and_run.
 
 ## 1.0.0 (2025-05-15)
 

sdk/ai/azure-ai-agents/azure/ai/agents/_version.py

@@ -6,4 +6,4 @@
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
 
-VERSION = "1.1.0b1"
+VERSION = "1.0.1"

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

@@ -1219,29 +1219,27 @@ def validate_tool_type(self, tool: Tool) -> None:
                 + "Please use AsyncFunctionTool instead and provide sync and/or async function(s)."
             )
 
+    async def _execute_single_tool_call(self, tool_call: Any):
+        try:
+            tool = self.get_tool(AsyncFunctionTool)
+            output = await tool.execute(tool_call)
+            return {"tool_call_id": tool_call.id, "output": str(output)}
+        except Exception as e:  # pylint: disable=broad-exception-caught
+            return {"tool_call_id": tool_call.id, "output": str(e)}
+
     async def execute_tool_calls(self, tool_calls: List[Any]) -> Any:
         """
-        Execute a tool of the specified type with the provided tool calls.
+        Execute a tool of the specified type with the provided tool calls concurrently.
 
         :param List[Any] tool_calls: A list of tool calls to execute.
         :return: The output of the tool operations.
         :rtype: Any
         """
-        tool_outputs = []
 
-        for tool_call in tool_calls:
-            try:
-                if tool_call.type == "function":
-                    tool = self.get_tool(AsyncFunctionTool)
-                    output = await tool.execute(tool_call)
-                    tool_output = {
-                        "tool_call_id": tool_call.id,
-                        "output": str(output),
-                    }
-                    tool_outputs.append(tool_output)
-            except Exception as e:  # pylint: disable=broad-exception-caught
-                tool_output = {"tool_call_id": tool_call.id, "output": str(e)}
-                tool_outputs.append(tool_output)
+        # Execute all tool calls concurrently
+        tool_outputs = await asyncio.gather(
+            *[self._execute_single_tool_call(tc) for tc in tool_calls if tc.type == "function"]
+        )
 
         return tool_outputs
 

sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_functions_async.py

@@ -18,9 +18,9 @@
     pip install azure-ai-agents azure-identity aiohttp
 
     Set these environment variables with your own values:
-    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview 
+    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
                           page of your Azure AI Foundry portal.
-    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in 
+    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
        the "Models + endpoints" tab in your Azure AI Foundry project.
 """
 import asyncio
@@ -29,6 +29,7 @@
 from azure.ai.agents.aio import AgentsClient
 from azure.ai.agents.models import (
     AsyncFunctionTool,
+    AsyncToolSet,
     RequiredFunctionToolCall,
     SubmitToolOutputsAction,
     ToolOutput,
@@ -44,6 +45,8 @@ async def main() -> None:
         async with AgentsClient(endpoint=os.environ["PROJECT_ENDPOINT"], credential=creds) as agents_client:
             # Initialize agent functions
             functions = AsyncFunctionTool(functions=user_async_functions)
+            toolset = AsyncToolSet()
+            toolset.add(functions)
 
             # Create agent
             agent = await agents_client.create_agent(
@@ -80,19 +83,7 @@ async def main() -> None:
                         await agents_client.runs.cancel(thread_id=thread.id, run_id=run.id)
                         break
 
-                    tool_outputs = []
-                    for tool_call in tool_calls:
-                        if isinstance(tool_call, RequiredFunctionToolCall):
-                            try:
-                                output = await functions.execute(tool_call)
-                                tool_outputs.append(
-                                    ToolOutput(
-                                        tool_call_id=tool_call.id,
-                                        output=output,
-                                    )
-                                )
-                            except Exception as e:
-                                print(f"Error executing tool_call {tool_call.id}: {e}")
+                    tool_outputs = await toolset.execute_tool_calls(tool_calls)
 
                     print(f"Tool outputs: {tool_outputs}")
                     if tool_outputs:

sdk/ai/azure-ai-agents/samples/agents_async/sample_agents_stream_eventhandler_with_functions_async.py

@@ -17,7 +17,7 @@
     pip install azure-ai-agents azure-identity aiohttp
 
     Set these environment variables with your own values:
-    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview 
+    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
                           page of your Azure AI Foundry portal.
     2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model.
 """
@@ -29,6 +29,7 @@
 from azure.ai.agents.models import (
     AsyncAgentEventHandler,
     AsyncFunctionTool,
+    AsyncToolSet,
     ListSortOrder,
     MessageTextContent,
     MessageDeltaChunk,
@@ -42,6 +43,11 @@
 from azure.identity.aio import DefaultAzureCredential
 from utils.user_async_functions import user_async_functions
 
+# Initialize function tool with user functions
+functions = AsyncFunctionTool(functions=user_async_functions)
+toolset = AsyncToolSet()
+toolset.add(functions)
+
 
 class MyEventHandler(AsyncAgentEventHandler[str]):
 
@@ -65,21 +71,8 @@ async def on_thread_run(self, run: "ThreadRun") -> None:
         if run.status == "requires_action" and isinstance(run.required_action, SubmitToolOutputsAction):
             tool_calls = run.required_action.submit_tool_outputs.tool_calls
 
-            tool_outputs = []
-            for tool_call in tool_calls:
-                if isinstance(tool_call, RequiredFunctionToolCall):
-                    try:
-                        output = await self.functions.execute(tool_call)
-                        tool_outputs.append(
-                            ToolOutput(
-                                tool_call_id=tool_call.id,
-                                output=output,
-                            )
-                        )
-                    except Exception as e:
-                        print(f"Error executing tool_call {tool_call.id}: {e}")
-
-            print(f"Tool outputs: {tool_outputs}")
+            tool_outputs = await toolset.execute_tool_calls(tool_calls)
+
             if tool_outputs:
                 await self.agents_client.runs.submit_tool_outputs_stream(
                     thread_id=run.thread_id, run_id=run.id, tool_outputs=tool_outputs, event_handler=self
@@ -105,16 +98,12 @@ async def main() -> None:
             credential=creds,
         ) as agents_client:
 
-            # [START create_agent_with_function_tool]
-            functions = AsyncFunctionTool(functions=user_async_functions)
-
             agent = await agents_client.create_agent(
                 model=os.environ["MODEL_DEPLOYMENT_NAME"],
                 name="my-agent",
                 instructions="You are a helpful agent",
                 tools=functions.definitions,
             )
-            # [END create_agent_with_function_tool]
             print(f"Created agent, ID: {agent.id}")
 
             thread = await agents_client.threads.create()