Add azure-monitor-opentelemetry to dev deps

Fixes Samples & Markdown CI failure. The PR's new transitive dep on
azure-monitor-opentelemetry-exporter (via azure-ai-agentserver-core) makes
pyright resolve the azure.monitor.opentelemetry namespace, flipping the
check_md_code_blocks diagnostic for `configure_azure_monitor` from
reportMissingImports (filtered) to reportAttributeAccessIssue (not filtered).
Installing the umbrella azure-monitor-opentelemetry package in dev makes
pyright resolve the symbol correctly, matching the install guidance the
observability README already gives users.

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

@@ -4,6 +4,7 @@ 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;
@@ -69,14 +70,7 @@ public sealed class AzureAgentProvider(Uri projectEndpoint, TokenCredential proj
                 include: null,
                 cancellationToken).ConfigureAwait(false);
 
-        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];
+        return newItems.AsChatMessages().Single();
 
         IEnumerable<ResponseItem> GetResponseItems()
         {
@@ -214,14 +208,7 @@ 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()];
-        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];
+        return items.AsChatMessages().Single();
     }
 
     /// <inheritdoc/>

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

@@ -49,11 +49,7 @@ internal sealed class InvokeAzureAgentExecutor(InvokeAzureAgent model, ResponseA
 
     public async ValueTask ResumeAsync(IWorkflowContext context, ExternalInputResponse response, CancellationToken cancellationToken)
     {
-        ChatMessage? lastMessage = response.Messages.LastOrDefault();
-        if (lastMessage is not null)
-        {
-            await context.SetLastMessageAsync(lastMessage).ConfigureAwait(false);
-        }
+        await context.SetLastMessageAsync(response.Messages.Last()).ConfigureAwait(false);
         await this.InvokeAgentAsync(context, response.Messages, cancellationToken).ConfigureAwait(false);
     }
 
@@ -89,19 +85,15 @@ 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.
-        string? lastMessageText = agentResponse.Messages.LastOrDefault()?.Text;
-        if (!string.IsNullOrEmpty(lastMessageText))
+        try
         {
-            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.
-            }
+            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.
         }
 
         if (this.Model.Input?.ExternalLoop?.When is not null)

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

@@ -122,13 +122,10 @@ internal sealed class QuestionExecutor(Question model, ResponseAgentProvider age
                 string? workflowConversationId = context.GetWorkflowConversation();
                 if (workflowConversationId is not null)
                 {
-                    // 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);
-                    }
+                    // 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);
                 }
             }
 

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

@@ -45,11 +45,7 @@ internal sealed class RequestExternalInputExecutor(RequestExternalInput model, R
                 await agentProvider.CreateMessageAsync(workflowConversationId, inputMessage, cancellationToken).ConfigureAwait(false);
             }
         }
-        ChatMessage? lastMessage = response.Messages.LastOrDefault();
-        if (lastMessage is not null)
-        {
-            await context.SetLastMessageAsync(lastMessage).ConfigureAwait(false);
-        }
+        await context.SetLastMessageAsync(response.Messages.Last()).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 = [CreateHandoffResult(handoffRequest.CallId)],
+                        Contents = [new FunctionResultContent(handoffRequest.CallId, "Transferred.")],
                         CreatedAt = DateTimeOffset.UtcNow,
                         MessageId = Guid.NewGuid().ToString("N"),
                         Role = ChatRole.Tool,
@@ -459,6 +459,4 @@ 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

@@ -3,6 +3,7 @@
 using System;
 using System.Collections.Generic;
 using System.Diagnostics.CodeAnalysis;
+using System.Linq;
 using Microsoft.Extensions.AI;
 
 namespace Microsoft.Agents.AI.Workflows.Specialized;
@@ -30,78 +31,113 @@ internal sealed class HandoffMessagesFilter
             return messages;
         }
 
-        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.
+        Dictionary<string, FilterCandidateState> filteringCandidates = new();
+        List<ChatMessage> filteredMessages = [];
+        HashSet<int> messagesToRemove = [];
 
+        bool filterHandoffOnly = this._filteringBehavior == HandoffToolCallFilteringBehavior.HandoffOnly;
         foreach (ChatMessage unfilteredMessage in messages)
         {
-            if (unfilteredMessage.Contents is null || unfilteredMessage.Contents.Count == 0)
-            {
-                retainedMessages.Add(unfilteredMessage);
-                continue;
-            }
+            ChatMessage filteredMessage = unfilteredMessage.Clone();
 
-            // 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);
+            // .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;
 
-            foreach (AIContent content in unfilteredMessage.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 (content is FunctionCallContent fcc
-                    && (filterAllToolCalls || IsHandoffFunctionName(fcc.Name)))
+                for (int i = 0; i < unfilteredMessage.Contents!.Count; i++)
                 {
-                    // 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))
+                    AIContent content = unfilteredMessage.Contents[i];
+                    if (content is not FunctionCallContent fcc || (filterHandoffOnly && !IsHandoffFunctionName(fcc.Name)))
                     {
-                        throw new InvalidOperationException($"Duplicate FunctionCallContent with CallId '{fcc.CallId}' without corresponding FunctionResultContent.");
-                    }
+                        filteredMessage.Contents.Add(content);
 
-                    // 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
+                        // 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
+                    }
+                }
+            }
+            else
+            {
+                if (!filterHandoffOnly)
+                {
                     continue;
                 }
-                else if (content is FunctionResultContent frc)
+
+                for (int i = 0; i < unfilteredMessage.Contents!.Count; i++)
                 {
-                    // 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))
+                    AIContent content = unfilteredMessage.Contents[i];
+                    if (content is not FunctionResultContent frc
+                        || (filteringCandidates.TryGetValue(frc.CallId, out FilterCandidateState? candidateState)
+                            && candidateState.IsHandoffFunction is false))
                     {
-                        continue;
+                        // 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);
                     }
+                    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 (retainedContents.Count == 0)
+            if (filteredMessage.Contents.Count > 0)
             {
-                // message was fully filtered, skip it
-                continue;
+                filteredMessages.Add(filteredMessage);
             }
-
-            ChatMessage filteredMessage = unfilteredMessage.Clone();
-            filteredMessage.Contents = retainedContents;
-            retainedMessages.Add(filteredMessage);
         }
 
-        return retainedMessages;
+        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; }
     }
 }

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

@@ -85,29 +85,6 @@ 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

@@ -1,115 +0,0 @@
-// 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/CHANGELOG.md

@@ -7,44 +7,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
-## [1.1.0] - 2026-04-21
-
-### Added
-- **agent-framework-gemini**: Add `GeminiChatClient` ([#4847](https://github.com/microsoft/agent-framework/pull/4847))
-- **agent-framework-core**: Add `context_providers` and `description` to `workflow.as_agent()` ([#4651](https://github.com/microsoft/agent-framework/pull/4651))
-- **agent-framework-core**: Add experimental file history provider ([#5248](https://github.com/microsoft/agent-framework/pull/5248))
-- **agent-framework-core**: Add OpenAI types to the default checkpoint encoding allow list ([#5297](https://github.com/microsoft/agent-framework/pull/5297))
-- **agent-framework-core**: Add `AgentExecutorResponse.with_text()` to preserve conversation history through custom executors ([#5255](https://github.com/microsoft/agent-framework/pull/5255))
-- **agent-framework-a2a**: Propagate A2A metadata from `Message`, `Artifact`, `Task`, and event types ([#5256](https://github.com/microsoft/agent-framework/pull/5256))
-- **agent-framework-core**: Add `finish_reason` support to `AgentResponse` and `AgentResponseUpdate` ([#5211](https://github.com/microsoft/agent-framework/pull/5211))
-- **agent-framework-hyperlight**: Add Hyperlight CodeAct package and docs ([#5185](https://github.com/microsoft/agent-framework/pull/5185))
-- **agent-framework-openai**: Add search tool content support for OpenAI responses ([#5302](https://github.com/microsoft/agent-framework/pull/5302))
-- **agent-framework-foundry**: Add support for Foundry Toolboxes ([#5346](https://github.com/microsoft/agent-framework/pull/5346))
-- **agent-framework-ag-ui**: Expose `forwardedProps` to agents and tools via session metadata ([#5264](https://github.com/microsoft/agent-framework/pull/5264))
-- **agent-framework-foundry**: Add hosted agent V2 support ([#5379](https://github.com/microsoft/agent-framework/pull/5379))
-
 ### Changed
 - **agent-framework-azure-cosmos**: [BREAKING] `CosmosCheckpointStorage` now uses restricted pickle deserialization by default, matching `FileCheckpointStorage` behavior. If your checkpoints contain application-defined types, pass them via `allowed_checkpoint_types=["my_app.models:MyState"]`. ([#5200](https://github.com/microsoft/agent-framework/issues/5200))
-- **agent-framework-core**: Improve skill name validation ([#4530](https://github.com/microsoft/agent-framework/pull/4530))
-- **agent-framework-azure-cosmos**: Add `allowed_checkpoint_types` support to `CosmosCheckpointStorage` for parity with `FileCheckpointStorage` ([#5202](https://github.com/microsoft/agent-framework/pull/5202))
-- **agent-framework-core**: Move `InMemory` history provider injection to first invocation ([#5236](https://github.com/microsoft/agent-framework/pull/5236))
-- **agent-framework-github-copilot**: Forward provider config to `SessionConfig` in `GitHubCopilotAgent` ([#5195](https://github.com/microsoft/agent-framework/pull/5195))
-- **agent-framework-hyperlight-codeact**: Flatten `execute_code` output ([#5333](https://github.com/microsoft/agent-framework/pull/5333))
-- **dependencies**: Bump `pygments` from `2.19.2` to `2.20.0` in `/python` ([#4978](https://github.com/microsoft/agent-framework/pull/4978))
-- **tests**: Bump misc integration retry delay to 30s ([#5293](https://github.com/microsoft/agent-framework/pull/5293))
-- **tests**: Improve misc integration test robustness ([#5295](https://github.com/microsoft/agent-framework/pull/5295))
-- **tests**: Skip hosted tools test on transient upstream MCP errors ([#5296](https://github.com/microsoft/agent-framework/pull/5296))
-
-### Fixed
-- **agent-framework-core**: Fix `python-feature-lifecycle` skill YAML frontmatter ([#5226](https://github.com/microsoft/agent-framework/pull/5226))
-- **agent-framework-core**: Fix `HandoffBuilder` dropping function-level middleware when cloning agents ([#5220](https://github.com/microsoft/agent-framework/pull/5220))
-- **agent-framework-ag-ui**: Fix deterministic state updates from tool results ([#5201](https://github.com/microsoft/agent-framework/pull/5201))
-- **agent-framework-devui**: Fix streaming memory growth and add cross-platform regression coverage ([#5221](https://github.com/microsoft/agent-framework/pull/5221))
-- **agent-framework-core**: Skip `get_final_response` in `_finalize_stream` when the stream has errored ([#5232](https://github.com/microsoft/agent-framework/pull/5232))
-- **agent-framework-openai**: Fix reasoning replay when `store=False` ([#5250](https://github.com/microsoft/agent-framework/pull/5250))
-- **agent-framework-foundry**: Handle `url_citation` annotations in `FoundryChatClient` streaming responses ([#5071](https://github.com/microsoft/agent-framework/pull/5071))
-- **agent-framework-gemini**: Fix Gemini client support for Gemini API and Vertex AI ([#5258](https://github.com/microsoft/agent-framework/pull/5258))
-- **agent-framework-copilotstudio**: Fix `CopilotStudioAgent` to reuse conversation ID from an existing session ([#5299](https://github.com/microsoft/agent-framework/pull/5299))
 
 ## [devui-1.0.0b260414] - 2026-04-14
 
@@ -939,8 +903,7 @@ Release candidate for **agent-framework-core** and **agent-framework-azure-ai**
 
 For more information, see the [announcement blog post](https://devblogs.microsoft.com/foundry/introducing-microsoft-agent-framework-the-open-source-engine-for-agentic-ai-apps/).
 
-[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.1.0...HEAD
-[1.1.0]: https://github.com/microsoft/agent-framework/compare/python-1.0.1...python-1.1.0
+[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.0.1...HEAD
 [1.0.1]: https://github.com/microsoft/agent-framework/compare/python-1.0.0...python-1.0.1
 [1.0.0]: https://github.com/microsoft/agent-framework/compare/python-1.0.0rc6...python-1.0.0
 [1.0.0rc6]: https://github.com/microsoft/agent-framework/compare/python-1.0.0rc5...python-1.0.0rc6

python/packages/a2a/pyproject.toml

@@ -4,7 +4,7 @@ description = "A2A integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "a2a-sdk>=0.3.5,<0.3.24",
 ]
 

python/packages/ag-ui/agent_framework_ag_ui/_agent_run.py

@@ -69,23 +69,19 @@ if TYPE_CHECKING:
 logger = logging.getLogger(__name__)
 
 # Keys that are internal to AG-UI orchestration and should not be passed to chat clients
-AG_UI_INTERNAL_METADATA_KEYS = {"ag_ui_thread_id", "ag_ui_run_id", "current_state", "forwarded_props"}
+AG_UI_INTERNAL_METADATA_KEYS = {"ag_ui_thread_id", "ag_ui_run_id", "current_state"}
 
 
 def _build_safe_metadata(thread_metadata: dict[str, Any] | None) -> dict[str, Any]:
-    """Build metadata dict with string values for Azure compatibility.
+    """Build metadata dict with truncated string values for Azure compatibility.
 
-    Azure has a 512 character limit per metadata value.  String values that
-    already fit are kept as-is.  Non-string values are JSON-serialized.  If the
-    resulting string exceeds 512 characters the key is **dropped** (with a
-    warning) instead of truncated, because truncation can produce invalid JSON
-    that downstream consumers cannot decode.
+    Azure has a 512 character limit per metadata value.
 
     Args:
         thread_metadata: Raw metadata dict
 
     Returns:
-        Metadata with safe string values (each <= 512 chars)
+        Metadata with string values truncated to 512 chars
     """
     if not thread_metadata:
         return {}
@@ -93,12 +89,7 @@ def _build_safe_metadata(thread_metadata: dict[str, Any] | None) -> dict[str, An
     for key, value in thread_metadata.items():
         value_str = value if isinstance(value, str) else json.dumps(value)
         if len(value_str) > 512:
-            logger.warning(
-                "Dropping metadata key %r: serialized value is %d chars (limit 512)",
-                key,
-                len(value_str),
-            )
-            continue
+            value_str = value_str[:512]
         safe_metadata[key] = value_str
     return safe_metadata
 
@@ -799,10 +790,6 @@ async def run_agent_stream(
         "ag_ui_thread_id": thread_id,
         "ag_ui_run_id": run_id,
     }
-    if "forwarded_props" in input_data:
-        base_metadata["forwarded_props"] = input_data["forwarded_props"]
-    elif "forwardedProps" in input_data:
-        base_metadata["forwarded_props"] = input_data["forwardedProps"]
     if flow.current_state:
         base_metadata["current_state"] = flow.current_state
     session.metadata = _build_safe_metadata(base_metadata)  # type: ignore[attr-defined]

python/packages/ag-ui/agent_framework_ag_ui/_workflow_run.py

@@ -4,7 +4,6 @@
 
 from __future__ import annotations
 
-import inspect
 import json
 import logging
 import uuid
@@ -582,33 +581,11 @@ async def run_workflow_stream(
         flow.accumulated_text = ""
         return [TextMessageEndEvent(message_id=current_message_id)]
 
-    fwd_kwargs: dict[str, Any] = {}
-    if "forwarded_props" in input_data:
-        forwarded_props = input_data["forwarded_props"]
-        fwd_kwargs["function_invocation_kwargs"] = {"forwarded_props": forwarded_props}
-    elif "forwardedProps" in input_data:
-        forwarded_props = input_data["forwardedProps"]
-        fwd_kwargs["function_invocation_kwargs"] = {"forwarded_props": forwarded_props}
-
-    # Only pass function_invocation_kwargs if the workflow.run signature accepts it
-    if fwd_kwargs:
-        try:
-            sig = inspect.signature(workflow.run)
-            params = sig.parameters
-            accepts_fwd = "function_invocation_kwargs" in params or any(
-                p.kind == inspect.Parameter.VAR_KEYWORD for p in params.values()
-            )
-        except (ValueError, TypeError):
-            accepts_fwd = False
-        if not accepts_fwd:
-            logger.debug("workflow.run() does not accept function_invocation_kwargs; dropping forwarded_props")
-            fwd_kwargs = {}
-
     try:
         if responses:
-            event_stream = workflow.run(responses=responses, stream=True, **fwd_kwargs)
+            event_stream = workflow.run(responses=responses, stream=True)
         else:
-            event_stream = workflow.run(message=messages, stream=True, **fwd_kwargs)
+            event_stream = workflow.run(message=messages, stream=True)
 
         async for event in event_stream:
             event_type = getattr(event, "type", None)

python/packages/ag-ui/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "agent-framework-ag-ui"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 description = "AG-UI protocol integration for Agent Framework"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -22,7 +22,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "ag-ui-protocol==0.1.13",
     "fastapi>=0.115.0,<0.133.1",
     "uvicorn[standard]>=0.30.0,<0.42.0"

python/packages/ag-ui/tests/ag_ui/test_forwarded_props_in_metadata.py

@@ -1,83 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-"""Tests for forwarded_props inclusion in AG-UI session metadata."""
-
-import json
-from typing import Any
-
-from agent_framework_ag_ui._agent_run import AG_UI_INTERNAL_METADATA_KEYS, _build_safe_metadata
-
-
-class TestForwardedPropsInSessionMetadata:
-    """Verify that forwarded_props is surfaced in session metadata and filtered from LLM metadata."""
-
-    def test_forwarded_props_in_internal_metadata_keys(self):
-        """forwarded_props is listed in AG_UI_INTERNAL_METADATA_KEYS to prevent LLM leakage."""
-        assert "forwarded_props" in AG_UI_INTERNAL_METADATA_KEYS
-
-    def test_forwarded_props_filtered_from_client_metadata(self):
-        """forwarded_props is filtered out when building LLM-bound client metadata."""
-        session_metadata: dict[str, Any] = {
-            "ag_ui_thread_id": "t1",
-            "ag_ui_run_id": "r1",
-            "forwarded_props": '{"custom_flag": true}',
-        }
-
-        client_metadata = {k: v for k, v in session_metadata.items() if k not in AG_UI_INTERNAL_METADATA_KEYS}
-
-        assert "forwarded_props" not in client_metadata
-        assert "ag_ui_thread_id" not in client_metadata
-
-
-class TestBuildSafeMetadata:
-    """Verify _build_safe_metadata handles various value types correctly."""
-
-    def test_string_value_unchanged(self):
-        result = _build_safe_metadata({"key": "hello"})
-        assert result == {"key": "hello"}
-
-    def test_dict_value_serialized_to_json(self):
-        result = _build_safe_metadata({"fp": {"flag": True, "source": "frontend"}})
-        assert "fp" in result
-        assert isinstance(result["fp"], str)
-        # Must be valid, decodable JSON
-        decoded = json.loads(result["fp"])
-        assert decoded == {"flag": True, "source": "frontend"}
-
-    def test_empty_dict_serialized_to_json(self):
-        result = _build_safe_metadata({"fp": {}})
-        assert result["fp"] == "{}"
-        assert json.loads(result["fp"]) == {}
-
-    def test_value_within_limit_kept(self):
-        value = "x" * 512
-        result = _build_safe_metadata({"key": value})
-        assert result["key"] == value
-
-    def test_value_exceeding_limit_dropped(self):
-        """Values exceeding 512 chars are dropped entirely (not truncated)."""
-        value = "x" * 513
-        result = _build_safe_metadata({"key": value})
-        assert "key" not in result
-
-    def test_json_value_exceeding_limit_dropped(self):
-        """JSON-serialized dict exceeding 512 chars is dropped, not truncated into invalid JSON."""
-        big_dict = {f"key_{i}": "v" * 100 for i in range(50)}
-        result = _build_safe_metadata({"forwarded_props": big_dict})
-        assert "forwarded_props" not in result
-
-    def test_other_keys_preserved_when_one_dropped(self):
-        """Dropping one oversized key does not affect other keys."""
-        result = _build_safe_metadata(
-            {
-                "small": "ok",
-                "big": "x" * 600,
-            }
-        )
-        assert result == {"small": "ok"}
-
-    def test_none_input_returns_empty(self):
-        assert _build_safe_metadata(None) == {}
-
-    def test_empty_input_returns_empty(self):
-        assert _build_safe_metadata({}) == {}

python/packages/ag-ui/tests/ag_ui/test_run.py

@@ -63,12 +63,12 @@ class TestBuildSafeMetadata:
         result = _build_safe_metadata(metadata)
         assert result == metadata
 
-    def test_drops_long_strings(self):
-        """Drops strings over 512 chars instead of truncating."""
+    def test_truncates_long_strings(self):
+        """Truncates strings over 512 chars."""
         long_value = "x" * 1000
         metadata = {"key": long_value}
         result = _build_safe_metadata(metadata)
-        assert "key" not in result
+        assert len(result["key"]) == 512
 
     def test_serializes_non_strings(self):
         """Serializes non-string values to JSON."""
@@ -77,12 +77,12 @@ class TestBuildSafeMetadata:
         assert result["count"] == "42"
         assert result["items"] == "[1, 2, 3]"
 
-    def test_drops_oversized_serialized_values(self):
-        """Drops serialized values over 512 chars instead of truncating."""
+    def test_truncates_serialized_values(self):
+        """Truncates serialized values over 512 chars."""
         long_list = list(range(200))
         metadata = {"data": long_list}
         result = _build_safe_metadata(metadata)
-        assert "data" not in result
+        assert len(result["data"]) == 512
 
 
 class TestHasOnlyToolCalls:

python/packages/ag-ui/tests/ag_ui/test_workflow_run.py

@@ -1672,210 +1672,3 @@ async def test_workflow_run_non_terminal_status_emits_custom():
     custom = [e for e in events if e.type == "CUSTOM" and e.name == "status"]
     assert len(custom) == 1
     assert custom[0].value == {"state": "running"}
-
-
-async def test_workflow_run_passes_forwarded_props_as_function_invocation_kwargs() -> None:
-    """forwarded_props from input_data is forwarded to workflow.run() via function_invocation_kwargs."""
-
-    class CapturingWorkflow:
-        def __init__(self) -> None:
-            self.captured_kwargs: dict[str, Any] = {}
-
-        def run(self, **kwargs: Any):
-            self.captured_kwargs = dict(kwargs)
-
-            async def _stream():
-                yield SimpleNamespace(type="started")
-
-            return _stream()
-
-    workflow = CapturingWorkflow()
-    events = [
-        event
-        async for event in run_workflow_stream(
-            {
-                "messages": [{"role": "user", "content": "hello"}],
-                "forwarded_props": {"custom_flag": True, "source": "copilotkit"},
-            },
-            cast(Any, workflow),
-        )
-    ]
-
-    event_types = [event.type for event in events]
-    assert "RUN_STARTED" in event_types
-    assert "RUN_FINISHED" in event_types
-
-    assert workflow.captured_kwargs["stream"] is True
-    assert "function_invocation_kwargs" in workflow.captured_kwargs
-    assert workflow.captured_kwargs["function_invocation_kwargs"] == {
-        "forwarded_props": {"custom_flag": True, "source": "copilotkit"},
-    }
-
-
-async def test_workflow_run_omits_function_invocation_kwargs_when_no_forwarded_props() -> None:
-    """function_invocation_kwargs is not passed when forwarded_props is absent."""
-
-    class CapturingWorkflow:
-        def __init__(self) -> None:
-            self.captured_kwargs: dict[str, Any] = {}
-
-        def run(self, **kwargs: Any):
-            self.captured_kwargs = dict(kwargs)
-
-            async def _stream():
-                yield SimpleNamespace(type="started")
-
-            return _stream()
-
-    workflow = CapturingWorkflow()
-    events = [
-        event
-        async for event in run_workflow_stream(
-            {"messages": [{"role": "user", "content": "hello"}]},
-            cast(Any, workflow),
-        )
-    ]
-
-    event_types = [event.type for event in events]
-    assert "RUN_STARTED" in event_types
-    assert workflow.captured_kwargs["stream"] is True
-    assert "function_invocation_kwargs" not in workflow.captured_kwargs
-
-
-async def test_workflow_run_accepts_camel_case_forwarded_props() -> None:
-    """forwardedProps (camelCase) is accepted as an alternative key."""
-
-    class CapturingWorkflow:
-        def __init__(self) -> None:
-            self.captured_kwargs: dict[str, Any] = {}
-
-        def run(self, **kwargs: Any):
-            self.captured_kwargs = dict(kwargs)
-
-            async def _stream():
-                yield SimpleNamespace(type="started")
-
-            return _stream()
-
-    workflow = CapturingWorkflow()
-    events = [
-        event
-        async for event in run_workflow_stream(
-            {
-                "messages": [{"role": "user", "content": "hello"}],
-                "forwardedProps": {"source": "frontend"},
-            },
-            cast(Any, workflow),
-        )
-    ]
-
-    event_types = [event.type for event in events]
-    assert "RUN_STARTED" in event_types
-
-    assert workflow.captured_kwargs["stream"] is True
-    assert "function_invocation_kwargs" in workflow.captured_kwargs
-    assert workflow.captured_kwargs["function_invocation_kwargs"] == {
-        "forwarded_props": {"source": "frontend"},
-    }
-
-
-async def test_workflow_run_passes_empty_dict_forwarded_props() -> None:
-    """An empty dict forwarded_props={} should still be forwarded (not dropped by truthiness)."""
-
-    class CapturingWorkflow:
-        def __init__(self) -> None:
-            self.captured_kwargs: dict[str, Any] = {}
-
-        def run(self, **kwargs: Any):
-            self.captured_kwargs = dict(kwargs)
-
-            async def _stream():
-                yield SimpleNamespace(type="started")
-
-            return _stream()
-
-    workflow = CapturingWorkflow()
-    events = [
-        event
-        async for event in run_workflow_stream(
-            {
-                "messages": [{"role": "user", "content": "hello"}],
-                "forwarded_props": {},
-            },
-            cast(Any, workflow),
-        )
-    ]
-
-    event_types = [event.type for event in events]
-    assert "RUN_STARTED" in event_types
-    assert "RUN_FINISHED" in event_types
-
-    assert workflow.captured_kwargs["stream"] is True
-    assert "function_invocation_kwargs" in workflow.captured_kwargs
-    assert workflow.captured_kwargs["function_invocation_kwargs"] == {
-        "forwarded_props": {},
-    }
-
-
-async def test_workflow_run_stream_true_always_passed() -> None:
-    """stream=True is always passed to workflow.run()."""
-
-    class CapturingWorkflow:
-        def __init__(self) -> None:
-            self.captured_kwargs: dict[str, Any] = {}
-
-        def run(self, **kwargs: Any):
-            self.captured_kwargs = dict(kwargs)
-
-            async def _stream():
-                yield SimpleNamespace(type="started")
-
-            return _stream()
-
-    workflow = CapturingWorkflow()
-    _ = [
-        event
-        async for event in run_workflow_stream(
-            {
-                "messages": [{"role": "user", "content": "hello"}],
-                "forwarded_props": {"key": "val"},
-            },
-            cast(Any, workflow),
-        )
-    ]
-
-    assert workflow.captured_kwargs["stream"] is True
-
-
-async def test_workflow_run_drops_fwd_kwargs_when_run_lacks_param() -> None:
-    """function_invocation_kwargs is silently dropped if workflow.run() does not accept it."""
-
-    class StrictWorkflow:
-        def __init__(self) -> None:
-            self.captured_kwargs: dict[str, Any] = {}
-
-        def run(self, *, message: Any = None, responses: Any = None, stream: bool = False):
-            self.captured_kwargs = {"message": message, "responses": responses, "stream": stream}
-
-            async def _stream():
-                yield SimpleNamespace(type="started")
-
-            return _stream()
-
-    workflow = StrictWorkflow()
-    events = [
-        event
-        async for event in run_workflow_stream(
-            {
-                "messages": [{"role": "user", "content": "hello"}],
-                "forwarded_props": {"custom": True},
-            },
-            cast(Any, workflow),
-        )
-    ]
-
-    event_types = [event.type for event in events]
-    assert "RUN_STARTED" in event_types
-    assert "RUN_FINISHED" in event_types
-    # No TypeError raised, and function_invocation_kwargs was not passed
-    assert "function_invocation_kwargs" not in workflow.captured_kwargs

python/packages/anthropic/pyproject.toml

@@ -4,7 +4,7 @@ description = "Anthropic integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "anthropic>=0.80.0,<0.80.1",
 ]
 

python/packages/azure-ai-search/pyproject.toml

@@ -4,7 +4,7 @@ description = "Azure AI Search integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "azure-search-documents>=11.7.0b2,<11.7.0b3",
 ]
 

python/packages/azure-cosmos/pyproject.toml

@@ -4,7 +4,7 @@ description = "Azure Cosmos DB history provider integration for Microsoft Agent
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "azure-cosmos>=4.3.0,<5",
 ]
 

python/packages/azurefunctions/pyproject.toml

@@ -4,7 +4,7 @@ description = "Azure Functions integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "agent-framework-durabletask",
     "azure-functions>=1.24.0,<2",
     "azure-functions-durable>=1.3.1,<2",

python/packages/bedrock/pyproject.toml

@@ -4,7 +4,7 @@ description = "Amazon Bedrock integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "boto3>=1.35.0,<2.0.0",
     "botocore>=1.35.0,<2.0.0",
 ]

python/packages/chatkit/pyproject.toml

@@ -4,7 +4,7 @@ description = "OpenAI ChatKit integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "openai-chatkit>=1.4.1,<2.0.0",
 ]
 

python/packages/claude/pyproject.toml

@@ -4,7 +4,7 @@ description = "Claude Agent SDK integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "claude-agent-sdk>=0.1.36,<0.1.49",
 ]
 

python/packages/copilotstudio/pyproject.toml

@@ -4,7 +4,7 @@ description = "Copilot Studio integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "microsoft-agents-copilotstudio-client>=0.3.1,<0.3.2",
 ]
 

python/packages/core/agent_framework/__init__.py

@@ -122,7 +122,6 @@ from ._telemetry import (
     APP_INFO,
     USER_AGENT_KEY,
     USER_AGENT_TELEMETRY_DISABLED_ENV_VAR,
-    get_user_agent_extra_headers,
     prepend_agent_framework_to_user_agent,
 )
 from ._tools import (
@@ -423,7 +422,6 @@ __all__ = [
     "evaluator",
     "executor",
     "function_middleware",
-    "get_user_agent_extra_headers",
     "handler",
     "included_messages",
     "included_token_count",

python/packages/core/agent_framework/_telemetry.py

@@ -59,24 +59,6 @@ def _get_user_agent() -> str:
     return f"{'/'.join(prefixes)}/{AGENT_FRAMEWORK_USER_AGENT}"
 
 
-def get_user_agent_extra_headers() -> dict[str, str]:
-    """Return extra headers containing the current User-Agent string for per-request injection.
-
-    This function evaluates the user agent at call time, picking up any active
-    ``user_agent_prefix`` context. Use it to supply ``extra_headers`` on individual
-    API calls so that the User-Agent reflects the current functional area.
-
-    When user agent telemetry is disabled, an empty dict is returned.
-
-    Returns:
-        A dict with ``"User-Agent"`` set to the runtime user agent string,
-        or an empty dict when telemetry is disabled.
-    """
-    if not IS_TELEMETRY_ENABLED:
-        return {}
-    return {USER_AGENT_KEY: _get_user_agent()}
-
-
 def prepend_agent_framework_to_user_agent(headers: dict[str, Any] | None = None) -> dict[str, Any]:
     """Prepend "agent-framework" to the User-Agent in the headers.
 

python/packages/core/pyproject.toml

@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.0"
+version = "1.0.1"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"

python/packages/core/tests/core/test_telemetry.py

@@ -6,7 +6,6 @@ from agent_framework import (
     AGENT_FRAMEWORK_USER_AGENT,
     USER_AGENT_KEY,
     USER_AGENT_TELEMETRY_DISABLED_ENV_VAR,
-    get_user_agent_extra_headers,
     prepend_agent_framework_to_user_agent,
 )
 from agent_framework._telemetry import user_agent_prefix
@@ -151,33 +150,3 @@ def test_user_agent_prefix_nesting():
     # Both removed
     result = prepend_agent_framework_to_user_agent()
     assert result["User-Agent"] == AGENT_FRAMEWORK_USER_AGENT
-
-
-# region Test get_user_agent_extra_headers
-
-
-def test_get_user_agent_extra_headers_returns_user_agent():
-    """Test that get_user_agent_extra_headers returns a User-Agent header."""
-    result = get_user_agent_extra_headers()
-    assert "User-Agent" in result
-    assert result["User-Agent"] == AGENT_FRAMEWORK_USER_AGENT
-
-
-def test_get_user_agent_extra_headers_with_prefix():
-    """Test that get_user_agent_extra_headers respects user_agent_prefix context."""
-    with user_agent_prefix("test-host"):
-        result = get_user_agent_extra_headers()
-        assert result["User-Agent"].startswith("test-host/")
-        assert AGENT_FRAMEWORK_USER_AGENT in result["User-Agent"]
-
-    # After exiting context, prefix is removed
-    result = get_user_agent_extra_headers()
-    assert result["User-Agent"] == AGENT_FRAMEWORK_USER_AGENT
-
-
-def test_get_user_agent_extra_headers_with_nested_prefix():
-    """Test that get_user_agent_extra_headers picks up nested prefixes."""
-    with user_agent_prefix("outer"), user_agent_prefix("inner"):
-        result = get_user_agent_extra_headers()
-        assert "outer" in result["User-Agent"]
-        assert "inner" in result["User-Agent"]

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

@@ -664,21 +664,6 @@ 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/packages/declarative/pyproject.toml

@@ -4,7 +4,7 @@ description = "Declarative specification support for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "powerfx>=0.0.32,<0.0.35; python_version < '3.14'",
     "pyyaml>=6.0,<7.0",
 ]

python/packages/devui/pyproject.toml

@@ -4,7 +4,7 @@ description = "Debug UI for Microsoft Agent Framework with OpenAI-compatible API
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260414"
 license-files = ["LICENSE"]
 urls.homepage = "https://github.com/microsoft/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
  dependencies = [
-     "agent-framework-core>=1.1.0,<2",
+     "agent-framework-core>=1.0.1,<2",
      "openai>=1.99.0,<3",
      "opentelemetry-sdk>=1.39.0,<2",
      "fastapi>=0.115.0,<0.133.1",

python/packages/durabletask/pyproject.toml

@@ -4,7 +4,7 @@ description = "Durable Task integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "durabletask>=1.3.0,<2",
     "durabletask-azuremanaged>=1.3.0,<2",
     "python-dateutil>=2.8.0,<3",

python/packages/foundry/pyproject.toml

@@ -4,7 +4,7 @@ description = "Microsoft Foundry integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.0"
+version = "1.0.1"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,8 +23,8 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
-    "agent-framework-openai>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
+    "agent-framework-openai>=1.0.1,<2",
     "azure-ai-inference>=1.0.0b9,<1.0.0b10",
     "azure-ai-projects>=2.1.0,<3.0",
 ]

python/packages/foundry_hosting/pyproject.toml

@@ -4,7 +4,7 @@ description = "Foundry Hosting integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260421"
+version = "1.0.0a260420"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.0,<2",
     "azure-ai-agentserver-core==2.0.0b2",
     "azure-ai-agentserver-responses==1.0.0b4",
     "azure-ai-agentserver-invocations==1.0.0b2",

python/packages/foundry_hosting/tests/test_responses.py

@@ -915,76 +915,3 @@ class TestToMessage:
 
 
 # endregion
-
-
-# region User Agent Prefix
-
-
-class TestUserAgentPrefix:
-    """Tests that the user_agent_prefix context manager is active during agent execution."""
-
-    async def test_user_agent_prefix_set_during_non_streaming(self) -> None:
-        """The user agent should contain the foundry-hosting prefix in non-streaming mode."""
-        from agent_framework._telemetry import _get_user_agent  # type: ignore
-
-        captured_user_agent: list[str] = []
-
-        async def run_and_capture(*args: Any, **kwargs: Any) -> AgentResponse:
-            captured_user_agent.append(_get_user_agent())
-            return AgentResponse(messages=[Message(role="assistant", contents=[Content.from_text("ok")])])
-
-        agent = _make_agent()
-        agent.run = AsyncMock(side_effect=run_and_capture)
-        server = _make_server(agent)
-        resp = await _post(server, input_text="Hi", stream=False)
-
-        assert resp.status_code == 200
-        assert len(captured_user_agent) == 1
-        assert "foundry-hosting" in captured_user_agent[0]
-
-    async def test_user_agent_prefix_set_during_streaming(self) -> None:
-        """The user agent should contain the foundry-hosting prefix in streaming mode."""
-        from agent_framework._telemetry import _get_user_agent  # type: ignore
-
-        captured_user_agent: list[str] = []
-
-        async def _stream_gen() -> AsyncIterator[AgentResponseUpdate]:
-            captured_user_agent.append(_get_user_agent())
-            yield AgentResponseUpdate(contents=[Content.from_text("hello")], role="assistant")
-
-        def run_streaming(*args: Any, **kwargs: Any) -> Any:
-            if kwargs.get("stream"):
-                return ResponseStream(_stream_gen())  # type: ignore
-            raise NotImplementedError
-
-        agent = _make_agent()
-        agent.run = MagicMock(side_effect=run_streaming)
-        server = _make_server(agent)
-        resp = await _post(server, stream=True)
-
-        assert resp.status_code == 200
-        assert len(captured_user_agent) == 1
-        assert "foundry-hosting" in captured_user_agent[0]
-
-    async def test_user_agent_extra_headers_during_run(self) -> None:
-        """get_user_agent_extra_headers() should include the prefix during a request."""
-        from agent_framework._telemetry import get_user_agent_extra_headers
-
-        captured_headers: list[dict[str, str]] = []
-
-        async def run_and_capture(*args: Any, **kwargs: Any) -> AgentResponse:
-            captured_headers.append(get_user_agent_extra_headers())
-            return AgentResponse(messages=[Message(role="assistant", contents=[Content.from_text("ok")])])
-
-        agent = _make_agent()
-        agent.run = AsyncMock(side_effect=run_and_capture)
-        server = _make_server(agent)
-        resp = await _post(server, input_text="Hi", stream=False)
-
-        assert resp.status_code == 200
-        assert len(captured_headers) == 1
-        assert "User-Agent" in captured_headers[0]
-        assert "foundry-hosting" in captured_headers[0]["User-Agent"]
-
-
-# endregion

python/packages/foundry_local/pyproject.toml

@@ -4,7 +4,7 @@ description = "Foundry Local integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,8 +23,8 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
-    "agent-framework-openai>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
+    "agent-framework-openai>=1.0.1,<2",
     "foundry-local-sdk>=0.5.1,<0.5.2",
 ]
 

python/packages/gemini/pyproject.toml

@@ -4,7 +4,7 @@ description = "Google Gemini integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260421"
+version = "1.0.0a260410"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -24,7 +24,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2.0",
+    "agent-framework-core>=1.0.0,<2.0",
     "google-genai>=1.0.0,<2.0.0",
 ]
 

python/packages/github_copilot/pyproject.toml

@@ -4,7 +4,7 @@ description = "GitHub Copilot integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "github-copilot-sdk>=0.2.1,<=0.2.1; python_version >= '3.11'",
 ]
 

python/packages/hyperlight/pyproject.toml

@@ -4,7 +4,7 @@ description = "Hyperlight CodeAct integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260421"
+version = "1.0.0a260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.0,<2",
     "hyperlight-sandbox>=0.3.0,<0.4",
     "hyperlight-sandbox-backend-wasm>=0.3.0,<0.4 ; ((sys_platform == 'linux' and platform_machine == 'x86_64') or (sys_platform == 'win32' and platform_machine == 'AMD64')) and python_version < '3.14'",
     "hyperlight-sandbox-python-guest>=0.3.0,<0.4",

python/packages/lab/pyproject.toml

@@ -4,7 +4,7 @@ description = "Experimental modules for Microsoft Agent Framework"
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
   "Programming Language :: Python :: 3.14",
 ]
 dependencies = [
-  "agent-framework-core>=1.1.0,<2",
+  "agent-framework-core>=1.0.1,<2",
 ]
 
 [project.optional-dependencies]

python/packages/mem0/pyproject.toml

@@ -4,7 +4,7 @@ description = "Mem0 integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "mem0ai>=1.0.0,<2",
 ]
 

python/packages/ollama/pyproject.toml

@@ -4,7 +4,7 @@ description = "Ollama integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://learn.microsoft.com/en-us/agent-framework/"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "ollama>=0.5.3,<0.5.4",
 ]
 

python/packages/openai/agent_framework_openai/_chat_client.py

@@ -32,7 +32,7 @@ from agent_framework._clients import BaseChatClient
 from agent_framework._compaction import CompactionStrategy, TokenizerProtocol
 from agent_framework._middleware import ChatAndFunctionMiddlewareTypes, ChatMiddlewareLayer
 from agent_framework._settings import SecretString
-from agent_framework._telemetry import USER_AGENT_KEY, get_user_agent_extra_headers
+from agent_framework._telemetry import USER_AGENT_KEY
 from agent_framework._tools import (
     SHELL_TOOL_KIND_VALUE,
     FunctionInvocationConfiguration,
@@ -482,13 +482,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
         client = self.client
         validated_options = await self._validate_options(options)
         run_options = await self._prepare_options(messages, validated_options)
-        ua_headers = get_user_agent_extra_headers()
-        if ua_headers:
-            existing = run_options.get("extra_headers")
-            if existing is None:
-                run_options["extra_headers"] = ua_headers
-            elif USER_AGENT_KEY not in existing:
-                run_options["extra_headers"] = {**existing, **ua_headers}
         return client, run_options, validated_options
 
     def _handle_request_error(self, ex: Exception) -> NoReturn:
@@ -532,7 +525,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
                         stream_response = await client.responses.retrieve(
                             continuation_token["response_id"],
                             stream=True,
-                            extra_headers=get_user_agent_extra_headers(),
                         )
                         async for chunk in stream_response:
                             yield self._parse_chunk_from_openai(
@@ -580,10 +572,7 @@ class RawOpenAIChatClient(  # type: ignore[misc]
                 client = self.client
                 validated_options = await self._validate_options(options)
                 try:
-                    response = await client.responses.retrieve(
-                        continuation_token["response_id"],
-                        extra_headers=get_user_agent_extra_headers(),
-                    )
+                    response = await client.responses.retrieve(continuation_token["response_id"])
                 except Exception as ex:
                     self._handle_request_error(ex)
                 return self._parse_response_from_openai(response, options=validated_options)

python/packages/openai/agent_framework_openai/_chat_completion_client.py

@@ -22,7 +22,7 @@ from agent_framework._compaction import CompactionStrategy, TokenizerProtocol
 from agent_framework._docstrings import apply_layered_docstring
 from agent_framework._middleware import ChatAndFunctionMiddlewareTypes, ChatMiddlewareLayer
 from agent_framework._settings import SecretString
-from agent_framework._telemetry import USER_AGENT_KEY, get_user_agent_extra_headers
+from agent_framework._telemetry import USER_AGENT_KEY
 from agent_framework._tools import (
     FunctionInvocationConfiguration,
     FunctionInvocationLayer,
@@ -671,16 +671,6 @@ class RawOpenAIChatCompletionClient(  # type: ignore[misc]
                 run_options["response_format"] = response_format
             else:
                 run_options["response_format"] = type_to_response_format_param(response_format)
-
-        # runtime user-agent header
-        ua_headers = get_user_agent_extra_headers()
-        if ua_headers:
-            existing = run_options.get("extra_headers")
-            if existing is None:
-                run_options["extra_headers"] = ua_headers
-            elif USER_AGENT_KEY not in existing:
-                run_options["extra_headers"] = {**existing, **ua_headers}
-
         return run_options
 
     def _parse_response_from_openai(self, response: ChatCompletion, options: Mapping[str, Any]) -> ChatResponse:

python/packages/openai/agent_framework_openai/_embedding_client.py

@@ -10,7 +10,7 @@ from typing import TYPE_CHECKING, Any, ClassVar, Generic, Literal, TypedDict, ov
 
 from agent_framework._clients import BaseEmbeddingClient
 from agent_framework._settings import SecretString
-from agent_framework._telemetry import USER_AGENT_KEY, get_user_agent_extra_headers
+from agent_framework._telemetry import USER_AGENT_KEY
 from agent_framework._types import Embedding, EmbeddingGenerationOptions, GeneratedEmbeddings, UsageDetails
 from agent_framework.observability import EmbeddingTelemetryLayer
 from openai import AsyncAzureOpenAI, AsyncOpenAI
@@ -282,13 +282,6 @@ class RawOpenAIEmbeddingClient(
             kwargs["encoding_format"] = encoding_format
         if user := opts.get("user"):
             kwargs["user"] = user
-        ua_headers = get_user_agent_extra_headers()
-        if ua_headers:
-            existing = kwargs.get("extra_headers")
-            if existing is None:
-                kwargs["extra_headers"] = ua_headers
-            elif USER_AGENT_KEY not in existing:
-                kwargs["extra_headers"] = {**existing, **ua_headers}
 
         response = await self.client.embeddings.create(**kwargs)  # type: ignore[union-attr]
 

python/packages/openai/agent_framework_openai/_shared.py

@@ -8,7 +8,7 @@ from copy import copy
 from typing import TYPE_CHECKING, Any, Literal, Union
 
 from agent_framework._settings import SecretString, load_settings
-from agent_framework._telemetry import APP_INFO
+from agent_framework._telemetry import APP_INFO, prepend_agent_framework_to_user_agent
 from agent_framework.exceptions import SettingNotFoundError
 from openai import AsyncAzureOpenAI, AsyncOpenAI, AsyncStream, _legacy_response  # type: ignore
 from openai.types import Completion
@@ -174,6 +174,7 @@ def load_openai_service_settings(
     merged_headers = dict(copy(default_headers)) if default_headers else {}
     if APP_INFO:
         merged_headers.update(APP_INFO)
+        merged_headers = prepend_agent_framework_to_user_agent(merged_headers)
 
     api_key_callable = api_key if callable(api_key) else None
     api_key_str = api_key if not callable(api_key) else None

python/packages/openai/pyproject.toml

@@ -4,7 +4,7 @@ description = "OpenAI integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.0"
+version = "1.0.1"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "openai>=1.99.0,<3",
 ]
 

python/packages/orchestrations/pyproject.toml

@@ -4,7 +4,7 @@ description = "Orchestration patterns for Microsoft Agent Framework. Includes Se
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
 ]
 
 [tool.uv]

python/packages/purview/pyproject.toml

@@ -4,7 +4,7 @@ description = "Microsoft Purview (Graph dataSecurityAndGovernance) integration f
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://github.com/microsoft/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -24,7 +24,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "azure-core>=1.30.0,<2",
     "httpx>=0.27.0,<0.29",
 ]

python/packages/redis/pyproject.toml

@@ -4,7 +4,7 @@ description = "Redis integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.0,<2",
+    "agent-framework-core>=1.0.1,<2",
     "redis>=6.4.0,<7.2.1",
     "redisvl>=0.11.0,<0.16",
     "numpy>=2.2.6,<3"

python/pyproject.toml

@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.0"
+version = "1.0.1"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
   "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core[all]==1.1.0",
+    "agent-framework-core[all]==1.0.1",
 ]
 
 [dependency-groups]

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 two requiring approval (execute_trade, set_stop_loss).
+2. Both agents have the same tools, including one requiring approval (execute_trade).
 3. Both agents receive the same task and work concurrently on their respective stocks.
-4. When either agent tries to execute a trade or set a stop-loss, it triggers an approval request.
+4. When either agent tries to execute a trade, 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 for different tools.
+agents may independently trigger approval requests.
 
 Demonstrate:
 - Handling multiple approval requests from different agents in concurrent workflows.
-- Handling approval requests for different tools during concurrent agent execution.
+- Handling  during concurrent agent execution.
 - Understanding that approval pauses only the agent that triggered it, not all agents.
 
 Prerequisites:
@@ -89,15 +89,6 @@ 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."""
@@ -127,17 +118,14 @@ 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" and request.function_call is not None:
-                print(f"\nSimulating human approval for: {request.function_call.name}")
+            if request.type == "function_approval_request":
+                print(f"\nSimulating human approval for: {request.function_call.name}")  # type: ignore
                 # Create approval response
                 responses[request_id] = request.to_function_approval_response(approved=True)
 
@@ -157,10 +145,9 @@ 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. "
-            "Use stop-loss orders to manage risk."
+            "You manage my portfolio and take actions based on market data."
         ),
-        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade, set_stop_loss],
+        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade],
     )
 
     google_agent = Agent(
@@ -168,10 +155,9 @@ 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. "
-            "Use stop-loss orders to manage risk."
+            "You manage my trades and portfolio based on market conditions."
         ),
-        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade, set_stop_loss],
+        tools=[get_stock_price, get_market_sentiment, get_portfolio_balance, execute_trade],
     )
 
     # 4. Build a concurrent workflow with both agents
@@ -186,8 +172,7 @@ 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. Set stop-loss orders to manage risk. "
-        "No need to confirm trades with me.",
+        "your best judgment based on market sentiment. No need to confirm trades with me.",
         stream=True,
     )
 
@@ -206,32 +191,22 @@ 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}
 
-    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. 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!
+            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!
     """
 
 

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" and request.function_call is not None:
+            if request.type == "function_approval_request":
                 print("\n[APPROVAL REQUIRED]")
-                print(f"  Tool: {request.function_call.name}")
-                print(f"  Arguments: {request.function_call.arguments}")
-                print(f"Simulating human approval for: {request.function_call.name}")
+                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
                 # 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" and request.function_call is not None:
+            if request.type == "function_approval_request":
                 print("\n[APPROVAL REQUIRED]")
-                print(f"  Tool: {request.function_call.name}")
-                print(f"  Arguments: {request.function_call.arguments}")
-                print(f"Simulating human approval for: {request.function_call.name}")
+                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
                 # Create approval response
                 responses[request_id] = request.to_function_approval_response(approved=True)
 

python/uv.lock

@@ -96,7 +96,7 @@ wheels = [
 
 [[package]]
 name = "agent-framework"
-version = "1.1.0"
+version = "1.0.1"
 source = { virtual = "." }
 dependencies = [
     { name = "agent-framework-core", extra = ["all"], marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -151,7 +151,7 @@ dev = [
 
 [[package]]
 name = "agent-framework-a2a"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/a2a" }
 dependencies = [
     { name = "a2a-sdk", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -166,7 +166,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-ag-ui"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/ag-ui" }
 dependencies = [
     { name = "ag-ui-protocol", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -194,7 +194,7 @@ provides-extras = ["dev"]
 
 [[package]]
 name = "agent-framework-anthropic"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/anthropic" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -209,7 +209,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-azure-ai-search"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/azure-ai-search" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -224,7 +224,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-azure-cosmos"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/azure-cosmos" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -239,7 +239,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-azurefunctions"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/azurefunctions" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -261,7 +261,7 @@ dev = []
 
 [[package]]
 name = "agent-framework-bedrock"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/bedrock" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -278,7 +278,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-chatkit"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/chatkit" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -293,7 +293,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-claude"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/claude" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -308,7 +308,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-copilotstudio"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/copilotstudio" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -323,7 +323,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-core"
-version = "1.1.0"
+version = "1.0.1"
 source = { editable = "packages/core" }
 dependencies = [
     { name = "opentelemetry-api", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -395,7 +395,7 @@ provides-extras = ["all"]
 
 [[package]]
 name = "agent-framework-declarative"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/declarative" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -420,7 +420,7 @@ dev = [{ name = "types-pyyaml", specifier = "==6.0.12.20250915" }]
 
 [[package]]
 name = "agent-framework-devui"
-version = "1.0.0b260421"
+version = "1.0.0b260414"
 source = { editable = "packages/devui" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -458,7 +458,7 @@ provides-extras = ["dev", "all"]
 
 [[package]]
 name = "agent-framework-durabletask"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/durabletask" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -485,7 +485,7 @@ dev = [{ name = "types-python-dateutil", specifier = "==2.9.0.20260402" }]
 
 [[package]]
 name = "agent-framework-foundry"
-version = "1.1.0"
+version = "1.0.1"
 source = { editable = "packages/foundry" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -504,7 +504,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-foundry-hosting"
-version = "1.0.0a260421"
+version = "1.0.0a260420"
 source = { editable = "packages/foundry_hosting" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -523,7 +523,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-foundry-local"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/foundry_local" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -540,7 +540,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-gemini"
-version = "1.0.0a260421"
+version = "1.0.0a260410"
 source = { editable = "packages/gemini" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -555,7 +555,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-github-copilot"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/github_copilot" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -570,7 +570,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-hyperlight"
-version = "1.0.0a260421"
+version = "1.0.0a260409"
 source = { editable = "packages/hyperlight" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -589,7 +589,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-lab"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/lab" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -670,7 +670,7 @@ dev = [
 
 [[package]]
 name = "agent-framework-mem0"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/mem0" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -685,7 +685,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-ollama"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/ollama" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -700,7 +700,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-openai"
-version = "1.1.0"
+version = "1.0.1"
 source = { editable = "packages/openai" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -715,7 +715,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-orchestrations"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/orchestrations" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -726,7 +726,7 @@ requires-dist = [{ name = "agent-framework-core", editable = "packages/core" }]
 
 [[package]]
 name = "agent-framework-purview"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/purview" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -743,7 +743,7 @@ requires-dist = [
 
 [[package]]
 name = "agent-framework-redis"
-version = "1.0.0b260421"
+version = "1.0.0b260409"
 source = { editable = "packages/redis" }
 dependencies = [
     { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },