Merge branch 'main' into dev/update_dotnet_version_1.2.0

* Gracefully handle agent scenarios when no response is returned

* Make relevant object disposable and improve exception handling.

dotnet/nuget/nuget-package.props

@@ -1,13 +1,14 @@
 <Project>
   <PropertyGroup>
     <!-- Central version prefix - applies to all nuget packages. -->
-    <VersionPrefix>1.1.0</VersionPrefix>
+    <VersionPrefix>1.2.0</VersionPrefix>
     <RCNumber>1</RCNumber>
+    <DateSuffix>260421</DateSuffix>
     <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260410.1</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260410.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).$(DateSuffix).1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.$(DateSuffix).1</PackageVersion>
     <PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
-    <GitTag>1.1.0</GitTag>
+    <GitTag>1.2.0</GitTag>
 
     <Configurations>Debug;Release;Publish</Configurations>
     <IsPackable>true</IsPackable>

dotnet/src/Microsoft.Agents.AI.Workflows.Declarative.Foundry/AzureAgentProvider.cs

@@ -4,7 +4,6 @@ using System;
 using System.ClientModel.Primitives;
 using System.Collections.Generic;
 using System.Collections.ObjectModel;
-using System.Linq;
 using System.Net.Http;
 using System.Runtime.CompilerServices;
 using System.Text.Json.Nodes;
@@ -70,7 +69,14 @@ public sealed class AzureAgentProvider(Uri projectEndpoint, TokenCredential proj
                 include: null,
                 cancellationToken).ConfigureAwait(false);
 
-        return newItems.AsChatMessages().Single();
+        ChatMessage[] createdMessages = [.. newItems.AsChatMessages()];
+        if (createdMessages.Length != 1)
+        {
+            throw new InvalidOperationException(
+                $"Expected exactly one chat message from created conversation item in conversation '{conversationId}', but got {createdMessages.Length}.");
+        }
+
+        return createdMessages[0];
 
         IEnumerable<ResponseItem> GetResponseItems()
         {
@@ -208,7 +214,14 @@ public sealed class AzureAgentProvider(Uri projectEndpoint, TokenCredential proj
     {
         AgentResponseItem responseItem = await this.GetConversationClient().GetProjectConversationItemAsync(conversationId, messageId, include: null, cancellationToken).ConfigureAwait(false);
         ResponseItem[] items = [responseItem.AsResponseResultItem()];
-        return items.AsChatMessages().Single();
+        ChatMessage[] messages = [.. items.AsChatMessages()];
+        if (messages.Length != 1)
+        {
+            throw new InvalidOperationException(
+                $"Expected exactly one chat message for message '{messageId}' in conversation '{conversationId}', but got {messages.Length}.");
+        }
+
+        return messages[0];
     }
 
     /// <inheritdoc/>

dotnet/src/Microsoft.Agents.AI.Workflows.Declarative/ObjectModel/InvokeAzureAgentExecutor.cs

@@ -49,7 +49,11 @@ internal sealed class InvokeAzureAgentExecutor(InvokeAzureAgent model, ResponseA
 
     public async ValueTask ResumeAsync(IWorkflowContext context, ExternalInputResponse response, CancellationToken cancellationToken)
     {
-        await context.SetLastMessageAsync(response.Messages.Last()).ConfigureAwait(false);
+        ChatMessage? lastMessage = response.Messages.LastOrDefault();
+        if (lastMessage is not null)
+        {
+            await context.SetLastMessageAsync(lastMessage).ConfigureAwait(false);
+        }
         await this.InvokeAgentAsync(context, response.Messages, cancellationToken).ConfigureAwait(false);
     }
 
@@ -85,15 +89,19 @@ internal sealed class InvokeAzureAgentExecutor(InvokeAzureAgent model, ResponseA
         await this.AssignAsync(this.AgentOutput?.Messages?.Path, agentResponse.Messages.ToTable(), context).ConfigureAwait(false);
 
         // Attempt to parse the last message as JSON and assign to the response object variable.
-        try
+        string? lastMessageText = agentResponse.Messages.LastOrDefault()?.Text;
+        if (!string.IsNullOrEmpty(lastMessageText))
         {
-            JsonDocument jsonDocument = JsonDocument.Parse(agentResponse.Messages.Last().Text);
-            Dictionary<string, object?> objectProperties = jsonDocument.ParseRecord(VariableType.RecordType);
-            await this.AssignAsync(this.AgentOutput?.ResponseObject?.Path, objectProperties.ToFormula(), context).ConfigureAwait(false);
-        }
-        catch
-        {
-            // Not valid json, skip assignment.
+            try
+            {
+                using JsonDocument jsonDocument = JsonDocument.Parse(lastMessageText);
+                Dictionary<string, object?> objectProperties = jsonDocument.ParseRecord(VariableType.RecordType);
+                await this.AssignAsync(this.AgentOutput?.ResponseObject?.Path, objectProperties.ToFormula(), context).ConfigureAwait(false);
+            }
+            catch (JsonException)
+            {
+                // Not valid json, skip assignment.
+            }
         }
 
         if (this.Model.Input?.ExternalLoop?.When is not null)

dotnet/src/Microsoft.Agents.AI.Workflows.Declarative/ObjectModel/QuestionExecutor.cs

@@ -122,10 +122,13 @@ internal sealed class QuestionExecutor(Question model, ResponseAgentProvider age
                 string? workflowConversationId = context.GetWorkflowConversation();
                 if (workflowConversationId is not null)
                 {
-                    // Input message always defined if values has been extracted.
-                    ChatMessage input = response.Messages.Last();
-                    await agentProvider.CreateMessageAsync(workflowConversationId, input, cancellationToken).ConfigureAwait(false);
-                    await context.SetLastMessageAsync(input).ConfigureAwait(false);
+                    // Input message expected to be defined when values have been extracted, but guard defensively.
+                    ChatMessage? input = response.Messages.LastOrDefault();
+                    if (input is not null)
+                    {
+                        await agentProvider.CreateMessageAsync(workflowConversationId, input, cancellationToken).ConfigureAwait(false);
+                        await context.SetLastMessageAsync(input).ConfigureAwait(false);
+                    }
                 }
             }
 

dotnet/src/Microsoft.Agents.AI.Workflows.Declarative/ObjectModel/RequestExternalInputExecutor.cs

@@ -45,7 +45,11 @@ internal sealed class RequestExternalInputExecutor(RequestExternalInput model, R
                 await agentProvider.CreateMessageAsync(workflowConversationId, inputMessage, cancellationToken).ConfigureAwait(false);
             }
         }
-        await context.SetLastMessageAsync(response.Messages.Last()).ConfigureAwait(false);
+        ChatMessage? lastMessage = response.Messages.LastOrDefault();
+        if (lastMessage is not null)
+        {
+            await context.SetLastMessageAsync(lastMessage).ConfigureAwait(false);
+        }
         await this.AssignAsync(this.Model.Variable?.Path, response.Messages.ToFormula(), context).ConfigureAwait(false);
 
         await context.RaiseCompletionEventAsync(this.Model, cancellationToken).ConfigureAwait(false);

dotnet/src/Microsoft.Agents.AI.Workflows/Specialized/HandoffAgentExecutor.cs

@@ -426,7 +426,7 @@ internal sealed class HandoffAgentExecutor :
                     {
                         AgentId = this._agent.Id,
                         AuthorName = this._agent.Name ?? this._agent.Id,
-                        Contents = [new FunctionResultContent(handoffRequest.CallId, "Transferred.")],
+                        Contents = [CreateHandoffResult(handoffRequest.CallId)],
                         CreatedAt = DateTimeOffset.UtcNow,
                         MessageId = Guid.NewGuid().ToString("N"),
                         Role = ChatRole.Tool,
@@ -459,4 +459,6 @@ internal sealed class HandoffAgentExecutor :
              ? this._handoffFunctionToAgentId.TryGetValue(requestedHandoff, out string? targetId) ? targetId : null
              : null;
     }
+
+    internal static FunctionResultContent CreateHandoffResult(string requestCallId) => new(requestCallId, "Transferred.");
 }

dotnet/src/Microsoft.Agents.AI.Workflows/Specialized/HandoffMessagesFilter.cs

@@ -3,7 +3,6 @@
 using System;
 using System.Collections.Generic;
 using System.Diagnostics.CodeAnalysis;
-using System.Linq;
 using Microsoft.Extensions.AI;
 
 namespace Microsoft.Agents.AI.Workflows.Specialized;
@@ -31,113 +30,78 @@ internal sealed class HandoffMessagesFilter
             return messages;
         }
 
-        Dictionary<string, FilterCandidateState> filteringCandidates = new();
-        List<ChatMessage> filteredMessages = [];
-        HashSet<int> messagesToRemove = [];
+        HashSet<string> filteredCallsWithoutResponses = new();
+        List<ChatMessage> retainedMessages = [];
+
+        bool filterAllToolCalls = this._filteringBehavior == HandoffToolCallFilteringBehavior.All;
+
+        // The logic of filtering is fairly straightforward: We are only interested in FunctionCallContent and FunctionResponseContent.
+        // We are going to assume that Handoff operates as follows:
+        //  * Each agent is only taking one turn at a time
+        //  * Each agent is taking a turn alone
+        //
+        // In the case of certain providers, like Gemini (see microsoft/agent-framework #5244), we will see the function call name as the
+        // call id as well, so we may see multiple calls with the same call id, and assume that the call is terminated before another
+        // "CallId-less" FCC is issued. We also need to rely on the idea that FRC follows their corresponding FCC in the message stream.
+        // (This changes the previous behaviour where FRC could arrive earlier, and relies on strict ordering).
+        //
+        // The benefit of expecting all the AIContent to be strictly ordered is that we never need to reach back into a post-filtered
+        // content to retroactively remove it, or to try to inject it back into the middle of a Message that has already been processed.
 
-        bool filterHandoffOnly = this._filteringBehavior == HandoffToolCallFilteringBehavior.HandoffOnly;
         foreach (ChatMessage unfilteredMessage in messages)
         {
-            ChatMessage filteredMessage = unfilteredMessage.Clone();
-
-            // .Clone() is shallow, so we cannot modify the contents of the cloned message in place.
-            List<AIContent> contents = [];
-            contents.Capacity = unfilteredMessage.Contents?.Count ?? 0;
-            filteredMessage.Contents = contents;
-
-            // Because this runs after the role changes from assistant to user for the target agent, we cannot rely on tool calls
-            // originating only from messages with the Assistant role. Instead, we need to inspect the contents of all non-Tool (result)
-            // FunctionCallContent.
-            if (unfilteredMessage.Role != ChatRole.Tool)
+            if (unfilteredMessage.Contents is null || unfilteredMessage.Contents.Count == 0)
             {
-                for (int i = 0; i < unfilteredMessage.Contents!.Count; i++)
-                {
-                    AIContent content = unfilteredMessage.Contents[i];
-                    if (content is not FunctionCallContent fcc || (filterHandoffOnly && !IsHandoffFunctionName(fcc.Name)))
-                    {
-                        filteredMessage.Contents.Add(content);
-
-                        // Track non-handoff function calls so their tool results are preserved in HandoffOnly mode
-                        if (filterHandoffOnly && content is FunctionCallContent nonHandoffFcc)
-                        {
-                            filteringCandidates[nonHandoffFcc.CallId] = new FilterCandidateState(nonHandoffFcc.CallId)
-                            {
-                                IsHandoffFunction = false,
-                            };
-                        }
-                    }
-                    else if (filterHandoffOnly)
-                    {
-                        if (!filteringCandidates.TryGetValue(fcc.CallId, out FilterCandidateState? candidateState))
-                        {
-                            filteringCandidates[fcc.CallId] = new FilterCandidateState(fcc.CallId)
-                            {
-                                IsHandoffFunction = true,
-                            };
-                        }
-                        else
-                        {
-                            candidateState.IsHandoffFunction = true;
-                            (int messageIndex, int contentIndex) = candidateState.FunctionCallResultLocation!.Value;
-                            ChatMessage messageToFilter = filteredMessages[messageIndex];
-                            messageToFilter.Contents.RemoveAt(contentIndex);
-                            if (messageToFilter.Contents.Count == 0)
-                            {
-                                messagesToRemove.Add(messageIndex);
-                            }
-                        }
-                    }
-                    else
-                    {
-                        // All mode: strip all FunctionCallContent
-                    }
-                }
+                retainedMessages.Add(unfilteredMessage);
+                continue;
             }
-            else
+
+            // We may need to filter out a subset of the message's content, but we won't know until we iterate through it. Create a new list
+            // of AIContent which we will stuff into a clone of the message if we need to filter out any content.
+            List<AIContent> retainedContents = new(capacity: unfilteredMessage.Contents.Count);
+
+            foreach (AIContent content in unfilteredMessage.Contents)
             {
-                if (!filterHandoffOnly)
+                if (content is FunctionCallContent fcc
+                    && (filterAllToolCalls || IsHandoffFunctionName(fcc.Name)))
                 {
+                    // If we already have an unmatched candidate with the same CallId, that means we have two FCCs in a row without an FRC,
+                    // which violates our assumption of strict ordering.
+                    if (!filteredCallsWithoutResponses.Add(fcc.CallId))
+                    {
+                        throw new InvalidOperationException($"Duplicate FunctionCallContent with CallId '{fcc.CallId}' without corresponding FunctionResultContent.");
+                    }
+
+                    // If we are filtering all tool calls, or this is a handoff call (and we are not filtering None, already checked), then
+                    // filter this FCC
                     continue;
                 }
-
-                for (int i = 0; i < unfilteredMessage.Contents!.Count; i++)
+                else if (content is FunctionResultContent frc)
                 {
-                    AIContent content = unfilteredMessage.Contents[i];
-                    if (content is not FunctionResultContent frc
-                        || (filteringCandidates.TryGetValue(frc.CallId, out FilterCandidateState? candidateState)
-                            && candidateState.IsHandoffFunction is false))
+                    // We rely on the corresponding FCC to have already been processed, so check if it is in the candidate dictionary.
+                    // If it is, we can filter out the FRC, but we need to remove the candidate from the dictionary, since a future FCC can
+                    // come in with the same CallId, and should be considered a new call that may need to be filtered.
+                    if (filteredCallsWithoutResponses.Remove(frc.CallId))
                     {
-                        // Either this is not a function result content, so we should let it through, or it is a FRC that
-                        // we know is not related to a handoff call. In either case, we should include it.
-                        filteredMessage.Contents.Add(content);
+                        continue;
                     }
-                    else if (candidateState is null)
-                    {
-                        // We haven't seen the corresponding function call yet, so add it as a candidate to be filtered later
-                        filteringCandidates[frc.CallId] = new FilterCandidateState(frc.CallId)
-                        {
-                            FunctionCallResultLocation = (filteredMessages.Count, filteredMessage.Contents.Count),
-                        };
-                    }
-                    // else we have seen the corresponding function call and it is a handoff, so we should filter it out.
                 }
+
+                // FCC/FRC, but not filtered, or neither FCC nor FRC: this should not be filtered out
+                retainedContents.Add(content);
             }
 
-            if (filteredMessage.Contents.Count > 0)
+            if (retainedContents.Count == 0)
             {
-                filteredMessages.Add(filteredMessage);
+                // message was fully filtered, skip it
+                continue;
             }
+
+            ChatMessage filteredMessage = unfilteredMessage.Clone();
+            filteredMessage.Contents = retainedContents;
+            retainedMessages.Add(filteredMessage);
         }
 
-        return filteredMessages.Where((_, index) => !messagesToRemove.Contains(index));
-    }
-
-    private class FilterCandidateState(string callId)
-    {
-        public (int MessageIndex, int ContentIndex)? FunctionCallResultLocation { get; set; }
-
-        public string CallId => callId;
-
-        public bool? IsHandoffFunction { get; set; }
+        return retainedMessages;
     }
 }

dotnet/tests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests/ObjectModel/RequestExternalInputExecutorTest.cs

@@ -85,6 +85,29 @@ public sealed class RequestExternalInputExecutorTest(ITestOutputHelper output) :
             expectMessagesCreated: true);
     }
 
+    [Fact]
+    public async Task CaptureResponseWithEmptyMessagesAsync()
+    {
+        await this.CaptureResponseTestAsync(
+            displayName: nameof(CaptureResponseWithEmptyMessagesAsync),
+            variableName: "TestVariable",
+            messageCount: 0);
+    }
+
+    [Fact]
+    public async Task CaptureResponseWithEmptyMessagesAndWorkflowConversationAsync()
+    {
+        // Arrange
+        this.State.Set(SystemScope.Names.ConversationId, FormulaValue.New("WorkflowConversationId"), VariableScopeNames.System);
+
+        // Act & Assert
+        await this.CaptureResponseTestAsync(
+            displayName: nameof(CaptureResponseWithEmptyMessagesAndWorkflowConversationAsync),
+            variableName: "TestVariable",
+            messageCount: 0,
+            expectMessagesCreated: false);
+    }
+
     private async Task ExecuteTestAsync(
         string displayName,
         string variableName)

dotnet/tests/Microsoft.Agents.AI.Workflows.UnitTests/HandoffMessageFilterTests.cs

@@ -0,0 +1,115 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System;
+using System.Collections.Generic;
+using FluentAssertions;
+using Microsoft.Agents.AI.Workflows.Specialized;
+using Microsoft.Extensions.AI;
+
+namespace Microsoft.Agents.AI.Workflows.UnitTests;
+
+public class HandoffMessageFilterTests
+{
+    private List<ChatMessage> CreateTestMessages(bool firstAgentUsesCallId, bool secondAgentUsesCallId, HandoffToolCallFilteringBehavior filter = HandoffToolCallFilteringBehavior.None)
+    {
+        FunctionCallContent handoffRequest1 = CreateHandoffCall(1, firstAgentUsesCallId);
+        FunctionResultContent handoffResponse1 = CreateHandoffResponse(handoffRequest1);
+
+        FunctionCallContent toolCall = CreateToolCall(secondAgentUsesCallId);
+        FunctionResultContent toolResponse = CreateToolResponse(toolCall);
+
+        // Approvals come from the function call middleware over ChatClient, so we can expect there to be a RequestId (not that we
+        // care, because we do not filter approval content)
+        ToolApprovalRequestContent toolApproval = new(Guid.NewGuid().ToString("N"), toolCall);
+        ToolApprovalResponseContent toolApprovalResponse = new(toolApproval.RequestId, true, toolCall);
+
+        FunctionCallContent handoffRequest2 = CreateHandoffCall(1, secondAgentUsesCallId);
+        FunctionResultContent handoffResponse2 = CreateHandoffResponse(handoffRequest2);
+
+        List<ChatMessage> result = [new(ChatRole.User, "Hello")];
+
+        // Agent 1 turn
+        result.Add(new(ChatRole.Assistant, "Hello! What do you want help with today?"));
+        result.Add(new(ChatRole.User, "Please explain temperature"));
+
+        // Unless we are filtering none, we expect the handoff call to be filtered out, so we add it conditionally
+        if (filter == HandoffToolCallFilteringBehavior.None)
+        {
+            result.Add(new(ChatRole.Assistant, [handoffRequest1]));
+            result.Add(new(ChatRole.Tool, [handoffResponse1]));
+        }
+
+        // Agent 2 turn
+
+        // Tool approvals are never filtered, so we add them unconditionally
+        result.Add(new(ChatRole.Assistant, [toolApproval]));
+        result.Add(new(ChatRole.User, [toolApprovalResponse]));
+
+        // Unless we are filtering all, we expect the tool call to be retained, so we add it conditionally
+        if (filter != HandoffToolCallFilteringBehavior.All)
+        {
+            result.Add(new(ChatRole.Assistant, [toolCall]));
+            result.Add(new(ChatRole.Tool, [toolResponse]));
+        }
+
+        result.Add(new(ChatRole.Assistant, "Temperature is a measure of the average kinetic energy of the particles in a substance."));
+
+        if (filter == HandoffToolCallFilteringBehavior.None)
+        {
+            result.Add(new(ChatRole.Assistant, [handoffRequest2]));
+            result.Add(new(ChatRole.Tool, [handoffResponse2]));
+        }
+
+        return result;
+    }
+
+    private static FunctionCallContent CreateHandoffCall(int id, bool useCallId)
+    {
+        string callName = $"{HandoffWorkflowBuilder.FunctionPrefix}{id}";
+        string callId = useCallId ? Guid.NewGuid().ToString("N") : callName;
+
+        return new FunctionCallContent(callId, callName);
+    }
+
+    private static FunctionResultContent CreateHandoffResponse(FunctionCallContent call)
+        => HandoffAgentExecutor.CreateHandoffResult(call.CallId);
+
+    private static FunctionCallContent CreateToolCall(bool useCallId)
+    {
+        const string CallName = "ToolFunction";
+        string callId = useCallId ? Guid.NewGuid().ToString("N") : CallName;
+
+        return new FunctionCallContent(callId, CallName);
+    }
+
+    private static FunctionResultContent CreateToolResponse(FunctionCallContent call)
+        => new(call.CallId, new object());
+
+    [Theory]
+    [InlineData(true, true, HandoffToolCallFilteringBehavior.None)]
+    [InlineData(true, false, HandoffToolCallFilteringBehavior.None)]
+    [InlineData(false, true, HandoffToolCallFilteringBehavior.None)]
+    [InlineData(false, false, HandoffToolCallFilteringBehavior.None)]
+    [InlineData(true, true, HandoffToolCallFilteringBehavior.HandoffOnly)]
+    [InlineData(true, false, HandoffToolCallFilteringBehavior.HandoffOnly)]
+    [InlineData(false, true, HandoffToolCallFilteringBehavior.HandoffOnly)]
+    [InlineData(false, false, HandoffToolCallFilteringBehavior.HandoffOnly)]
+    [InlineData(true, true, HandoffToolCallFilteringBehavior.All)]
+    [InlineData(true, false, HandoffToolCallFilteringBehavior.All)]
+    [InlineData(false, true, HandoffToolCallFilteringBehavior.All)]
+    [InlineData(false, false, HandoffToolCallFilteringBehavior.All)]
+    public void Test_HandoffMessageFilter_FiltersOnlyExpectedMessages(bool firstAgentUsesCallId, bool secondAgentUsesCallId, HandoffToolCallFilteringBehavior behavior)
+    {
+        // Arrange
+        List<ChatMessage> messages = this.CreateTestMessages(firstAgentUsesCallId, secondAgentUsesCallId);
+        List<ChatMessage> expected = this.CreateTestMessages(firstAgentUsesCallId, secondAgentUsesCallId, behavior);
+
+        HandoffMessagesFilter filter = new(behavior);
+
+        // Act
+        IEnumerable<ChatMessage> filteredMessages = filter.FilterMessages(messages);
+
+        // Assert
+        filteredMessages.Should().BeEquivalentTo(expected);
+    }
+}

python/packages/core/tests/core/test_types.py

@@ -664,6 +664,21 @@ def test_function_approval_serialization_roundtrip():
     # The Content union will need to be handled differently when we fully migrate
 
 
+def test_function_approval_request_function_call_none_guard():
+    """Test that accessing function_call attributes is safe when function_call is None."""
+    # Construct a Content with type "function_approval_request" but no function_call.
+    # This verifies the None-guard pattern used in samples to prevent AttributeError.
+    content = Content("function_approval_request", id="req-none")
+    assert content.function_call is None
+
+    # A proper approval request always has function_call set
+    fc = Content.from_function_call(call_id="call-1", name="do_something", arguments={"a": 1})
+    req = Content.from_function_approval_request(id="req-1", function_call=fc)
+    assert req.function_call is not None
+    assert req.function_call.name == "do_something"
+    assert req.function_call.arguments == {"a": 1}
+
+
 def test_function_approval_accepts_mcp_call():
     """Ensure FunctionApprovalRequestContent supports MCP server tool calls."""
     mcp_call = Content.from_mcp_server_tool_call(

python/samples/03-workflows/tool-approval/concurrent_builder_tool_approval.py

@@ -29,19 +29,19 @@ approval will pause the workflow until the human responds.
 
 This sample works as follows:
 1. A ConcurrentBuilder workflow is created with two agents running in parallel.
-2. Both agents have the same tools, including one requiring approval (execute_trade).
+2. Both agents have the same tools, including two requiring approval (execute_trade, set_stop_loss).
 3. Both agents receive the same task and work concurrently on their respective stocks.
-4. When either agent tries to execute a trade, it triggers an approval request.
+4. When either agent tries to execute a trade or set a stop-loss, it triggers an approval request.
 5. The sample simulates human approval and the workflow completes.
 6. Results from both agents are aggregated and output.
 
 Purpose:
 Show how tool call approvals work in parallel execution scenarios where multiple
-agents may independently trigger approval requests.
+agents may independently trigger approval requests for different tools.
 
 Demonstrate:
 - Handling multiple approval requests from different agents in concurrent workflows.
-- Handling  during concurrent agent execution.
+- Handling approval requests for different tools during concurrent agent execution.
 - Understanding that approval pauses only the agent that triggered it, not all agents.
 
 Prerequisites:
@@ -89,6 +89,15 @@ def execute_trade(
     return f"Trade executed: {action.upper()} {quantity} shares of {symbol.upper()}"
 
 
+@tool(approval_mode="always_require")
+def set_stop_loss(
+    symbol: Annotated[str, "The stock ticker symbol"],
+    stop_price: Annotated[float, "The stop-loss price"],
+) -> str:
+    """Set a stop-loss order for a stock. Requires human approval due to financial impact."""
+    return f"Stop-loss set for {symbol.upper()} at ${stop_price:.2f}"
+
+
 @tool(approval_mode="never_require")
 def get_portfolio_balance() -> str:
     """Get current portfolio balance and available funds."""
@@ -118,14 +127,17 @@ async def process_event_stream(stream: AsyncIterable[WorkflowEvent]) -> dict[str
         if event.type == "request_info" and isinstance(event.data, Content):
             # We are only expecting tool approval requests in this sample
             requests[event.request_id] = event.data
+            if event.data.type == "function_approval_request" and event.data.function_call is not None:
+                print(f"\nApproval requested for tool: {event.data.function_call.name}")
+                print(f"Arguments: {event.data.function_call.arguments}")
         elif event.type == "output":
             _print_output(event)
 
     responses: dict[str, Content] = {}
     if requests:
         for request_id, request in requests.items():
-            if request.type == "function_approval_request":
-                print(f"\nSimulating human approval for: {request.function_call.name}")  # type: ignore
+            if request.type == "function_approval_request" and request.function_call is not None:
+                print(f"\nSimulating human approval for: {request.function_call.name}")
                 # Create approval response
                 responses[request_id] = request.to_function_approval_response(approved=True)
 
@@ -145,9 +157,10 @@ async def main() -> None:
         name="MicrosoftAgent",
         instructions=(
             "You are a personal trading assistant focused on Microsoft (MSFT). "
-            "You manage my portfolio and take actions based on market data."
+            "You manage my portfolio and take actions based on market data. "
+            "Use stop-loss orders to manage risk."
         ),
-        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade],
+        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade, set_stop_loss],
     )
 
     google_agent = Agent(
@@ -155,9 +168,10 @@ async def main() -> None:
         name="GoogleAgent",
         instructions=(
             "You are a personal trading assistant focused on Google (GOOGL). "
-            "You manage my trades and portfolio based on market conditions."
+            "You manage my trades and portfolio based on market conditions. "
+            "Use stop-loss orders to manage risk."
         ),
-        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade],
+        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade, set_stop_loss],
     )
 
     # 4. Build a concurrent workflow with both agents
@@ -172,7 +186,8 @@ async def main() -> None:
     # Runs are not isolated; state is preserved across multiple calls to run.
     stream = workflow.run(
         "Manage my portfolio. Use a max of 5000 dollars to adjust my position using "
-        "your best judgment based on market sentiment. No need to confirm trades with me.",
+        "your best judgment based on market sentiment. Set stop-loss orders to manage risk. "
+        "No need to confirm trades with me.",
         stream=True,
     )
 
@@ -191,22 +206,32 @@ async def main() -> None:
     Approval requested for tool: execute_trade
     Arguments: {"symbol":"MSFT","action":"buy","quantity":13}
 
+    Approval requested for tool: set_stop_loss
+    Arguments: {"symbol":"MSFT","stop_price":340.0}
+
     Approval requested for tool: execute_trade
     Arguments: {"symbol":"GOOGL","action":"buy","quantity":35}
 
-    Simulating human approval for: execute_trade
+    Approval requested for tool: set_stop_loss
+    Arguments: {"symbol":"GOOGL","stop_price":126.0}
 
     Simulating human approval for: execute_trade
 
+    Simulating human approval for: set_stop_loss
+
+    Simulating human approval for: execute_trade
+
+    Simulating human approval for: set_stop_loss
+
     ------------------------------------------------------------
     Workflow completed. Aggregated results from both agents:
     - user: Manage my portfolio. Use a max of 5000 dollars to adjust my position using your best judgment based on
-            market sentiment. No need to confirm trades with me.
-    - MicrosoftAgent: I have successfully executed the trade, purchasing 13 shares of Microsoft (MSFT). This action
-                      was based on the positive market sentiment and available funds within the specified limit.
-                      Your portfolio has been adjusted accordingly.
-    - GoogleAgent: I have successfully executed the trade, purchasing 35 shares of GOOGL. If you need further
-                   assistance or any adjustments, feel free to ask!
+            market sentiment. Set stop-loss orders to manage risk. No need to confirm trades with me.
+    - MicrosoftAgent: I have successfully purchased 13 shares of Microsoft (MSFT) and set a stop-loss at $340.00.
+                      This action was based on the positive market sentiment and available funds within the
+                      specified limit. Your portfolio has been adjusted accordingly.
+    - GoogleAgent: I have successfully purchased 35 shares of GOOGL and set a stop-loss at $126.00. If you need
+                   further assistance or any adjustments, feel free to ask!
     """
 
 

python/samples/03-workflows/tool-approval/group_chat_builder_tool_approval.py

@@ -121,11 +121,11 @@ async def process_event_stream(stream: AsyncIterable[WorkflowEvent]) -> dict[str
     responses: dict[str, Content] = {}
     if requests:
         for request_id, request in requests.items():
-            if request.type == "function_approval_request":
+            if request.type == "function_approval_request" and request.function_call is not None:
                 print("\n[APPROVAL REQUIRED]")
-                print(f"  Tool: {request.function_call.name}")  # type: ignore
-                print(f"  Arguments: {request.function_call.arguments}")  # type: ignore
-                print(f"Simulating human approval for: {request.function_call.name}")  # type: ignore
+                print(f"  Tool: {request.function_call.name}")
+                print(f"  Arguments: {request.function_call.arguments}")
+                print(f"Simulating human approval for: {request.function_call.name}")
                 # Create approval response
                 responses[request_id] = request.to_function_approval_response(approved=True)
 

python/samples/03-workflows/tool-approval/sequential_builder_tool_approval.py

@@ -94,11 +94,11 @@ async def process_event_stream(stream: AsyncIterable[WorkflowEvent]) -> dict[str
     responses: dict[str, Content] = {}
     if requests:
         for request_id, request in requests.items():
-            if request.type == "function_approval_request":
+            if request.type == "function_approval_request" and request.function_call is not None:
                 print("\n[APPROVAL REQUIRED]")
-                print(f"  Tool: {request.function_call.name}")  # type: ignore
-                print(f"  Arguments: {request.function_call.arguments}")  # type: ignore
-                print(f"Simulating human approval for: {request.function_call.name}")  # type: ignore
+                print(f"  Tool: {request.function_call.name}")
+                print(f"  Arguments: {request.function_call.arguments}")
+                print(f"Simulating human approval for: {request.function_call.name}")
                 # Create approval response
                 responses[request_id] = request.to_function_approval_response(approved=True)