Python: fix(azure-ai): Fix response_format handling for structured outputs (#3114 )

* fix(azure-ai): read response_format from chat_options instead of run_options * refactor: use explicit None checks for response_format * Fix mypy error * Mypy fix
Python: Streaming sample for azurefunctions (#3057 )
2026-06-16 21:04:09 +08:00 · 2026-01-07 23:11:28 +00:00 · 2026-01-07 22:20:42 +00:00 · 2026-01-07 15:39:31 +00:00 · 2026-01-07 14:55:43 +00:00 · 2026-01-07 11:40:39 +00:00
91 changed files with 9874 additions and 2974 deletions
@@ -1,8 +1,8 @@
-blank_issues_enabled: false
+blank_issues_enabled: true
 contact_links:
  - name: Documentation
    url: https://aka.ms/agent-framework
    about: Check out the official documentation for guides and API reference.
  - name: Discussions
    url: https://github.com/microsoft/agent-framework/discussions
-    about: Ask questions and share ideas in GitHub Discussions.
+    about: Ask questions about Agent Framework.
@@ -0,0 +1,70 @@
+name: .NET Bug Report
+description: Report a bug in the Agent Framework .NET SDK
+title: ".NET: [Bug]: "
+labels: ["bug", ".NET"]
+type: bug
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: Please provide a clear and detailed description of the bug.
+      placeholder: |
+        - What happened?
+        - What did you expect to happen?
+        - Steps to reproduce the issue
+    validations:
+      required: true
+
+  - type: textarea
+    id: code-sample
+    attributes:
+      label: Code Sample
+      description: If applicable, provide a minimal code sample that demonstrates the issue.
+      placeholder: |
+        ```csharp
+        // Your code here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: textarea
+    id: error-messages
+    attributes:
+      label: Error Messages / Stack Traces
+      description: Include any error messages or stack traces you received.
+      placeholder: |
+        ```
+        Paste error messages or stack traces here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: input
+    id: dotnet-packages
+    attributes:
+      label: Package Versions
+      description: List the Microsoft.Agents.* packages and versions you are using
+      placeholder: "e.g., Microsoft.Agents.AI.Abstractions: 1.0.0, Microsoft.Agents.AI.OpenAI: 1.0.0"
+    validations:
+      required: true
+
+  - type: input
+    id: dotnet-version
+    attributes:
+      label: .NET Version
+      description: What version of .NET are you using?
+      placeholder: "e.g., .NET 8.0"
+    validations:
+      required: false
+
+  - type: textarea
+    id: additional-context
+    attributes:
+      label: Additional Context
+      description: Add any other context or screenshots that might be helpful.
+      placeholder: "Any additional information..."
+    validations:
+      required: false
@@ -0,0 +1,51 @@
+name: Feature Request
+description: Request a new feature for Microsoft Agent Framework
+title: "[Feature]: "
+type: feature
+body:
+
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: Please describe the feature you'd like and why it would be useful.
+      placeholder: |
+        Describe the feature you're requesting:
+        - What problem does it solve?
+        - What would the expected behavior be?
+        - Are there any alternatives you've considered?
+    validations:
+      required: true
+
+  - type: textarea
+    id: code-sample
+    attributes:
+      label: Code Sample
+      description: If applicable, provide a code sample showing how you'd like to use this feature.
+      placeholder: |
+        ```python
+        # Your code here
+        ```
+
+        or
+
+        ```csharp
+        // Your code here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: dropdown
+    id: language
+    attributes:
+      label: Language/SDK
+      description: Which language/SDK does this feature apply to?
+      options:
+        - Both
+        - .NET
+        - Python
+        - Other / Not Applicable
+      default: 0
+    validations:
+      required: false
@@ -1,203 +0,0 @@
-name: Issue Report
-description: Report a bug, request a feature, or ask a question about Microsoft Agent Framework
-title: "[Issue]: "
-labels: ["triage"]
-body:
-  - type: dropdown
-    id: language
-    attributes:
-      label: Language
-      description: Which language/SDK are you using?
-      options:
-        - .NET
-        - Python
-        - None / Not Applicable
-    validations:
-      required: true
-
-  - type: dropdown
-    id: issue-type
-    attributes:
-      label: Type of Issue
-      description: What type of issue is this?
-      options:
-        - Bug
-        - Feature Request
-        - Question
-    validations:
-      required: true
-
-  - type: markdown
-    attributes:
-      value: |
-        ## Version Information
-        Please provide the version of the package(s) you are using. Select the relevant packages below.
-
-  - type: markdown
-    attributes:
-      value: "### .NET Packages"
-
-  - type: input
-    id: dotnet-agents-ai
-    attributes:
-      label: Microsoft.Agents.AI
-      description: Version of Microsoft.Agents.AI (e.g., 1.0.0)
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-agents-ai-abstractions
-    attributes:
-      label: Microsoft.Agents.AI.Abstractions
-      description: Version of Microsoft.Agents.AI.Abstractions
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-agents-ai-openai
-    attributes:
-      label: Microsoft.Agents.AI.OpenAI
-      description: Version of Microsoft.Agents.AI.OpenAI
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-agents-ai-azureai
-    attributes:
-      label: Microsoft.Agents.AI.AzureAI
-      description: Version of Microsoft.Agents.AI.AzureAI
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-agents-ai-anthropic
-    attributes:
-      label: Microsoft.Agents.AI.Anthropic
-      description: Version of Microsoft.Agents.AI.Anthropic
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-agents-ai-hosting
-    attributes:
-      label: Microsoft.Agents.AI.Hosting
-      description: Version of Microsoft.Agents.AI.Hosting
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-agents-ai-workflows
-    attributes:
-      label: Microsoft.Agents.AI.Workflows
-      description: Version of Microsoft.Agents.AI.Workflows
-      placeholder: "e.g., 1.0.0"
-    validations:
-      required: false
-
-  - type: input
-    id: dotnet-other-packages
-    attributes:
-      label: Other .NET Packages
-      description: List any other Microsoft.Agents.* packages and versions you are using
-      placeholder: "e.g., Microsoft.Agents.AI.CopilotStudio: 1.0.0, Microsoft.Agents.AI.Purview: 1.0.0"
-    validations:
-      required: false
-
-  - type: markdown
-    attributes:
-      value: "### Python Packages"
-
-  - type: input
-    id: python-core
-    attributes:
-      label: agent-framework-core
-      description: Version of agent-framework-core
-      placeholder: "e.g., 1.0.0b1"
-    validations:
-      required: false
-
-  - type: input
-    id: python-azure-ai
-    attributes:
-      label: agent-framework-azure-ai
-      description: Version of agent-framework-azure-ai
-      placeholder: "e.g., 1.0.0b1"
-    validations:
-      required: false
-
-  - type: input
-    id: python-anthropic
-    attributes:
-      label: agent-framework-anthropic
-      description: Version of agent-framework-anthropic
-      placeholder: "e.g., 1.0.0b1"
-    validations:
-      required: false
-
-  - type: input
-    id: python-azurefunctions
-    attributes:
-      label: agent-framework-azurefunctions
-      description: Version of agent-framework-azurefunctions
-      placeholder: "e.g., 1.0.0b1"
-    validations:
-      required: false
-
-  - type: input
-    id: python-other-packages
-    attributes:
-      label: Other Python Packages
-      description: List any other agent-framework-* packages and versions you are using
-      placeholder: "e.g., agent-framework-mem0: 1.0.0b1, agent-framework-redis: 1.0.0b1"
-    validations:
-      required: false
-
-  - type: markdown
-    attributes:
-      value: "---"
-
-  - type: textarea
-    id: description
-    attributes:
-      label: Description
-      description: Please provide a clear and detailed description of the issue, feature request, or question.
-      placeholder: |
-        For bugs: Describe what happened, what you expected to happen, and steps to reproduce.
-        For features: Describe the feature you'd like and why it would be useful.
-        For questions: Describe what you're trying to accomplish.
-    validations:
-      required: true
-
-  - type: textarea
-    id: code-sample
-    attributes:
-      label: Code Sample
-      description: If applicable, provide a minimal code sample that demonstrates the issue or your use case.
-      placeholder: |
-        ```python
-        # Your code here
-        ```
-
-        or
-
-        ```csharp
-        // Your code here
-        ```
-      render: markdown
-    validations:
-      required: false
-
-  - type: textarea
-    id: additional-context
-    attributes:
-      label: Additional Context
-      description: Add any other context, screenshots, error messages, or stack traces that might be helpful.
-      placeholder: "Any additional information..."
-    validations:
-      required: false
@@ -0,0 +1,70 @@
+name: Python Bug Report
+description: Report a bug in the Agent Framework Python SDK
+title: "Python: [Bug]: "
+labels: ["bug", "Python"]
+type: bug
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: Please provide a clear and detailed description of the bug.
+      placeholder: |
+        - What happened?
+        - What did you expect to happen?
+        - Steps to reproduce the issue
+    validations:
+      required: true
+
+  - type: textarea
+    id: code-sample
+    attributes:
+      label: Code Sample
+      description: If applicable, provide a minimal code sample that demonstrates the issue.
+      placeholder: |
+        ```python
+        # Your code here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: textarea
+    id: error-messages
+    attributes:
+      label: Error Messages / Stack Traces
+      description: Include any error messages or stack traces you received.
+      placeholder: |
+        ```
+        Paste error messages or stack traces here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: input
+    id: python-packages
+    attributes:
+      label: Package Versions
+      description: List the agent-framework-* packages and versions you are using
+      placeholder: "e.g., agent-framework-core: 1.0.0, agent-framework-azure-ai: 1.0.0"
+    validations:
+      required: true
+
+  - type: input
+    id: python-version
+    attributes:
+      label: Python Version
+      description: What version of Python are you using?
+      placeholder: "e.g., Python 3.11"
+    validations:
+      required: false
+
+  - type: textarea
+    id: additional-context
+    attributes:
+      label: Additional Context
+      description: Add any other context or screenshots that might be helpful.
+      placeholder: "Any additional information..."
+    validations:
+      required: false
@@ -291,6 +291,15 @@ public class AgentRunResponse
        return updates;
    }

+    /// <summary>
+    /// Deserializes the response text into the given type.
+    /// </summary>
+    /// <typeparam name="T">The output type to deserialize into.</typeparam>
+    /// <returns>The result as the requested type.</returns>
+    /// <exception cref="InvalidOperationException">The result is not parsable into the requested type.</exception>
+    public T Deserialize<T>() =>
+        this.Deserialize<T>(AgentAbstractionsJsonUtilities.DefaultOptions);
+
    /// <summary>
    /// Deserializes the response text into the given type using the specified serializer options.
    /// </summary>
@@ -311,6 +320,15 @@ public class AgentRunResponse
        };
    }

+    /// <summary>
+    /// Tries to deserialize response text into the given type.
+    /// </summary>
+    /// <typeparam name="T">The output type to deserialize into.</typeparam>
+    /// <param name="structuredOutput">The parsed structured output.</param>
+    /// <returns><see langword="true" /> if parsing was successful; otherwise, <see langword="false" />.</returns>
+    public bool TryDeserialize<T>([NotNullWhen(true)] out T? structuredOutput) =>
+        this.TryDeserialize(AgentAbstractionsJsonUtilities.DefaultOptions, out structuredOutput);
+
    /// <summary>
    /// Tries to deserialize response text into the given type using the specified serializer options.
    /// </summary>
@@ -80,7 +80,7 @@ public sealed class ChatClientAgentOptions
    /// <summary>
    /// Context object passed to the <see cref="AIContextProviderFactory"/> to create a new instance of <see cref="AIContextProvider"/>.
    /// </summary>
-    public class AIContextProviderFactoryContext
+    public sealed class AIContextProviderFactoryContext
    {
        /// <summary>
        /// Gets or sets the serialized state of the <see cref="AIContextProvider"/>, if any.
@@ -97,7 +97,7 @@ public sealed class ChatClientAgentOptions
    /// <summary>
    /// Context object passed to the <see cref="ChatMessageStoreFactory"/> to create a new instance of <see cref="ChatMessageStore"/>.
    /// </summary>
-    public class ChatMessageStoreFactoryContext
+    public sealed class ChatMessageStoreFactoryContext
    {
        /// <summary>
        /// Gets or sets the serialized state of the chat message store, if any.
@@ -40,7 +40,6 @@ public sealed class ChatClientAgentRunResponse<T> : AgentRunResponse<T>
    /// </summary>
    /// <remarks>
    /// If the response did not contain JSON, or if deserialization fails, this property will throw.
-    /// To avoid exceptions, use <see cref="AgentRunResponse.TryDeserialize{T}"/> instead.
    /// </remarks>
    public override T Result => this._response.Result;
 }
@@ -214,6 +214,12 @@ public class AgentRunResponseTests
        Assert.Equal(100, usageContent.Details.TotalTokenCount);
    }

+#if NETFRAMEWORK
+    /// <summary>
+    /// Since Json Serialization using reflection is disabled in .net core builds, and we are using a custom type here that wouldn't
+    /// be registered with the default source generated serializer, this test will only pass in .net framework builds where reflection-based
+    /// serialization is available.
+    /// </summary>
    [Fact]
    public void ParseAsStructuredOutputSuccess()
    {
@@ -221,6 +227,24 @@ public class AgentRunResponseTests
        var expectedResult = new Animal { Id = 1, FullName = "Tigger", Species = Species.Tiger };
        var response = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, JsonSerializer.Serialize(expectedResult, TestJsonSerializerContext.Default.Animal)));

+        // Act.
+        var animal = response.Deserialize<Animal>();
+
+        // Assert.
+        Assert.NotNull(animal);
+        Assert.Equal(expectedResult.Id, animal.Id);
+        Assert.Equal(expectedResult.FullName, animal.FullName);
+        Assert.Equal(expectedResult.Species, animal.Species);
+    }
+#endif
+
+    [Fact]
+    public void ParseAsStructuredOutputWithJSOSuccess()
+    {
+        // Arrange.
+        var expectedResult = new Animal { Id = 1, FullName = "Tigger", Species = Species.Tiger };
+        var response = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, JsonSerializer.Serialize(expectedResult, TestJsonSerializerContext.Default.Animal)));
+
        // Act.
        var animal = response.Deserialize<Animal>(TestJsonSerializerContext.Default.Options);

@@ -262,6 +286,12 @@ public class AgentRunResponseTests
        Assert.Throws<JsonException>(() => response.Deserialize<Animal>(TestJsonSerializerContext.Default.Options));
    }

+#if NETFRAMEWORK
+    /// <summary>
+    /// Since Json Serialization using reflection is disabled in .net core builds, and we are using a custom type here that wouldn't
+    /// be registered with the default source generated serializer, this test will only pass in .net framework builds where reflection-based
+    /// serialization is available.
+    /// </summary>
    [Fact]
    public void TryParseAsStructuredOutputSuccess()
    {
@@ -269,6 +299,24 @@ public class AgentRunResponseTests
        var expectedResult = new Animal { Id = 1, FullName = "Tigger", Species = Species.Tiger };
        var response = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, JsonSerializer.Serialize(expectedResult, TestJsonSerializerContext.Default.Animal)));

+        // Act.
+        response.TryDeserialize(out Animal? animal);
+
+        // Assert.
+        Assert.NotNull(animal);
+        Assert.Equal(expectedResult.Id, animal.Id);
+        Assert.Equal(expectedResult.FullName, animal.FullName);
+        Assert.Equal(expectedResult.Species, animal.Species);
+    }
+#endif
+
+    [Fact]
+    public void TryParseAsStructuredOutputWithJSOSuccess()
+    {
+        // Arrange.
+        var expectedResult = new Animal { Id = 1, FullName = "Tigger", Species = Species.Tiger };
+        var response = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, JsonSerializer.Serialize(expectedResult, TestJsonSerializerContext.Default.Animal)));
+
        // Act.
        response.TryDeserialize(TestJsonSerializerContext.Default.Options, out Animal? animal);

@@ -7,6 +7,25 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

+## [1.0.0b260106] - 2026-01-06
+
+### Added
+
+- **repo**: Add issue template and additional labeling ([#3006](https://github.com/microsoft/agent-framework/pull/3006)) by @eavanvalkenburg
+
+### Changed
+
+- None
+
+### Fixed
+
+- **agent-framework-core**: Fix max tokens translation and add extra integer test ([#3037](https://github.com/microsoft/agent-framework/pull/3037)) by @eavanvalkenburg
+- **agent-framework-azure-ai**: Fix failure when conversation history contains assistant messages ([#3076](https://github.com/microsoft/agent-framework/pull/3076)) by @moonbox3
+- **agent-framework-core**: Use HTTP exporter for http/protobuf protocol ([#3070](https://github.com/microsoft/agent-framework/pull/3070)) by @takanori-terai
+- **agent-framework-core**: Fix ExecutorInvokedEvent and ExecutorCompletedEvent observability data ([#3090](https://github.com/microsoft/agent-framework/pull/3090)) by @moonbox3
+- **agent-framework-core**: Honor tool_choice parameter passed to agent.run() and chat client methods ([#3095](https://github.com/microsoft/agent-framework/pull/3095)) by @moonbox3
+- **samples**: AzureAI SharePoint sample fix ([#3108](https://github.com/microsoft/agent-framework/pull/3108)) by @giles17
+
 ## [1.0.0b251223] - 2025-12-23

 ### Added
@@ -426,7 +445,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 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-1.0.0b251223...HEAD
+[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.0.0b260106...HEAD
+[1.0.0b260106]: https://github.com/microsoft/agent-framework/compare/python-1.0.0b251223...python-1.0.0b260106
 [1.0.0b251223]: https://github.com/microsoft/agent-framework/compare/python-1.0.0b251218...python-1.0.0b251223
 [1.0.0b251218]: https://github.com/microsoft/agent-framework/compare/python-1.0.0b251216...python-1.0.0b251218
 [1.0.0b251216]: https://github.com/microsoft/agent-framework/compare/python-1.0.0b251211...python-1.0.0b251216
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -31,6 +31,7 @@ from agent_framework import (
    FunctionCallContent,
    FunctionResultContent,
    TextContent,
+    prepare_function_call_results,
 )

 from ._utils import generate_event_id
@@ -391,12 +392,7 @@ class AgentFrameworkEventBridge:
            self.state_delta_count = 0

        result_message_id = generate_event_id()
-        if isinstance(content.result, dict):
-            result_content = json.dumps(content.result)  # type: ignore[arg-type]
-        elif content.result is not None:
-            result_content = str(content.result)
-        else:
-            result_content = ""
+        result_content = prepare_function_call_results(content.result)

        result_event = ToolCallResultEvent(
            message_id=result_message_id,
@@ -2,6 +2,7 @@

 """Message format conversion between AG-UI and Agent Framework."""

+import json
 from typing import Any, cast

 from agent_framework import (
@@ -11,6 +12,7 @@ from agent_framework import (
    FunctionResultContent,
    Role,
    TextContent,
+    prepare_function_call_results,
 )

 # Role mapping constants
@@ -59,10 +61,8 @@ def agui_messages_to_agent_framework(messages: list[dict[str, Any]]) -> list[Cha
            # Distinguish approval payloads from actual tool results
            is_approval = False
            if isinstance(result_content, str) and result_content:
-                import json as _json
-
                try:
-                    parsed = _json.loads(result_content)
+                    parsed = json.loads(result_content)
                    is_approval = isinstance(parsed, dict) and "accepted" in parsed
                except Exception:
                    is_approval = False
@@ -237,13 +237,8 @@ def agent_framework_messages_to_agui(messages: list[ChatMessage] | list[dict[str
            elif isinstance(content, FunctionResultContent):
                # Tool result content - extract call_id and result
                tool_result_call_id = content.call_id
-                # Serialize result to string
-                if isinstance(content.result, dict):
-                    import json
-
-                    content_text = json.dumps(content.result)  # type: ignore
-                elif content.result is not None:
-                    content_text = str(content.result)
+                # Serialize result to string using core utility
+                content_text = prepare_function_call_results(content.result)

        agui_msg: dict[str, Any] = {
            "id": msg.message_id if msg.message_id else generate_event_id(),  # Always include id
@@ -1,6 +1,6 @@
 [project]
 name = "agent-framework-ag-ui"
-version = "1.0.0b251223"
+version = "1.0.0b260106"
 description = "AG-UI protocol integration for Agent Framework"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -201,7 +201,8 @@ async def test_tool_result_with_none():
    assert len(events) == 2
    assert events[0].type == "TOOL_CALL_END"
    assert events[1].type == "TOOL_CALL_RESULT"
-    assert events[1].content == ""
+    # prepare_function_call_results serializes None as JSON "null"
+    assert events[1].content == "null"


 async def test_multiple_tool_results_in_sequence():
@@ -688,3 +689,97 @@ async def test_state_delta_count_logging():

    # State delta count should have incremented (one per unique state update)
    assert bridge.state_delta_count >= 1
+
+
+# Tests for list type tool results (MCP tool serialization)
+
+
+async def test_tool_result_with_empty_list():
+    """Test FunctionResultContent with empty list result."""
+    from agent_framework_ag_ui._events import AgentFrameworkEventBridge
+
+    bridge = AgentFrameworkEventBridge(run_id="test_run", thread_id="test_thread")
+
+    update = AgentRunResponseUpdate(contents=[FunctionResultContent(call_id="call_123", result=[])])
+    events = await bridge.from_agent_run_update(update)
+
+    assert len(events) == 2
+    assert events[0].type == "TOOL_CALL_END"
+    assert events[1].type == "TOOL_CALL_RESULT"
+    # Empty list serializes as JSON empty array
+    assert events[1].content == "[]"
+
+
+async def test_tool_result_with_single_text_content():
+    """Test FunctionResultContent with single TextContent-like item (MCP tool result)."""
+    from dataclasses import dataclass
+
+    from agent_framework_ag_ui._events import AgentFrameworkEventBridge
+
+    @dataclass
+    class MockTextContent:
+        text: str
+
+    bridge = AgentFrameworkEventBridge(run_id="test_run", thread_id="test_thread")
+
+    update = AgentRunResponseUpdate(
+        contents=[FunctionResultContent(call_id="call_123", result=[MockTextContent("Hello from MCP tool!")])]
+    )
+    events = await bridge.from_agent_run_update(update)
+
+    assert len(events) == 2
+    assert events[0].type == "TOOL_CALL_END"
+    assert events[1].type == "TOOL_CALL_RESULT"
+    # TextContent text is extracted and serialized as JSON array
+    assert events[1].content == '["Hello from MCP tool!"]'
+
+
+async def test_tool_result_with_multiple_text_contents():
+    """Test FunctionResultContent with multiple TextContent-like items (MCP tool result)."""
+    from dataclasses import dataclass
+
+    from agent_framework_ag_ui._events import AgentFrameworkEventBridge
+
+    @dataclass
+    class MockTextContent:
+        text: str
+
+    bridge = AgentFrameworkEventBridge(run_id="test_run", thread_id="test_thread")
+
+    update = AgentRunResponseUpdate(
+        contents=[
+            FunctionResultContent(
+                call_id="call_123",
+                result=[MockTextContent("First result"), MockTextContent("Second result")],
+            )
+        ]
+    )
+    events = await bridge.from_agent_run_update(update)
+
+    assert len(events) == 2
+    assert events[0].type == "TOOL_CALL_END"
+    assert events[1].type == "TOOL_CALL_RESULT"
+    # Multiple TextContent items should return JSON array
+    assert events[1].content == '["First result", "Second result"]'
+
+
+async def test_tool_result_with_model_dump_objects():
+    """Test FunctionResultContent with Pydantic BaseModel objects."""
+    from pydantic import BaseModel
+
+    from agent_framework_ag_ui._events import AgentFrameworkEventBridge
+
+    class MockModel(BaseModel):
+        value: int
+
+    bridge = AgentFrameworkEventBridge(run_id="test_run", thread_id="test_thread")
+
+    update = AgentRunResponseUpdate(
+        contents=[FunctionResultContent(call_id="call_123", result=[MockModel(value=1), MockModel(value=2)])]
+    )
+    events = await bridge.from_agent_run_update(update)
+
+    assert len(events) == 2
+    assert events[1].type == "TOOL_CALL_RESULT"
+    # Should be properly serialized JSON array without double escaping
+    assert events[1].content == '[{"value": 1}, {"value": 2}]'
@@ -3,7 +3,7 @@
 """Tests for message adapters."""

 import pytest
-from agent_framework import ChatMessage, FunctionCallContent, Role, TextContent
+from agent_framework import ChatMessage, FunctionCallContent, FunctionResultContent, Role, TextContent

 from agent_framework_ag_ui._message_adapters import (
    agent_framework_messages_to_agui,
@@ -278,3 +278,119 @@ def test_extract_text_from_custom_contents():
    result = extract_text_from_contents(contents)

    assert result == "Custom Mixed"
+
+
+# Tests for FunctionResultContent serialization in agent_framework_messages_to_agui
+
+
+def test_agent_framework_to_agui_function_result_dict():
+    """Test converting FunctionResultContent with dict result to AG-UI."""
+    msg = ChatMessage(
+        role=Role.TOOL,
+        contents=[FunctionResultContent(call_id="call-123", result={"key": "value", "count": 42})],
+        message_id="msg-789",
+    )
+
+    messages = agent_framework_messages_to_agui([msg])
+
+    assert len(messages) == 1
+    agui_msg = messages[0]
+    assert agui_msg["role"] == "tool"
+    assert agui_msg["toolCallId"] == "call-123"
+    assert agui_msg["content"] == '{"key": "value", "count": 42}'
+
+
+def test_agent_framework_to_agui_function_result_none():
+    """Test converting FunctionResultContent with None result to AG-UI."""
+    msg = ChatMessage(
+        role=Role.TOOL,
+        contents=[FunctionResultContent(call_id="call-123", result=None)],
+        message_id="msg-789",
+    )
+
+    messages = agent_framework_messages_to_agui([msg])
+
+    assert len(messages) == 1
+    agui_msg = messages[0]
+    # None serializes as JSON null
+    assert agui_msg["content"] == "null"
+
+
+def test_agent_framework_to_agui_function_result_string():
+    """Test converting FunctionResultContent with string result to AG-UI."""
+    msg = ChatMessage(
+        role=Role.TOOL,
+        contents=[FunctionResultContent(call_id="call-123", result="plain text result")],
+        message_id="msg-789",
+    )
+
+    messages = agent_framework_messages_to_agui([msg])
+
+    assert len(messages) == 1
+    agui_msg = messages[0]
+    assert agui_msg["content"] == "plain text result"
+
+
+def test_agent_framework_to_agui_function_result_empty_list():
+    """Test converting FunctionResultContent with empty list result to AG-UI."""
+    msg = ChatMessage(
+        role=Role.TOOL,
+        contents=[FunctionResultContent(call_id="call-123", result=[])],
+        message_id="msg-789",
+    )
+
+    messages = agent_framework_messages_to_agui([msg])
+
+    assert len(messages) == 1
+    agui_msg = messages[0]
+    # Empty list serializes as JSON empty array
+    assert agui_msg["content"] == "[]"
+
+
+def test_agent_framework_to_agui_function_result_single_text_content():
+    """Test converting FunctionResultContent with single TextContent-like item."""
+    from dataclasses import dataclass
+
+    @dataclass
+    class MockTextContent:
+        text: str
+
+    msg = ChatMessage(
+        role=Role.TOOL,
+        contents=[FunctionResultContent(call_id="call-123", result=[MockTextContent("Hello from MCP!")])],
+        message_id="msg-789",
+    )
+
+    messages = agent_framework_messages_to_agui([msg])
+
+    assert len(messages) == 1
+    agui_msg = messages[0]
+    # TextContent text is extracted and serialized as JSON array
+    assert agui_msg["content"] == '["Hello from MCP!"]'
+
+
+def test_agent_framework_to_agui_function_result_multiple_text_contents():
+    """Test converting FunctionResultContent with multiple TextContent-like items."""
+    from dataclasses import dataclass
+
+    @dataclass
+    class MockTextContent:
+        text: str
+
+    msg = ChatMessage(
+        role=Role.TOOL,
+        contents=[
+            FunctionResultContent(
+                call_id="call-123",
+                result=[MockTextContent("First result"), MockTextContent("Second result")],
+            )
+        ],
+        message_id="msg-789",
+    )
+
+    messages = agent_framework_messages_to_agui([msg])
+
+    assert len(messages) == 1
+    agui_msg = messages[0]
+    # Multiple items should return JSON array
+    assert agui_msg["content"] == '["First result", "Second result"]'
@@ -5,7 +5,11 @@
 from dataclasses import dataclass
 from datetime import date, datetime

-from agent_framework_ag_ui._utils import generate_event_id, make_json_safe, merge_state
+from agent_framework_ag_ui._utils import (
+    generate_event_id,
+    make_json_safe,
+    merge_state,
+)


 def test_generate_event_id():
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -300,13 +300,26 @@ class AzureAIClient(OpenAIBaseResponsesClient):
        raise ServiceInvalidRequestError("response_format must be a Pydantic model or mapping.")

    async def _get_agent_reference_or_create(
-        self, run_options: dict[str, Any], messages_instructions: str | None
+        self,
+        run_options: dict[str, Any],
+        messages_instructions: str | None,
+        chat_options: ChatOptions | None = None,
    ) -> dict[str, str]:
        """Determine which agent to use and create if needed.

+        Args:
+            run_options: The prepared options for the API call.
+            messages_instructions: Instructions extracted from messages.
+            chat_options: The chat options containing response_format and other settings.
+
        Returns:
            dict[str, str]: The agent reference to use.
        """
+        # chat_options is needed separately because the base class excludes response_format
+        # from run_options (transforming it to text/text_format for OpenAI). Azure's agent
+        # creation API requires the original response_format to build its own config format.
+        if chat_options is None:
+            chat_options = ChatOptions()
        # Agent name must be explicitly provided by the user.
        if self.agent_name is None:
            raise ServiceInitializationError(
@@ -341,8 +354,14 @@ class AzureAIClient(OpenAIBaseResponsesClient):
            if "top_p" in run_options:
                args["top_p"] = run_options["top_p"]

-            if "response_format" in run_options:
-                response_format = run_options["response_format"]
+            # response_format is accessed from chat_options or additional_properties
+            # since the base class excludes it from run_options
+            response_format: Any = (
+                chat_options.response_format
+                if chat_options.response_format is not None
+                else chat_options.additional_properties.get("response_format")
+            )
+            if response_format:
                args["text"] = PromptAgentDefinitionText(format=self._create_text_format_config(response_format))

            # Combine instructions from messages and options
@@ -390,12 +409,12 @@ class AzureAIClient(OpenAIBaseResponsesClient):

        if not self._is_application_endpoint:
            # Application-scoped response APIs do not support "agent" property.
-            agent_reference = await self._get_agent_reference_or_create(run_options, instructions)
+            agent_reference = await self._get_agent_reference_or_create(run_options, instructions, chat_options)
            run_options["extra_body"] = {"agent": agent_reference}

        # Remove properties that are not supported on request level
        # but were configured on agent level
-        exclude = ["model", "tools", "response_format", "temperature", "top_p"]
+        exclude = ["model", "tools", "response_format", "temperature", "top_p", "text", "text_format"]

        for property in exclude:
            run_options.pop(property, None)
@@ -4,7 +4,7 @@ description = "Azure AI Foundry integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -723,9 +723,10 @@ async def test_azure_ai_client_agent_creation_with_response_format(
    mock_agent.version = "1.0"
    mock_project_client.agents.create_version = AsyncMock(return_value=mock_agent)

-    run_options = {"model": "test-model", "response_format": ResponseFormatModel}
+    run_options = {"model": "test-model"}
+    chat_options = ChatOptions(response_format=ResponseFormatModel)

-    await client._get_agent_reference_or_create(run_options, None)  # type: ignore
+    await client._get_agent_reference_or_create(run_options, None, chat_options)  # type: ignore

    # Verify agent was created with response format configuration
    call_args = mock_project_client.agents.create_version.call_args
@@ -776,19 +777,18 @@ async def test_azure_ai_client_agent_creation_with_mapping_response_format(
        "additionalProperties": False,
    }

-    run_options = {
-        "model": "test-model",
-        "response_format": {
-            "type": "json_schema",
-            "json_schema": {
-                "name": runtime_schema["title"],
-                "strict": True,
-                "schema": runtime_schema,
-            },
+    run_options = {"model": "test-model"}
+    response_format_mapping = {
+        "type": "json_schema",
+        "json_schema": {
+            "name": runtime_schema["title"],
+            "strict": True,
+            "schema": runtime_schema,
        },
    }
+    chat_options = ChatOptions(response_format=response_format_mapping)  # type: ignore

-    await client._get_agent_reference_or_create(run_options, None)  # type: ignore
+    await client._get_agent_reference_or_create(run_options, None, chat_options)  # type: ignore

    call_args = mock_project_client.agents.create_version.call_args
    created_definition = call_args[1]["definition"]
@@ -805,7 +805,7 @@ async def test_azure_ai_client_agent_creation_with_mapping_response_format(
 async def test_azure_ai_client_prepare_options_excludes_response_format(
    mock_project_client: MagicMock,
 ) -> None:
-    """Test that prepare_options excludes response_format from final run options."""
+    """Test that prepare_options excludes response_format, text, and text_format from final run options."""
    client = create_test_azure_ai_client(mock_project_client, agent_name="test-agent", agent_version="1.0")

    messages = [ChatMessage(role=Role.USER, contents=[TextContent(text="Hello")])]
@@ -815,7 +815,12 @@ async def test_azure_ai_client_prepare_options_excludes_response_format(
        patch.object(
            client.__class__.__bases__[0],
            "_prepare_options",
-            return_value={"model": "test-model", "response_format": ResponseFormatModel},
+            return_value={
+                "model": "test-model",
+                "response_format": ResponseFormatModel,
+                "text": {"format": {"type": "json_schema", "name": "test"}},
+                "text_format": ResponseFormatModel,
+            },
        ),
        patch.object(
            client,
@@ -825,8 +830,11 @@ async def test_azure_ai_client_prepare_options_excludes_response_format(
    ):
        run_options = await client._prepare_options(messages, chat_options)

-        # response_format should be excluded from final run options
+        # response_format, text, and text_format should be excluded from final run options
+        # because they are configured at agent level, not request level
        assert "response_format" not in run_options
+        assert "text" not in run_options
+        assert "text_format" not in run_options
        # But extra_body should contain agent reference
        assert "extra_body" in run_options
        assert run_options["extra_body"]["agent"]["name"] == "test-agent"
@@ -1009,3 +1017,91 @@ async def test_azure_ai_chat_client_agent_with_tools() -> None:
        assert response.text is not None
        assert len(response.text) > 0
        assert any(word in response.text.lower() for word in ["sunny", "25"])
+
+
+class ReleaseBrief(BaseModel):
+    """Structured output model for release brief."""
+
+    title: str = Field(description="A short title for the release.")
+    summary: str = Field(description="A brief summary of what was released.")
+    highlights: list[str] = Field(description="Key highlights from the release.")
+    model_config = ConfigDict(extra="forbid")
+
+
+@pytest.mark.flaky
+@skip_if_azure_ai_integration_tests_disabled
+async def test_azure_ai_chat_client_agent_with_response_format() -> None:
+    """Test ChatAgent with response_format (structured output) using AzureAIClient."""
+    async with (
+        temporary_chat_client(agent_name="ResponseFormatAgent") as chat_client,
+        ChatAgent(chat_client=chat_client) as agent,
+    ):
+        response = await agent.run(
+            "Summarize the following release notes into a ReleaseBrief:\n\n"
+            "Version 2.0 Release Notes:\n"
+            "- Added new streaming API for real-time responses\n"
+            "- Improved error handling with detailed messages\n"
+            "- Performance boost of 50% in batch processing\n"
+            "- Fixed memory leak in connection pooling",
+            response_format=ReleaseBrief,
+        )
+
+        # Validate response
+        assert isinstance(response, AgentRunResponse)
+        assert response.value is not None
+        assert isinstance(response.value, ReleaseBrief)
+
+        # Validate structured output fields
+        brief = response.value
+        assert len(brief.title) > 0
+        assert len(brief.summary) > 0
+        assert len(brief.highlights) > 0
+
+
+@pytest.mark.flaky
+@skip_if_azure_ai_integration_tests_disabled
+async def test_azure_ai_chat_client_agent_with_runtime_json_schema() -> None:
+    """Test ChatAgent with runtime JSON schema (structured output) using AzureAIClient."""
+    runtime_schema = {
+        "title": "WeatherDigest",
+        "type": "object",
+        "properties": {
+            "location": {"type": "string"},
+            "conditions": {"type": "string"},
+            "temperature_c": {"type": "number"},
+            "advisory": {"type": "string"},
+        },
+        "required": ["location", "conditions", "temperature_c", "advisory"],
+        "additionalProperties": False,
+    }
+
+    async with (
+        temporary_chat_client(agent_name="RuntimeSchemaAgent") as chat_client,
+        ChatAgent(chat_client=chat_client) as agent,
+    ):
+        response = await agent.run(
+            "Give a brief weather digest for Seattle.",
+            additional_chat_options={
+                "response_format": {
+                    "type": "json_schema",
+                    "json_schema": {
+                        "name": runtime_schema["title"],
+                        "strict": True,
+                        "schema": runtime_schema,
+                    },
+                },
+            },
+        )
+
+        # Validate response
+        assert isinstance(response, AgentRunResponse)
+        assert response.text is not None
+
+        # Parse JSON and validate structure
+        import json
+
+        parsed = json.loads(response.text)
+        assert "location" in parsed
+        assert "conditions" in parsed
+        assert "temperature_c" in parsed
+        assert "advisory" in parsed
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -1,102 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-"""
-Integration Tests for Callbacks Sample
-
-Tests the callbacks sample for event tracking and management.
-
-The function app is automatically started by the test fixture.
-
-Prerequisites:
- Azure OpenAI credentials configured (see packages/azurefunctions/tests/integration_tests/.env.example)
- Azurite or Azure Storage account configured
-
-Usage:
-    uv run pytest packages/azurefunctions/tests/integration_tests/test_03_callbacks.py -v
-"""
-
-from typing import Any
-
-import pytest
-import requests
-
-from .testutils import (
-    TIMEOUT,
-    SampleTestHelper,
-    skip_if_azure_functions_integration_tests_disabled,
-)
-
-# Module-level markers - applied to all tests in this file
-pytestmark = [
-    pytest.mark.sample("03_callbacks"),
-    pytest.mark.usefixtures("function_app_for_test"),
-    skip_if_azure_functions_integration_tests_disabled,
-]
-
-
-class TestSampleCallbacks:
-    """Tests for 03_callbacks sample."""
-
-    @pytest.fixture(autouse=True)
-    def _set_base_url(self, base_url: str) -> None:
-        """Provide the callback agent base URL for each test."""
-        self.base_url = f"{base_url}/api/agents/CallbackAgent"
-
-    @staticmethod
-    def _wait_for_callback_events(base_url: str, thread_id: str) -> list[dict[str, Any]]:
-        events: list[dict[str, Any]] = []
-        response = SampleTestHelper.get(f"{base_url}/callbacks/{thread_id}")
-        if response.status_code == 200:
-            events = response.json()
-        return events
-
-    def test_agent_with_callbacks(self) -> None:
-        """Test agent execution with callback tracking."""
-        thread_id = "test-callback"
-
-        response = SampleTestHelper.post_json(
-            f"{self.base_url}/run",
-            {"message": "Tell me about Python", "thread_id": thread_id},
-        )
-        assert response.status_code == 200
-        data = response.json()
-
-        assert data["status"] == "success"
-
-        events = self._wait_for_callback_events(self.base_url, thread_id)
-
-        assert events
-        assert any(event.get("event_type") == "final" for event in events)
-
-    def test_get_callbacks(self) -> None:
-        """Test retrieving callback events."""
-        thread_id = "test-callback-retrieve"
-
-        # Send a message first
-        SampleTestHelper.post_json(
-            f"{self.base_url}/run",
-            {"message": "Hello", "thread_id": thread_id, "wait_for_response": False},
-        )
-
-        # Get callbacks
-        response = SampleTestHelper.get(f"{self.base_url}/callbacks/{thread_id}")
-        assert response.status_code == 200
-        data = response.json()
-        assert isinstance(data, list)
-
-    def test_delete_callbacks(self) -> None:
-        """Test clearing callback events."""
-        thread_id = "test-callback-delete"
-
-        # Send a message first
-        SampleTestHelper.post_json(
-            f"{self.base_url}/run",
-            {"message": "Test", "thread_id": thread_id, "wait_for_response": False},
-        )
-
-        # Delete callbacks
-        response = requests.delete(f"{self.base_url}/callbacks/{thread_id}", timeout=TIMEOUT)
-        assert response.status_code == 204
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v"])
@@ -0,0 +1,125 @@
+# Copyright (c) Microsoft. All rights reserved.
+"""
+Integration Tests for Reliable Streaming Sample
+
+Tests the reliable streaming sample using Redis Streams for persistent message delivery.
+
+The function app is automatically started by the test fixture.
+
+Prerequisites:
+- Azure OpenAI credentials configured (see packages/azurefunctions/tests/integration_tests/.env.example)
+- Azurite or Azure Storage account configured
+- Redis running (docker run -d --name redis -p 6379:6379 redis:latest)
+
+Usage:
+    uv run pytest packages/azurefunctions/tests/integration_tests/test_03_reliable_streaming.py -v
+"""
+
+import time
+
+import pytest
+import requests
+
+from .testutils import (
+    SampleTestHelper,
+    skip_if_azure_functions_integration_tests_disabled,
+)
+
+# Module-level markers - applied to all tests in this file
+pytestmark = [
+    pytest.mark.sample("03_reliable_streaming"),
+    pytest.mark.usefixtures("function_app_for_test"),
+    skip_if_azure_functions_integration_tests_disabled,
+]
+
+
+class TestSampleReliableStreaming:
+    """Tests for 03_reliable_streaming sample."""
+
+    @pytest.fixture(autouse=True)
+    def _set_base_url(self, base_url: str) -> None:
+        """Provide the base URL for each test."""
+        self.base_url = base_url
+        self.agent_url = f"{base_url}/api/agents/TravelPlanner"
+        self.stream_url = f"{base_url}/api/agent/stream"
+
+    def test_agent_run_and_stream(self) -> None:
+        """Test agent execution with Redis streaming."""
+        # Start agent run
+        response = SampleTestHelper.post_json(
+            f"{self.agent_url}/run",
+            {"message": "Plan a 1-day trip to Seattle in 1 sentence", "wait_for_response": False},
+        )
+        assert response.status_code == 202
+        data = response.json()
+
+        thread_id = data.get("thread_id")
+
+        # Wait a moment for the agent to start writing to Redis
+        time.sleep(2)
+
+        # Stream response from Redis with shorter timeout
+        # Note: We use text/plain to avoid SSE parsing complexity
+        stream_response = requests.get(
+            f"{self.stream_url}/{thread_id}",
+            headers={"Accept": "text/plain"},
+            timeout=30,  # Shorter timeout for test
+        )
+        assert stream_response.status_code == 200
+
+    def test_stream_with_sse_format(self) -> None:
+        """Test streaming with Server-Sent Events format."""
+        # Start agent run
+        response = SampleTestHelper.post_json(
+            f"{self.agent_url}/run",
+            {"message": "What's the weather like?", "wait_for_response": False},
+        )
+        assert response.status_code == 202
+        data = response.json()
+        thread_id = data.get("thread_id")
+
+        # Wait for agent to start writing
+        time.sleep(2)
+
+        # Stream with SSE format
+        stream_response = requests.get(
+            f"{self.stream_url}/{thread_id}",
+            headers={"Accept": "text/event-stream"},
+            timeout=30,  # Shorter timeout
+        )
+        assert stream_response.status_code == 200
+        content_type = stream_response.headers.get("content-type", "")
+        assert "text/event-stream" in content_type
+
+        # Check for SSE event markers if we got content
+        content = stream_response.text
+        if content:
+            assert "event:" in content or "data:" in content
+
+    def test_stream_nonexistent_conversation(self) -> None:
+        """Test streaming from a non-existent conversation.
+
+        The endpoint will wait for data in Redis, but since the conversation
+        doesn't exist, it will timeout. This is expected behavior.
+        """
+        fake_id = "nonexistent-conversation-12345"
+
+        # Should timeout since the conversation doesn't exist
+        with pytest.raises(requests.exceptions.ReadTimeout):
+            requests.get(
+                f"{self.stream_url}/{fake_id}",
+                headers={"Accept": "text/plain"},
+                timeout=10,  # Short timeout for non-existent ID
+            )
+
+    def test_health_endpoint(self) -> None:
+        """Test health check endpoint."""
+        response = SampleTestHelper.get(f"{self.base_url}/api/health")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["status"] == "healthy"
+        assert "agents" in data
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -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 = "1.0.0b251120"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -1869,6 +1869,9 @@ def _prepare_function_call_results_as_dumpable(content: Contents | Any | list[Co
        return content.model_dump()
    if hasattr(content, "to_dict"):
        return content.to_dict(exclude={"raw_representation", "additional_properties"})
+    # Handle objects with text attribute (e.g., MCP TextContent)
+    if hasattr(content, "text") and isinstance(content.text, str):
+        return content.text
    return content


@@ -439,16 +439,23 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
        if (tool_choice := run_options.get("tool_choice")) and isinstance(tool_choice, dict) and "mode" in tool_choice:
            run_options["tool_choice"] = tool_choice["mode"]

-        # additional properties
+        # additional properties (excluding response_format which is handled separately)
        additional_options = {
-            key: value for key, value in chat_options.additional_properties.items() if value is not None
+            key: value
+            for key, value in chat_options.additional_properties.items()
+            if value is not None and key != "response_format"
        }
        if additional_options:
            run_options.update(additional_options)

        # response format and text config (after additional_properties so user can pass text via additional_properties)
-        response_format = chat_options.response_format
-        text_config = run_options.pop("text", None)
+        # Check both chat_options.response_format and additional_properties for response_format
+        response_format: Any = (
+            chat_options.response_format
+            if chat_options.response_format is not None
+            else chat_options.additional_properties.get("response_format")
+        )
+        text_config: Any = run_options.pop("text", None)
        response_format, text_config = self._prepare_response_and_text_format(
            response_format=response_format, text_config=text_config
        )
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -2133,3 +2133,55 @@ def test_prepare_function_call_results_nested_pydantic_model():
    assert "Seattle" in json_result
    assert "rainy" in json_result
    assert "18.0" in json_result or "18" in json_result
+
+
+# region prepare_function_call_results with MCP TextContent-like objects
+
+
+def test_prepare_function_call_results_text_content_single():
+    """Test that objects with text attribute (like MCP TextContent) are properly handled."""
+    from dataclasses import dataclass
+
+    @dataclass
+    class MockTextContent:
+        text: str
+
+    result = [MockTextContent("Hello from MCP tool!")]
+    json_result = prepare_function_call_results(result)
+
+    # Should extract text and serialize as JSON array of strings
+    assert isinstance(json_result, str)
+    assert json_result == '["Hello from MCP tool!"]'
+
+
+def test_prepare_function_call_results_text_content_multiple():
+    """Test that multiple TextContent-like objects are serialized correctly."""
+    from dataclasses import dataclass
+
+    @dataclass
+    class MockTextContent:
+        text: str
+
+    result = [MockTextContent("First result"), MockTextContent("Second result")]
+    json_result = prepare_function_call_results(result)
+
+    # Should extract text from each and serialize as JSON array
+    assert isinstance(json_result, str)
+    assert json_result == '["First result", "Second result"]'
+
+
+def test_prepare_function_call_results_text_content_with_non_string_text():
+    """Test that objects with non-string text attribute are not treated as TextContent."""
+
+    class BadTextContent:
+        def __init__(self):
+            self.text = 12345  # Not a string!
+
+    result = [BadTextContent()]
+    json_result = prepare_function_call_results(result)
+
+    # Should not extract text since it's not a string, will serialize the object
+    assert isinstance(json_result, str)
+
+
+# endregion
@@ -2355,3 +2355,91 @@ async def test_openai_responses_client_agent_local_mcp_tool() -> None:
        assert len(response.text) > 0
        # Should contain Azure-related content since it's asking about Azure CLI
        assert any(term in response.text.lower() for term in ["azure", "storage", "account", "cli"])
+
+
+class ReleaseBrief(BaseModel):
+    """Structured output model for release brief testing."""
+
+    title: str
+    summary: str
+    highlights: list[str]
+    model_config = {"extra": "forbid"}
+
+
+@pytest.mark.flaky
+@skip_if_openai_integration_tests_disabled
+async def test_openai_responses_client_agent_with_response_format_pydantic() -> None:
+    """Integration test for response_format with Pydantic model using OpenAI Responses Client."""
+    async with ChatAgent(
+        chat_client=OpenAIResponsesClient(),
+        instructions="You are a helpful assistant that returns structured JSON responses.",
+    ) as agent:
+        response = await agent.run(
+            "Summarize the following release notes into a ReleaseBrief:\n\n"
+            "Version 2.0 Release Notes:\n"
+            "- Added new streaming API for real-time responses\n"
+            "- Improved error handling with detailed messages\n"
+            "- Performance boost of 50% in batch processing\n"
+            "- Fixed memory leak in connection pooling",
+            response_format=ReleaseBrief,
+        )
+
+        # Validate response
+        assert isinstance(response, AgentRunResponse)
+        assert response.value is not None
+        assert isinstance(response.value, ReleaseBrief)
+
+        # Validate structured output fields
+        brief = response.value
+        assert len(brief.title) > 0
+        assert len(brief.summary) > 0
+        assert len(brief.highlights) > 0
+
+
+@pytest.mark.flaky
+@skip_if_openai_integration_tests_disabled
+async def test_openai_responses_client_agent_with_runtime_json_schema() -> None:
+    """Integration test for response_format with runtime JSON schema using OpenAI Responses Client."""
+    runtime_schema = {
+        "title": "WeatherDigest",
+        "type": "object",
+        "properties": {
+            "location": {"type": "string"},
+            "conditions": {"type": "string"},
+            "temperature_c": {"type": "number"},
+            "advisory": {"type": "string"},
+        },
+        "required": ["location", "conditions", "temperature_c", "advisory"],
+        "additionalProperties": False,
+    }
+
+    async with ChatAgent(
+        chat_client=OpenAIResponsesClient(),
+        instructions="Return only JSON that matches the provided schema. Do not add commentary.",
+    ) as agent:
+        response = await agent.run(
+            "Give a brief weather digest for Seattle.",
+            additional_chat_options={
+                "response_format": {
+                    "type": "json_schema",
+                    "json_schema": {
+                        "name": runtime_schema["title"],
+                        "strict": True,
+                        "schema": runtime_schema,
+                    },
+                },
+            },
+        )
+
+        # Validate response
+        assert isinstance(response, AgentRunResponse)
+        assert response.text is not None
+
+        # Parse JSON and validate structure
+        import json
+
+        parsed = json.loads(response.text)
+        assert "location" in parsed
+        assert "conditions" in parsed
+        assert "temperature_c" in parsed
+        assert "advisory" in parsed
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -102,12 +102,32 @@ agents/
 └── .env                 # Optional: shared environment variables
 ```

-## Viewing Telemetry (Otel Traces) in DevUI
+### Importing from External Modules

-Agent Framework emits OpenTelemetry (Otel) traces for various operations. You can view these traces in DevUI by enabling tracing when starting the server.
+If your agents import tools or utilities from sibling directories (e.g., `from tools.helpers import my_tool`), you must set `PYTHONPATH` to include the parent directory:

 ```bash
-devui ./agents --tracing framework
+# Project structure:
+# backend/
+# ├── agents/
+# │   └── my_agent/
+# │       └── agent.py    # contains: from tools.helpers import my_tool
+# └── tools/
+#     └── helpers.py
+
+# Run from project root with PYTHONPATH
+cd backend
+PYTHONPATH=. devui ./agents --port 8080
+```
+
+Without `PYTHONPATH`, Python cannot find modules in sibling directories and DevUI will report an import error.
+
+## Viewing Telemetry (Otel Traces) in DevUI
+
+Agent Framework emits OpenTelemetry (Otel) traces for various operations. You can view these traces in DevUI by enabling instrumentation when starting the server.
+
+```bash
+devui ./agents --instrumentation
 ```

 ## OpenAI-Compatible API
@@ -196,11 +216,12 @@ Options:
  --port, -p      Port (default: 8080)
  --host          Host (default: 127.0.0.1)
  --headless      API only, no UI
-  --config        YAML config file
-  --tracing       none|framework|workflow|all
+  --no-open       Don't automatically open browser
+  --instrumentation  Enable OpenTelemetry instrumentation
  --reload        Enable auto-reload
  --mode          developer|user (default: developer)
  --auth          Enable Bearer token authentication
+  --auth-token    Custom authentication token
 ```

 ### UI Modes
@@ -94,7 +94,7 @@ def serve(
    auto_open: bool = False,
    cors_origins: list[str] | None = None,
    ui_enabled: bool = True,
-    tracing_enabled: bool = False,
+    instrumentation_enabled: bool = False,
    mode: str = "developer",
    auth_enabled: bool = False,
    auth_token: str | None = None,
@@ -109,7 +109,7 @@ def serve(
        auto_open: Whether to automatically open browser
        cors_origins: List of allowed CORS origins
        ui_enabled: Whether to enable the UI
-        tracing_enabled: Whether to enable OpenTelemetry tracing
+        instrumentation_enabled: Whether to enable OpenTelemetry instrumentation
        mode: Server mode - 'developer' (full access, verbose errors) or 'user' (restricted APIs, generic errors)
        auth_enabled: Whether to enable Bearer token authentication
        auth_token: Custom authentication token (auto-generated if not provided with auth_enabled=True)
@@ -172,22 +172,12 @@ def serve(
        os.environ["AUTH_REQUIRED"] = "true"
        os.environ["DEVUI_AUTH_TOKEN"] = auth_token

-    # Configure tracing environment variables if enabled
-    if tracing_enabled:
-        import os
+    # Enable instrumentation if requested
+    if instrumentation_enabled:
+        from agent_framework.observability import enable_instrumentation

-        # Only set if not already configured by user
-        if not os.environ.get("ENABLE_INSTRUMENTATION"):
-            os.environ["ENABLE_INSTRUMENTATION"] = "true"
-            logger.info("Set ENABLE_INSTRUMENTATION=true for tracing")
-
-        if not os.environ.get("ENABLE_SENSITIVE_DATA"):
-            os.environ["ENABLE_SENSITIVE_DATA"] = "true"
-            logger.info("Set ENABLE_SENSITIVE_DATA=true for tracing")
-
-        if not os.environ.get("OTLP_ENDPOINT"):
-            os.environ["OTLP_ENDPOINT"] = "http://localhost:4317"
-            logger.info("Set OTLP_ENDPOINT=http://localhost:4317 for tracing")
+        enable_instrumentation(enable_sensitive_data=True)
+        logger.info("Enabled Agent Framework instrumentation with sensitive data")

    # Create server with direct parameters
    server = DevServer(
@@ -28,7 +28,7 @@ Examples:
  devui ./agents                    # Scan specific directory
  devui --port 8000                 # Custom port
  devui --headless                  # API only, no UI
-  devui --tracing                   # Enable OpenTelemetry tracing
+  devui --instrumentation           # Enable OpenTelemetry instrumentation
        """,
    )

@@ -53,7 +53,7 @@ Examples:

    parser.add_argument("--reload", action="store_true", help="Enable auto-reload for development")

-    parser.add_argument("--tracing", action="store_true", help="Enable OpenTelemetry tracing for Agent Framework")
+    parser.add_argument("--instrumentation", action="store_true", help="Enable OpenTelemetry instrumentation")

    parser.add_argument(
        "--mode",
@@ -182,7 +182,7 @@ def main() -> None:
            host=args.host,
            auto_open=not args.no_open,
            ui_enabled=ui_enabled,
-            tracing_enabled=args.tracing,
+            instrumentation_enabled=args.instrumentation,
            mode=mode,
            auth_enabled=args.auth,
            auth_token=args.auth_token,  # Pass through explicit token only
@@ -176,6 +176,31 @@ class ConversationStore(ABC):
        """
        pass

+    @abstractmethod
+    def add_trace(self, conversation_id: str, trace_event: dict[str, Any]) -> None:
+        """Add a trace event to the conversation for context inspection.
+
+        Traces capture execution metadata like token usage, timing, and LLM context
+        that isn't stored in the AgentThread but is useful for debugging.
+
+        Args:
+            conversation_id: Conversation ID
+            trace_event: Trace event data (from ResponseTraceEvent.data)
+        """
+        pass
+
+    @abstractmethod
+    def get_traces(self, conversation_id: str) -> list[dict[str, Any]]:
+        """Get all trace events for a conversation.
+
+        Args:
+            conversation_id: Conversation ID
+
+        Returns:
+            List of trace event dicts, or empty list if not found
+        """
+        pass
+

 class InMemoryConversationStore(ConversationStore):
    """In-memory conversation storage wrapping AgentThread.
@@ -215,6 +240,7 @@ class InMemoryConversationStore(ConversationStore):
            "metadata": metadata or {},
            "created_at": created_at,
            "items": [],
+            "traces": [],  # Trace events for context inspection (token usage, timing, etc.)
        }

        # Initialize item index for this conversation
@@ -407,10 +433,20 @@ class InMemoryConversationStore(ConversationStore):
                    elif content_type == "function_result":
                        # Function result - create separate ConversationItem
                        call_id = getattr(content, "call_id", None)
-                        # Output is stored in additional_properties
-                        output = ""
-                        if hasattr(content, "additional_properties"):
-                            output = content.additional_properties.get("output", "")
+                        # Output is stored in the 'result' field of FunctionResultContent
+                        result_value = getattr(content, "result", None)
+                        # Convert result to string (it could be dict, list, or other types)
+                        if result_value is None:
+                            output = ""
+                        elif isinstance(result_value, str):
+                            output = result_value
+                        else:
+                            import json
+
+                            try:
+                                output = json.dumps(result_value)
+                            except (TypeError, ValueError):
+                                output = str(result_value)

                        if call_id:
                            function_results.append(
@@ -556,6 +592,34 @@ class InMemoryConversationStore(ConversationStore):
        conv_data = self._conversations.get(conversation_id)
        return conv_data["thread"] if conv_data else None

+    def add_trace(self, conversation_id: str, trace_event: dict[str, Any]) -> None:
+        """Add a trace event to the conversation for context inspection.
+
+        Traces capture execution metadata like token usage, timing, and LLM context
+        that isn't stored in the AgentThread but is useful for debugging.
+
+        Args:
+            conversation_id: Conversation ID
+            trace_event: Trace event data (from ResponseTraceEvent.data)
+        """
+        conv_data = self._conversations.get(conversation_id)
+        if conv_data:
+            traces = conv_data.get("traces", [])
+            traces.append(trace_event)
+            conv_data["traces"] = traces
+
+    def get_traces(self, conversation_id: str) -> list[dict[str, Any]]:
+        """Get all trace events for a conversation.
+
+        Args:
+            conversation_id: Conversation ID
+
+        Returns:
+            List of trace event dicts, or empty list if not found
+        """
+        conv_data = self._conversations.get(conversation_id)
+        return conv_data.get("traces", []) if conv_data else []
+
    async def list_conversations_by_metadata(self, metadata_filter: dict[str, str]) -> list[Conversation]:
        """Filter conversations by metadata (e.g., agent_id)."""
        results = []
@@ -666,7 +666,16 @@ class EntityDiscovery:
            logger.debug(f"Successfully imported {pattern}")
            return module, None

-        except ModuleNotFoundError:
+        except ModuleNotFoundError as e:
+            # Distinguish between "module pattern doesn't exist" vs "module has import errors"
+            # If the missing module is the pattern itself, it's just not found (try next pattern)
+            # If the missing module is something else (a dependency), capture the error
+            missing_module = getattr(e, "name", None)
+            if missing_module and missing_module != pattern and not pattern.endswith(f".{missing_module}"):
+                # The module exists but has an import error (missing dependency)
+                logger.warning(f"Error importing {pattern}: {e}")
+                return None, e
+            # The module pattern itself doesn't exist - this is expected, try next pattern
            logger.debug(f"Import pattern {pattern} not found")
            return None, None
        except Exception as e:
@@ -4,7 +4,6 @@

 import json
 import logging
-import os
 from collections.abc import AsyncGenerator
 from typing import Any

@@ -45,8 +44,8 @@ class AgentFrameworkExecutor:
        """
        self.entity_discovery = entity_discovery
        self.message_mapper = message_mapper
-        self._setup_tracing_provider()
-        self._setup_agent_framework_tracing()
+        self._setup_instrumentation_provider()
+        self._setup_agent_framework_instrumentation()

        # Use provided conversation store or default to in-memory
        self.conversation_store = conversation_store or InMemoryConversationStore()
@@ -56,7 +55,7 @@ class AgentFrameworkExecutor:

        self.checkpoint_manager = CheckpointConversationManager(self.conversation_store)

-    def _setup_tracing_provider(self) -> None:
+    def _setup_instrumentation_provider(self) -> None:
        """Set up our own TracerProvider so we can add processors."""
        try:
            from opentelemetry import trace
@@ -71,7 +70,7 @@ class AgentFrameworkExecutor:
                })
                provider = TracerProvider(resource=resource)
                trace.set_tracer_provider(provider)
-                logger.info("Set up TracerProvider for server tracing")
+                logger.info("Set up TracerProvider for instrumentation")
            else:
                logger.debug("TracerProvider already exists")

@@ -80,25 +79,86 @@ class AgentFrameworkExecutor:
        except Exception as e:
            logger.warning(f"Failed to setup TracerProvider: {e}")

-    def _setup_agent_framework_tracing(self) -> None:
-        """Set up Agent Framework's built-in tracing."""
-        # Configure Agent Framework tracing only if ENABLE_INSTRUMENTATION is set
-        if os.environ.get("ENABLE_INSTRUMENTATION"):
-            try:
-                from agent_framework.observability import OBSERVABILITY_SETTINGS, configure_otel_providers
+    def _setup_agent_framework_instrumentation(self) -> None:
+        """Set up Agent Framework's built-in instrumentation."""
+        try:
+            from agent_framework.observability import OBSERVABILITY_SETTINGS, configure_otel_providers

-                # Only configure if not already executed
+            # Configure if instrumentation is enabled (via enable_instrumentation() or env var)
+            if OBSERVABILITY_SETTINGS.ENABLED:
+                # Only configure providers if not already executed
                if not OBSERVABILITY_SETTINGS._executed_setup:
-                    # Run the configure_otel_providers
-                    # This ensures OTLP exporters are created even if env vars were set late
-                    configure_otel_providers(enable_sensitive_data=True)
+                    # Call configure_otel_providers to set up exporters.
+                    # If OTEL_EXPORTER_OTLP_ENDPOINT is set, exporters will be created automatically.
+                    # If not set, no exporters are created (no console spam), but DevUI's
+                    # TracerProvider from _setup_instrumentation_provider() remains active for local capture.
+                    configure_otel_providers(enable_sensitive_data=OBSERVABILITY_SETTINGS.SENSITIVE_DATA_ENABLED)
                    logger.info("Enabled Agent Framework observability")
                else:
                    logger.debug("Agent Framework observability already configured")
+            else:
+                logger.debug("Instrumentation not enabled, skipping observability setup")
+        except Exception as e:
+            logger.warning(f"Failed to enable Agent Framework observability: {e}")
+
+    async def _ensure_mcp_connections(self, agent: Any) -> None:
+        """Ensure MCP tool connections are healthy before agent execution.
+
+        This is a workaround for an Agent Framework bug where MCP tool connections
+        can become stale (underlying streams closed) but is_connected remains True.
+        This happens when HTTP streaming responses end and GeneratorExit propagates.
+
+        This method detects stale connections and reconnects them. It's designed to
+        be a no-op once the Agent Framework fixes this issue upstream.
+
+        Args:
+            agent: Agent object that may have MCP tools
+        """
+        if not hasattr(agent, "_local_mcp_tools"):
+            return
+
+        for mcp_tool in agent._local_mcp_tools:
+            if not getattr(mcp_tool, "is_connected", False):
+                continue
+
+            tool_name = getattr(mcp_tool, "name", "unknown")
+
+            try:
+                # Check if underlying write stream is closed
+                session = getattr(mcp_tool, "session", None)
+                if session is None:
+                    continue
+
+                write_stream = getattr(session, "_write_stream", None)
+                if write_stream is None:
+                    continue
+
+                # Detect stale connection: is_connected=True but stream is closed
+                is_closed = getattr(write_stream, "_closed", False)
+                if not is_closed:
+                    continue  # Connection is healthy
+
+                # Stale connection detected - reconnect
+                logger.warning(f"MCP tool '{tool_name}' has stale connection (stream closed), reconnecting...")
+
+                # Clean up old connection
+                try:
+                    if hasattr(mcp_tool, "close"):
+                        await mcp_tool.close()
+                except Exception as close_err:
+                    logger.debug(f"Error closing stale MCP tool '{tool_name}': {close_err}")
+                    # Force reset state
+                    mcp_tool.is_connected = False
+                    mcp_tool.session = None
+
+                # Reconnect
+                if hasattr(mcp_tool, "connect"):
+                    await mcp_tool.connect()
+                    logger.info(f"MCP tool '{tool_name}' reconnected successfully")
+
            except Exception as e:
-                logger.warning(f"Failed to enable Agent Framework observability: {e}")
-        else:
-            logger.debug("ENABLE_INSTRUMENTATION not set, skipping observability setup")
+                # If detection fails, log and continue - let it fail naturally during execution
+                logger.debug(f"Error checking MCP tool '{tool_name}' connection: {e}")

    async def discover_entities(self) -> list[EntityInfo]:
        """Discover all available entities.
@@ -192,11 +252,11 @@ class AgentFrameworkExecutor:

            logger.info(f"Executing {entity_info.type}: {entity_id}")

-            # Extract session_id from request for trace context
-            session_id = getattr(request.extra_body, "session_id", None) if request.extra_body else None
+            # Extract response_id from request for trace context (added by _server.py)
+            response_id = request.extra_body.get("response_id") if request.extra_body else None

            # Use simplified trace capture
-            with capture_traces(session_id=session_id, entity_id=entity_id) as trace_collector:
+            with capture_traces(response_id=response_id, entity_id=entity_id) as trace_collector:
                if entity_info.type == "agent":
                    async for event in self._execute_agent(entity_obj, request, trace_collector):
                        yield event
@@ -260,6 +320,12 @@ class AgentFrameworkExecutor:
                logger.debug(f"Executing agent with text input: {user_message[:100]}...")
            else:
                logger.debug(f"Executing agent with multimodal ChatMessage: {type(user_message)}")
+
+            # Workaround for MCP tool stale connection bug (GitHub issue pending)
+            # When HTTP streaming ends, GeneratorExit can close MCP stdio streams
+            # but is_connected stays True. Detect and reconnect before execution.
+            await self._ensure_mcp_connections(agent)
+
            # Check if agent supports streaming
            if hasattr(agent, "run_stream") and callable(agent.run_stream):
                # Use Agent Framework's native streaming with optional thread
@@ -12,6 +12,7 @@ from datetime import datetime
 from typing import Any, Union
 from uuid import uuid4

+from agent_framework import ChatMessage, TextContent
 from openai.types.responses import (
    Response,
    ResponseContentPartAddedEvent,
@@ -225,27 +226,128 @@ class MessageMapper:
            Final aggregated OpenAI response
        """
        try:
-            # Extract text content from events
-            content_parts = []
+            # Collect output items in order
+            output_items: list[Any] = []
+
+            # Track text content parts per message (keyed by item_id)
+            text_parts_by_message: dict[str, list[str]] = {}
+
+            # Track function calls (keyed by call_id) to accumulate arguments
+            function_calls: dict[str, dict[str, Any]] = {}
+
+            # Track function results (keyed by call_id)
+            function_results: dict[str, dict[str, Any]] = {}

            for event in events:
-                # Extract delta text from ResponseTextDeltaEvent
-                if hasattr(event, "delta") and hasattr(event, "type") and event.type == "response.output_text.delta":
-                    content_parts.append(event.delta)
+                event_type = getattr(event, "type", None)

-            # Combine content
-            full_content = "".join(content_parts)
+                # Handle text deltas - accumulate text per message
+                if event_type == "response.output_text.delta":
+                    item_id = getattr(event, "item_id", "default")
+                    if item_id not in text_parts_by_message:
+                        text_parts_by_message[item_id] = []
+                    text_parts_by_message[item_id].append(event.delta)

-            # Create proper OpenAI Response
-            response_output_text = ResponseOutputText(type="output_text", text=full_content, annotations=[])
+                # Handle output_item.added events (function_call, message, etc.)
+                elif event_type == "response.output_item.added":
+                    item = getattr(event, "item", None)
+                    if item:
+                        # Handle both object and dict formats
+                        item_type = item.get("type") if isinstance(item, dict) else getattr(item, "type", None)

-            response_output_message = ResponseOutputMessage(
-                type="message",
-                role="assistant",
-                content=[response_output_text],
-                id=f"msg_{uuid.uuid4().hex[:8]}",
-                status="completed",
-            )
+                        # Track function calls to accumulate their arguments
+                        if item_type == "function_call":
+                            # Handle both object and dict formats
+                            if isinstance(item, dict):
+                                call_id = item.get("call_id") or item.get("id")
+                                if call_id:
+                                    function_calls[call_id] = {
+                                        "id": item.get("id", call_id),
+                                        "call_id": call_id,
+                                        "name": item.get("name", ""),
+                                        "arguments": item.get("arguments", ""),
+                                        "type": "function_call",
+                                        "status": item.get("status", "completed"),
+                                    }
+                            else:
+                                call_id = getattr(item, "call_id", None) or getattr(item, "id", None)
+                                if call_id:
+                                    function_calls[call_id] = {
+                                        "id": getattr(item, "id", call_id),
+                                        "call_id": call_id,
+                                        "name": getattr(item, "name", ""),
+                                        "arguments": getattr(item, "arguments", ""),
+                                        "type": "function_call",
+                                        "status": getattr(item, "status", "completed"),
+                                    }
+
+                        # Other output items (message, etc.) - track for later
+                        elif item_type == "message":
+                            # Messages will be built from text_parts_by_message
+                            pass
+
+                # Handle function call arguments delta - accumulate arguments
+                elif event_type == "response.function_call_arguments.delta":
+                    item_id = getattr(event, "item_id", None)
+                    delta = getattr(event, "delta", "")
+                    # item_id for function calls is the call_id
+                    if item_id and item_id in function_calls:
+                        function_calls[item_id]["arguments"] += delta
+
+                # Handle function result complete events
+                elif event_type == "response.function_result.complete":
+                    call_id = getattr(event, "call_id", None)
+                    if call_id:
+                        function_results[call_id] = {
+                            "type": "function_call_output",
+                            "call_id": call_id,
+                            "output": getattr(event, "output", ""),
+                            "status": getattr(event, "status", "completed"),
+                        }
+
+            # Build output array in order: function_calls, then final message
+
+            # Add function call items
+            for _call_id, fc_data in function_calls.items():
+                output_items.append(ResponseFunctionToolCall(**fc_data))
+
+            # Note: function_call_output items are NOT added to output array
+            # In OpenAI's Responses API, function results are user inputs, not assistant outputs
+            # The function_results dict is kept for potential future use or debugging
+            # but we don't include them in the Response output
+            _ = function_results  # Acknowledge but don't use
+
+            # Build final text message from accumulated deltas
+            # Combine all text parts (usually there's just one message)
+            all_text_parts = []
+            for _item_id, parts in text_parts_by_message.items():
+                all_text_parts.extend(parts)
+
+            full_content = "".join(all_text_parts)
+
+            # Only add message if there's text content
+            if full_content:
+                response_output_text = ResponseOutputText(type="output_text", text=full_content, annotations=[])
+                response_output_message = ResponseOutputMessage(
+                    type="message",
+                    role="assistant",
+                    content=[response_output_text],
+                    id=f"msg_{uuid.uuid4().hex[:8]}",
+                    status="completed",
+                )
+                output_items.append(response_output_message)
+
+            # If no output items at all, create an empty message
+            if not output_items:
+                response_output_text = ResponseOutputText(type="output_text", text="", annotations=[])
+                response_output_message = ResponseOutputMessage(
+                    type="message",
+                    role="assistant",
+                    content=[response_output_text],
+                    id=f"msg_{uuid.uuid4().hex[:8]}",
+                    status="completed",
+                )
+                output_items.append(response_output_message)

            # Get usage from accumulator (OpenAI standard)
            request_id = str(id(request))
@@ -278,7 +380,7 @@ class MessageMapper:
                object="response",
                created_at=datetime.now().timestamp(),
                model=request.model or "devui",
-                output=[response_output_message],
+                output=output_items,
                usage=usage,
                parallel_tool_calls=False,
                tool_choice="none",
@@ -501,7 +603,7 @@ class MessageMapper:
                return events

            # Check if we're streaming text content
-            has_text_content = any(content.__class__.__name__ == "TextContent" for content in update.contents)
+            has_text_content = any(isinstance(content, TextContent) for content in update.contents)

            # Check if we're in an executor context with an existing item
            executor_id = context.get("current_executor_id")
@@ -791,17 +893,35 @@ class MessageMapper:

                    # Extract text from output data based on type
                    text = None
-                    if hasattr(output_data, "__class__") and output_data.__class__.__name__ == "ChatMessage":
+                    if isinstance(output_data, ChatMessage):
                        # Handle ChatMessage (from Magentic and AgentExecutor with output_response=True)
                        text = getattr(output_data, "text", None)
                        if not text:
                            # Fallback to string representation
                            text = str(output_data)
+                    elif isinstance(output_data, list):
+                        # Handle list of ChatMessage objects (from Magentic yield_output([final_answer]))
+                        text_parts = []
+                        for item in output_data:
+                            if isinstance(item, ChatMessage):
+                                item_text = getattr(item, "text", None)
+                                if item_text:
+                                    text_parts.append(item_text)
+                                else:
+                                    text_parts.append(str(item))
+                            elif isinstance(item, str):
+                                text_parts.append(item)
+                            else:
+                                try:
+                                    text_parts.append(json.dumps(item, indent=2))
+                                except (TypeError, ValueError):
+                                    text_parts.append(str(item))
+                        text = "\n".join(text_parts) if text_parts else str(output_data)
                    elif isinstance(output_data, str):
                        # String output
                        text = output_data
                    else:
-                        # Object/dict/list → JSON string
+                        # Object/dict → JSON string
                        try:
                            text = json.dumps(output_data, indent=2)
                        except (TypeError, ValueError):
@@ -1081,275 +1201,6 @@ class MessageMapper:

                return [trace_event]

-            # Handle Magentic-specific events
-            if event_class == "MagenticAgentDeltaEvent":
-                agent_id = getattr(event, "agent_id", "unknown_agent")
-                text = getattr(event, "text", None)
-
-                if text:
-                    # Check if we're inside an executor - route to executor's item
-                    # This prevents duplicate timeline entries (executor + inner agent)
-                    current_executor_id = context.get("current_executor_id")
-                    executor_item_key = f"exec_item_{current_executor_id}" if current_executor_id else None
-
-                    if executor_item_key and executor_item_key in context:
-                        # Route delta to the executor's item instead of creating a new message item
-                        item_id = context[executor_item_key]
-
-                        # Emit text delta event routed to the executor's item
-                        return [
-                            ResponseTextDeltaEvent(
-                                type="response.output_text.delta",
-                                output_index=context.get("output_index", 0),
-                                content_index=0,
-                                item_id=item_id,
-                                delta=text,
-                                logprobs=[],
-                                sequence_number=self._next_sequence(context),
-                            )
-                        ]
-
-                    # Fallback: No executor context - create separate message item (original behavior)
-                    # This handles cases where MagenticAgentDeltaEvent is emitted outside an executor
-                    events = []
-
-                    # Track Magentic agent messages separately from regular messages
-                    # Use timestamp to ensure uniqueness for multiple runs of same agent
-                    magentic_key = f"magentic_message_{agent_id}"
-
-                    # Check if this is the first delta from this agent (need to create message container)
-                    if magentic_key not in context:
-                        # Create a unique message ID for this agent's streaming session
-                        message_id = f"msg_{agent_id}_{uuid4().hex[:8]}"
-                        context[magentic_key] = message_id
-                        context["output_index"] = context.get("output_index", -1) + 1
-
-                        # Import required types for creating message containers
-                        from openai.types.responses import ResponseOutputMessage, ResponseOutputText
-                        from openai.types.responses.response_content_part_added_event import (
-                            ResponseContentPartAddedEvent,
-                        )
-                        from openai.types.responses.response_output_item_added_event import ResponseOutputItemAddedEvent
-
-                        # Emit message output item (container for the agent's message)
-                        # This matches what _convert_agent_update does for regular agents
-                        events.append(
-                            ResponseOutputItemAddedEvent(
-                                type="response.output_item.added",
-                                output_index=context["output_index"],
-                                sequence_number=self._next_sequence(context),
-                                item=ResponseOutputMessage(
-                                    type="message",
-                                    id=message_id,
-                                    role="assistant",
-                                    content=[],
-                                    status="in_progress",
-                                    # Add metadata to identify this as a Magentic agent message
-                                    metadata={"agent_id": agent_id, "source": "magentic"},  # type: ignore[call-arg]
-                                ),
-                            )
-                        )
-
-                        # Add content part for text (establishes the text container)
-                        events.append(
-                            ResponseContentPartAddedEvent(
-                                type="response.content_part.added",
-                                output_index=context["output_index"],
-                                content_index=0,
-                                item_id=message_id,
-                                sequence_number=self._next_sequence(context),
-                                part=ResponseOutputText(type="output_text", text="", annotations=[]),
-                            )
-                        )
-
-                    # Get the message ID for this agent
-                    message_id = context[magentic_key]
-
-                    # Emit text delta event using the message ID (matches regular agent behavior)
-                    events.append(
-                        ResponseTextDeltaEvent(
-                            type="response.output_text.delta",
-                            output_index=context["output_index"],
-                            content_index=0,  # Always 0 for single text content
-                            item_id=message_id,
-                            delta=text,
-                            logprobs=[],
-                            sequence_number=self._next_sequence(context),
-                        )
-                    )
-                    return events
-
-                # Handle function calls from Magentic agents
-                if getattr(event, "function_call_id", None) and getattr(event, "function_call_name", None):
-                    # Handle function call initiation
-                    function_call_id = getattr(event, "function_call_id", None)
-                    function_call_name = getattr(event, "function_call_name", None)
-                    function_call_arguments = getattr(event, "function_call_arguments", None)
-
-                    # Track function call for accumulating arguments
-                    context["active_function_calls"][function_call_id] = {
-                        "item_id": function_call_id,
-                        "name": function_call_name,
-                        "arguments_chunks": [],
-                    }
-
-                    # Emit function call output item
-                    return [
-                        ResponseOutputItemAddedEvent(
-                            type="response.output_item.added",
-                            item=ResponseFunctionToolCall(
-                                id=function_call_id,
-                                call_id=function_call_id,
-                                name=function_call_name,
-                                arguments=json.dumps(function_call_arguments) if function_call_arguments else "",
-                                type="function_call",
-                                status="in_progress",
-                            ),
-                            output_index=context["output_index"],
-                            sequence_number=self._next_sequence(context),
-                        )
-                    ]
-
-                # For other non-text deltas, emit as trace for debugging
-                return [
-                    ResponseTraceEventComplete(
-                        type="response.trace.completed",
-                        data={
-                            "trace_type": "magentic_delta",
-                            "agent_id": agent_id,
-                            "function_call_id": getattr(event, "function_call_id", None),
-                            "function_call_name": getattr(event, "function_call_name", None),
-                            "function_result_id": getattr(event, "function_result_id", None),
-                            "timestamp": datetime.now().isoformat(),
-                        },
-                        span_id=f"magentic_delta_{uuid4().hex[:8]}",
-                        item_id=context["item_id"],
-                        output_index=context.get("output_index", 0),
-                        sequence_number=self._next_sequence(context),
-                    )
-                ]
-
-            if event_class == "MagenticAgentMessageEvent":
-                agent_id = getattr(event, "agent_id", "unknown_agent")
-                message = getattr(event, "message", None)
-
-                # Check if we're inside an executor - if so, deltas were already routed there
-                # We don't need to emit a separate message completion event
-                current_executor_id = context.get("current_executor_id")
-                executor_item_key = f"exec_item_{current_executor_id}" if current_executor_id else None
-
-                if executor_item_key and executor_item_key in context:
-                    # Deltas were routed to executor item - no separate message item to complete
-                    # The executor's output_item.done will mark completion
-                    logger.debug(
-                        f"MagenticAgentMessageEvent from {agent_id} - "
-                        f"deltas routed to executor {current_executor_id}, skipping"
-                    )
-                    return []
-
-                # Fallback: Handle case where we created a separate message item (no executor context)
-                magentic_key = f"magentic_message_{agent_id}"
-
-                # Check if we were streaming for this agent
-                if magentic_key in context:
-                    # Mark the streaming message as complete
-                    message_id = context[magentic_key]
-
-                    # Import required types
-                    from openai.types.responses import ResponseOutputMessage
-                    from openai.types.responses.response_output_item_done_event import ResponseOutputItemDoneEvent
-
-                    # Extract text from ChatMessage for the completed message
-                    text = None
-                    if message and hasattr(message, "text"):
-                        text = message.text
-
-                    # Emit output_item.done to mark message as complete
-                    events = [
-                        ResponseOutputItemDoneEvent(
-                            type="response.output_item.done",
-                            output_index=context["output_index"],
-                            sequence_number=self._next_sequence(context),
-                            item=ResponseOutputMessage(
-                                type="message",
-                                id=message_id,
-                                role="assistant",
-                                content=[],  # Content already streamed via deltas
-                                status="completed",
-                                metadata={"agent_id": agent_id, "source": "magentic"},  # type: ignore[call-arg]
-                            ),
-                        )
-                    ]
-
-                    # Clean up context for this agent
-                    del context[magentic_key]
-
-                    logger.debug(f"MagenticAgentMessageEvent from {agent_id} marked streaming message as complete")
-                    return events
-                # No streaming occurred, create a complete message (shouldn't happen normally)
-                # Extract text from ChatMessage
-                text = None
-                if message and hasattr(message, "text"):
-                    text = message.text
-
-                if text:
-                    # Emit as output item for this agent
-                    from openai.types.responses import ResponseOutputMessage, ResponseOutputText
-                    from openai.types.responses.response_output_item_added_event import ResponseOutputItemAddedEvent
-
-                    context["output_index"] = context.get("output_index", -1) + 1
-
-                    text_content = ResponseOutputText(type="output_text", text=text, annotations=[])
-
-                    output_message = ResponseOutputMessage(
-                        type="message",
-                        id=f"msg_{agent_id}_{uuid4().hex[:8]}",
-                        role="assistant",
-                        content=[text_content],
-                        status="completed",
-                        metadata={"agent_id": agent_id, "source": "magentic"},  # type: ignore[call-arg]
-                    )
-
-                    logger.debug(
-                        f"MagenticAgentMessageEvent from {agent_id} converted to output_item.added (non-streaming)"
-                    )
-                    return [
-                        ResponseOutputItemAddedEvent(
-                            type="response.output_item.added",
-                            item=output_message,
-                            output_index=context["output_index"],
-                            sequence_number=self._next_sequence(context),
-                        )
-                    ]
-
-            if event_class == "MagenticOrchestratorMessageEvent":
-                orchestrator_id = getattr(event, "orchestrator_id", "orchestrator")
-                message = getattr(event, "message", None)
-                kind = getattr(event, "kind", "unknown")
-
-                # Extract text from ChatMessage
-                text = None
-                if message and hasattr(message, "text"):
-                    text = message.text
-
-                # Emit as trace event for orchestrator messages (typically task ledger, instructions)
-                return [
-                    ResponseTraceEventComplete(
-                        type="response.trace.completed",
-                        data={
-                            "trace_type": "magentic_orchestrator",
-                            "orchestrator_id": orchestrator_id,
-                            "kind": kind,
-                            "text": text or "",
-                            "timestamp": datetime.now().isoformat(),
-                        },
-                        span_id=f"magentic_orch_{uuid4().hex[:8]}",
-                        item_id=context["item_id"],
-                        output_index=context.get("output_index", 0),
-                        sequence_number=self._next_sequence(context),
-                    )
-                ]
-
            # For unknown/legacy events, still emit as workflow event for backward compatibility
            # Get event data and serialize if it's a SerializationMixin
            raw_event_data = getattr(event, "data", None)
@@ -407,7 +407,7 @@ class DevServer:
                framework="agent_framework",
                runtime="python",  # Python DevUI backend
                capabilities={
-                    "tracing": os.getenv("ENABLE_INSTRUMENTATION") == "true",
+                    "instrumentation": os.getenv("ENABLE_INSTRUMENTATION") == "true",
                    "openai_proxy": openai_executor.is_configured,
                    "deployment": True,  # Deployment feature is available
                },
@@ -748,6 +748,11 @@ class DevServer:
                    response_id = f"resp_{uuid.uuid4().hex[:8]}"
                    logger.info(f"[CANCELLATION] Creating response {response_id} for entity {entity_id}")

+                    # Inject response_id into extra_body for trace context
+                    if request.extra_body is None:
+                        request.extra_body = {}
+                    request.extra_body["response_id"] = response_id
+
                    return StreamingResponse(
                        self._stream_with_cancellation(executor, request, response_id),
                        media_type="text/event-stream",
@@ -1000,10 +1005,16 @@ class DevServer:
                        logger.warning(f"Unexpected item type: {type(item)}, converting to dict")
                        serialized_items.append(dict(item))

+                # Get stored traces for context inspection (DevUI extension)
+                traces = executor.conversation_store.get_traces(conversation_id)
+
                return {
                    "object": "list",
                    "data": serialized_items,
                    "has_more": has_more,
+                    "metadata": {
+                        "traces": traces,  # Trace events for token usage, timing, LLM context
+                    },
                }
            except ValueError as e:
                raise HTTPException(status_code=404, detail=str(e)) from e
@@ -1080,10 +1091,22 @@ class DevServer:
            # Collect events for final response.completed event
            events = []

+            # Get conversation_id for trace storage
+            conversation_id = request._get_conversation_id()
+
            # Stream all events
            async for event in executor.execute_streaming(request):
                events.append(event)

+                # Store trace events for context inspection (persisted with conversation)
+                if conversation_id and hasattr(event, "type") and event.type == "response.trace.completed":
+                    try:
+                        trace_data = event.data if hasattr(event, "data") else None
+                        if trace_data:
+                            executor.conversation_store.add_trace(conversation_id, trace_data)
+                    except Exception as e:
+                        logger.debug(f"Failed to store trace event: {e}")
+
                # IMPORTANT: Check model_dump_json FIRST because to_json() can have newlines (pretty-printing)
                # which breaks SSE format. model_dump_json() returns single-line JSON.
                if hasattr(event, "model_dump_json"):
@@ -18,14 +18,14 @@ logger = logging.getLogger(__name__)
 class SimpleTraceCollector(SpanExporter):
    """Simple trace collector that captures spans for direct yielding."""

-    def __init__(self, session_id: str | None = None, entity_id: str | None = None) -> None:
+    def __init__(self, response_id: str | None = None, entity_id: str | None = None) -> None:
        """Initialize trace collector.

        Args:
-            session_id: Session identifier for context
+            response_id: Response identifier for grouping traces by turn
            entity_id: Entity identifier for context
        """
-        self.session_id = session_id
+        self.response_id = response_id
        self.entity_id = entity_id
        self.collected_events: list[ResponseTraceEvent] = []

@@ -93,7 +93,7 @@ class SimpleTraceCollector(SpanExporter):
                "duration_ms": duration_ms,
                "attributes": dict(span.attributes) if span.attributes else {},
                "status": str(span.status.status_code) if hasattr(span, "status") else "OK",
-                "session_id": self.session_id,
+                "response_id": self.response_id,
                "entity_id": self.entity_id,
            }

@@ -121,18 +121,18 @@ class SimpleTraceCollector(SpanExporter):

@contextmanager
 def capture_traces(
-    session_id: str | None = None, entity_id: str | None = None
+    response_id: str | None = None, entity_id: str | None = None
 ) -> Generator[SimpleTraceCollector, None, None]:
    """Context manager to capture traces during execution.

    Args:
-        session_id: Session identifier for context
+        response_id: Response identifier for grouping traces by turn
        entity_id: Entity identifier for context

    Yields:
        SimpleTraceCollector instance to get trace events from
    """
-    collector = SimpleTraceCollector(session_id, entity_id)
+    collector = SimpleTraceCollector(response_id, entity_id)

    try:
        from opentelemetry import trace
@@ -146,7 +146,7 @@ def capture_traces(
        # Check if this is a real TracerProvider (not the default NoOpTracerProvider)
        if isinstance(provider, TracerProvider):
            provider.add_span_processor(processor)
-            logger.debug(f"Added trace collector to TracerProvider for session: {session_id}, entity: {entity_id}")
+            logger.debug(f"Added trace collector to TracerProvider for response: {response_id}, entity: {entity_id}")

            try:
                yield collector
@@ -390,7 +390,7 @@ class MetaResponse(BaseModel):
    """Backend runtime/language - 'python' or 'dotnet' for deployment guides and feature availability."""

    capabilities: dict[str, bool] = {}
-    """Server capabilities (e.g., tracing, openai_proxy)."""
+    """Server capabilities (e.g., instrumentation, openai_proxy)."""

    auth_required: bool = False
    """Whether the server requires Bearer token authentication."""
@@ -19,5 +19,13 @@ export default tseslint.config([
      ecmaVersion: 2020,
      globals: globals.browser,
    },
+    rules: {
+      // Allow exporting constants alongside components in specific patterns
+      // This is common for shadcn/ui components (buttonVariants) and form utilities
+      'react-refresh/only-export-components': [
+        'warn',
+        { allowConstantExport: true }
+      ],
+    },
  },
 ])
@@ -19,6 +19,7 @@
    "@radix-ui/react-slot": "^1.2.3",
    "@radix-ui/react-switch": "^1.2.6",
    "@radix-ui/react-tabs": "^1.1.13",
+    "@radix-ui/react-tooltip": "^1.2.8",
    "@tailwindcss/vite": "^4.1.12",
    "@xyflow/react": "^12.8.4",
    "class-variance-authority": "^0.7.1",
@@ -270,6 +270,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
  const conversationUsage = useDevUIStore((state) => state.conversationUsage);
  const pendingApprovals = useDevUIStore((state) => state.pendingApprovals);
  const oaiMode = useDevUIStore((state) => state.oaiMode);
+  const streamingEnabled = useDevUIStore((state) => state.streamingEnabled);

  // Get conversation actions from Zustand (only the ones we actually use)
  const setCurrentConversation = useDevUIStore((state) => state.setCurrentConversation);
@@ -570,6 +571,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
              let allItems: unknown[] = [];
              let hasMore = true;
              let after: string | undefined = undefined;
+              let storedTraces: unknown[] = [];

              while (hasMore) {
                const result = await apiClient.listConversationItems(
@@ -578,7 +580,12 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
                );
                allItems = allItems.concat(result.data);
                hasMore = result.has_more;
-                
+
+                // Capture traces from metadata (only need from one response, they accumulate)
+                if (result.metadata?.traces && result.metadata.traces.length > 0) {
+                  storedTraces = result.metadata.traces;
+                }
+
                // Get the last item's ID for pagination
                if (hasMore && result.data.length > 0) {
                  const lastItem = result.data[result.data.length - 1] as { id?: string };
@@ -590,6 +597,21 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
              setChatItems(allItems as import("@/types/openai").ConversationItem[]);
              setIsStreaming(false);

+              // Restore stored traces as debug events for context inspection
+              if (storedTraces.length > 0) {
+                // Clear any previous debug events first
+                onDebugEvent("clear");
+                for (const trace of storedTraces) {
+                  // Convert stored trace back to ResponseTraceComplete event format
+                  const traceEvent: ExtendedResponseStreamEvent = {
+                    type: "response.trace.completed",
+                    data: trace as Record<string, unknown>,
+                    sequence_number: 0, // Not used for display
+                  };
+                  onDebugEvent(traceEvent);
+                }
+              }
+
              // Check for incomplete stream and resume if needed
              const state = loadStreamingState(mostRecent.id);
              
@@ -724,6 +746,9 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
      useDevUIStore.setState({ conversationUsage: { total_tokens: 0, message_count: 0 } });
      accumulatedTextRef.current = "";

+      // Clear debug panel for fresh conversation
+      onDebugEvent("clear");
+
      // Update localStorage cache with new conversation
      const cachedKey = `devui_convs_${selectedAgent.id}`;
      const updated = [newConversation, ...availableConversations];
@@ -736,7 +761,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
        type: "conversation_creation_error",
      });
    }
-  }, [selectedAgent, setCurrentConversation, setAvailableConversations, setChatItems, setIsStreaming]);
+  }, [selectedAgent, onDebugEvent, setCurrentConversation, setAvailableConversations, setChatItems, setIsStreaming]);

  // Handle conversation deletion
  const handleDeleteConversation = useCallback(
@@ -843,6 +868,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
        let allItems: unknown[] = [];
        let hasMore = true;
        let after: string | undefined = undefined;
+        let storedTraces: unknown[] = [];

        while (hasMore) {
          const result = await apiClient.listConversationItems(conversationId, {
@@ -851,7 +877,12 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
          });
          allItems = allItems.concat(result.data);
          hasMore = result.has_more;
-          
+
+          // Capture traces from metadata (only need from one response, they accumulate)
+          if (result.metadata?.traces && result.metadata.traces.length > 0) {
+            storedTraces = result.metadata.traces;
+          }
+
          // Get the last item's ID for pagination
          if (hasMore && result.data.length > 0) {
            const lastItem = result.data[result.data.length - 1] as { id?: string };
@@ -865,6 +896,19 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
        setChatItems(items);
        setIsStreaming(false);

+        // Restore stored traces as debug events for context inspection
+        if (storedTraces.length > 0) {
+          for (const trace of storedTraces) {
+            // Convert stored trace back to ResponseTraceComplete event format
+            const traceEvent: ExtendedResponseStreamEvent = {
+              type: "response.trace.completed",
+              data: trace as Record<string, unknown>,
+              sequence_number: 0, // Not used for display
+            };
+            onDebugEvent(traceEvent);
+          }
+        }
+
        // Calculate usage from loaded items
        useDevUIStore.setState({
          conversationUsage: {
@@ -1249,13 +1293,15 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {

            // Handle function calls as separate conversation items
            if (item.type === "function_call") {
+              // Type assertion for function call - narrows from union type
+              const funcCall = item as import("@/types/openai").ResponseFunctionToolCall;
              const functionCallItem: import("@/types/openai").ConversationFunctionCall = {
-                id: item.id || `call-${Date.now()}`,
+                id: funcCall.id || `call-${Date.now()}`,
                type: "function_call",
-                name: item.name,
-                arguments: item.arguments || "",
-                call_id: item.call_id,
-                status: (item.status === "failed" || item.status === "cancelled" ? "incomplete" : item.status) || "in_progress",
+                name: funcCall.name,
+                arguments: funcCall.arguments || "",
+                call_id: funcCall.call_id,
+                status: funcCall.status || "in_progress",
                created_at: Math.floor(Date.now() / 1000),
              };

@@ -1414,6 +1460,209 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
    [selectedAgent, currentConversation, onDebugEvent, setChatItems, setIsStreaming, setCurrentConversation, setAvailableConversations, setPendingApprovals, updateConversationUsage, createAbortSignal, resetCancelling]
  );

+  // Handle non-streaming message sending
+  const handleSendMessageSync = useCallback(
+    async (request: RunAgentRequest) => {
+      if (!selectedAgent) return;
+
+      // Check if this is a function approval response (internal, don't show in chat)
+      const isApprovalResponse = request.input.some(
+        (inputItem) =>
+          inputItem.type === "message" &&
+          Array.isArray(inputItem.content) &&
+          inputItem.content.some((c) => c.type === "function_approval_response")
+      );
+
+      // Extract content from OpenAI format to create ConversationMessage
+      const messageContent: import("@/types/openai").MessageContent[] = [];
+
+      // Parse OpenAI ResponseInputParam to extract content
+      for (const inputItem of request.input) {
+        if (inputItem.type === "message" && Array.isArray(inputItem.content)) {
+          for (const contentItem of inputItem.content) {
+            if (contentItem.type === "input_text") {
+              messageContent.push({
+                type: "text",
+                text: contentItem.text,
+              });
+            } else if (contentItem.type === "input_image") {
+              messageContent.push({
+                type: "input_image",
+                image_url: contentItem.image_url || "",
+                detail: "auto",
+              });
+            } else if (contentItem.type === "input_file") {
+              const fileItem = contentItem as import("@/types/agent-framework").ResponseInputFileParam;
+              messageContent.push({
+                type: "input_file",
+                file_data: fileItem.file_data,
+                filename: fileItem.filename,
+              });
+            }
+          }
+        }
+      }
+
+      // Capture timestamp once for both user and assistant messages
+      const messageTimestamp = Math.floor(Date.now() / 1000); // Unix seconds
+
+      // Only add user message to UI if it's not an approval response (internal messages)
+      if (!isApprovalResponse && messageContent.length > 0) {
+        const userMessage: import("@/types/openai").ConversationMessage = {
+          id: `user-${Date.now()}`,
+          type: "message",
+          role: "user",
+          content: messageContent,
+          status: "completed",
+          created_at: messageTimestamp,
+        };
+
+        setChatItems([...useDevUIStore.getState().chatItems, userMessage]);
+      }
+
+      // Show loading state (but not streaming indicator)
+      setIsSubmitting(true);
+
+      try {
+        // If no conversation selected, create one automatically
+        let conversationToUse = currentConversation;
+        if (!conversationToUse) {
+          try {
+            conversationToUse = await apiClient.createConversation({
+              agent_id: selectedAgent.id,
+            });
+            setCurrentConversation(conversationToUse);
+            setAvailableConversations([conversationToUse, ...useDevUIStore.getState().availableConversations]);
+            setConversationError(null);
+          } catch (error) {
+            const errorMessage = error instanceof Error ? error.message : "Failed to create conversation";
+            setConversationError({
+              message: errorMessage,
+              type: "conversation_creation_error",
+            });
+            setIsSubmitting(false);
+            return;
+          }
+        }
+
+        // Call non-streaming API
+        const response = await apiClient.runAgentSync(selectedAgent.id, {
+          input: request.input,
+          conversation_id: conversationToUse?.id,
+        });
+
+        // Extract content from response output
+        const assistantContent: import("@/types/openai").MessageContent[] = [];
+        const toolCalls: import("@/types/openai").ConversationFunctionCall[] = [];
+        const toolResults: import("@/types/openai").ConversationFunctionCallOutput[] = [];
+
+        if (response.output) {
+          for (const outputItem of response.output) {
+            if (outputItem.type === "message") {
+              // Extract message content
+              const msgItem = outputItem as import("@/types/openai").ResponseOutputMessage;
+              if (msgItem.content) {
+                for (const content of msgItem.content) {
+                  if (content.type === "output_text") {
+                    assistantContent.push({
+                      type: "text",
+                      text: (content as { text: string }).text,
+                    } as import("@/types/openai").MessageTextContent);
+                  } else if (content.type === "output_image") {
+                    assistantContent.push(content as unknown as import("@/types/openai").MessageOutputImage);
+                  } else if (content.type === "output_file") {
+                    assistantContent.push(content as unknown as import("@/types/openai").MessageOutputFile);
+                  } else if (content.type === "output_data") {
+                    assistantContent.push(content as unknown as import("@/types/openai").MessageOutputData);
+                  }
+                }
+              }
+            } else if (outputItem.type === "function_call") {
+              const funcCall = outputItem as unknown as import("@/types/openai").ResponseFunctionToolCall;
+              toolCalls.push({
+                id: funcCall.id || `call-${Date.now()}`,
+                type: "function_call",
+                name: funcCall.name,
+                arguments: funcCall.arguments || "",
+                call_id: funcCall.call_id,
+                status: funcCall.status || "completed",
+                created_at: messageTimestamp,
+              });
+            } else if (outputItem.type === "function_call_output") {
+              const resultItem = outputItem as unknown as { call_id: string; output: string };
+              toolResults.push({
+                id: `result-${Date.now()}`,
+                type: "function_call_output",
+                call_id: resultItem.call_id,
+                output: resultItem.output,
+                status: "completed",
+                created_at: messageTimestamp,
+              });
+            }
+          }
+        }
+
+        // Create assistant message with all content
+        const assistantMessage: import("@/types/openai").ConversationMessage = {
+          id: `assistant-${Date.now()}`,
+          type: "message",
+          role: "assistant",
+          content: assistantContent,
+          status: "completed",
+          created_at: messageTimestamp,
+          usage: response.usage ? {
+            input_tokens: response.usage.input_tokens,
+            output_tokens: response.usage.output_tokens,
+            total_tokens: response.usage.total_tokens,
+          } : undefined,
+        };
+
+        // Add all items to chat
+        const currentItems = useDevUIStore.getState().chatItems;
+        const newItems: import("@/types/openai").ConversationItem[] = [
+          ...currentItems,
+          assistantMessage,
+          ...toolCalls,
+          ...toolResults,
+        ];
+        setChatItems(newItems);
+
+        // Update conversation-level usage stats
+        if (response.usage) {
+          updateConversationUsage(response.usage.total_tokens);
+        }
+
+        // Send debug event with response completed
+        onDebugEvent({
+          type: "response.completed",
+          response: response,
+          sequence_number: 0,
+        } as ExtendedResponseStreamEvent);
+
+      } catch (error) {
+        // Show error message
+        const errorMessage = error instanceof Error ? error.message : "Failed to get response";
+        const assistantMessage: import("@/types/openai").ConversationMessage = {
+          id: `assistant-${Date.now()}`,
+          type: "message",
+          role: "assistant",
+          content: [{
+            type: "text",
+            text: `Error: ${errorMessage}`,
+          } as import("@/types/openai").MessageTextContent],
+          status: "incomplete",
+          created_at: messageTimestamp,
+        };
+
+        const currentItems = useDevUIStore.getState().chatItems;
+        setChatItems([...currentItems, assistantMessage]);
+      } finally {
+        setIsSubmitting(false);
+      }
+    },
+    [selectedAgent, currentConversation, onDebugEvent, setChatItems, setCurrentConversation, setAvailableConversations, updateConversationUsage, setIsSubmitting]
+  );
+

  // Handle message submission from ChatMessageInput
  const handleChatInputSubmit = async (content: import("@/types/agent-framework").ResponseInputContent[]) => {
@@ -1435,11 +1684,17 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
        },
      ];

-      // Use pure OpenAI format
-      await handleSendMessage({
+      const request = {
        input: openaiInput,
        conversation_id: currentConversation?.id,
-      });
+      };
+
+      // Use streaming or non-streaming based on setting
+      if (streamingEnabled) {
+        await handleSendMessage(request);
+      } else {
+        await handleSendMessageSync(request);
+      }
    } finally {
      setIsSubmitting(false);
    }
@@ -0,0 +1,949 @@
+/**
+ * ContextInspector - Token usage visualization and context analysis
+ *
+ * Features:
+ * - Stacked bar chart showing input/output tokens per turn
+ * - Composition view showing what fills the context (system, user, assistant, tools)
+ * - Per-turn vs cumulative modes
+ * - Summary statistics (total, average, peak)
+ * - Pure CSS visualization (no external charting library)
+ */
+
+import { useState, useMemo } from "react";
+import { useDevUIStore } from "@/stores/devuiStore";
+import {
+  BarChart3,
+  Layers,
+  Info,
+  ChevronDown,
+  ChevronRight,
+} from "lucide-react";
+import { Badge } from "@/components/ui/badge";
+import { Checkbox } from "@/components/ui/checkbox";
+import { ScrollArea } from "@/components/ui/scroll-area";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import type { ExtendedResponseStreamEvent } from "@/types";
+import {
+  TraceAttributes,
+  type TypedTraceAttributes,
+  type TraceMessage,
+  parseTraceMessages,
+  isTextPart,
+  isToolCallPart,
+  isToolResultPart,
+} from "@/types/openai";
+
+// Trace data interface matching debug-panel types
+interface TraceEventData {
+  operation_name?: string;
+  duration_ms?: number;
+  status?: string;
+  attributes?: TypedTraceAttributes;
+  span_id?: string;
+  trace_id?: string;
+  parent_span_id?: string | null;
+  start_time?: number;
+  end_time?: number;
+  entity_id?: string;
+  response_id?: string | null;
+}
+
+// Context composition breakdown
+interface ContextComposition {
+  system: number;      // character count
+  user: number;
+  assistant: number;
+  toolCalls: number;   // function definitions + arguments
+  toolResults: number; // function outputs
+  total: number;
+}
+
+// Turn data extracted from traces
+interface TurnData {
+  response_id: string;
+  timestamp: number;
+  input_tokens: number;
+  output_tokens: number;
+  total_tokens: number;
+  model?: string;
+  entity_id?: string;
+  duration_ms: number;
+  composition: ContextComposition;
+}
+
+// Props for the component
+interface ContextInspectorProps {
+  events: ExtendedResponseStreamEvent[];
+}
+
+// Parse message content to extract composition using typed TraceMessage format
+function parseComposition(messagesJson: string | unknown): ContextComposition {
+  const composition: ContextComposition = {
+    system: 0,
+    user: 0,
+    assistant: 0,
+    toolCalls: 0,
+    toolResults: 0,
+    total: 0,
+  };
+
+  try {
+    // Use the typed parser for string input
+    let messages: TraceMessage[];
+
+    if (typeof messagesJson === "string") {
+      messages = parseTraceMessages(messagesJson);
+    } else if (Array.isArray(messagesJson)) {
+      messages = messagesJson as TraceMessage[];
+    } else {
+      return composition;
+    }
+
+    for (const message of messages) {
+      if (!message || typeof message !== "object") continue;
+
+      const role = message.role;
+      const parts = message.parts;
+
+      // Calculate character count for this message
+      let charCount = 0;
+
+      // Handle parts array (Agent Framework format)
+      // Using type guards for type-safe access to part properties
+      if (Array.isArray(parts)) {
+        for (const part of parts) {
+          if (!part || typeof part !== "object") continue;
+
+          if (isTextPart(part)) {
+            // Text content can be in either 'content' or 'text' field
+            const text = part.content || part.text || "";
+            charCount += text.length;
+          } else if (isToolCallPart(part)) {
+            // Tool call includes name and arguments
+            const name = part.name || "";
+            const args = part.arguments || "";
+            composition.toolCalls += name.length + args.length;
+          } else if (isToolResultPart(part)) {
+            // Tool result - check both 'result' and 'response' fields
+            const result = part.result || part.response || "";
+            composition.toolResults += result.length;
+          }
+        }
+      }
+
+      // Categorize by role
+      if (role === "system") {
+        composition.system += charCount;
+      } else if (role === "user") {
+        composition.user += charCount;
+      } else if (role === "assistant") {
+        composition.assistant += charCount;
+      } else if (role === "tool") {
+        composition.toolResults += charCount;
+      }
+    }
+
+    composition.total =
+      composition.system +
+      composition.user +
+      composition.assistant +
+      composition.toolCalls +
+      composition.toolResults;
+
+  } catch {
+    // Parsing failed, return empty composition
+  }
+
+  return composition;
+}
+
+// Extract turn data from trace events
+function extractTurnData(events: ExtendedResponseStreamEvent[]): TurnData[] {
+  const traceEvents = events.filter(e => e.type === "response.trace.completed");
+
+  // Group by response_id
+  const byResponseId = new Map<string, TraceEventData[]>();
+
+  for (const event of traceEvents) {
+    if (!("data" in event)) continue;
+    const data = event.data as TraceEventData;
+    const responseId = data.response_id || "unknown";
+
+    if (!byResponseId.has(responseId)) {
+      byResponseId.set(responseId, []);
+    }
+    byResponseId.get(responseId)!.push(data);
+  }
+
+  const turns: TurnData[] = [];
+
+  for (const [responseId, traces] of byResponseId) {
+    let inputTokens = 0;
+    let outputTokens = 0;
+    let model: string | undefined;
+    let timestamp = Date.now() / 1000;
+    let entity_id: string | undefined;
+    let totalDuration = 0;
+    let composition: ContextComposition = {
+      system: 0, user: 0, assistant: 0, toolCalls: 0, toolResults: 0, total: 0
+    };
+
+    for (const trace of traces) {
+      const attrs = trace.attributes || {};
+
+      // Get token counts using typed attribute keys
+      const traceInput = attrs[TraceAttributes.INPUT_TOKENS];
+      const traceOutput = attrs[TraceAttributes.OUTPUT_TOKENS];
+
+      if (traceInput !== undefined) {
+        inputTokens += Number(traceInput);
+      }
+      if (traceOutput !== undefined) {
+        outputTokens += Number(traceOutput);
+      }
+
+      // Get model using typed attribute key
+      if (attrs[TraceAttributes.MODEL]) {
+        model = String(attrs[TraceAttributes.MODEL]);
+      }
+
+      // Get timestamp
+      if (trace.start_time && trace.start_time < timestamp) {
+        timestamp = trace.start_time;
+      }
+
+      // Get entity_id
+      if (trace.entity_id) {
+        entity_id = trace.entity_id;
+      }
+
+      // Sum durations
+      if (trace.duration_ms) {
+        totalDuration += Number(trace.duration_ms);
+      }
+
+      // Parse composition from input messages using typed attribute key
+      const inputMessages = attrs[TraceAttributes.INPUT_MESSAGES];
+      if (inputMessages && composition.total === 0) {
+        composition = parseComposition(inputMessages);
+      }
+
+      // Also check for system instructions using typed attribute key
+      const systemInstructions = attrs[TraceAttributes.SYSTEM_INSTRUCTIONS];
+      if (systemInstructions && typeof systemInstructions === "string" && composition.system === 0) {
+        composition.system = systemInstructions.length;
+        composition.total += systemInstructions.length;
+      }
+    }
+
+    // Only include turns that have token data
+    if (inputTokens > 0 || outputTokens > 0) {
+      turns.push({
+        response_id: responseId,
+        timestamp,
+        input_tokens: inputTokens,
+        output_tokens: outputTokens,
+        total_tokens: inputTokens + outputTokens,
+        model,
+        entity_id,
+        duration_ms: totalDuration,
+        composition,
+      });
+    }
+  }
+
+  // Sort by timestamp (oldest first)
+  turns.sort((a, b) => a.timestamp - b.timestamp);
+
+  return turns;
+}
+
+// Calculate summary stats
+function calculateStats(turns: TurnData[]) {
+  if (turns.length === 0) {
+    return {
+      totalInput: 0,
+      totalOutput: 0,
+      totalTokens: 0,
+      avgInput: 0,
+      avgOutput: 0,
+      avgTotal: 0,
+      peakInput: 0,
+      peakOutput: 0,
+      peakTotal: 0,
+      turnCount: 0,
+    };
+  }
+
+  const totalInput = turns.reduce((sum, t) => sum + t.input_tokens, 0);
+  const totalOutput = turns.reduce((sum, t) => sum + t.output_tokens, 0);
+  const totalTokens = totalInput + totalOutput;
+
+  const peakInput = Math.max(...turns.map(t => t.input_tokens));
+  const peakOutput = Math.max(...turns.map(t => t.output_tokens));
+  const peakTotal = Math.max(...turns.map(t => t.total_tokens));
+
+  return {
+    totalInput,
+    totalOutput,
+    totalTokens,
+    avgInput: Math.round(totalInput / turns.length),
+    avgOutput: Math.round(totalOutput / turns.length),
+    avgTotal: Math.round(totalTokens / turns.length),
+    peakInput,
+    peakOutput,
+    peakTotal,
+    turnCount: turns.length,
+  };
+}
+
+// Aggregate composition across all turns
+function aggregateComposition(turns: TurnData[]): ContextComposition {
+  return turns.reduce(
+    (acc, turn) => ({
+      system: acc.system + turn.composition.system,
+      user: acc.user + turn.composition.user,
+      assistant: acc.assistant + turn.composition.assistant,
+      toolCalls: acc.toolCalls + turn.composition.toolCalls,
+      toolResults: acc.toolResults + turn.composition.toolResults,
+      total: acc.total + turn.composition.total,
+    }),
+    { system: 0, user: 0, assistant: 0, toolCalls: 0, toolResults: 0, total: 0 }
+  );
+}
+
+// Format large numbers with K suffix
+function formatTokenCount(n: number): string {
+  if (n >= 1000) {
+    return `${(n / 1000).toFixed(1)}k`;
+  }
+  return String(n);
+}
+
+// Color constants - single source of truth for all visualizations
+const SEGMENT_COLORS = {
+  // Token segments
+  input: "bg-blue-500 dark:bg-blue-600",
+  output: "bg-emerald-500 dark:bg-emerald-600",
+  // Composition segments
+  system: "bg-purple-500 dark:bg-purple-600",
+  user: "bg-blue-500 dark:bg-blue-600",
+  assistant: "bg-emerald-500 dark:bg-emerald-600",
+  toolCalls: "bg-amber-500 dark:bg-amber-600",
+  toolResults: "bg-orange-500 dark:bg-orange-600",
+} as const;
+
+// Segment definition for the unified bar component
+interface BarSegment {
+  key: string;
+  value: number;
+  color: string;
+  label: string;
+}
+
+// Unified segmented bar component with tooltips
+// Replaces both TokenBar and CompositionBar for consistency and maintainability
+function SegmentedBar({
+  segments,
+  maxValue,
+  height = 20,
+  renderLabel,
+}: {
+  segments: BarSegment[];
+  maxValue: number;
+  height?: number;
+  renderLabel?: (total: number, segments: BarSegment[]) => React.ReactNode;
+}) {
+  const total = segments.reduce((sum, s) => sum + s.value, 0);
+
+  if (total === 0) {
+    return (
+      <div className="flex items-center gap-2 w-full">
+        <div
+          className="rounded bg-muted/30 flex-1"
+          style={{ height: `${height}px` }}
+        />
+      </div>
+    );
+  }
+
+  // When maxValue is 0, use full width (100%) - focus on ratios within the bar
+  // When maxValue > 0, scale relative to max - focus on size comparison
+  const widthPercent = maxValue > 0 ? (total / maxValue) * 100 : 100;
+
+  // Pre-compute segment metadata for tooltips
+  const segmentsWithMeta = segments
+    .filter(s => s.value > 0)
+    .map(seg => ({
+      ...seg,
+      percent: Math.round((seg.value / total) * 100),
+    }));
+
+  return (
+    <div className="flex items-center gap-2 w-full">
+      <div
+        className="relative rounded overflow-hidden bg-muted/30 flex-1"
+        style={{ height: `${height}px` }}
+      >
+        <TooltipProvider delayDuration={150}>
+          <div
+            className="h-full flex transition-all duration-300"
+            style={{ width: `${widthPercent}%` }}
+          >
+            {segmentsWithMeta.map((seg) => (
+              <Tooltip key={seg.key}>
+                <TooltipTrigger asChild>
+                  <div
+                    className={`h-full ${seg.color} transition-all duration-150 hover:brightness-110 hover:scale-y-[1.15] origin-bottom cursor-default`}
+                    style={{ width: `${(seg.value / total) * 100}%` }}
+                  />
+                </TooltipTrigger>
+                <TooltipContent side="top" className="text-xs">
+                  <div className="flex items-center gap-1.5">
+                    <div className={`w-2 h-2 rounded-sm ${seg.color} flex-shrink-0`} />
+                    <span className="font-medium">{seg.label}</span>
+                    <span className="opacity-80">{formatTokenCount(seg.value)} ({seg.percent}%)</span>
+                  </div>
+                </TooltipContent>
+              </Tooltip>
+            ))}
+          </div>
+        </TooltipProvider>
+      </div>
+
+      {renderLabel?.(total, segments)}
+    </div>
+  );
+}
+
+// Helper to create token segments (input/output)
+function createTokenSegments(input: number, output: number): BarSegment[] {
+  return [
+    { key: "input", value: input, color: SEGMENT_COLORS.input, label: "Input" },
+    { key: "output", value: output, color: SEGMENT_COLORS.output, label: "Output" },
+  ];
+}
+
+// Helper to create composition segments
+function createCompositionSegments(composition: ContextComposition): BarSegment[] {
+  return [
+    { key: "system", value: composition.system, color: SEGMENT_COLORS.system, label: "System" },
+    { key: "user", value: composition.user, color: SEGMENT_COLORS.user, label: "User" },
+    { key: "assistant", value: composition.assistant, color: SEGMENT_COLORS.assistant, label: "Assistant" },
+    { key: "toolCalls", value: composition.toolCalls, color: SEGMENT_COLORS.toolCalls, label: "Tool Calls" },
+    { key: "toolResults", value: composition.toolResults, color: SEGMENT_COLORS.toolResults, label: "Tool Results" },
+  ];
+}
+
+// Composition breakdown list
+function CompositionBreakdown({
+  composition,
+  className = "",
+}: {
+  composition: ContextComposition;
+  className?: string;
+}) {
+  const { system, user, assistant, toolCalls, toolResults, total } = composition;
+
+  if (total === 0) {
+    return (
+      <div className={`text-xs text-muted-foreground ${className}`}>
+        No composition data available
+      </div>
+    );
+  }
+
+  const items = [
+    { label: "System", value: system, color: SEGMENT_COLORS.system },
+    { label: "User", value: user, color: SEGMENT_COLORS.user },
+    { label: "Assistant", value: assistant, color: SEGMENT_COLORS.assistant },
+    { label: "Tool Calls", value: toolCalls, color: SEGMENT_COLORS.toolCalls },
+    { label: "Tool Results", value: toolResults, color: SEGMENT_COLORS.toolResults },
+  ].filter(item => item.value > 0);
+
+  return (
+    <div className={`space-y-1.5 ${className}`}>
+      {items.map((item) => {
+        const percent = Math.round((item.value / total) * 100);
+        return (
+          <div key={item.label} className="flex items-center gap-2 text-xs">
+            <div className={`w-2 h-2 rounded-sm ${item.color}`} />
+            <span className="text-muted-foreground w-20">{item.label}</span>
+            <div className="flex-1 h-3 bg-muted/30 rounded overflow-hidden">
+              <div
+                className={`h-full ${item.color} transition-all duration-300`}
+                style={{ width: `${percent}%` }}
+              />
+            </div>
+            <span className="font-mono w-10 text-right text-muted-foreground">
+              {percent}%
+            </span>
+          </div>
+        );
+      })}
+    </div>
+  );
+}
+
+// Turn row component
+function TurnRow({
+  turn,
+  index,
+  maxValue,
+  maxCompositionValue,
+  cumulativeInput,
+  cumulativeOutput,
+  cumulativeComposition,
+  showCumulative,
+  viewMode,
+}: {
+  turn: TurnData;
+  index: number;
+  maxValue: number;
+  maxCompositionValue: number;
+  cumulativeInput: number;
+  cumulativeOutput: number;
+  cumulativeComposition: ContextComposition;
+  showCumulative: boolean;
+  viewMode: "tokens" | "composition";
+}) {
+  const [isExpanded, setIsExpanded] = useState(false);
+
+  const displayInput = showCumulative ? cumulativeInput : turn.input_tokens;
+  const displayOutput = showCumulative ? cumulativeOutput : turn.output_tokens;
+  const displayComposition = showCumulative ? cumulativeComposition : turn.composition;
+
+  const timestamp = new Date(turn.timestamp * 1000).toLocaleTimeString([], {
+    hour: "2-digit",
+    minute: "2-digit",
+    second: "2-digit",
+  });
+
+  return (
+    <div className="border-b border-muted/50 last:border-0">
+      <div
+        className="flex items-center gap-3 py-2 px-2 hover:bg-muted/30 cursor-pointer transition-colors"
+        onClick={() => setIsExpanded(!isExpanded)}
+      >
+        {/* Turn number */}
+        <div className="w-6 h-6 rounded-full bg-muted flex items-center justify-center text-xs font-medium flex-shrink-0">
+          {index + 1}
+        </div>
+
+        {/* Bar */}
+        <div className="flex-1 min-w-0">
+          {viewMode === "tokens" ? (
+            <SegmentedBar
+              segments={createTokenSegments(displayInput, displayOutput)}
+              maxValue={maxValue}
+              height={20}
+              renderLabel={(_, segs) => (
+                <div className="flex items-center gap-1 text-xs font-mono text-muted-foreground min-w-[80px] justify-end">
+                  <span className="text-blue-600 dark:text-blue-400">↑{formatTokenCount(segs[0]?.value || 0)}</span>
+                  <span>/</span>
+                  <span className="text-emerald-600 dark:text-emerald-400">↓{formatTokenCount(segs[1]?.value || 0)}</span>
+                </div>
+              )}
+            />
+          ) : (
+            <SegmentedBar
+              segments={createCompositionSegments(displayComposition)}
+              maxValue={maxCompositionValue}
+              height={20}
+              renderLabel={(total) => (
+                <div className="text-xs font-mono text-muted-foreground min-w-[50px] text-right">
+                  {formatTokenCount(Math.round(total / 4))}~
+                </div>
+              )}
+            />
+          )}
+        </div>
+
+        {/* Expand icon */}
+        <div className="text-muted-foreground flex-shrink-0">
+          {isExpanded ? (
+            <ChevronDown className="h-4 w-4" />
+          ) : (
+            <ChevronRight className="h-4 w-4" />
+          )}
+        </div>
+      </div>
+
+      {/* Expanded details */}
+      {isExpanded && (
+        <div className="pb-3">
+          {/* Connector line */}
+          <div className="flex items-start gap-3 px-2">
+            <div className="w-6 flex justify-center flex-shrink-0">
+              <div className="w-px h-full bg-muted" />
+            </div>
+            <div className="flex-1 min-w-0">
+              {/* L-connector and composition */}
+              <div className="flex items-start gap-2">
+                <div className="text-muted-foreground text-xs mt-1">└─</div>
+                <div className="flex-1 space-y-3">
+                  {/* Basic info */}
+                  <div className="grid grid-cols-2 gap-x-4 gap-y-1 text-xs text-muted-foreground">
+                    <div>Time: <span className="font-mono text-foreground">{timestamp}</span></div>
+                    <div>Duration: <span className="font-mono text-foreground">{turn.duration_ms.toFixed(0)}ms</span></div>
+                    {turn.model && (
+                      <div>Model: <span className="font-mono text-foreground">{turn.model}</span></div>
+                    )}
+                    {turn.entity_id && (
+                      <div>Entity: <span className="font-mono text-foreground">{turn.entity_id}</span></div>
+                    )}
+                  </div>
+
+                  {/* Token counts - shown in tokens mode */}
+                  {viewMode === "tokens" && (
+                    <div className="flex gap-4 text-xs">
+                      <div>
+                        <span className="text-blue-600 dark:text-blue-400">Input:</span>{" "}
+                        <span className="font-mono">{turn.input_tokens.toLocaleString()}</span>
+                      </div>
+                      <div>
+                        <span className="text-emerald-600 dark:text-emerald-400">Output:</span>{" "}
+                        <span className="font-mono">{turn.output_tokens.toLocaleString()}</span>
+                      </div>
+                      <div>
+                        <span className="text-muted-foreground">Total:</span>{" "}
+                        <span className="font-mono">{turn.total_tokens.toLocaleString()}</span>
+                      </div>
+                    </div>
+                  )}
+
+                  {/* Composition breakdown - shown in composition mode */}
+                  {viewMode === "composition" && turn.composition.total > 0 && (
+                    <div>
+                      <div className="text-xs text-muted-foreground mb-2 flex items-center gap-1">
+                        <Info className="h-3 w-3" />
+                        Context Composition (estimated from ~{formatTokenCount(Math.round(turn.composition.total / 4))} tokens)
+                      </div>
+                      <CompositionBreakdown composition={turn.composition} />
+                    </div>
+                  )}
+                </div>
+              </div>
+            </div>
+          </div>
+        </div>
+      )}
+    </div>
+  );
+}
+
+// Summary stats card
+function StatCard({
+  label,
+  value,
+  icon: Icon,
+  color = "default",
+}: {
+  label: string;
+  value: string | number;
+  icon: typeof BarChart3;
+  color?: "default" | "blue" | "green";
+}) {
+  const colorClass = {
+    default: "text-muted-foreground",
+    blue: "text-blue-600 dark:text-blue-400",
+    green: "text-emerald-600 dark:text-emerald-400",
+  }[color];
+
+  return (
+    <div className="flex items-center gap-2 p-2 bg-muted/30 rounded">
+      <Icon className={`h-4 w-4 ${colorClass}`} />
+      <div className="flex-1 min-w-0">
+        <div className="text-xs text-muted-foreground truncate">{label}</div>
+        <div className="font-mono text-sm font-medium">{value}</div>
+      </div>
+    </div>
+  );
+}
+
+// Main component
+export function ContextInspector({ events }: ContextInspectorProps) {
+  // Use persisted store state instead of local useState
+  const viewMode = useDevUIStore((state) => state.contextInspectorViewMode);
+  const setViewMode = useDevUIStore((state) => state.setContextInspectorViewMode);
+  const showCumulative = useDevUIStore((state) => state.contextInspectorCumulative);
+  const setShowCumulative = useDevUIStore((state) => state.setContextInspectorCumulative);
+
+  // Extract turn data from traces
+  const turns = useMemo(() => extractTurnData(events), [events]);
+
+  // Calculate stats
+  const stats = useMemo(() => calculateStats(turns), [turns]);
+
+  // Aggregate composition
+  const totalComposition = useMemo(() => aggregateComposition(turns), [turns]);
+
+  // Calculate max value for bar scaling (tokens)
+  // In non-cumulative mode, use 0 to signal full-width bars (focus on ratios)
+  // In cumulative mode, scale relative to total (focus on growth)
+  const maxValue = useMemo(() => {
+    if (turns.length === 0) return 0;
+
+    if (showCumulative) {
+      return stats.totalTokens;
+    } else {
+      // Return 0 to signal "use full width" - each bar shows its own ratio
+      return 0;
+    }
+  }, [turns, showCumulative, stats.totalTokens]);
+
+  // Calculate max value for composition bar scaling
+  // Same logic: full-width in non-cumulative, scaled in cumulative
+  const maxCompositionValue = useMemo(() => {
+    if (turns.length === 0) return 0;
+
+    if (showCumulative) {
+      return totalComposition.total;
+    } else {
+      // Return 0 to signal "use full width"
+      return 0;
+    }
+  }, [turns, showCumulative, totalComposition.total]);
+
+  // Calculate cumulative values for tokens and composition
+  const cumulativeData = useMemo(() => {
+    let cumInput = 0;
+    let cumOutput = 0;
+    let cumComposition: ContextComposition = {
+      system: 0, user: 0, assistant: 0, toolCalls: 0, toolResults: 0, total: 0
+    };
+
+    return turns.map(t => {
+      cumInput += t.input_tokens;
+      cumOutput += t.output_tokens;
+      cumComposition = {
+        system: cumComposition.system + t.composition.system,
+        user: cumComposition.user + t.composition.user,
+        assistant: cumComposition.assistant + t.composition.assistant,
+        toolCalls: cumComposition.toolCalls + t.composition.toolCalls,
+        toolResults: cumComposition.toolResults + t.composition.toolResults,
+        total: cumComposition.total + t.composition.total,
+      };
+      return {
+        input: cumInput,
+        output: cumOutput,
+        composition: { ...cumComposition }
+      };
+    });
+  }, [turns]);
+
+  // No data state
+  if (turns.length === 0) {
+    return (
+      <div className="flex flex-col items-center text-center p-6 pt-9">
+        <BarChart3 className="h-8 w-8 text-muted-foreground mb-3" />
+        <div className="text-sm font-medium mb-1">No Data</div>
+        <div className="text-xs text-muted-foreground max-w-[200px]">
+          Run{" "}
+          <span className="font-mono bg-accent/10 px-1 rounded">
+            devui --instrumentation
+          </span>{" "}
+          and start a conversation.
+        </div>
+      </div>
+    );
+  }
+
+  return (
+    <div className="h-full flex flex-col">
+      {/* Header */}
+      <div className="p-3 border-b flex-shrink-0 space-y-2">
+        {/* Title row */}
+        <div className="flex items-center justify-between gap-2">
+          <div className="flex items-center gap-2">
+            <BarChart3 className="h-4 w-4" />
+            <span className="font-medium text-sm">Context Inspector</span>
+            <Badge variant="outline" className="text-xs">
+              {turns.length} turn{turns.length !== 1 ? "s" : ""}
+            </Badge>
+          </div>
+
+          {/* Cumulative checkbox */}
+          <label className="flex items-center gap-1.5 text-xs text-muted-foreground cursor-pointer">
+            <Checkbox
+              checked={showCumulative}
+              onCheckedChange={(checked) => setShowCumulative(checked === true)}
+              className="h-3.5 w-3.5"
+            />
+            <span>Cumulative</span>
+          </label>
+        </div>
+
+        {/* View mode segmented control */}
+        <div className="flex items-center bg-muted rounded-md p-1">
+          <button
+            onClick={() => setViewMode("tokens")}
+            className={`flex-1 px-3 py-1.5 text-xs rounded transition-colors ${
+              viewMode === "tokens"
+                ? "bg-background shadow-sm font-medium"
+                : "text-muted-foreground hover:text-foreground"
+            }`}
+          >
+            Tokens
+          </button>
+          <button
+            onClick={() => setViewMode("composition")}
+            className={`flex-1 px-3 py-1.5 text-xs rounded transition-colors ${
+              viewMode === "composition"
+                ? "bg-background shadow-sm font-medium"
+                : "text-muted-foreground hover:text-foreground"
+            }`}
+          >
+            Composition
+          </button>
+        </div>
+
+        {/* View mode description */}
+        <div className="text-xs text-muted-foreground">
+          {viewMode === "tokens"
+            ? "Token usage per turn"
+            : "Context breakdown by message type (chars)"}
+        </div>
+      </div>
+
+      <ScrollArea className="flex-1">
+        <div className="p-3 space-y-4">
+          {/* Legend */}
+          <div className="flex items-center gap-4 text-xs px-1 flex-wrap">
+            {viewMode === "tokens" ? (
+              <>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-3 h-3 rounded ${SEGMENT_COLORS.input}`} />
+                  <span className="text-muted-foreground">Input (↑)</span>
+                </div>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-3 h-3 rounded ${SEGMENT_COLORS.output}`} />
+                  <span className="text-muted-foreground">Output (↓)</span>
+                </div>
+              </>
+            ) : (
+              <>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-2.5 h-2.5 rounded-sm ${SEGMENT_COLORS.system}`} />
+                  <span className="text-muted-foreground">System</span>
+                </div>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-2.5 h-2.5 rounded-sm ${SEGMENT_COLORS.user}`} />
+                  <span className="text-muted-foreground">User</span>
+                </div>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-2.5 h-2.5 rounded-sm ${SEGMENT_COLORS.assistant}`} />
+                  <span className="text-muted-foreground">Assistant</span>
+                </div>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-2.5 h-2.5 rounded-sm ${SEGMENT_COLORS.toolCalls}`} />
+                  <span className="text-muted-foreground">Tools</span>
+                </div>
+                <div className="flex items-center gap-1.5">
+                  <div className={`w-2.5 h-2.5 rounded-sm ${SEGMENT_COLORS.toolResults}`} />
+                  <span className="text-muted-foreground">Results</span>
+                </div>
+              </>
+            )}
+            <div className="flex-1" />
+            <div className="flex items-center gap-1 text-muted-foreground">
+              <Info className="h-3 w-3" />
+              <span>Click for details</span>
+            </div>
+          </div>
+
+          {/* Turn bars */}
+          <div className="border rounded-lg overflow-hidden">
+            {turns.map((turn, index) => (
+              <TurnRow
+                key={turn.response_id}
+                turn={turn}
+                index={index}
+                maxValue={maxValue}
+                maxCompositionValue={maxCompositionValue}
+                cumulativeInput={cumulativeData[index]?.input || 0}
+                cumulativeOutput={cumulativeData[index]?.output || 0}
+                cumulativeComposition={cumulativeData[index]?.composition || turn.composition}
+                showCumulative={showCumulative}
+                viewMode={viewMode}
+              />
+            ))}
+          </div>
+
+          {/* Session summary */}
+          <div className="border rounded-lg overflow-hidden">
+            <div className="p-3 bg-muted/30 border-b">
+              <span className="text-xs font-medium">Session Summary</span>
+            </div>
+
+            <div className="p-3 space-y-3">
+              {/* Token summary cards */}
+              <div className="grid grid-cols-3 gap-2">
+                <StatCard
+                  label="Total Tokens"
+                  value={formatTokenCount(stats.totalTokens)}
+                  icon={Layers}
+                />
+                <StatCard
+                  label="Input"
+                  value={formatTokenCount(stats.totalInput)}
+                  icon={BarChart3}
+                  color="blue"
+                />
+                <StatCard
+                  label="Output"
+                  value={formatTokenCount(stats.totalOutput)}
+                  icon={BarChart3}
+                  color="green"
+                />
+              </div>
+
+              {/* Per-turn statistics (only for multi-turn sessions) */}
+              {turns.length > 1 && (
+                <div className="grid grid-cols-2 gap-x-4 gap-y-1 text-xs pt-2 border-t border-muted/50">
+                  <div className="flex justify-between">
+                    <span className="text-muted-foreground">Avg per turn:</span>
+                    <span className="font-mono">{formatTokenCount(stats.avgTotal)}</span>
+                  </div>
+                  <div className="flex justify-between">
+                    <span className="text-muted-foreground">Peak turn:</span>
+                    <span className="font-mono">{formatTokenCount(stats.peakTotal)}</span>
+                  </div>
+                  <div className="flex justify-between">
+                    <span className="text-muted-foreground">Avg input:</span>
+                    <span className="font-mono text-blue-600 dark:text-blue-400">{formatTokenCount(stats.avgInput)}</span>
+                  </div>
+                  <div className="flex justify-between">
+                    <span className="text-muted-foreground">Avg output:</span>
+                    <span className="font-mono text-emerald-600 dark:text-emerald-400">{formatTokenCount(stats.avgOutput)}</span>
+                  </div>
+                </div>
+              )}
+
+              {/* Total composition */}
+              {totalComposition.total > 0 && (
+                <div className="pt-3 border-t border-muted/50">
+                  <div className="flex items-start gap-2">
+                    <div className="text-muted-foreground text-xs mt-0.5">└─</div>
+                    <div className="flex-1">
+                      <div className="text-xs text-muted-foreground mb-2 flex items-center gap-1">
+                        <Info className="h-3 w-3" />
+                        Total Composition (all turns)
+                      </div>
+                      <CompositionBreakdown composition={totalComposition} />
+                    </div>
+                  </div>
+                </div>
+              )}
+            </div>
+          </div>
+        </div>
+      </ScrollArea>
+    </div>
+  );
+}
@@ -133,10 +133,10 @@ function useBase64ToBlobUrl(data: string | undefined, mimeType: string): string
 function FileContentRenderer({ content, className }: ContentRendererProps) {
  const [isExpanded, setIsExpanded] = useState(true);

-  if (content.type !== "input_file" && content.type !== "output_file") return null;
-
-  const fileUrl = content.file_url || content.file_data;
-  const filename = content.filename || "file";
+  // Determine file properties (must be before hooks for conditional logic)
+  const isFileContent = content.type === "input_file" || content.type === "output_file";
+  const fileUrl = isFileContent ? (content.file_url || content.file_data) : undefined;
+  const filename = isFileContent ? (content.filename || "file") : undefined;

  // Determine file type from filename or data URI
  const isPdf = filename?.toLowerCase().endsWith(".pdf") || fileUrl?.includes("application/pdf");
@@ -144,9 +144,13 @@ function FileContentRenderer({ content, className }: ContentRendererProps) {

  // Convert base64 to blob URL for PDFs (better browser compatibility)
  // Use file_data (raw base64) if available, otherwise try file_url
-  const pdfData = isPdf ? (content.file_data || content.file_url) : undefined;
+  // Hook must be called unconditionally - pass undefined if not a PDF
+  const pdfData = (isFileContent && isPdf) ? (content.file_data || content.file_url) : undefined;
  const pdfBlobUrl = useBase64ToBlobUrl(pdfData, 'application/pdf');

+  // Early return after all hooks
+  if (!isFileContent) return null;
+
  // Use blob URL if available, otherwise fall back to original URL
  const effectivePdfUrl = pdfBlobUrl || fileUrl;

@@ -299,9 +303,12 @@ function DataContentRenderer({ content, className }: ContentRendererProps) {

 // Function approval request renderer - compact version
 function FunctionApprovalRequestRenderer({ content, className }: ContentRendererProps) {
+  // Hooks must be called unconditionally
+  const [isExpanded, setIsExpanded] = useState(false);
+
+  // Early return after hooks
  if (content.type !== "function_approval_request") return null;

-  const [isExpanded, setIsExpanded] = useState(false);
  const { status, function_call } = content;

  // Status styling - compact
@@ -23,7 +23,7 @@ import {
 } from "lucide-react";
 import { cn } from "@/lib/utils";
 import { apiClient } from "@/services/api";
-import type { CheckpointItem, WorkflowSession } from "@/types";
+import type { CheckpointItem, WorkflowSession, FullCheckpoint, PendingRequestInfoEvent } from "@/types";

 interface CheckpointInfoModalProps {
  session: WorkflowSession | null;
@@ -39,7 +39,7 @@ export function CheckpointInfoModal({
  onOpenChange,
 }: CheckpointInfoModalProps) {
  const [selectedCheckpointId, setSelectedCheckpointId] = useState<string | null>(null);
-  const [fullCheckpoint, setFullCheckpoint] = useState<any>(null);
+  const [fullCheckpoint, setFullCheckpoint] = useState<FullCheckpoint | null>(null);
  const [loading, setLoading] = useState(false);
  const [jsonExpanded, setJsonExpanded] = useState(true);

@@ -68,7 +68,7 @@ export function CheckpointInfoModal({
          session.conversation_id,
          `checkpoint_${selectedCheckpointId}`
        );
-        setFullCheckpoint((item as CheckpointItem).metadata?.full_checkpoint);
+        setFullCheckpoint((item as CheckpointItem).metadata?.full_checkpoint ?? null);
      } catch (error) {
        console.error("Failed to load checkpoint:", error);
        setFullCheckpoint(null);
@@ -276,7 +276,7 @@ export function CheckpointInfoModal({
                  )}

                  {/* Messages */}
-                  {messageExecutors.length > 0 && (
+                  {messageExecutors.length > 0 && fullCheckpoint && (
                    <div>
                      <div className="text-sm font-medium mb-3 flex items-center gap-2">
                        <MessageSquare className="h-4 w-4" />
@@ -311,7 +311,7 @@ export function CheckpointInfoModal({
                        </div>
                        <div className="space-y-2">
                          {Object.entries(fullCheckpoint.pending_request_info_events).map(
-                            ([reqId, reqData]: [string, any]) => (
+                            ([reqId, reqData]: [string, PendingRequestInfoEvent]) => (
                              <div
                                key={reqId}
                                className="bg-muted/50 border border-border p-3 rounded-lg"
@@ -9,6 +9,8 @@ import { Button } from "@/components/ui/button";
 import { Badge } from "@/components/ui/badge";
 import { HilTimelineItem } from "./hil-timeline-item";
 import { RunWorkflowButton } from "./run-workflow-button";
+import { ChatMessageInput } from "@/components/ui/chat-message-input";
+import { isChatMessageSchema } from "@/utils/workflow-utils";
 import {
  Loader2,
  CheckCircle,
@@ -21,6 +23,7 @@ import {
  Square,
 } from "lucide-react";
 import type { ExtendedResponseStreamEvent, JSONSchemaProperty } from "@/types";
+import type { ResponseInputContent } from "@/types/agent-framework";
 import type { ExecutorState } from "./executor-node";
 import { truncateText } from "@/utils/workflow-utils";

@@ -262,8 +265,8 @@ export function ExecutionTimeline({
        const item = (event as import("@/types/openai").ResponseOutputItemAddedEvent).item;

        // Handle both executor_action items AND message items from Magentic agents
-        if (item && item.type === "executor_action" && item.executor_id && item.id) {
-          const executorId = item.executor_id;
+        if (item && item.type === "executor_action" && "executor_id" in item && item.id) {
+          const executorId = String(item.executor_id);
          const itemId = item.id;
          const runNumber = (runCount.get(executorId) || 0) + 1;
          runCount.set(executorId, runNumber);
@@ -277,22 +280,25 @@ export function ExecutionTimeline({
            timestamp: uiTimestamp,
            runNumber,
          });
-        } else if (item && item.type === "message" && item.metadata?.agent_id && item.metadata?.source === "magentic" && item.id) {
+        } else if (item && item.type === "message" && "metadata" in item && item.id) {
          // Handle message items from Magentic agents
-          const executorId = item.metadata.agent_id;
-          const itemId = item.id;
-          const runNumber = (runCount.get(executorId) || 0) + 1;
-          runCount.set(executorId, runNumber);
+          const metadata = item.metadata as { agent_id?: string; source?: string } | undefined;
+          if (metadata?.agent_id && metadata?.source === "magentic") {
+            const executorId = metadata.agent_id;
+            const itemId = item.id;
+            const runNumber = (runCount.get(executorId) || 0) + 1;
+            runCount.set(executorId, runNumber);

-          runs.push({
-            executorId,
-            executorName: truncateText(executorId, 35),
-            itemId,
-            state: "running",
-            output: itemOutputs[itemId] || "",
-            timestamp: uiTimestamp,
-            runNumber,
-          });
+            runs.push({
+              executorId,
+              executorName: truncateText(executorId, 35),
+              itemId,
+              state: "running",
+              output: itemOutputs[itemId] || "",
+              timestamp: uiTimestamp,
+              runNumber,
+            });
+          }
        }
      }

@@ -301,7 +307,7 @@ export function ExecutionTimeline({
        const item = (event as import("@/types/openai").ResponseOutputItemDoneEvent).item;

        // Handle both executor_action items AND message items from Magentic agents
-        if (item && item.type === "executor_action" && item.executor_id && item.id) {
+        if (item && item.type === "executor_action" && "executor_id" in item && item.id) {
          const itemId = item.id;
          // Find the run by ITEM ID (not executor ID!) to handle multiple runs correctly
          const existingRun = runs.find((r) => r.itemId === itemId);
@@ -315,18 +321,21 @@ export function ExecutionTimeline({
                : "completed";
            // Use item-specific output, not executor-wide output
            existingRun.output = itemOutputs[itemId] || "";
-            if (item.status === "failed" && item.error) {
-              existingRun.error = item.error;
+            if (item.status === "failed" && "error" in item && item.error) {
+              existingRun.error = String(item.error);
            }
          }
-        } else if (item && item.type === "message" && item.metadata?.agent_id && item.metadata?.source === "magentic" && item.id) {
+        } else if (item && item.type === "message" && "metadata" in item && item.id) {
          // Handle message completion from Magentic agents
-          const itemId = item.id;
-          const existingRun = runs.find((r) => r.itemId === itemId);
+          const metadata = item.metadata as { agent_id?: string; source?: string } | undefined;
+          if (metadata?.agent_id && metadata?.source === "magentic") {
+            const itemId = item.id;
+            const existingRun = runs.find((r) => r.itemId === itemId);

-          if (existingRun) {
-            existingRun.state = item.status === "completed" ? "completed" : "failed";
-            existingRun.output = itemOutputs[itemId] || "";
+            if (existingRun) {
+              existingRun.state = item.status === "completed" ? "completed" : "failed";
+              existingRun.output = itemOutputs[itemId] || "";
+            }
          }
        }
      }
@@ -625,16 +634,35 @@ export function ExecutionTimeline({
      {/* Bottom Control Bar - Sticky (hidden when HIL is active) */}
      {(onRun || onCancel) && pendingHilRequests.length === 0 && (
        <div className="border-t p-3 bg-background flex-shrink-0">
-          <RunWorkflowButton
-            inputSchema={inputSchema}
-            onRun={onRun || (() => {})}
-            onCancel={onCancel}
-            isSubmitting={workflowState === "running"}
-            isCancelling={isCancelling}
-            workflowState={workflowState}
-            checkpoints={checkpoints}
-            showCheckpoints={false}
-          />
+          {inputSchema && isChatMessageSchema(inputSchema) ? (
+            <ChatMessageInput
+              onSubmit={async (content: ResponseInputContent[]) => {
+                // Wrap in OpenAI message format (same as run-workflow-button modal)
+                const openaiInput = [
+                  { type: "message", role: "user", content },
+                ];
+                onRun?.(openaiInput as unknown as Record<string, unknown>);
+              }}
+              isSubmitting={workflowState === "running"}
+              isStreaming={workflowState === "running"}
+              onCancel={onCancel}
+              isCancelling={isCancelling}
+              placeholder="Message workflow..."
+              showFileUpload={true}
+              entityName="workflow"
+            />
+          ) : (
+            <RunWorkflowButton
+              inputSchema={inputSchema}
+              onRun={onRun || (() => {})}
+              onCancel={onCancel}
+              isSubmitting={workflowState === "running"}
+              isCancelling={isCancelling}
+              workflowState={workflowState}
+              checkpoints={checkpoints}
+              showCheckpoints={false}
+            />
+          )}
        </div>
      )}

@@ -1,9 +1,11 @@
-import { memo } from "react";
+import { memo, useState } from "react";
 import { Handle, Position, type NodeProps } from "@xyflow/react";
 import {
  Workflow,
  Home,
  Loader2,
+  ChevronRight,
+  ChevronDown,
 } from "lucide-react";
 import { cn } from "@/lib/utils";
 import { truncateText } from "@/utils/workflow-utils";
@@ -70,8 +72,9 @@ const getExecutorStateConfig = (state: ExecutorState) => {
 export const ExecutorNode = memo(({ data, selected }: NodeProps) => {
  const nodeData = data as ExecutorNodeData;
  const config = getExecutorStateConfig(nodeData.state);
+  const [isOutputExpanded, setIsOutputExpanded] = useState(false);

-  const hasData = nodeData.inputData || nodeData.outputData || nodeData.error;
+  const hasOutput = nodeData.outputData || nodeData.error;
  const isRunning = nodeData.state === "running";
  const shouldAnimate = isRunning && (nodeData.isStreaming ?? true); // Default to true for backwards compatibility

@@ -80,19 +83,13 @@ export const ExecutorNode = memo(({ data, selected }: NodeProps) => {
  const targetPosition = isVertical ? Position.Top : Position.Left;
  const sourcePosition = isVertical ? Position.Bottom : Position.Right;

-  // Helper to safely render data with full details
+  // Helper to render output/error details when expanded
  const renderDataDetails = () => {
-    const details = [];
-
    if (nodeData.error && typeof nodeData.error === "string") {
-      // Truncate error to first 150 characters for node display
-      const truncatedError = truncateText(nodeData.error, 150);
-      details.push(
-        <div key="error" className="mb-2">
-          <div className="text-xs font-medium text-red-600 dark:text-red-400 mb-1">Error:</div>
-          <div className="text-xs text-red-600 dark:text-red-400 bg-red-50 dark:bg-red-950/20 p-2 rounded border border-red-200 dark:border-red-800 break-words">
-            {truncatedError}
-          </div>
+      const truncatedError = truncateText(nodeData.error, 200);
+      return (
+        <div className="text-xs text-red-600 dark:text-red-400 bg-red-50 dark:bg-red-950/20 p-2 rounded border border-red-200 dark:border-red-800 break-words max-h-32 overflow-auto">
+          {truncatedError}
        </div>
      );
    }
@@ -103,53 +100,21 @@ export const ExecutorNode = memo(({ data, selected }: NodeProps) => {
          typeof nodeData.outputData === "string"
            ? nodeData.outputData
            : JSON.stringify(nodeData.outputData, null, 2);
-        details.push(
-          <div key="output" className="mb-2">
-            <div className="text-xs font-medium text-green-600 dark:text-green-400 mb-1">Output:</div>
-            <div className="text-xs text-gray-700 dark:text-gray-300 bg-green-50 dark:bg-green-950/20 p-2 rounded border border-green-200 dark:border-green-800 max-h-20 overflow-auto">
-              <pre className="whitespace-pre-wrap font-mono">{outputStr}</pre>
-            </div>
+        return (
+          <div className="text-xs text-gray-700 dark:text-gray-300 bg-muted/50 p-2 rounded border max-h-32 overflow-auto">
+            <pre className="whitespace-pre-wrap font-mono">{outputStr}</pre>
          </div>
        );
      } catch {
-        details.push(
-          <div key="output" className="mb-2">
-            <div className="text-xs font-medium text-green-600 dark:text-green-400 mb-1">Output:</div>
-            <div className="text-xs text-gray-600 dark:text-gray-400 bg-green-50 dark:bg-green-950/20 p-2 rounded border border-green-200 dark:border-green-800">
-              [Unable to display output data]
-            </div>
+        return (
+          <div className="text-xs text-gray-600 dark:text-gray-400 bg-muted/50 p-2 rounded border">
+            [Unable to display output]
          </div>
        );
      }
    }

-    if (nodeData.inputData) {
-      try {
-        const inputStr =
-          typeof nodeData.inputData === "string"
-            ? nodeData.inputData
-            : JSON.stringify(nodeData.inputData, null, 2);
-        details.push(
-          <div key="input" className="mb-2">
-            <div className="text-xs font-medium text-blue-600 dark:text-blue-400 mb-1">Input:</div>
-            <div className="text-xs text-gray-700 dark:text-gray-300 bg-blue-50 dark:bg-blue-950/20 p-2 rounded border border-blue-200 dark:border-blue-800 max-h-20 overflow-auto">
-              <pre className="whitespace-pre-wrap font-mono">{inputStr}</pre>
-            </div>
-          </div>
-        );
-      } catch {
-        details.push(
-          <div key="input" className="mb-2">
-            <div className="text-xs font-medium text-blue-600 dark:text-blue-400 mb-1">Input:</div>
-            <div className="text-xs text-gray-600 dark:text-gray-400 bg-blue-50 dark:bg-blue-950/20 p-2 rounded border border-blue-200 dark:border-blue-800">
-              [Unable to display input data]
-            </div>
-          </div>
-        );
-      }
-    }
-
-    return details.length > 0 ? details : null;
+    return null;
  };

  return (
@@ -218,10 +183,28 @@ export const ExecutorNode = memo(({ data, selected }: NodeProps) => {
          </div>
        </div>

-        {/* Data details */}
-        {hasData && (
-          <div className="mt-3">
-            {renderDataDetails()}
+        {/* Collapsible output section */}
+        {hasOutput && (
+          <div className="mt-2 border-t border-border/50 pt-2">
+            <button
+              onClick={(e) => {
+                e.stopPropagation();
+                setIsOutputExpanded(!isOutputExpanded);
+              }}
+              className="flex items-center gap-1 text-xs text-muted-foreground hover:text-foreground transition-colors w-full"
+            >
+              {isOutputExpanded ? (
+                <ChevronDown className="w-3 h-3" />
+              ) : (
+                <ChevronRight className="w-3 h-3" />
+              )}
+              <span>{nodeData.error ? "Show error" : "Show output"}</span>
+            </button>
+            {isOutputExpanded && (
+              <div className="mt-2">
+                {renderDataDetails()}
+              </div>
+            )}
          </div>
        )}

@@ -110,6 +110,7 @@ export function WorkflowView({
  const removeSession = useDevUIStore((state) => state.removeSession);
  const addToast = useDevUIStore((state) => state.addToast);
  const runtime = useDevUIStore((state) => state.runtime);
+  const streamingEnabled = useDevUIStore((state) => state.streamingEnabled);

  // View options state
  const [viewOptions, setViewOptions] = useState(() => {
@@ -304,8 +305,9 @@ export function WorkflowView({
        { limit: 100 }
      );
      const checkpointItems = response.data.filter(
-        (item: any) => item.type === "checkpoint"
-      ) as CheckpointItem[];
+        (item): item is CheckpointItem =>
+          typeof item === "object" && item !== null && "type" in item && (item as { type: string }).type === "checkpoint"
+      );
      setSessionCheckpoints(checkpointItems);
    } catch (error) {
      console.error(`Failed to load checkpoints for session ${currentSession.conversation_id}:`, error);
@@ -453,9 +455,9 @@ export function WorkflowView({
            | import("@/types/openai").ResponseOutputItemAddedEvent
            | import("@/types/openai").ResponseOutputItemDoneEvent
        ).item;
-        if (item && item.type === "executor_action" && item.executor_id) {
+        if (item && item.type === "executor_action" && "executor_id" in item && item.executor_id) {
          history.push({
-            executorId: item.executor_id,
+            executorId: String(item.executor_id),
            message:
              event.type === "response.output_item.added"
                ? "Executor started"
@@ -624,7 +626,8 @@ export function WorkflowView({
            if (
              item &&
              item.type === "message" &&
-              item.metadata?.source === "magentic" &&
+              "metadata" in item &&
+              (item.metadata as { source?: string } | undefined)?.source === "magentic" &&
              item.id
            ) {
              // Track this message ID as the current streaming target for Magentic agents
@@ -639,19 +642,21 @@ export function WorkflowView({
            if (
              item &&
              item.type === "message" &&
-              !item.metadata?.source &&
-              item.content
+              (!("metadata" in item) || !(item.metadata as { source?: string } | undefined)?.source) &&
+              "content" in item &&
+              Array.isArray(item.content)
            ) {
              // Extract text from message content
-              for (const content of item.content) {
+              for (const content of item.content as Array<{ type: string; text?: string }>) {
                if (content.type === "output_text" && content.text) {
+                  const text = content.text; // Capture for closure
                  // Append to workflow result (support multiple yield_output calls)
                  setWorkflowResult((prev) => {
                    if (prev && prev.length > 0) {
                      // If there's existing output, add separator
-                      return prev + "\n\n" + content.text;
+                      return prev + "\n\n" + text;
                    }
-                    return content.text;
+                    return text;
                  });

                  // Try to parse as JSON for structured metadata
@@ -820,6 +825,99 @@ export function WorkflowView({
    ]
  );

+  // Handle non-streaming workflow data sending
+  const handleSendWorkflowDataSync = useCallback(
+    async (inputData: Record<string, unknown>, checkpointId?: string) => {
+      if (!selectedWorkflow || selectedWorkflow.type !== "workflow") return;
+
+      setIsStreaming(false); // Not actually streaming
+      setWasCancelled(false);
+      setOpenAIEvents([]);
+      setWorkflowResult("");
+      itemOutputs.current = {};
+      currentStreamingItemId.current = null;
+      workflowMetadata.current = null;
+      setPendingHilRequests([]);
+      setHilResponses({});
+      onDebugEvent("clear");
+
+      try {
+        const response = await apiClient.runWorkflowSync(selectedWorkflow.id, {
+          input_data: inputData,
+          conversation_id: currentSession?.conversation_id || undefined,
+          checkpoint_id: checkpointId,
+        });
+
+        // Extract workflow result from response output
+        if (response.output) {
+          for (const outputItem of response.output) {
+            if (outputItem.type === "message" && "content" in outputItem && Array.isArray(outputItem.content)) {
+              for (const content of outputItem.content as Array<{ type: string; text?: string }>) {
+                if (content.type === "output_text" && content.text) {
+                  setWorkflowResult((prev) => {
+                    if (prev && prev.length > 0) {
+                      return prev + "\n\n" + content.text;
+                    }
+                    return content.text || "";
+                  });
+
+                  // Try to parse as JSON for structured metadata
+                  try {
+                    const parsed = JSON.parse(content.text || "");
+                    if (typeof parsed === "object" && parsed !== null) {
+                      workflowMetadata.current = parsed;
+                    }
+                  } catch {
+                    // Not JSON, keep as text
+                  }
+                }
+              }
+            }
+          }
+        }
+
+        // Create a synthetic completion event for the timeline
+        const completedEvent = {
+          type: "response.completed",
+          response: response,
+          sequence_number: 0,
+        } as ExtendedResponseStreamEvent;
+        setOpenAIEvents([completedEvent]);
+        onDebugEvent(completedEvent);
+
+        // Refetch checkpoints after completion
+        await loadCheckpoints();
+      } catch (error) {
+        console.error("Workflow execution error:", error);
+
+        // Create a synthetic error event for the timeline
+        const errorMessage = error instanceof Error ? error.message : "Workflow execution failed";
+        const errorEvent: ExtendedResponseStreamEvent = {
+          type: "response.failed",
+          response: {
+            error: { message: errorMessage },
+          },
+          sequence_number: 0,
+        } as ExtendedResponseStreamEvent;
+        setOpenAIEvents([errorEvent]);
+        onDebugEvent(errorEvent);
+      }
+    },
+    [selectedWorkflow, currentSession, onDebugEvent, loadCheckpoints]
+  );
+
+  // Wrapper to choose between streaming and non-streaming
+  const handleWorkflowRun = useCallback(
+    async (inputData: Record<string, unknown>, checkpointId?: string) => {
+      if (streamingEnabled) {
+        await handleSendWorkflowData(inputData, checkpointId);
+      } else {
+        await handleSendWorkflowDataSync(inputData, checkpointId);
+      }
+    },
+    [streamingEnabled, handleSendWorkflowData, handleSendWorkflowDataSync]
+  );
+
  // Check if all HIL responses are valid
  const areAllHilResponsesValid = useCallback(() => {
    // Check each pending request has a valid response
@@ -979,22 +1077,23 @@ export function WorkflowView({
          }

          // Handle workflow output messages
-          if (item && item.type === "message" && item.content) {
+          if (item && item.type === "message" && "content" in item && Array.isArray(item.content)) {
            // Extract text from message content
-            for (const content of item.content) {
+            for (const content of item.content as Array<{ type: string; text?: string }>) {
              if (content.type === "output_text" && content.text) {
+                const text = content.text; // Capture for closure
                // Append to workflow result (support multiple yield_output calls)
                setWorkflowResult((prev) => {
                  if (prev && prev.length > 0) {
                    // If there's existing output, add separator
-                    return prev + "\n\n" + content.text;
+                    return prev + "\n\n" + text;
                  }
-                  return content.text;
+                  return text;
                });

                // Try to parse as JSON for structured metadata
                try {
-                  const parsed = JSON.parse(content.text);
+                  const parsed = JSON.parse(text);
                  if (typeof parsed === "object" && parsed !== null) {
                    workflowMetadata.current = parsed;
                  }
@@ -1296,7 +1395,7 @@ export function WorkflowView({
              {timelineMinimized && (
                <RunWorkflowButton
                  inputSchema={workflowInfo.input_schema}
-                  onRun={handleSendWorkflowData}
+                  onRun={handleWorkflowRun}
                  onCancel={handleCancel}
                  isSubmitting={isStreaming}
                  isCancelling={isCancelling}
@@ -1481,7 +1580,7 @@ export function WorkflowView({
                    inputSchema={workflowInfo?.input_schema}
                    onRun={(data, checkpointId) => {
                      // Use the form data from timeline
-                      handleSendWorkflowData(data, checkpointId);
+                      handleWorkflowRun(data, checkpointId);
                    }}
                    onCancel={handleCancel}
                    isCancelling={isCancelling}
@@ -3,7 +3,8 @@
 * Features: Real-time event streaming, trace visualization, tool call details
 */

-import { useRef, useState } from "react";
+import { useRef, useState, useMemo } from "react";
+import { useDevUIStore } from "@/stores/devuiStore";
 import { ScrollArea } from "@/components/ui/scroll-area";
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
 import { Badge } from "@/components/ui/badge";
@@ -19,8 +20,9 @@ import {
  MessageSquare,
  ChevronRight,
  ChevronDown,
-  Info,
+  BarChart3,
 } from "lucide-react";
+import { ContextInspector } from "@/components/features/agent/context-inspector";
 import type { ExtendedResponseStreamEvent } from "@/types";

 // Simple visual separator component
@@ -88,7 +90,23 @@ interface TraceEventData extends EventDataBase {
  start_time?: number;
  end_time?: number;
  entity_id?: string;
-  session_id?: string | null;
+  response_id?: string | null;
+}
+
+// Helper type for trace hierarchy
+interface TraceNode {
+  event: ExtendedResponseStreamEvent;
+  data: TraceEventData;
+  children: TraceNode[];
+}
+
+// Helper type for grouped traces by response
+interface TraceGroup {
+  response_id: string;
+  timestamp: number;
+  traces: TraceNode[];
+  totalDuration: number;
+  entity_id?: string;
 }

 interface DebugPanelProps {
@@ -149,20 +167,22 @@ function processEventsForDisplay(
      const item = outputEvent.item;

      // If it's a function call item, extract metadata
-      if (item.type === "function_call" && item.call_id && item.name) {
-        const callId = item.call_id;
+      if (item.type === "function_call") {
+        // Type assertion for function call
+        const funcCall = item as import("@/types").ResponseFunctionToolCall;
+        const callId = funcCall.call_id;

        // Initialize function call tracking with REAL function name from backend!
        functionCalls.set(callId, {
-          name: item.name, // ← REAL NAME! (not "unknown")
+          name: funcCall.name, // ← REAL NAME! (not "unknown")
          arguments: "",
          callId: callId,
-          itemId: item.id, // Track item_id for delta matching
+          itemId: funcCall.id, // Track item_id for delta matching
          timestamp: new Date().toISOString(),
        });

        // Also track in callIdToName map for result pairing
-        callIdToName.set(callId, item.name);
+        callIdToName.set(callId, funcCall.name);
      }

      // Pass through the event for display
@@ -955,27 +975,7 @@ function EventExpandedContent({
                  </span>
                  <div className="mt-1 max-h-32 overflow-auto">
                    <pre className="text-xs bg-background border rounded p-2 whitespace-pre-wrap break-all">
-                      {(() => {
-                        try {
-                          // Try to pretty-print JSON, and unescape string values that contain JSON
-                          const attrs = { ...data.attributes };
-                          Object.keys(attrs).forEach((key) => {
-                            if (
-                              typeof attrs[key] === "string" &&
-                              attrs[key].startsWith("[")
-                            ) {
-                              try {
-                                attrs[key] = JSON.parse(attrs[key]);
-                              } catch {
-                                // Keep original if parsing fails
-                              }
-                            }
-                          });
-                          return JSON.stringify(attrs, null, 2);
-                        } catch {
-                          return JSON.stringify(data.attributes, null, 2);
-                        }
-                      })()}
+                      {formatTraceAttributes(data.attributes)}
                    </pre>
                  </div>
                </div>
@@ -1149,257 +1149,418 @@ function EventsTab({
  );
 }

-function TracesTab({ events }: { events: ExtendedResponseStreamEvent[] }) {
-  // ONLY show actual trace events - handle both event type formats
-  const traceEvents = events.filter(
-    (e) =>
-      e.type === "response.trace.completed" ||
-      e.type === "response.trace.completed"
-  );
+// Build hierarchical trace structure from flat trace events
+function buildTraceHierarchy(traceEvents: ExtendedResponseStreamEvent[]): TraceGroup[] {
+  // Group by response_id first
+  const groupedByResponse = new Map<string, ExtendedResponseStreamEvent[]>();

-  // Add separators between message rounds
-  const tracesWithSeparators = addSeparatorsToEvents(traceEvents);
+  for (const event of traceEvents) {
+    if (!("data" in event)) continue;
+    const data = event.data as TraceEventData;
+    const responseId = data.response_id || "unknown";

-  // Reverse to show latest traces at the top
-  const reversedTraceEvents = [...tracesWithSeparators].reverse();
+    if (!groupedByResponse.has(responseId)) {
+      groupedByResponse.set(responseId, []);
+    }
+    groupedByResponse.get(responseId)!.push(event);
+  }
+
+  // Convert each group to hierarchical structure
+  const groups: TraceGroup[] = [];
+
+  for (const [responseId, events] of groupedByResponse) {
+    // Build tree from parent_span_id relationships
+    const nodeMap = new Map<string, TraceNode>();
+    const rootNodes: TraceNode[] = [];
+
+    // First pass: create all nodes
+    for (const event of events) {
+      if (!("data" in event)) continue;
+      const data = (event as { data: TraceEventData }).data;
+      const spanId = data.span_id || `span_${Math.random()}`;
+      nodeMap.set(spanId, {
+        event,
+        data,
+        children: [],
+      });
+    }
+
+    // Second pass: build parent-child relationships
+    for (const event of events) {
+      if (!("data" in event)) continue;
+      const data = (event as { data: TraceEventData }).data;
+      const spanId = data.span_id || "";
+      const parentSpanId = data.parent_span_id;
+      const node = nodeMap.get(spanId);
+
+      if (!node) continue;
+
+      if (parentSpanId && nodeMap.has(parentSpanId)) {
+        // Has a parent in this group
+        nodeMap.get(parentSpanId)!.children.push(node);
+      } else {
+        // Root node (no parent or parent not in this group)
+        rootNodes.push(node);
+      }
+    }
+
+    // Sort root nodes by start_time (earliest first)
+    rootNodes.sort((a, b) => (a.data.start_time || 0) - (b.data.start_time || 0));
+
+    // Sort children recursively by start_time
+    const sortChildren = (node: TraceNode) => {
+      node.children.sort((a, b) => (a.data.start_time || 0) - (b.data.start_time || 0));
+      node.children.forEach(sortChildren);
+    };
+    rootNodes.forEach(sortChildren);
+
+    // Calculate group metadata
+    const firstEvent = events[0];
+    const firstData = firstEvent && "data" in firstEvent ? (firstEvent.data as TraceEventData) : null;
+    const timestamp = Math.min(...events.map(e => {
+      const d = "data" in e ? (e.data as TraceEventData) : null;
+      return d?.start_time || Date.now() / 1000;
+    }));
+    const totalDuration = events.reduce((sum, e) => {
+      const d = "data" in e ? (e.data as TraceEventData) : null;
+      return sum + (d?.duration_ms || 0);
+    }, 0);
+
+    groups.push({
+      response_id: responseId,
+      timestamp,
+      traces: rootNodes,
+      totalDuration,
+      entity_id: firstData?.entity_id,
+    });
+  }
+
+  // Sort groups by timestamp (newest first)
+  groups.sort((a, b) => b.timestamp - a.timestamp);
+
+  return groups;
+}
+
+// Recursively parse escaped JSON strings at any depth
+function parseEscapedJson(value: unknown): unknown {
+  if (typeof value === "string") {
+    // Try to parse JSON strings (arrays or objects)
+    const trimmed = value.trim();
+    if (trimmed.startsWith("[") || trimmed.startsWith("{")) {
+      try {
+        const parsed = JSON.parse(value);
+        // Recursively process the parsed result
+        return parseEscapedJson(parsed);
+      } catch {
+        return value;
+      }
+    }
+    return value;
+  }
+
+  if (Array.isArray(value)) {
+    return value.map(parseEscapedJson);
+  }
+
+  if (value !== null && typeof value === "object") {
+    const result: Record<string, unknown> = {};
+    for (const [k, v] of Object.entries(value)) {
+      result[k] = parseEscapedJson(v);
+    }
+    return result;
+  }
+
+  return value;
+}
+
+// Format trace attributes by parsing escaped JSON strings for better readability
+function formatTraceAttributes(attributes: Record<string, unknown>): string {
+  try {
+    const formatted = parseEscapedJson(attributes);
+    return JSON.stringify(formatted, null, 2);
+  } catch {
+    return JSON.stringify(attributes, null, 2);
+  }
+}
+
+// Get operation type badge color
+function getOperationColor(operationName: string): string {
+  if (operationName.includes("invoke_agent") || operationName.includes("Agent")) {
+    return "bg-purple-100 dark:bg-purple-900 text-purple-800 dark:text-purple-200";
+  }
+  if (operationName.includes("chat") || operationName.includes("Chat")) {
+    return "bg-blue-100 dark:bg-blue-900 text-blue-800 dark:text-blue-200";
+  }
+  if (operationName.includes("tool") || operationName.includes("execute")) {
+    return "bg-green-100 dark:bg-green-900 text-green-800 dark:text-green-200";
+  }
+  return "bg-orange-100 dark:bg-orange-900 text-orange-800 dark:text-orange-200";
+}
+
+// Recursive component for rendering trace tree nodes
+function TraceTreeNode({ node, depth = 0 }: { node: TraceNode; depth?: number }) {
+  const [isExpanded, setIsExpanded] = useState(depth < 2); // Auto-expand first 2 levels
+  const [showDetails, setShowDetails] = useState(false);
+
+  const { data } = node;
+  const operationName = data.operation_name || "Unknown";
+  const duration = data.duration_ms ? `${Number(data.duration_ms).toFixed(1)}ms` : "";
+  const hasChildren = node.children.length > 0;
+
+  // Extract token usage from attributes if available
+  const inputTokens = data.attributes?.["gen_ai.usage.input_tokens"];
+  const outputTokens = data.attributes?.["gen_ai.usage.output_tokens"];
+  const hasTokens = inputTokens !== undefined || outputTokens !== undefined;

  return (
-    <div className="h-full flex flex-col">
-      <div className="flex items-center gap-2 p-3 border-b">
-        <Search className="h-4 w-4" />
-        <span className="font-medium">Traces</span>
-        <Badge variant="outline">{traceEvents.length}</Badge>
+    <div className="relative">
+      {/* Vertical line for tree structure */}
+      {depth > 0 && (
+        <div
+          className="absolute left-0 top-0 bottom-0 border-l-2 border-muted"
+          style={{ marginLeft: `${(depth - 1) * 16 + 8}px` }}
+        />
+      )}
+
+      <div
+        className="flex items-center gap-2 py-1.5 hover:bg-muted/50 rounded transition-colors"
+        style={{ paddingLeft: `${depth * 16}px` }}
+      >
+        {/* Expand/collapse for children OR details */}
+        <button
+          onClick={() => hasChildren ? setIsExpanded(!isExpanded) : setShowDetails(!showDetails)}
+          className="w-4 h-4 flex items-center justify-center text-muted-foreground hover:text-foreground"
+        >
+          {hasChildren ? (
+            isExpanded ? <ChevronDown className="h-3 w-3" /> : <ChevronRight className="h-3 w-3" />
+          ) : (
+            showDetails ? <ChevronDown className="h-3 w-3" /> : <ChevronRight className="h-3 w-3" />
+          )}
+        </button>
+
+        {/* Operation badge */}
+        <span className={`text-xs px-1.5 py-0.5 rounded font-medium ${getOperationColor(operationName)}`}>
+          {operationName.replace("ChatAgent.", "").replace("invoke_agent ", "")}
+        </span>
+
+        {/* Duration */}
+        {duration && (
+          <span className="text-xs text-muted-foreground font-mono">
+            {duration}
+          </span>
+        )}
+
+        {/* Token usage */}
+        {hasTokens && (
+          <span className="text-xs text-muted-foreground font-mono">
+            {inputTokens !== undefined && <span>↑{String(inputTokens)}</span>}
+            {inputTokens !== undefined && outputTokens !== undefined && <span className="mx-0.5">/</span>}
+            {outputTokens !== undefined && <span>↓{String(outputTokens)}</span>}
+          </span>
+        )}
      </div>

-      <ScrollArea className="flex-1">
-        <div className="p-3">
-          {traceEvents.length === 0 ? (
-            <div className="text-center text-muted-foreground text-sm py-8">
-              No trace data available.
-              <br />
-              {events && events.length > 0 && (
-                <div className="mt-3 text-xs border rounded p-2">
-                  {" "}
-                  <Info className="inline h-4 w-4 mr-1  " />
-                  You may have to set the environment variable{" "}
-                  <span className="font-mono bg-accent/10 px-1 rounded">
-                    ENABLE_INSTRUMENTATION=true
-                  </span>{" "}
-                  or restart devui with the tracing flag{" "}
-                  <div className="font-mono bg-accent/10 px-1 rounded">
-                    devui --tracing
-                  </div>
-                  to enable tracing.
-                </div>
-              )}
-            </div>
-          ) : (
-            <div className="space-y-3">
-              {reversedTraceEvents.map((event, index) => {
-                if ('type' in event && event.type === "separator") {
-                  return <MessageSeparator key={(event as { type: "separator"; id: string }).id} />;
-                }
-                return <TraceEventItem key={index} event={event as ExtendedResponseStreamEvent} />;
-              })}
-            </div>
-          )}
+      {/* Details panel */}
+      {showDetails && !hasChildren && (
+        <div
+          className="ml-4 mt-1 mb-2 p-2 bg-muted/30 rounded border text-xs"
+          style={{ marginLeft: `${depth * 16 + 20}px` }}
+        >
+          <div className="space-y-1">
+            {data.span_id && (
+              <div className="flex gap-2">
+                <span className="text-muted-foreground w-20">Span ID:</span>
+                <span className="font-mono text-xs break-all">{data.span_id}</span>
+              </div>
+            )}
+            {data.trace_id && (
+              <div className="flex gap-2">
+                <span className="text-muted-foreground w-20">Trace ID:</span>
+                <span className="font-mono text-xs break-all">{data.trace_id}</span>
+              </div>
+            )}
+            {data.status && (
+              <div className="flex gap-2">
+                <span className="text-muted-foreground w-20">Status:</span>
+                <span className={`px-1.5 py-0.5 rounded text-xs ${
+                  data.status === "StatusCode.UNSET" || data.status === "OK"
+                    ? "bg-green-100 dark:bg-green-900 text-green-800 dark:text-green-200"
+                    : "bg-red-100 dark:bg-red-900 text-red-800 dark:text-red-200"
+                }`}>
+                  {data.status}
+                </span>
+              </div>
+            )}
+            {data.attributes && Object.keys(data.attributes).length > 0 && (
+              <div className="mt-2">
+                <span className="text-muted-foreground block mb-1">Attributes:</span>
+                <pre className="text-xs bg-background border rounded p-2 overflow-auto max-h-32 whitespace-pre-wrap break-all">
+                  {formatTraceAttributes(data.attributes)}
+                </pre>
+              </div>
+            )}
+          </div>
        </div>
-      </ScrollArea>
+      )}
+
+      {/* Children */}
+      {hasChildren && isExpanded && (
+        <div>
+          {node.children.map((child, idx) => (
+            <TraceTreeNode key={child.data.span_id || idx} node={child} depth={depth + 1} />
+          ))}
+        </div>
+      )}
    </div>
  );
 }

-function TraceEventItem({ event }: { event: ExtendedResponseStreamEvent }) {
-  const [isExpanded, setIsExpanded] = useState(false);
+// Component for a single trace group (one response/turn)
+function TraceGroupItem({ group }: { group: TraceGroup }) {
+  const [isExpanded, setIsExpanded] = useState(true);

-  if (
-    (event.type !== "response.trace.completed" &&
-      event.type !== "response.trace.completed") ||
-    !("data" in event)
-  ) {
-    return (
-      <div className="border rounded p-3 text-red-600 dark:text-red-400 text-xs">
-        Error: Expected trace event but got {event.type}
-      </div>
-    );
-  }
-
-  const data = event.data as TraceEventData;
-
-  // Use stored UI timestamp first, then trace timestamps, then fallback to current time
-  let timestamp: string;
-  if ('_uiTimestamp' in event && typeof event._uiTimestamp === 'number') {
-    // Use stored UI timestamp from when event was received
-    timestamp = new Date(event._uiTimestamp * 1000).toLocaleTimeString();
-  } else if (data.end_time) {
-    timestamp = new Date(data.end_time * 1000).toLocaleTimeString();
-  } else if (data.start_time) {
-    timestamp = new Date(data.start_time * 1000).toLocaleTimeString();
-  } else if (data.timestamp) {
-    timestamp = new Date(data.timestamp).toLocaleTimeString();
-  } else {
-    timestamp = new Date().toLocaleTimeString();
-  }
-
-  const operationName = data.operation_name || "Unknown Operation";
-  const duration = data.duration_ms
-    ? `${Number(data.duration_ms).toFixed(1)}ms`
-    : "";
-  const entityId = data.entity_id || "";
+  const timestamp = new Date(group.timestamp * 1000).toLocaleTimeString();
+  const duration = group.totalDuration > 0 ? `${group.totalDuration.toFixed(0)}ms` : "";
+  const spanCount = group.traces.reduce((count, node) => {
+    const countNode = (n: TraceNode): number => 1 + n.children.reduce((c, child) => c + countNode(child), 0);
+    return count + countNode(node);
+  }, 0);

  return (
-    <div className="border-l-2 border-muted pl-3 py-2 hover:bg-muted/50 transition-colors">
-      <div className="flex items-center gap-2 text-xs text-muted-foreground mb-1">
-        <Search className="h-3 w-3 text-orange-600 dark:text-orange-400" />
-        <span className="font-mono">{timestamp}</span>
-        <Badge variant="outline" className="text-xs py-0">
-          trace
-        </Badge>
+    <div className="border rounded-lg overflow-hidden">
+      {/* Group header */}
+      <div
+        className="flex items-center gap-2 p-2 bg-muted/50 cursor-pointer hover:bg-muted/70 transition-colors"
+        onClick={() => setIsExpanded(!isExpanded)}
+      >
+        <div className="text-muted-foreground">
+          {isExpanded ? <ChevronDown className="h-4 w-4" /> : <ChevronRight className="h-4 w-4" />}
+        </div>
+
+        <span className="font-mono text-xs text-muted-foreground">{timestamp}</span>
+
+        {group.entity_id && (
+          <Badge variant="outline" className="text-xs py-0">
+            {group.entity_id.replace("agent_", "").replace("workflow_", "")}
+          </Badge>
+        )}
+
+        <div className="flex-1" />
+
        {duration && (
          <Badge variant="secondary" className="text-xs py-0">
            {duration}
          </Badge>
        )}
+
+        <span className="text-xs text-muted-foreground">
+          {spanCount} span{spanCount !== 1 ? "s" : ""}
+        </span>
      </div>

-      <div className="text-sm">
-        <div
-          className="flex items-center gap-2 cursor-pointer"
-          onClick={() => setIsExpanded(!isExpanded)}
-        >
-          <div className="text-muted-foreground">
-            {isExpanded ? (
-              <ChevronDown className="h-3 w-3" />
-            ) : (
-              <ChevronRight className="h-3 w-3" />
-            )}
-          </div>
-          <div className="text-muted-foreground flex-1 break-all">
-            <span className="font-medium">{operationName}</span>
-            {entityId && <span className="ml-2 text-xs">({entityId})</span>}
-          </div>
+      {/* Group content - trace tree */}
+      {isExpanded && (
+        <div className="p-2 border-t">
+          {group.traces.map((node, idx) => (
+            <TraceTreeNode key={node.data.span_id || idx} node={node} depth={0} />
+          ))}
        </div>
+      )}
+    </div>
+  );
+}

-        {/* Expandable content */}
-        {isExpanded && (
-          <div className="mt-2 ml-5 p-3 bg-muted/30 rounded border">
-            <div className="space-y-2">
+function TracesTab({ events }: { events: ExtendedResponseStreamEvent[] }) {
+  // Use persisted store state instead of local useState
+  const subTab = useDevUIStore((state) => state.debugTraceSubTab);
+  const setSubTab = useDevUIStore((state) => state.setDebugTraceSubTab);
+
+  // ONLY show actual trace events
+  const traceEvents = events.filter(
+    (e) => e.type === "response.trace.completed"
+  );
+
+  // Build hierarchical structure grouped by response_id
+  const traceGroups = buildTraceHierarchy(traceEvents);
+
+  return (
+    <div className="h-full flex flex-col">
+      {/* Sub-tab header */}
+      <div className="flex items-center gap-2 p-3 border-b">
+        <Search className="h-4 w-4" />
+        <span className="font-medium">Traces</span>
+        <Badge variant="outline">{traceEvents.length}</Badge>
+
+        {/* Sub-tab toggle */}
+        <div className="flex-1" />
+        <div className="flex items-center bg-muted rounded-md p-1 min-w-0">
+          <button
+            onClick={() => setSubTab("spans")}
+            className={`px-3 py-1.5 text-xs rounded transition-colors truncate ${
+              subTab === "spans"
+                ? "bg-background shadow-sm font-medium"
+                : "text-muted-foreground hover:text-foreground"
+            }`}
+          >
+            OTel Spans
+          </button>
+          <button
+            onClick={() => setSubTab("context")}
+            className={`px-3 py-1.5 text-xs rounded transition-colors flex items-center gap-1.5 min-w-0 ${
+              subTab === "context"
+                ? "bg-background shadow-sm font-medium"
+                : "text-muted-foreground hover:text-foreground"
+            }`}
+          >
+            <BarChart3 className="h-3.5 w-3.5 flex-shrink-0" />
+            <span className="truncate">Context Inspector</span>
+          </button>
+        </div>
+      </div>
+
+      {/* Sub-tab content */}
+      {subTab === "spans" ? (
+        <div className="flex-1 flex flex-col min-h-0">
+          {/* OTel Spans header - only show when we have data */}
+          {traceEvents.length > 0 && (
+            <div className="p-3 border-b flex-shrink-0">
              <div className="flex items-center gap-2">
-                <Search className="h-4 w-4 text-orange-500" />
-                <span className="font-semibold text-sm">Trace Details</span>
-              </div>
-              <div className="grid grid-cols-1 gap-2 text-xs">
-                <div>
-                  <span className="font-medium text-muted-foreground">
-                    Operation:
-                  </span>
-                  <span className="ml-2 font-mono bg-orange-100 dark:bg-orange-900 px-2 py-1 rounded">
-                    {operationName}
-                  </span>
-                </div>
-                {data.span_id && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Span ID:
-                    </span>
-                    <span className="ml-2 font-mono text-xs break-all">
-                      {data.span_id}
-                    </span>
-                  </div>
-                )}
-                {data.trace_id && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Trace ID:
-                    </span>
-                    <span className="ml-2 font-mono text-xs break-all">
-                      {data.trace_id}
-                    </span>
-                  </div>
-                )}
-                {data.parent_span_id && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Parent Span:
-                    </span>
-                    <span className="ml-2 font-mono text-xs break-all">
-                      {data.parent_span_id}
-                    </span>
-                  </div>
-                )}
-                {data.duration_ms && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Duration:
-                    </span>
-                    <span className="ml-2 font-mono text-xs">
-                      {Number(data.duration_ms).toFixed(2)}ms
-                    </span>
-                  </div>
-                )}
-                {data.status && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Status:
-                    </span>
-                    <span
-                      className={`ml-2 px-2 py-1 rounded text-xs font-medium ${data.status === "StatusCode.UNSET" ||
-                          data.status === "OK"
-                          ? "bg-green-100 dark:bg-green-900 text-green-800 dark:text-green-200"
-                          : "bg-red-100 dark:bg-red-900 text-red-800 dark:text-red-200"
-                        }`}
-                    >
-                      {data.status || "unknown"}
-                    </span>
-                  </div>
-                )}
-                {data.entity_id && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Entity:
-                    </span>
-                    <span className="ml-2 font-mono text-xs break-all">
-                      {data.entity_id}
-                    </span>
-                  </div>
-                )}
-                {data.attributes && Object.keys(data.attributes).length > 0 && (
-                  <div>
-                    <span className="font-medium text-muted-foreground">
-                      Attributes:
-                    </span>
-                    <div className="mt-1 max-h-32 overflow-auto">
-                      <pre className="text-xs bg-background border rounded p-2 whitespace-pre-wrap max-w-full break-all">
-                        {(() => {
-                          try {
-                            // Try to pretty-print JSON, and unescape string values that contain JSON
-                            const attrs = { ...data.attributes };
-                            Object.keys(attrs).forEach((key) => {
-                              if (
-                                typeof attrs[key] === "string" &&
-                                attrs[key].startsWith("[")
-                              ) {
-                                try {
-                                  attrs[key] = JSON.parse(attrs[key]);
-                                } catch {
-                                  // Keep original if parsing fails
-                                }
-                              }
-                            });
-                            return JSON.stringify(attrs, null, 2);
-                          } catch {
-                            return JSON.stringify(data.attributes, null, 2);
-                          }
-                        })()}
-                      </pre>
-                    </div>
-                  </div>
-                )}
+                <Search className="h-4 w-4" />
+                <span className="font-medium text-sm">OTel Spans</span>
+                <Badge variant="outline" className="text-xs">
+                  {traceGroups.length} turn{traceGroups.length !== 1 ? "s" : ""}
+                </Badge>
              </div>
            </div>
-          </div>
-        )}
-      </div>
+          )}
+
+          {traceEvents.length === 0 ? (
+            <div className="flex flex-col items-center text-center p-6 pt-9">
+              <BarChart3 className="h-8 w-8 text-muted-foreground mb-3" />
+              <div className="text-sm font-medium mb-1">No Data</div>
+              <div className="text-xs text-muted-foreground max-w-[200px]">
+                Run{" "}
+                <span className="font-mono bg-accent/10 px-1 rounded">
+                  devui --instrumentation
+                </span>{" "}
+                and start a conversation.
+              </div>
+            </div>
+          ) : (
+            <ScrollArea className="flex-1">
+              <div className="p-3">
+                <div className="space-y-3">
+                  {traceGroups.map((group) => (
+                    <TraceGroupItem key={group.response_id} group={group} />
+                  ))}
+                </div>
+              </div>
+            </ScrollArea>
+          )}
+        </div>
+      ) : (
+        <ContextInspector events={events} />
+      )}
    </div>
  );
 }
@@ -1590,19 +1751,48 @@ export function DebugPanel({
  isStreaming = false,
  onMinimize,
 }: DebugPanelProps) {
+  // Use persisted store state for active tab
+  const activeTab = useDevUIStore((state) => state.debugPanelTab);
+  const setActiveTab = useDevUIStore((state) => state.setDebugPanelTab);
+
+  // Compute counts once for tab badges (memoized to avoid perf hits)
+  const counts = useMemo(() => {
+    const processedEvents = processEventsForDisplay(events);
+    const eventsCount = processedEvents.length;
+    const tracesCount = events.filter(e => e.type === "response.trace.completed").length;
+    const toolsCount = processedEvents.filter(e => e.type === "response.function_call.complete").length
+      + events.filter(e => getFunctionResultFromEvent(e) !== null).length;
+    return { eventsCount, tracesCount, toolsCount };
+  }, [events]);
+
  return (
    <div className="flex-1 border-l flex flex-col min-h-0">
-      <Tabs defaultValue="events" className="flex-1 flex flex-col min-h-0">
+      <Tabs value={activeTab} onValueChange={(v) => setActiveTab(v as "events" | "traces" | "tools")} className="flex-1 flex flex-col min-h-0">
        <div className="px-3 pt-3 flex items-center gap-2 flex-shrink-0">
          <TabsList className="flex-1">
-            <TabsTrigger value="events" className="flex-1">
+            <TabsTrigger value="events" className="flex-1 gap-1.5">
              Events
+              {counts.eventsCount > 0 && (
+                <span className="text-[10px] bg-muted-foreground/20 text-muted-foreground px-1.5 py-0.5 rounded-full min-w-[1.25rem] text-center">
+                  {counts.eventsCount}
+                </span>
+              )}
            </TabsTrigger>
-            <TabsTrigger value="traces" className="flex-1">
+            <TabsTrigger value="traces" className="flex-1 gap-1.5">
              Traces
+              {counts.tracesCount > 0 && (
+                <span className="text-[10px] bg-muted-foreground/20 text-muted-foreground px-1.5 py-0.5 rounded-full min-w-[1.25rem] text-center">
+                  {counts.tracesCount}
+                </span>
+              )}
            </TabsTrigger>
-            <TabsTrigger value="tools" className="flex-1">
+            <TabsTrigger value="tools" className="flex-1 gap-1.5">
              Tools
+              {counts.toolsCount > 0 && (
+                <span className="text-[10px] bg-muted-foreground/20 text-muted-foreground px-1.5 py-0.5 rounded-full min-w-[1.25rem] text-center">
+                  {counts.toolsCount}
+                </span>
+              )}
            </TabsTrigger>
          </TabsList>
          {onMinimize && (
@@ -209,7 +209,7 @@ export function DeploymentModal({
        setCopiedTemplate(null);
        timeoutRef.current = null;
      }, 2000);
-    } catch (err) {
+    } catch {
      // Reset state on error - clipboard write failed
      setCopiedTemplate(null);
    }
@@ -248,7 +248,7 @@ services:
      - AZURE_OPENAI_API_KEY=\${AZURE_OPENAI_API_KEY}
      - AZURE_OPENAI_ENDPOINT=\${AZURE_OPENAI_ENDPOINT}
      - AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=\${AZURE_OPENAI_CHAT_DEPLOYMENT_NAME}
-      # Optional: Enable tracing
+      # Optional: Enable instrumentation
      - ENABLE_INSTRUMENTATION=\${ENABLE_INSTRUMENTATION:-false}
    ports:
      - "8080:8080"
@@ -41,8 +41,8 @@ export function SettingsModal({
 }: SettingsModalProps) {
  const [activeTab, setActiveTab] = useState<Tab>("general");

-  // OpenAI proxy mode, Azure deployment, auth status, server capabilities, and version from store
-  const { oaiMode, setOAIMode, azureDeploymentEnabled, setAzureDeploymentEnabled, authRequired, serverCapabilities, serverVersion, runtime, uiMode } = useDevUIStore();
+  // OpenAI proxy mode, Azure deployment, auth status, server capabilities, streaming, and version from store
+  const { oaiMode, setOAIMode, azureDeploymentEnabled, setAzureDeploymentEnabled, authRequired, serverCapabilities, serverVersion, runtime, uiMode, streamingEnabled, setStreamingEnabled } = useDevUIStore();

  // Get current backend URL from localStorage or default
  const defaultUrl = import.meta.env.VITE_API_BASE_URL !== undefined ? import.meta.env.VITE_API_BASE_URL : "";
@@ -353,6 +353,37 @@ export function SettingsModal({
                  />
                </div>
              </div>
+
+              {/* Streaming Mode Setting */}
+              <div className="space-y-3 border-t pt-6">
+                <div className="flex items-center justify-between">
+                  <div className="space-y-0.5">
+                    <Label className="text-sm font-medium">
+                      Streaming Mode
+                    </Label>
+                    <p className="text-xs text-muted-foreground">
+                      Stream responses token-by-token as they're generated
+                    </p>
+                  </div>
+                  <Switch
+                    checked={streamingEnabled}
+                    onCheckedChange={setStreamingEnabled}
+                  />
+                </div>
+                {!streamingEnabled && (
+                  <div className="flex items-start gap-2 text-xs text-amber-600 dark:text-amber-400 bg-amber-500/10 p-3 rounded">
+                    <Info className="h-3.5 w-3.5 flex-shrink-0 mt-0.5" />
+                    <div>
+                      <p className="font-medium">Non-streaming mode limitations:</p>
+                      <ul className="mt-1 space-y-0.5 list-disc list-inside text-amber-600/80 dark:text-amber-400/80">
+                        <li>Tool calls won't display in real-time</li>
+                        <li>No typing indicator during generation</li>
+                        <li>Response appears all at once when complete</li>
+                      </ul>
+                    </div>
+                  </div>
+                )}
+              </div>
            </div>
          )}

@@ -628,11 +659,11 @@ export function SettingsModal({
                <div className="space-y-2 pt-2">
                  <p className="text-xs font-medium text-muted-foreground uppercase tracking-wide">Capabilities</p>
                  <div className="space-y-1 text-sm">
-                    {serverCapabilities?.tracing !== undefined && (
+                    {serverCapabilities?.instrumentation !== undefined && (
                      <div className="flex justify-between items-center">
-                        <span className="text-muted-foreground">Tracing:</span>
-                        <span className={`text-xs px-2 py-0.5 rounded-full ${serverCapabilities.tracing ? 'bg-green-500/10 text-green-600 dark:text-green-400' : 'bg-muted text-muted-foreground'}`}>
-                          {serverCapabilities.tracing ? 'Enabled' : 'Disabled'}
+                        <span className="text-muted-foreground">Instrumentation:</span>
+                        <span className={`text-xs px-2 py-0.5 rounded-full ${serverCapabilities.instrumentation ? 'bg-green-500/10 text-green-600 dark:text-green-400' : 'bg-muted text-muted-foreground'}`}>
+                          {serverCapabilities.instrumentation ? 'Enabled' : 'Disabled'}
                        </span>
                      </div>
                    )}
@@ -0,0 +1,30 @@
+import * as React from "react";
+import * as TooltipPrimitive from "@radix-ui/react-tooltip";
+
+import { cn } from "@/lib/utils";
+
+const TooltipProvider = TooltipPrimitive.Provider;
+
+const Tooltip = TooltipPrimitive.Root;
+
+const TooltipTrigger = TooltipPrimitive.Trigger;
+
+const TooltipContent = React.forwardRef<
+  React.ElementRef<typeof TooltipPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof TooltipPrimitive.Content>
+>(({ className, sideOffset = 4, ...props }, ref) => (
+  <TooltipPrimitive.Portal>
+    <TooltipPrimitive.Content
+      ref={ref}
+      sideOffset={sideOffset}
+      className={cn(
+        "z-50 overflow-hidden rounded-md bg-primary px-3 py-1.5 text-xs text-primary-foreground animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2",
+        className
+      )}
+      {...props}
+    />
+  </TooltipPrimitive.Portal>
+));
+TooltipContent.displayName = TooltipPrimitive.Content.displayName;
+
+export { Tooltip, TooltipTrigger, TooltipContent, TooltipProvider };
@@ -398,7 +398,11 @@ class ApiClient {
  async listConversationItems(
    conversationId: string,
    options?: { limit?: number; after?: string; order?: "asc" | "desc" }
-  ): Promise<{ data: unknown[]; has_more: boolean }> {
+  ): Promise<{
+    data: unknown[];
+    has_more: boolean;
+    metadata?: { traces?: unknown[] };
+  }> {
    const params = new URLSearchParams();
    if (options?.limit) params.set("limit", options.limit.toString());
    if (options?.after) params.set("after", options.after);
@@ -409,7 +413,11 @@ class ApiClient {
      queryString ? `?${queryString}` : ""
    }`;

-    return this.request<{ data: unknown[]; has_more: boolean }>(url);
+    return this.request<{
+      data: unknown[];
+      has_more: boolean;
+      metadata?: { traces?: unknown[] };
+    }>(url);
  }

  async getConversationItem(
@@ -800,34 +808,68 @@ class ApiClient {
    yield* this.streamOpenAIResponse(openAIRequest, request.conversation_id, signal);
  }

-  // REMOVED: Legacy streaming methods - use streamAgentExecutionOpenAI and streamWorkflowExecutionOpenAI instead
+  // ========================================
+  // Non-Streaming Execution Methods
+  // ========================================

-  // Non-streaming execution (for testing)
-  async runAgent(
+  // Non-streaming agent execution using /v1/responses with stream=false
+  async runAgentSync(
    agentId: string,
    request: RunAgentRequest
-  ): Promise<{
-    conversation_id: string;
-    result: unknown[];
-    message_count: number;
-  }> {
-    return this.request(`/agents/${agentId}/run`, {
+  ): Promise<import("@/types/openai").OpenAIResponse> {
+    // Check if OAI proxy mode is enabled
+    const { oaiMode } = await import("@/stores").then((m) => ({
+      oaiMode: m.useDevUIStore.getState().oaiMode,
+    }));
+
+    const openAIRequest: AgentFrameworkRequest = {
+      metadata: { entity_id: agentId },
+      input: request.input,
+      stream: false,
+      conversation: request.conversation_id,
+    };
+
+    // Apply OAI mode settings if enabled
+    if (oaiMode.enabled) {
+      openAIRequest.model = oaiMode.model;
+      if (oaiMode.temperature !== undefined) {
+        openAIRequest.temperature = oaiMode.temperature;
+      }
+      if (oaiMode.max_output_tokens !== undefined) {
+        openAIRequest.max_output_tokens = oaiMode.max_output_tokens;
+      }
+    }
+
+    const headers: Record<string, string> = {};
+    if (oaiMode.enabled) {
+      headers["X-Proxy-Backend"] = "openai";
+    }
+
+    return this.request<import("@/types/openai").OpenAIResponse>("/v1/responses", {
      method: "POST",
-      body: JSON.stringify(request),
+      headers,
+      body: JSON.stringify(openAIRequest),
    });
  }

-  async runWorkflow(
+  // Non-streaming workflow execution using /v1/responses with stream=false
+  async runWorkflowSync(
    workflowId: string,
    request: RunWorkflowRequest
-  ): Promise<{
-    result: string;
-    events: number;
-    message_count: number;
-  }> {
-    return this.request(`/workflows/${workflowId}/run`, {
+  ): Promise<import("@/types/openai").OpenAIResponse> {
+    const openAIRequest: AgentFrameworkRequest = {
+      metadata: { entity_id: workflowId },
+      input: JSON.stringify(request.input_data || {}),
+      stream: false,
+      conversation: request.conversation_id,
+      extra_body: request.checkpoint_id
+        ? { entity_id: workflowId, checkpoint_id: request.checkpoint_id }
+        : undefined,
+    };
+
+    return this.request<import("@/types/openai").OpenAIResponse>("/v1/responses", {
      method: "POST",
-      body: JSON.stringify(request),
+      body: JSON.stringify(openAIRequest),
    });
  }

@@ -60,6 +60,13 @@ interface DevUIState {
  debugEvents: ExtendedResponseStreamEvent[];
  isResizing: boolean;
  showToolCalls: boolean; // UI setting to show/hide tool calls in chat
+  streamingEnabled: boolean; // Whether to use streaming mode for responses
+
+  // Debug Panel Preferences (persisted)
+  debugPanelTab: "events" | "traces" | "tools"; // Main debug panel tab
+  debugTraceSubTab: "spans" | "context"; // OTel Spans vs Context Inspector
+  contextInspectorViewMode: "tokens" | "composition";
+  contextInspectorCumulative: boolean;

  // Modal Slice
  showAboutModal: boolean;
@@ -82,7 +89,7 @@ interface DevUIState {
  uiMode: "developer" | "user";
  runtime: "python" | "dotnet";
  serverCapabilities: {
-    tracing: boolean;
+    instrumentation: boolean;
    openai_proxy: boolean;
    deployment: boolean;
  };
@@ -146,6 +153,13 @@ interface DevUIActions {
  clearDebugEvents: () => void;
  setIsResizing: (resizing: boolean) => void;
  setShowToolCalls: (show: boolean) => void;
+  setStreamingEnabled: (enabled: boolean) => void;
+
+  // Debug Panel Preference Actions
+  setDebugPanelTab: (tab: "events" | "traces" | "tools") => void;
+  setDebugTraceSubTab: (tab: "spans" | "context") => void;
+  setContextInspectorViewMode: (mode: "tokens" | "composition") => void;
+  setContextInspectorCumulative: (cumulative: boolean) => void;

  // Modal Actions
  setShowAboutModal: (show: boolean) => void;
@@ -166,7 +180,7 @@ interface DevUIActions {
  toggleOAIMode: () => void;

  // Server Meta Actions
-  setServerMeta: (meta: { uiMode: "developer" | "user"; runtime: "python" | "dotnet"; capabilities: { tracing: boolean; openai_proxy: boolean; deployment: boolean }; authRequired: boolean; version?: string }) => void;
+  setServerMeta: (meta: { uiMode: "developer" | "user"; runtime: "python" | "dotnet"; capabilities: { instrumentation: boolean; openai_proxy: boolean; deployment: boolean }; authRequired: boolean; version?: string }) => void;

  // Deployment Actions
  startDeployment: () => void;
@@ -228,6 +242,13 @@ export const useDevUIStore = create<DevUIStore>()(
        debugEvents: [],
        isResizing: false,
        showToolCalls: true, // Default to showing tool calls
+        streamingEnabled: true, // Default to streaming mode (recommended)
+
+        // Debug Panel Preferences (persisted)
+        debugPanelTab: "events", // Default to events tab
+        debugTraceSubTab: "spans", // Default to spans sub-tab
+        contextInspectorViewMode: "tokens", // Default to tokens view
+        contextInspectorCumulative: false, // Default to per-message view

        // Modal State
        showAboutModal: false,
@@ -248,7 +269,7 @@ export const useDevUIStore = create<DevUIStore>()(
        uiMode: "developer", // Default to developer mode
        runtime: "python", // Default to Python runtime
        serverCapabilities: {
-          tracing: false,
+          instrumentation: false,
          openai_proxy: false,
          deployment: false,
        },
@@ -371,14 +392,16 @@ export const useDevUIStore = create<DevUIStore>()(
        setDebugPanelMinimized: (minimized) => set({ debugPanelMinimized: minimized }),
        setDebugPanelWidth: (width) => set({ debugPanelWidth: width }),
        setShowToolCalls: (show) => set({ showToolCalls: show }),
+        setStreamingEnabled: (enabled) => set({ streamingEnabled: enabled }),
        addDebugEvent: (event) =>
          set((state) => {
            // Generate unique timestamp for each event
            // Use current time + small increment to ensure uniqueness even for rapid events
            const baseTimestamp = Math.floor(Date.now() / 1000);
-            const lastTimestamp = state.debugEvents.length > 0
-              ? (state.debugEvents[state.debugEvents.length - 1] as any)._uiTimestamp || 0
-              : 0;
+            const lastEvent = state.debugEvents.length > 0
+              ? state.debugEvents[state.debugEvents.length - 1] as { _uiTimestamp?: number }
+              : null;
+            const lastTimestamp = lastEvent?._uiTimestamp ?? 0;
            // Ensure new timestamp is always greater than the last one
            const uniqueTimestamp = Math.max(baseTimestamp, lastTimestamp + 1);

@@ -399,6 +422,12 @@ export const useDevUIStore = create<DevUIStore>()(
        clearDebugEvents: () => set({ debugEvents: [] }),
        setIsResizing: (resizing) => set({ isResizing: resizing }),

+        // Debug Panel Preference Actions
+        setDebugPanelTab: (tab) => set({ debugPanelTab: tab }),
+        setDebugTraceSubTab: (tab) => set({ debugTraceSubTab: tab }),
+        setContextInspectorViewMode: (mode) => set({ contextInspectorViewMode: mode }),
+        setContextInspectorCumulative: (cumulative) => set({ contextInspectorCumulative: cumulative }),
+
        // ========================================
        // Modal Actions
        // ========================================
@@ -605,8 +634,14 @@ export const useDevUIStore = create<DevUIStore>()(
          debugPanelMinimized: state.debugPanelMinimized,
          debugPanelWidth: state.debugPanelWidth,
          showToolCalls: state.showToolCalls, // Persist tool calls visibility preference
+          streamingEnabled: state.streamingEnabled, // Persist streaming mode preference
          oaiMode: state.oaiMode, // Persist OpenAI proxy mode settings
          azureDeploymentEnabled: state.azureDeploymentEnabled, // Persist Azure deployment preference
+          // Debug panel tab preferences
+          debugPanelTab: state.debugPanelTab,
+          debugTraceSubTab: state.debugTraceSubTab,
+          contextInspectorViewMode: state.contextInspectorViewMode,
+          contextInspectorCumulative: state.contextInspectorCumulative,
        }),
      }
    ),
@@ -130,6 +130,7 @@ export type {
  ResponseCompletedEvent,
  ResponseFailedEvent,
  ResponseFunctionResultComplete,
+  ResponseFunctionToolCall,
  StructuredEvent,
  WorkflowItem,
  ExecutorActionItem,
@@ -159,7 +160,7 @@ export interface MetaResponse {
  framework: string;
  runtime: "python" | "dotnet";
  capabilities: {
-    tracing: boolean;
+    instrumentation: boolean;
    openai_proxy: boolean;
    deployment: boolean;
  };
@@ -266,6 +267,29 @@ export interface CheckpointInfo {
  metadata?: Record<string, unknown>;
 }

+// Full checkpoint data structure
+export interface FullCheckpoint {
+  checkpoint_id: string;
+  workflow_id: string;
+  timestamp: string;
+  messages: Record<string, unknown[]>;
+  shared_state: Record<string, unknown>;
+  pending_request_info_events: Record<string, PendingRequestInfoEvent>;
+  iteration_count: number;
+  metadata: Record<string, unknown>;
+  version: string;
+}
+
+// Pending request info event data
+export interface PendingRequestInfoEvent {
+  source_executor_id: string;
+  request_type?: string;
+  response_type?: string;
+  request_data?: Record<string, unknown>;
+  request_schema?: Record<string, unknown>;
+  timestamp?: string;
+}
+
 // Checkpoint item from conversation items API
 export interface CheckpointItem {
  id: string;
@@ -281,16 +305,6 @@ export interface CheckpointItem {
    message_count: number;
    size_bytes?: number;
    version: string;
-    full_checkpoint?: {
-      checkpoint_id: string;
-      workflow_id: string;
-      timestamp: string;
-      messages: Record<string, unknown[]>;
-      shared_state: Record<string, unknown>;
-      pending_request_info_events: Record<string, unknown>;
-      iteration_count: number;
-      metadata: Record<string, unknown>;
-      version: string;
-    };
+    full_checkpoint?: FullCheckpoint;
  };
 }
@@ -3,6 +3,45 @@
 * Based on OpenAI's official response types
 */

+// OpenAI Response Error (from response_error.py)
+export type ResponseErrorCode =
+  | "server_error"
+  | "rate_limit_exceeded"
+  | "invalid_prompt"
+  | "vector_store_timeout"
+  | "invalid_image"
+  | "invalid_image_format"
+  | "invalid_base64_image"
+  | "invalid_image_url"
+  | "image_too_large"
+  | "image_too_small"
+  | "image_parse_error"
+  | "image_content_policy_violation"
+  | "invalid_image_mode"
+  | "image_file_too_large"
+  | "unsupported_image_media_type"
+  | "empty_image_file"
+  | "failed_to_download_image"
+  | "image_file_not_found";
+
+export interface ResponseError {
+  code: ResponseErrorCode;
+  message: string;
+}
+
+// OpenAI Response Usage (from response_usage.py)
+export interface ResponseUsage {
+  input_tokens: number;
+  output_tokens: number;
+  total_tokens: number;
+  input_tokens_details?: {
+    cached_tokens: number;
+  };
+  output_tokens_details?: {
+    reasoning_tokens: number;
+  };
+}
+
 // Core OpenAI Response Stream Event
 export interface ResponseStreamEvent {
  type: string;
@@ -28,7 +67,7 @@ export interface ResponseCreatedEvent {
    id: string;
    status: "in_progress";
    created_at: number;
-    output?: any[];
+    output?: ResponseOutputItem[];
  };
  sequence_number?: number;
 }
@@ -47,9 +86,11 @@ export interface ResponseCompletedEvent {
  response: {
    id: string;
    status?: "completed";
-    usage?: any;  // Optional usage information
+    usage?: ResponseUsage;  // Optional usage information
    model?: string;  // Optional model information
-    [key: string]: any; // Allow any additional fields
+    output?: ResponseOutputItem[];  // Output items
+    error?: ResponseError;  // Error if failed
+    metadata?: Record<string, unknown>;  // Additional metadata
  };
  sequence_number?: number;
 }
@@ -59,7 +100,7 @@ export interface ResponseFailedEvent {
  response: {
    id: string;
    status: "failed";
-    error?: any;
+    error?: ResponseError;
  };
  sequence_number?: number;
 }
@@ -157,16 +198,16 @@ export interface WorkflowItem {
  type: string;  // "executor_action", "workflow_action", "message", or any future type
  id: string;
  status?: "in_progress" | "completed" | "failed" | "cancelled";
-  [key: string]: any;  // Allow any additional fields
+  [key: string]: unknown;  // Allow any additional fields with unknown type
 }

 // Executor Action Item (DevUI specific)
 export interface ExecutorActionItem extends WorkflowItem {
  type: "executor_action";
  executor_id: string;
-  metadata?: Record<string, any>;
-  result?: any;
-  error?: any;
+  metadata?: Record<string, unknown>;
+  result?: unknown;
+  error?: unknown;
 }

 // Type guard for executor actions
@@ -364,18 +405,7 @@ export interface ResponseOutputText {
  annotations: Record<string, unknown>[];
 }

-export interface ResponseUsage {
-  input_tokens: number;
-  output_tokens: number;
-  total_tokens: number;
-  input_tokens_details: {
-    cached_tokens: number;
-  };
-  output_tokens_details: {
-    reasoning_tokens: number;
-  };
-}
-
+// Note: ResponseUsage is defined at the top of this file

 // Request format for Agent Framework
 // AgentFrameworkRequest moved to agent-framework.ts to avoid conflicts
@@ -404,11 +434,62 @@ export interface MessageInputTextContent {
  text: string;
 }

+// Annotation types for output text (from response_output_text.py)
+export interface AnnotationFileCitation {
+  type: "file_citation";
+  file_id: string;
+  filename: string;
+  index: number;
+}
+
+export interface AnnotationURLCitation {
+  type: "url_citation";
+  url: string;
+  title: string;
+  start_index: number;
+  end_index: number;
+}
+
+export interface AnnotationContainerFileCitation {
+  type: "container_file_citation";
+  container_id: string;
+  file_id: string;
+  filename: string;
+  start_index: number;
+  end_index: number;
+}
+
+export interface AnnotationFilePath {
+  type: "file_path";
+  file_id: string;
+  index: number;
+}
+
+export type OutputTextAnnotation =
+  | AnnotationFileCitation
+  | AnnotationURLCitation
+  | AnnotationContainerFileCitation
+  | AnnotationFilePath;
+
+// Logprob types for output text
+export interface LogprobTopLogprob {
+  token: string;
+  bytes: number[];
+  logprob: number;
+}
+
+export interface Logprob {
+  token: string;
+  bytes: number[];
+  logprob: number;
+  top_logprobs: LogprobTopLogprob[];
+}
+
 export interface MessageOutputTextContent {
  type: "output_text";
  text: string;
-  annotations?: any[];
-  logprobs?: any[];
+  annotations?: OutputTextAnnotation[];
+  logprobs?: Logprob[];
 }

 export interface MessageInputImage {
@@ -541,9 +622,218 @@ export interface Conversation {
  metadata?: Record<string, unknown>;
 }

-// List response
+// ============================================================================
+// OpenTelemetry Trace Attribute Keys
+// Mirrored from Python: agent_framework/observability.py ObservabilityAttributes
+// ============================================================================
+
+/**
+ * Standard attribute keys for OpenTelemetry traces.
+ * These match the Python ObservabilityAttributes enum exactly.
+ */
+export const TraceAttributes = {
+  // Request attributes
+  MODEL: "gen_ai.request.model",
+  MAX_TOKENS: "gen_ai.request.max_tokens",
+  TEMPERATURE: "gen_ai.request.temperature",
+  TOP_P: "gen_ai.request.top_p",
+  SEED: "gen_ai.request.seed",
+  FREQUENCY_PENALTY: "gen_ai.request.frequency_penalty",
+  PRESENCE_PENALTY: "gen_ai.request.presence_penalty",
+  STOP_SEQUENCES: "gen_ai.request.stop_sequences",
+
+  // Response attributes
+  FINISH_REASONS: "gen_ai.response.finish_reasons",
+  RESPONSE_ID: "gen_ai.response.id",
+
+  // Usage attributes
+  INPUT_TOKENS: "gen_ai.usage.input_tokens",
+  OUTPUT_TOKENS: "gen_ai.usage.output_tokens",
+
+  // Content attributes (messages sent/received)
+  INPUT_MESSAGES: "gen_ai.input.messages",
+  OUTPUT_MESSAGES: "gen_ai.output.messages",
+  SYSTEM_INSTRUCTIONS: "gen_ai.system_instructions",
+  OUTPUT_TYPE: "gen_ai.output.type",
+
+  // Tool attributes
+  TOOL_CALL_ID: "gen_ai.tool.call.id",
+  TOOL_NAME: "gen_ai.tool.name",
+  TOOL_TYPE: "gen_ai.tool.type",
+  TOOL_DEFINITIONS: "gen_ai.tool.definitions",
+  TOOL_ARGUMENTS: "gen_ai.tool.call.arguments",
+  TOOL_RESULT: "gen_ai.tool.call.result",
+
+  // Agent attributes
+  AGENT_ID: "gen_ai.agent.id",
+  AGENT_NAME: "gen_ai.agent.name",
+  AGENT_DESCRIPTION: "gen_ai.agent.description",
+  CONVERSATION_ID: "gen_ai.conversation.id",
+
+  // Workflow attributes
+  WORKFLOW_ID: "workflow.id",
+  WORKFLOW_NAME: "workflow.name",
+  EXECUTOR_ID: "executor.id",
+  EXECUTOR_TYPE: "executor.type",
+} as const;
+
+/**
+ * Type for trace attribute keys - ensures type safety when accessing attributes
+ */
+export type TraceAttributeKey = (typeof TraceAttributes)[keyof typeof TraceAttributes];
+
+/**
+ * Typed interface for known trace attributes.
+ * Using this instead of Record<string, unknown> provides compile-time safety.
+ */
+export interface TypedTraceAttributes {
+  // Request attributes
+  [TraceAttributes.MODEL]?: string;
+  [TraceAttributes.MAX_TOKENS]?: number;
+  [TraceAttributes.TEMPERATURE]?: number;
+  [TraceAttributes.TOP_P]?: number;
+  [TraceAttributes.SEED]?: number;
+
+  // Usage attributes
+  [TraceAttributes.INPUT_TOKENS]?: number;
+  [TraceAttributes.OUTPUT_TOKENS]?: number;
+
+  // Content attributes (JSON strings that need parsing)
+  [TraceAttributes.INPUT_MESSAGES]?: string;
+  [TraceAttributes.OUTPUT_MESSAGES]?: string;
+  [TraceAttributes.SYSTEM_INSTRUCTIONS]?: string;
+
+  // Tool attributes
+  [TraceAttributes.TOOL_NAME]?: string;
+  [TraceAttributes.TOOL_DEFINITIONS]?: string;
+  [TraceAttributes.TOOL_ARGUMENTS]?: string;
+  [TraceAttributes.TOOL_RESULT]?: string;
+
+  // Agent/workflow attributes
+  [TraceAttributes.AGENT_NAME]?: string;
+  [TraceAttributes.WORKFLOW_NAME]?: string;
+  [TraceAttributes.EXECUTOR_ID]?: string;
+
+  // Allow additional unknown attributes
+  [key: string]: unknown;
+}
+
+/**
+ * Message part types used in gen_ai.input.messages / gen_ai.output.messages
+ *
+ * Source: Python agent_framework/observability.py _to_otel_part()
+ *
+ * Python produces:
+ *   - text:               {"type": "text", "content": "..."}
+ *   - function_call:      {"type": "tool_call", "id": "...", "name": "...", "arguments": "..."}
+ *   - function_result:    {"type": "tool_call_response", "id": "...", "response": "..."}
+ */
+
+// Text content part
+// Python: {"type": "text", "content": content.text}
+export interface TraceTextPart {
+  type: "text";
+  content?: string; // Agent Framework format (from Python)
+  text?: string; // Alternative field name (OpenAI format)
+}
+
+// Tool/function call part (from assistant)
+// Python: {"type": "tool_call", "id": content.call_id, "name": content.name, "arguments": content.arguments}
+export interface TraceToolCallPart {
+  type: "tool_call" | "function_call";
+  id?: string; // Tool call ID for correlation
+  name?: string; // Function name
+  arguments?: string; // JSON string of arguments
+}
+
+// Tool/function result part (response to tool call)
+// Python: {"type": "tool_call_response", "id": content.call_id, "response": response}
+export interface TraceToolResultPart {
+  type: "tool_call_response" | "tool_result" | "function_result";
+  id?: string; // Tool call ID for correlation
+  response?: string; // Agent Framework format (from Python)
+  result?: string; // Alternative field name (other formats)
+}
+
+// Union type for all message parts
+export type TraceMessagePart = TraceTextPart | TraceToolCallPart | TraceToolResultPart;
+
+// Helper type guard functions
+export function isTextPart(part: TraceMessagePart): part is TraceTextPart {
+  return part.type === "text";
+}
+
+export function isToolCallPart(part: TraceMessagePart): part is TraceToolCallPart {
+  return part.type === "tool_call" || part.type === "function_call";
+}
+
+export function isToolResultPart(part: TraceMessagePart): part is TraceToolResultPart {
+  return (
+    part.type === "tool_result" ||
+    part.type === "function_result" ||
+    part.type === "tool_call_response"
+  );
+}
+
+/**
+ * Message structure in gen_ai.input.messages / gen_ai.output.messages
+ * Format: [{role: "system"|"user"|"assistant"|"tool", parts: [...]}]
+ */
+export interface TraceMessage {
+  role: "system" | "user" | "assistant" | "tool";
+  parts: TraceMessagePart[];
+}
+
+/**
+ * Helper to safely get a typed attribute value
+ */
+export function getTraceAttribute<K extends keyof TypedTraceAttributes>(
+  attributes: TypedTraceAttributes,
+  key: K
+): TypedTraceAttributes[K] {
+  return attributes[key];
+}
+
+/**
+ * Helper to parse JSON message array from trace attributes
+ */
+export function parseTraceMessages(jsonString: string | undefined): TraceMessage[] {
+  if (!jsonString) return [];
+  try {
+    return JSON.parse(jsonString) as TraceMessage[];
+  } catch {
+    return [];
+  }
+}
+
+// Stored trace span (from conversation metadata)
+export interface TraceSpan {
+  type?: string;
+  span_id: string;
+  trace_id: string;
+  parent_span_id?: string | null;
+  operation_name: string;
+  start_time: number;
+  end_time?: number;
+  duration_ms?: number;
+  attributes: TypedTraceAttributes;
+  status: string;
+  response_id?: string | null;
+  entity_id?: string;
+  events?: Array<{
+    name: string;
+    timestamp: number;
+    attributes?: Record<string, unknown>;
+  }>;
+  error?: string;
+}
+
+// List response with trace metadata (DevUI extension)
 export interface ConversationItemsListResponse {
  object: "list";
  data: ConversationItem[];
  has_more: boolean;
+  metadata?: {
+    traces?: TraceSpan[];
+  };
 }
@@ -99,54 +99,54 @@ export interface Workflow {
 * Type guards for runtime type checking
 */
 export function isWorkflow(obj: unknown): obj is Workflow {
+  if (typeof obj !== "object" || obj === null) return false;
+  const record = obj as Record<string, unknown>;
  return (
-    typeof obj === "object" &&
-    obj !== null &&
-    "id" in obj &&
-    "edge_groups" in obj &&
-    "executors" in obj &&
-    "start_executor_id" in obj &&
-    "max_iterations" in obj &&
-    typeof (obj as any).id === "string" &&
-    Array.isArray((obj as any).edge_groups) &&
-    typeof (obj as any).executors === "object" &&
-    typeof (obj as any).start_executor_id === "string" &&
-    typeof (obj as any).max_iterations === "number"
+    "id" in record &&
+    "edge_groups" in record &&
+    "executors" in record &&
+    "start_executor_id" in record &&
+    "max_iterations" in record &&
+    typeof record.id === "string" &&
+    Array.isArray(record.edge_groups) &&
+    typeof record.executors === "object" &&
+    typeof record.start_executor_id === "string" &&
+    typeof record.max_iterations === "number"
  );
 }

 export function isExecutor(obj: unknown): obj is Executor {
+  if (typeof obj !== "object" || obj === null) return false;
+  const record = obj as Record<string, unknown>;
  return (
-    typeof obj === "object" &&
-    obj !== null &&
-    "id" in obj &&
-    "type" in obj &&
-    typeof (obj as any).id === "string" &&
-    typeof (obj as any).type === "string"
+    "id" in record &&
+    "type" in record &&
+    typeof record.id === "string" &&
+    typeof record.type === "string"
  );
 }

 export function isEdge(obj: unknown): obj is Edge {
+  if (typeof obj !== "object" || obj === null) return false;
+  const record = obj as Record<string, unknown>;
  return (
-    typeof obj === "object" &&
-    obj !== null &&
-    "source_id" in obj &&
-    "target_id" in obj &&
-    typeof (obj as any).source_id === "string" &&
-    typeof (obj as any).target_id === "string"
+    "source_id" in record &&
+    "target_id" in record &&
+    typeof record.source_id === "string" &&
+    typeof record.target_id === "string"
  );
 }

 export function isEdgeGroup(obj: unknown): obj is EdgeGroup {
+  if (typeof obj !== "object" || obj === null) return false;
+  const record = obj as Record<string, unknown>;
  return (
-    typeof obj === "object" &&
-    obj !== null &&
-    "id" in obj &&
-    "type" in obj &&
-    "edges" in obj &&
-    typeof (obj as any).id === "string" &&
-    typeof (obj as any).type === "string" &&
-    Array.isArray((obj as any).edges)
+    "id" in record &&
+    "type" in record &&
+    "edges" in record &&
+    typeof record.id === "string" &&
+    typeof record.type === "string" &&
+    Array.isArray(record.edges)
  );
 }

@@ -7,6 +7,8 @@ import type {
 import type {
  ExtendedResponseStreamEvent,
  ResponseWorkflowEventComplete,
+  ResponseOutputItemAddedEvent,
+  ResponseOutputItemDoneEvent,
  JSONSchemaProperty,
 } from "@/types";
 import type { Workflow } from "@/types/workflow";
@@ -389,9 +391,10 @@ export function processWorkflowEvents(
  events.forEach((event) => {
    // Handle new standard OpenAI events
    if (event.type === "response.output_item.added" || event.type === "response.output_item.done") {
-      const item = (event as any).item;
-      if (item && item.type === "executor_action" && item.executor_id) {
-        const executorId = item.executor_id;
+      const outputEvent = event as ResponseOutputItemAddedEvent | ResponseOutputItemDoneEvent;
+      const item = outputEvent.item;
+      if (item && item.type === "executor_action" && "executor_id" in item) {
+        const executorId = item.executor_id as string;
        const itemId = item.id;

        // Track the latest item ID for this executor
@@ -492,16 +495,17 @@ export function processWorkflowEvents(
    // This prevents setting to "running" after the executor has already completed
    const hasCompletionEvent = events.some((event) => {
      if (event.type === "response.output_item.done") {
-        const item = (event as any).item;
-        return item && item.type === "executor_action" && item.executor_id === startExecutorId;
+        const outputEvent = event as ResponseOutputItemDoneEvent;
+        const item = outputEvent.item;
+        return item && item.type === "executor_action" && "executor_id" in item && item.executor_id === startExecutorId;
      }
      if (event.type === "response.workflow_event.completed" && "data" in event && event.data) {
-        const data = event.data as any;
+        const data = event.data as Record<string, unknown>;
        return data.executor_id === startExecutorId &&
               (data.event_type === "ExecutorCompletedEvent" ||
                data.event_type === "ExecutorFailedEvent" ||
-                data.event_type?.includes("Error") ||
-                data.event_type?.includes("Failed"));
+                (typeof data.event_type === "string" && data.event_type.includes("Error")) ||
+                (typeof data.event_type === "string" && data.event_type.includes("Failed")));
      }
      return false;
    });
@@ -565,9 +569,10 @@ export function getCurrentlyExecutingExecutors(
  events.forEach((event) => {
    // Handle new standard OpenAI events
    if (event.type === "response.output_item.added" || event.type === "response.output_item.done") {
-      const item = (event as any).item;
-      if (item && item.type === "executor_action" && item.executor_id) {
-        const executorId = item.executor_id;
+      const outputEvent = event as ResponseOutputItemAddedEvent | ResponseOutputItemDoneEvent;
+      const item = outputEvent.item;
+      if (item && item.type === "executor_action" && "executor_id" in item) {
+        const executorId = item.executor_id as string;

        executorTimeline[executorId] = {
          lastEvent: event.type === "response.output_item.added" ? "ExecutorInvokedEvent" : "ExecutorCompletedEvent",
@@ -24,7 +24,7 @@
  resolved "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.28.0.tgz"
  integrity sha512-60X7qkglvrap8mn1lh2ebxXdZYtUcpd7gsmy9kLaBJ4i/WdY8PqTSdxyA8qraikqKQK5C1KRBKXqznrVapyNaw==

-"@babel/core@^7.28.3":
+"@babel/core@^7.0.0", "@babel/core@^7.0.0-0", "@babel/core@^7.28.3":
  version "7.28.3"
  resolved "https://registry.npmjs.org/@babel/core/-/core-7.28.3.tgz"
  integrity sha512-yDBHV9kQNcr2/sUr9jghVyz9C3Y5G2zUM2H2lo+9mKv4sFgbA8s8Z9t8D1jiTkGoO/NoIfKMyKWr4s6CN23ZwQ==
@@ -168,158 +168,11 @@
    "@babel/helper-string-parser" "^7.27.1"
    "@babel/helper-validator-identifier" "^7.27.1"

-"@emnapi/core@^1.4.3", "@emnapi/core@^1.4.5":
-  version "1.7.1"
-  resolved "https://registry.yarnpkg.com/@emnapi/core/-/core-1.7.1.tgz#3a79a02dbc84f45884a1806ebb98e5746bdfaac4"
-  integrity sha512-o1uhUASyo921r2XtHYOHy7gdkGLge8ghBEQHMWmyJFoXlpU58kIrhhN3w26lpQb6dspetweapMn2CSNwQ8I4wg==
-  dependencies:
-    "@emnapi/wasi-threads" "1.1.0"
-    tslib "^2.4.0"
-
-"@emnapi/runtime@^1.4.3", "@emnapi/runtime@^1.4.5":
-  version "1.7.1"
-  resolved "https://registry.yarnpkg.com/@emnapi/runtime/-/runtime-1.7.1.tgz#a73784e23f5d57287369c808197288b52276b791"
-  integrity sha512-PVtJr5CmLwYAU9PZDMITZoR5iAOShYREoR45EyyLrbntV50mdePTgUn4AmOw90Ifcj+x2kRjdzr1HP3RrNiHGA==
-  dependencies:
-    tslib "^2.4.0"
-
-"@emnapi/wasi-threads@1.1.0", "@emnapi/wasi-threads@^1.0.4":
-  version "1.1.0"
-  resolved "https://registry.yarnpkg.com/@emnapi/wasi-threads/-/wasi-threads-1.1.0.tgz#60b2102fddc9ccb78607e4a3cf8403ea69be41bf"
-  integrity sha512-WI0DdZ8xFSbgMjR1sFsKABJ/C5OnRrjT06JXbZKexJGrDuPTzZdDYfFlsgcCXCyf+suG5QU2e/y1Wo2V/OapLQ==
-  dependencies:
-    tslib "^2.4.0"
-
-"@esbuild/aix-ppc64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/aix-ppc64/-/aix-ppc64-0.25.9.tgz#bef96351f16520055c947aba28802eede3c9e9a9"
-  integrity sha512-OaGtL73Jck6pBKjNIe24BnFE6agGl+6KxDtTfHhy1HmhthfKouEcOhqpSL64K4/0WCtbKFLOdzD/44cJ4k9opA==
-
-"@esbuild/android-arm64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/android-arm64/-/android-arm64-0.25.9.tgz#d2e70be7d51a529425422091e0dcb90374c1546c"
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-
-"@esbuild/android-arm@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/android-arm/-/android-arm-0.25.9.tgz#d2a753fe2a4c73b79437d0ba1480e2d760097419"
-  integrity sha512-5WNI1DaMtxQ7t7B6xa572XMXpHAaI/9Hnhk8lcxF4zVN4xstUgTlvuGDorBguKEnZO70qwEcLpfifMLoxiPqHQ==
-
-"@esbuild/android-x64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/android-x64/-/android-x64-0.25.9.tgz#5278836e3c7ae75761626962f902a0d55352e683"
-  integrity sha512-I853iMZ1hWZdNllhVZKm34f4wErd4lMyeV7BLzEExGEIZYsOzqDWDf+y082izYUE8gtJnYHdeDpN/6tUdwvfiw==
-
 "@esbuild/darwin-arm64@0.25.9":
  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/darwin-arm64/-/darwin-arm64-0.25.9.tgz#f1513eaf9ec8fa15dcaf4c341b0f005d3e8b47ae"
+  resolved "https://registry.npmjs.org/@esbuild/darwin-arm64/-/darwin-arm64-0.25.9.tgz"
  integrity sha512-XIpIDMAjOELi/9PB30vEbVMs3GV1v2zkkPnuyRRURbhqjyzIINwj+nbQATh4H9GxUgH1kFsEyQMxwiLFKUS6Rg==

-"@esbuild/darwin-x64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/darwin-x64/-/darwin-x64-0.25.9.tgz#e27dbc3b507b3a1cea3b9280a04b8b6b725f82be"
-  integrity sha512-jhHfBzjYTA1IQu8VyrjCX4ApJDnH+ez+IYVEoJHeqJm9VhG9Dh2BYaJritkYK3vMaXrf7Ogr/0MQ8/MeIefsPQ==
-
-"@esbuild/freebsd-arm64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/freebsd-arm64/-/freebsd-arm64-0.25.9.tgz#364e3e5b7a1fd45d92be08c6cc5d890ca75908ca"
-  integrity sha512-z93DmbnY6fX9+KdD4Ue/H6sYs+bhFQJNCPZsi4XWJoYblUqT06MQUdBCpcSfuiN72AbqeBFu5LVQTjfXDE2A6Q==
-
-"@esbuild/freebsd-x64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/freebsd-x64/-/freebsd-x64-0.25.9.tgz#7c869b45faeb3df668e19ace07335a0711ec56ab"
-  integrity sha512-mrKX6H/vOyo5v71YfXWJxLVxgy1kyt1MQaD8wZJgJfG4gq4DpQGpgTB74e5yBeQdyMTbgxp0YtNj7NuHN0PoZg==
-
-"@esbuild/linux-arm64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-arm64/-/linux-arm64-0.25.9.tgz#48d42861758c940b61abea43ba9a29b186d6cb8b"
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-"@esbuild/linux-arm@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-arm/-/linux-arm-0.25.9.tgz#6ce4b9cabf148274101701d112b89dc67cc52f37"
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-"@esbuild/linux-ia32@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-ia32/-/linux-ia32-0.25.9.tgz#207e54899b79cac9c26c323fc1caa32e3143f1c4"
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-
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-loong64/-/linux-loong64-0.25.9.tgz#0ba48a127159a8f6abb5827f21198b999ffd1fc0"
-  integrity sha512-Sbe10Bnn0oUAB2AalYztvGcK+o6YFFA/9829PhOCUS9vkJElXGdphz0A3DbMdP8gmKkqPmPcMJmJOrI3VYB1JQ==
-
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-mips64el/-/linux-mips64el-0.25.9.tgz#a4d4cc693d185f66a6afde94f772b38ce5d64eb5"
-  integrity sha512-YcM5br0mVyZw2jcQeLIkhWtKPeVfAerES5PvOzaDxVtIyZ2NUBZKNLjC5z3/fUlDgT6w89VsxP2qzNipOaaDyA==
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-ppc64/-/linux-ppc64-0.25.9.tgz#0f5805c1c6d6435a1dafdc043cb07a19050357db"
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-
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-riscv64/-/linux-riscv64-0.25.9.tgz#6776edece0f8fca79f3386398b5183ff2a827547"
-  integrity sha512-uNIBa279Y3fkjV+2cUjx36xkx7eSjb8IvnL01eXUKXez/CBHNRw5ekCGMPM0BcmqBxBcdgUWuUXmVWwm4CH9kg==
-
-"@esbuild/linux-s390x@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-s390x/-/linux-s390x-0.25.9.tgz#3f6f29ef036938447c2218d309dc875225861830"
-  integrity sha512-Mfiphvp3MjC/lctb+7D287Xw1DGzqJPb/J2aHHcHxflUo+8tmN/6d4k6I2yFR7BVo5/g7x2Monq4+Yew0EHRIA==
-
-"@esbuild/linux-x64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/linux-x64/-/linux-x64-0.25.9.tgz#831fe0b0e1a80a8b8391224ea2377d5520e1527f"
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-
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/netbsd-arm64/-/netbsd-arm64-0.25.9.tgz#06f99d7eebe035fbbe43de01c9d7e98d2a0aa548"
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-
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/netbsd-x64/-/netbsd-x64-0.25.9.tgz#db99858e6bed6e73911f92a88e4edd3a8c429a52"
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-
-"@esbuild/openbsd-arm64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/openbsd-arm64/-/openbsd-arm64-0.25.9.tgz#afb886c867e36f9d86bb21e878e1185f5d5a0935"
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-
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-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/openbsd-x64/-/openbsd-x64-0.25.9.tgz#30855c9f8381fac6a0ef5b5f31ac6e7108a66ecf"
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-
-"@esbuild/openharmony-arm64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/openharmony-arm64/-/openharmony-arm64-0.25.9.tgz#2f2144af31e67adc2a8e3705c20c2bd97bd88314"
-  integrity sha512-4Xd0xNiMVXKh6Fa7HEJQbrpP3m3DDn43jKxMjxLLRjWnRsfxjORYJlXPO4JNcXtOyfajXorRKY9NkOpTHptErg==
-
-"@esbuild/sunos-x64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/sunos-x64/-/sunos-x64-0.25.9.tgz#69b99a9b5bd226c9eb9c6a73f990fddd497d732e"
-  integrity sha512-WjH4s6hzo00nNezhp3wFIAfmGZ8U7KtrJNlFMRKxiI9mxEK1scOMAaa9i4crUtu+tBr+0IN6JCuAcSBJZfnphw==
-
-"@esbuild/win32-arm64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/win32-arm64/-/win32-arm64-0.25.9.tgz#d789330a712af916c88325f4ffe465f885719c6b"
-  integrity sha512-mGFrVJHmZiRqmP8xFOc6b84/7xa5y5YvR1x8djzXpJBSv/UsNK6aqec+6JDjConTgvvQefdGhFDAs2DLAds6gQ==
-
-"@esbuild/win32-ia32@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.yarnpkg.com/@esbuild/win32-ia32/-/win32-ia32-0.25.9.tgz#52fc735406bd49688253e74e4e837ac2ba0789e3"
-  integrity sha512-b33gLVU2k11nVx1OhX3C8QQP6UHQK4ZtN56oFWvVXvz2VkDoe6fbG8TOgHFxEvqeqohmRnIHe5A1+HADk4OQww==
-
-"@esbuild/win32-x64@0.25.9":
-  version "0.25.9"
-  resolved "https://registry.npmjs.org/@esbuild/win32-x64/-/win32-x64-0.25.9.tgz"
-  integrity sha512-PPOl1mi6lpLNQxnGoyAfschAodRFYXJ+9fs6WHXz7CSWKbOqiMZsubC+BQsVKuul+3vKLuwTHsS2c2y9EoKwxQ==
-
 "@eslint-community/eslint-utils@^4.2.0", "@eslint-community/eslint-utils@^4.7.0":
  version "4.7.0"
  resolved "https://registry.npmjs.org/@eslint-community/eslint-utils/-/eslint-utils-4.7.0.tgz"
@@ -368,7 +221,7 @@
    minimatch "^3.1.2"
    strip-json-comments "^3.1.1"

-"@eslint/js@9.33.0", "@eslint/js@^9.33.0":
+"@eslint/js@^9.33.0", "@eslint/js@9.33.0":
  version "9.33.0"
  resolved "https://registry.npmjs.org/@eslint/js/-/js-9.33.0.tgz"
  integrity sha512-5K1/mKhWaMfreBGJTwval43JJmkip0RmM+3+IuqupeSKNC/Th2Kc7ucaq5ovTSra/OOKB9c58CGSz3QMVbWt0A==
@@ -482,15 +335,6 @@
    "@jridgewell/resolve-uri" "^3.1.0"
    "@jridgewell/sourcemap-codec" "^1.4.14"

-"@napi-rs/wasm-runtime@^0.2.12":
-  version "0.2.12"
-  resolved "https://registry.yarnpkg.com/@napi-rs/wasm-runtime/-/wasm-runtime-0.2.12.tgz#3e78a8b96e6c33a6c517e1894efbd5385a7cb6f2"
-  integrity sha512-ZVWUcfwY4E/yPitQJl481FjFo3K22D6qF0DuFH6Y/nbnE11GY5uguDxZMGXPQ8WQ0128MXQD7TnfHyK4oWoIJQ==
-  dependencies:
-    "@emnapi/core" "^1.4.3"
-    "@emnapi/runtime" "^1.4.3"
-    "@tybys/wasm-util" "^0.10.0"
-
 "@nodelib/fs.scandir@2.1.5":
  version "2.1.5"
  resolved "https://registry.npmjs.org/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz"
@@ -499,7 +343,7 @@
    "@nodelib/fs.stat" "2.0.5"
    run-parallel "^1.1.9"

-"@nodelib/fs.stat@2.0.5", "@nodelib/fs.stat@^2.0.2":
+"@nodelib/fs.stat@^2.0.2", "@nodelib/fs.stat@2.0.5":
  version "2.0.5"
  resolved "https://registry.npmjs.org/@nodelib/fs.stat/-/fs.stat-2.0.5.tgz"
  integrity sha512-RkhPPp2zrqDAQA/2jNhnztcPAlv64XdhIp7a7454A5ovI7Bukxgt7MX7udwAu3zg1DcpPU0rz3VV1SeaqvY4+A==
@@ -742,12 +586,12 @@

 "@radix-ui/react-separator@^1.1.7":
  version "1.1.7"
-  resolved "https://registry.yarnpkg.com/@radix-ui/react-separator/-/react-separator-1.1.7.tgz#a18bd7fd07c10fda1bba14f2a3032e7b1a2b3470"
+  resolved "https://registry.npmjs.org/@radix-ui/react-separator/-/react-separator-1.1.7.tgz"
  integrity sha512-0HEb8R9E8A+jZjvmFCy/J4xhbXy3TV+9XSnGJ3KvTtjlIUy/YQ/p6UYZvi7YbeoeXdyU9+Y3scizK6hkY37baA==
  dependencies:
    "@radix-ui/react-primitive" "2.1.3"

-"@radix-ui/react-slot@1.2.3", "@radix-ui/react-slot@^1.2.3":
+"@radix-ui/react-slot@^1.2.3", "@radix-ui/react-slot@1.2.3":
  version "1.2.3"
  resolved "https://registry.npmjs.org/@radix-ui/react-slot/-/react-slot-1.2.3.tgz"
  integrity sha512-aeNmHnBxbi2St0au6VBVC7JXFlhLlOnvIIlePNniyUNAClzmtAUEY8/pBiK3iHjufOlwA+c20/8jngo7xcrg8A==
@@ -756,7 +600,7 @@

 "@radix-ui/react-switch@^1.2.6":
  version "1.2.6"
-  resolved "https://registry.yarnpkg.com/@radix-ui/react-switch/-/react-switch-1.2.6.tgz#ff79acb831f0d5ea9216cfcc5b939912571358e3"
+  resolved "https://registry.npmjs.org/@radix-ui/react-switch/-/react-switch-1.2.6.tgz"
  integrity sha512-bByzr1+ep1zk4VubeEVViV592vu2lHE2BZY5OnzehZqOOgogN80+mNtCqPkhn2gklJqOpxWgPoYTSnhBCqpOXQ==
  dependencies:
    "@radix-ui/primitive" "1.1.3"
@@ -781,6 +625,24 @@
    "@radix-ui/react-roving-focus" "1.1.11"
    "@radix-ui/react-use-controllable-state" "1.2.2"

+"@radix-ui/react-tooltip@^1.2.8":
+  version "1.2.8"
+  resolved "https://registry.npmjs.org/@radix-ui/react-tooltip/-/react-tooltip-1.2.8.tgz"
+  integrity sha512-tY7sVt1yL9ozIxvmbtN5qtmH2krXcBCfjEiCgKGLqunJHvgvZG2Pcl2oQ3kbcZARb1BGEHdkLzcYGO8ynVlieg==
+  dependencies:
+    "@radix-ui/primitive" "1.1.3"
+    "@radix-ui/react-compose-refs" "1.1.2"
+    "@radix-ui/react-context" "1.1.2"
+    "@radix-ui/react-dismissable-layer" "1.1.11"
+    "@radix-ui/react-id" "1.1.1"
+    "@radix-ui/react-popper" "1.2.8"
+    "@radix-ui/react-portal" "1.1.9"
+    "@radix-ui/react-presence" "1.1.5"
+    "@radix-ui/react-primitive" "2.1.3"
+    "@radix-ui/react-slot" "1.2.3"
+    "@radix-ui/react-use-controllable-state" "1.2.2"
+    "@radix-ui/react-visually-hidden" "1.2.3"
+
 "@radix-ui/react-use-callback-ref@1.1.1":
  version "1.1.1"
  resolved "https://registry.npmjs.org/@radix-ui/react-use-callback-ref/-/react-use-callback-ref-1.1.1.tgz"
@@ -849,106 +711,11 @@
  resolved "https://registry.npmjs.org/@rolldown/pluginutils/-/pluginutils-1.0.0-beta.32.tgz"
  integrity sha512-QReCdvxiUZAPkvp1xpAg62IeNzykOFA6syH2CnClif4YmALN1XKpB39XneL80008UbtMShthSVDKmrx05N1q/g==

-"@rollup/rollup-android-arm-eabi@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-android-arm-eabi/-/rollup-android-arm-eabi-4.47.1.tgz#6e236cd2fd29bb01a300ad4ff6ed0f1a17550e69"
-  integrity sha512-lTahKRJip0knffA/GTNFJMrToD+CM+JJ+Qt5kjzBK/sFQ0EWqfKW3AYQSlZXN98tX0lx66083U9JYIMioMMK7g==
-
-"@rollup/rollup-android-arm64@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-android-arm64/-/rollup-android-arm64-4.47.1.tgz#808f2c9c7e68161add613ebcb0eac5a058a0df3c"
-  integrity sha512-uqxkb3RJLzlBbh/bbNQ4r7YpSZnjgMgyoEOY7Fy6GCbelkDSAzeiogxMG9TfLsBbqmGsdDObo3mzGqa8hps4MA==
-
 "@rollup/rollup-darwin-arm64@4.47.1":
  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-darwin-arm64/-/rollup-darwin-arm64-4.47.1.tgz#fa41e413c8e73d61039d6375b234595f24b1e5e3"
+  resolved "https://registry.npmjs.org/@rollup/rollup-darwin-arm64/-/rollup-darwin-arm64-4.47.1.tgz"
  integrity sha512-tV6reObmxBDS4DDyLzTDIpymthNlxrLBGAoQx6m2a7eifSNEZdkXQl1PE4ZjCkEDPVgNXSzND/k9AQ3mC4IOEQ==

-"@rollup/rollup-darwin-x64@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-darwin-x64/-/rollup-darwin-x64-4.47.1.tgz#9aac64e886435493f2e3a0aa5e4aad098a90814c"
-  integrity sha512-XuJRPTnMk1lwsSnS3vYyVMu4x/+WIw1MMSiqj5C4j3QOWsMzbJEK90zG+SWV1h0B1ABGCQ0UZUjti+TQK35uHQ==
-
-"@rollup/rollup-freebsd-arm64@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-freebsd-arm64/-/rollup-freebsd-arm64-4.47.1.tgz#9fc804264f7b7a7cdad3747950299f990163be1f"
-  integrity sha512-79BAm8Ag/tmJ5asCqgOXsb3WY28Rdd5Lxj8ONiQzWzy9LvWORd5qVuOnjlqiWWZJw+dWewEktZb5yiM1DLLaHw==
-
-"@rollup/rollup-freebsd-x64@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-freebsd-x64/-/rollup-freebsd-x64-4.47.1.tgz#933feaff864feb03bbbcd0c18ea351ade957cf79"
-  integrity sha512-OQ2/ZDGzdOOlyfqBiip0ZX/jVFekzYrGtUsqAfLDbWy0jh1PUU18+jYp8UMpqhly5ltEqotc2miLngf9FPSWIA==
-
-"@rollup/rollup-linux-arm-gnueabihf@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm-gnueabihf/-/rollup-linux-arm-gnueabihf-4.47.1.tgz#02915e6b2c55fe5961c27404aba2d9c8ef48ac6c"
-  integrity sha512-HZZBXJL1udxlCVvoVadstgiU26seKkHbbAMLg7680gAcMnRNP9SAwTMVet02ANA94kXEI2VhBnXs4e5nf7KG2A==
-
-"@rollup/rollup-linux-arm-musleabihf@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm-musleabihf/-/rollup-linux-arm-musleabihf-4.47.1.tgz#1afef33191b26e76ae7f0d0dc767efc6be1285ce"
-  integrity sha512-sZ5p2I9UA7T950JmuZ3pgdKA6+RTBr+0FpK427ExW0t7n+QwYOcmDTK/aRlzoBrWyTpJNlS3kacgSlSTUg6P/Q==
-
-"@rollup/rollup-linux-arm64-gnu@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm64-gnu/-/rollup-linux-arm64-gnu-4.47.1.tgz#6e7f38fb99d14143de3ce33204e6cd61e1c2c780"
-  integrity sha512-3hBFoqPyU89Dyf1mQRXCdpc6qC6At3LV6jbbIOZd72jcx7xNk3aAp+EjzAtN6sDlmHFzsDJN5yeUySvorWeRXA==
-
-"@rollup/rollup-linux-arm64-musl@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm64-musl/-/rollup-linux-arm64-musl-4.47.1.tgz#25ab09f14bbcba85a604bcee2962d2486db90794"
-  integrity sha512-49J4FnMHfGodJWPw73Ve+/hsPjZgcXQGkmqBGZFvltzBKRS+cvMiWNLadOMXKGnYRhs1ToTGM0sItKISoSGUNA==
-
-"@rollup/rollup-linux-loongarch64-gnu@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-loongarch64-gnu/-/rollup-linux-loongarch64-gnu-4.47.1.tgz#d3e3a3fd61e21b2753094391dee9b515a2bc9ecd"
-  integrity sha512-4yYU8p7AneEpQkRX03pbpLmE21z5JNys16F1BZBZg5fP9rIlb0TkeQjn5du5w4agConCCEoYIG57sNxjryHEGg==
-
-"@rollup/rollup-linux-ppc64-gnu@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-ppc64-gnu/-/rollup-linux-ppc64-gnu-4.47.1.tgz#6b44445e2bd5866692010de241bf18d2ae8b0cb8"
-  integrity sha512-fAiq+J28l2YMWgC39jz/zPi2jqc0y3GSRo1yyxlBHt6UN0yYgnegHSRPa3pnHS5amT/efXQrm0ug5+aNEu9UuQ==
-
-"@rollup/rollup-linux-riscv64-gnu@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-riscv64-gnu/-/rollup-linux-riscv64-gnu-4.47.1.tgz#3ff412d20d3b157e6aadabf84788e8c5cb221ba7"
-  integrity sha512-daoT0PMENNdjVYYU9xec30Y2prb1AbEIbb64sqkcQcSaR0zYuKkoPuhIztfxuqN82KYCKKrj+tQe4Gi7OSm1ow==
-
-"@rollup/rollup-linux-riscv64-musl@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-riscv64-musl/-/rollup-linux-riscv64-musl-4.47.1.tgz#104f451497d53d82a49c6d08c13c59f5f30eed57"
-  integrity sha512-JNyXaAhWtdzfXu5pUcHAuNwGQKevR+6z/poYQKVW+pLaYOj9G1meYc57/1Xv2u4uTxfu9qEWmNTjv/H/EpAisw==
-
-"@rollup/rollup-linux-s390x-gnu@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-s390x-gnu/-/rollup-linux-s390x-gnu-4.47.1.tgz#d04de7b21d181f30750760cb3553946306506172"
-  integrity sha512-U/CHbqKSwEQyZXjCpY43/GLYcTVKEXeRHw0rMBJP7fP3x6WpYG4LTJWR3ic6TeYKX6ZK7mrhltP4ppolyVhLVQ==
-
-"@rollup/rollup-linux-x64-gnu@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-x64-gnu/-/rollup-linux-x64-gnu-4.47.1.tgz#a6ba88ff7480940a435b1e67ddbb3f207a7ae02f"
-  integrity sha512-uTLEakjxOTElfeZIGWkC34u2auLHB1AYS6wBjPGI00bWdxdLcCzK5awjs25YXpqB9lS8S0vbO0t9ZcBeNibA7g==
-
-"@rollup/rollup-linux-x64-musl@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-x64-musl/-/rollup-linux-x64-musl-4.47.1.tgz#c912c8ffa0c242ed3175cd91cdeaef98109afa54"
-  integrity sha512-Ft+d/9DXs30BK7CHCTX11FtQGHUdpNDLJW0HHLign4lgMgBcPFN3NkdIXhC5r9iwsMwYreBBc4Rho5ieOmKNVQ==
-
-"@rollup/rollup-win32-arm64-msvc@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-win32-arm64-msvc/-/rollup-win32-arm64-msvc-4.47.1.tgz#ca5eaae89443554b461bb359112a056528cfdac0"
-  integrity sha512-N9X5WqGYzZnjGAFsKSfYFtAShYjwOmFJoWbLg3dYixZOZqU7hdMq+/xyS14zKLhFhZDhP9VfkzQnsdk0ZDS9IA==
-
-"@rollup/rollup-win32-ia32-msvc@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.yarnpkg.com/@rollup/rollup-win32-ia32-msvc/-/rollup-win32-ia32-msvc-4.47.1.tgz#34e76172515fb4b374eb990d59f54faff938246e"
-  integrity sha512-O+KcfeCORZADEY8oQJk4HK8wtEOCRE4MdOkb8qGZQNun3jzmj2nmhV/B/ZaaZOkPmJyvm/gW9n0gsB4eRa1eiQ==
-
-"@rollup/rollup-win32-x64-msvc@4.47.1":
-  version "4.47.1"
-  resolved "https://registry.npmjs.org/@rollup/rollup-win32-x64-msvc/-/rollup-win32-x64-msvc-4.47.1.tgz"
-  integrity sha512-CpKnYa8eHthJa3c+C38v/E+/KZyF1Jdh2Cz3DyKZqEWYgrM1IHFArXNWvBLPQCKUEsAqqKX27tTqVEFbDNUcOA==
-
 "@tailwindcss/node@4.1.12":
  version "4.1.12"
  resolved "https://registry.npmjs.org/@tailwindcss/node/-/node-4.1.12.tgz"
@@ -962,73 +729,11 @@
    source-map-js "^1.2.1"
    tailwindcss "4.1.12"

-"@tailwindcss/oxide-android-arm64@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-android-arm64/-/oxide-android-arm64-4.1.12.tgz#27920fe61fa2743afe8a8ca296fa640b609d17d5"
-  integrity sha512-oNY5pq+1gc4T6QVTsZKwZaGpBb2N1H1fsc1GD4o7yinFySqIuRZ2E4NvGasWc6PhYJwGK2+5YT1f9Tp80zUQZQ==
-
 "@tailwindcss/oxide-darwin-arm64@4.1.12":
  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-darwin-arm64/-/oxide-darwin-arm64-4.1.12.tgz#e8bd4798f26ec1d012bf0683aeb77449f71505cd"
+  resolved "https://registry.npmjs.org/@tailwindcss/oxide-darwin-arm64/-/oxide-darwin-arm64-4.1.12.tgz"
  integrity sha512-cq1qmq2HEtDV9HvZlTtrj671mCdGB93bVY6J29mwCyaMYCP/JaUBXxrQQQm7Qn33AXXASPUb2HFZlWiiHWFytw==

-"@tailwindcss/oxide-darwin-x64@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-darwin-x64/-/oxide-darwin-x64-4.1.12.tgz#8ddb7e5ddfd9b049ec84a2bda99f2b04a86859f5"
-  integrity sha512-6UCsIeFUcBfpangqlXay9Ffty9XhFH1QuUFn0WV83W8lGdX8cD5/+2ONLluALJD5+yJ7k8mVtwy3zMZmzEfbLg==
-
-"@tailwindcss/oxide-freebsd-x64@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-freebsd-x64/-/oxide-freebsd-x64-4.1.12.tgz#da1c0b16b7a5f95a1e400f299a3ec94fb6fd40ac"
-  integrity sha512-JOH/f7j6+nYXIrHobRYCtoArJdMJh5zy5lr0FV0Qu47MID/vqJAY3r/OElPzx1C/wdT1uS7cPq+xdYYelny1ww==
-
-"@tailwindcss/oxide-linux-arm-gnueabihf@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-linux-arm-gnueabihf/-/oxide-linux-arm-gnueabihf-4.1.12.tgz#34e558aa6e869c6fe9867cb78ed7ba651b9fcaa4"
-  integrity sha512-v4Ghvi9AU1SYgGr3/j38PD8PEe6bRfTnNSUE3YCMIRrrNigCFtHZ2TCm8142X8fcSqHBZBceDx+JlFJEfNg5zQ==
-
-"@tailwindcss/oxide-linux-arm64-gnu@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-linux-arm64-gnu/-/oxide-linux-arm64-gnu-4.1.12.tgz#0a00a8146ab6215f81b2d385056c991441bf390e"
-  integrity sha512-YP5s1LmetL9UsvVAKusHSyPlzSRqYyRB0f+Kl/xcYQSPLEw/BvGfxzbH+ihUciePDjiXwHh+p+qbSP3SlJw+6g==
-
-"@tailwindcss/oxide-linux-arm64-musl@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-linux-arm64-musl/-/oxide-linux-arm64-musl-4.1.12.tgz#b138f494068884ae0d8c343dc1904b22f5e98dc6"
-  integrity sha512-V8pAM3s8gsrXcCv6kCHSuwyb/gPsd863iT+v1PGXC4fSL/OJqsKhfK//v8P+w9ThKIoqNbEnsZqNy+WDnwQqCA==
-
-"@tailwindcss/oxide-linux-x64-gnu@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-linux-x64-gnu/-/oxide-linux-x64-gnu-4.1.12.tgz#5b9d5f23b15cdb714639f5b9741c0df5d610f794"
-  integrity sha512-xYfqYLjvm2UQ3TZggTGrwxjYaLB62b1Wiysw/YE3Yqbh86sOMoTn0feF98PonP7LtjsWOWcXEbGqDL7zv0uW8Q==
-
-"@tailwindcss/oxide-linux-x64-musl@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-linux-x64-musl/-/oxide-linux-x64-musl-4.1.12.tgz#f68ec530d3ca6875ea9015bcd5dd0762ee5e2f5d"
-  integrity sha512-ha0pHPamN+fWZY7GCzz5rKunlv9L5R8kdh+YNvP5awe3LtuXb5nRi/H27GeL2U+TdhDOptU7T6Is7mdwh5Ar3A==
-
-"@tailwindcss/oxide-wasm32-wasi@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-wasm32-wasi/-/oxide-wasm32-wasi-4.1.12.tgz#9fd15a1ebde6076c42c445c5e305c31673ead965"
-  integrity sha512-4tSyu3dW+ktzdEpuk6g49KdEangu3eCYoqPhWNsZgUhyegEda3M9rG0/j1GV/JjVVsj+lG7jWAyrTlLzd/WEBg==
-  dependencies:
-    "@emnapi/core" "^1.4.5"
-    "@emnapi/runtime" "^1.4.5"
-    "@emnapi/wasi-threads" "^1.0.4"
-    "@napi-rs/wasm-runtime" "^0.2.12"
-    "@tybys/wasm-util" "^0.10.0"
-    tslib "^2.8.0"
-
-"@tailwindcss/oxide-win32-arm64-msvc@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-win32-arm64-msvc/-/oxide-win32-arm64-msvc-4.1.12.tgz#938bcc6a82e1120ea4fe2ce94be0a8cdf3ae92c7"
-  integrity sha512-iGLyD/cVP724+FGtMWslhcFyg4xyYyM+5F4hGvKA7eifPkXHRAUDFaimu53fpNg9X8dfP75pXx/zFt/jlNF+lg==
-
-"@tailwindcss/oxide-win32-x64-msvc@4.1.12":
-  version "4.1.12"
-  resolved "https://registry.npmjs.org/@tailwindcss/oxide-win32-x64-msvc/-/oxide-win32-x64-msvc-4.1.12.tgz"
-  integrity sha512-NKIh5rzw6CpEodv/++r0hGLlfgT/gFN+5WNdZtvh6wpU2BpGNgdjvj6H2oFc8nCM839QM1YOhjpgbAONUb4IxA==
-
 "@tailwindcss/oxide@4.1.12":
  version "4.1.12"
  resolved "https://registry.npmjs.org/@tailwindcss/oxide/-/oxide-4.1.12.tgz"
@@ -1059,13 +764,6 @@
    "@tailwindcss/oxide" "4.1.12"
    tailwindcss "4.1.12"

-"@tybys/wasm-util@^0.10.0":
-  version "0.10.1"
-  resolved "https://registry.yarnpkg.com/@tybys/wasm-util/-/wasm-util-0.10.1.tgz#ecddd3205cf1e2d5274649ff0eedd2991ed7f414"
-  integrity sha512-9tTaPJLSiejZKx+Bmog4uSubteqTvFrVrURwkmHixBo0G4seD0zUxp98E1DzUBJxLQ3NPwXrGKDiVjwx/DpPsg==
-  dependencies:
-    tslib "^2.4.0"
-
 "@types/babel__core@^7.20.5":
  version "7.20.5"
  resolved "https://registry.npmjs.org/@types/babel__core/-/babel__core-7.20.5.tgz"
@@ -1138,7 +836,7 @@
    "@types/d3-interpolate" "*"
    "@types/d3-selection" "*"

-"@types/estree@1.0.8", "@types/estree@^1.0.6":
+"@types/estree@^1.0.6", "@types/estree@1.0.8":
  version "1.0.8"
  resolved "https://registry.npmjs.org/@types/estree/-/estree-1.0.8.tgz"
  integrity sha512-dWHzHa2WqEXI/O1E9OjrocMTKJl2mSrEolh1Iomrv6U+JuNwaHXsXx9bLu5gG7BUWFIN0skIQJQ/L1rIex4X6w==
@@ -1148,19 +846,19 @@
  resolved "https://registry.npmjs.org/@types/json-schema/-/json-schema-7.0.15.tgz"
  integrity sha512-5+fP8P8MFNC+AyZCDxrB2pkZFPGzqQWUzpSeuuVLvm8VMcorNYavBqoFcxK8bQz4Qsbn4oUEEem4wDLfcysGHA==

-"@types/node@^24.3.0":
+"@types/node@^20.19.0 || >=22.12.0", "@types/node@^24.3.0":
  version "24.3.0"
  resolved "https://registry.npmjs.org/@types/node/-/node-24.3.0.tgz"
  integrity sha512-aPTXCrfwnDLj4VvXrm+UUCQjNEvJgNA8s5F1cvwQU+3KNltTOkBm1j30uNLyqqPNe7gE3KFzImYoZEfLhp4Yow==
  dependencies:
    undici-types "~7.10.0"

-"@types/react-dom@^19.1.7":
+"@types/react-dom@*", "@types/react-dom@^19.1.7":
  version "19.1.7"
  resolved "https://registry.npmjs.org/@types/react-dom/-/react-dom-19.1.7.tgz"
  integrity sha512-i5ZzwYpqjmrKenzkoLM2Ibzt6mAsM7pxB6BCIouEVVmgiqaMj1TjaK7hnA36hbW5aZv20kx7Lw6hWzPWg0Rurw==

-"@types/react@^19.1.10":
+"@types/react@*", "@types/react@^19.0.0", "@types/react@^19.1.10", "@types/react@>=16.8", "@types/react@>=18.0.0":
  version "19.1.10"
  resolved "https://registry.npmjs.org/@types/react/-/react-19.1.10.tgz"
  integrity sha512-EhBeSYX0Y6ye8pNebpKrwFJq7BoQ8J5SO6NlvNwwHjSj6adXJViPQrKlsyPw7hLBLvckEMO1yxeGdR82YBBlDg==
@@ -1182,7 +880,7 @@
    natural-compare "^1.4.0"
    ts-api-utils "^2.1.0"

-"@typescript-eslint/parser@8.40.0":
+"@typescript-eslint/parser@^8.40.0", "@typescript-eslint/parser@8.40.0":
  version "8.40.0"
  resolved "https://registry.npmjs.org/@typescript-eslint/parser/-/parser-8.40.0.tgz"
  integrity sha512-jCNyAuXx8dr5KJMkecGmZ8KI61KBUhkCob+SD+C+I5+Y1FWI2Y3QmY4/cxMCC5WAsZqoEtEETVhUiUMIGCf6Bw==
@@ -1210,7 +908,7 @@
    "@typescript-eslint/types" "8.40.0"
    "@typescript-eslint/visitor-keys" "8.40.0"

-"@typescript-eslint/tsconfig-utils@8.40.0", "@typescript-eslint/tsconfig-utils@^8.40.0":
+"@typescript-eslint/tsconfig-utils@^8.40.0", "@typescript-eslint/tsconfig-utils@8.40.0":
  version "8.40.0"
  resolved "https://registry.npmjs.org/@typescript-eslint/tsconfig-utils/-/tsconfig-utils-8.40.0.tgz"
  integrity sha512-jtMytmUaG9d/9kqSl/W3E3xaWESo4hFDxAIHGVW/WKKtQhesnRIJSAJO6XckluuJ6KDB5woD1EiqknriCtAmcw==
@@ -1226,7 +924,7 @@
    debug "^4.3.4"
    ts-api-utils "^2.1.0"

-"@typescript-eslint/types@8.40.0", "@typescript-eslint/types@^8.40.0":
+"@typescript-eslint/types@^8.40.0", "@typescript-eslint/types@8.40.0":
  version "8.40.0"
  resolved "https://registry.npmjs.org/@typescript-eslint/types/-/types-8.40.0.tgz"
  integrity sha512-ETdbFlgbAmXHyFPwqUIYrfc12ArvpBhEVgGAxVYSwli26dn8Ko+lIo4Su9vI9ykTZdJn+vJprs/0eZU0YMAEQg==
@@ -1306,7 +1004,7 @@ acorn-jsx@^5.3.2:
  resolved "https://registry.npmjs.org/acorn-jsx/-/acorn-jsx-5.3.2.tgz"
  integrity sha512-rq9s+JNhf0IChjtDXxllJ7g41oZk5SlXtp0LHwyA5cejwn7vKmKp4pPri6YEePv2PU65sAsegbXtIinmDFDXgQ==

-acorn@^8.15.0:
+"acorn@^6.0.0 || ^7.0.0 || ^8.0.0", acorn@^8.15.0:
  version "8.15.0"
  resolved "https://registry.npmjs.org/acorn/-/acorn-8.15.0.tgz"
  integrity sha512-NZyJarBfL7nWwIq+FDL6Zp/yHEhePMNnnJ0y3qfieCrmNvYct8uvtiV41UvlSe6apAfk0fY1FbWx+NwfmpvtTg==
@@ -1367,7 +1065,7 @@ braces@^3.0.3:
  dependencies:
    fill-range "^7.1.1"

-browserslist@^4.24.0:
+browserslist@^4.24.0, "browserslist@>= 4.21.0":
  version "4.25.3"
  resolved "https://registry.npmjs.org/browserslist/-/browserslist-4.25.3.tgz"
  integrity sha512-cDGv1kkDI4/0e5yON9yM5G/0A5u8sf5TnmdX5C9qHzI9PPu++sQ9zjm1k9NiOrf3riY4OkK0zSGqfvJyJsgCBQ==
@@ -1463,7 +1161,7 @@ csstype@^3.0.2:
  resolved "https://registry.npmjs.org/d3-dispatch/-/d3-dispatch-3.0.1.tgz"
  integrity sha512-rzUyPU/S7rwUflMyLc1ETDeBj0NRuHKKAcvukozwhshr6g6c5d8zh4c2gQjY2bZ0dXeGLWc1PF174P2tVvKhfg==

-"d3-drag@2 - 3", d3-drag@^3.0.0:
+d3-drag@^3.0.0, "d3-drag@2 - 3":
  version "3.0.0"
  resolved "https://registry.npmjs.org/d3-drag/-/d3-drag-3.0.0.tgz"
  integrity sha512-pWbUJLdETVA8lQNJecMxoXfH6x+mO2UQo8rSmZ+QqxcbyA3hfeprFgIT//HW2nlHChWeIIMwS2Fq+gEARkhTkg==
@@ -1476,14 +1174,14 @@ csstype@^3.0.2:
  resolved "https://registry.npmjs.org/d3-ease/-/d3-ease-3.0.1.tgz"
  integrity sha512-wR/XK3D3XcLIZwpbvQwQ5fK+8Ykds1ip7A2Txe0yxncXSdq1L9skcG7blcedkOX+ZcgxGAmLX1FrRGbADwzi0w==

-"d3-interpolate@1 - 3", d3-interpolate@^3.0.1:
+d3-interpolate@^3.0.1, "d3-interpolate@1 - 3":
  version "3.0.1"
  resolved "https://registry.npmjs.org/d3-interpolate/-/d3-interpolate-3.0.1.tgz"
  integrity sha512-3bYs1rOD33uo8aqJfKP3JWPAibgw8Zm2+L9vBKEHJ2Rg+viTR7o5Mmv5mZcieN+FRYaAOWX5SJATX6k1PWz72g==
  dependencies:
    d3-color "1 - 3"

-"d3-selection@2 - 3", d3-selection@3, d3-selection@^3.0.0:
+d3-selection@^3.0.0, "d3-selection@2 - 3", d3-selection@3:
  version "3.0.0"
  resolved "https://registry.npmjs.org/d3-selection/-/d3-selection-3.0.0.tgz"
  integrity sha512-fmTRWbNMmsmWq6xJV8D19U/gw/bwrHfNXxrIN+HfZgnzqTHp9jOmKMhsTUjXOJnZOdZY9Q28y4yebKzqDKlxlQ==
@@ -1620,7 +1318,7 @@ eslint-visitor-keys@^4.2.1:
  resolved "https://registry.npmjs.org/eslint-visitor-keys/-/eslint-visitor-keys-4.2.1.tgz"
  integrity sha512-Uhdk5sfqcee/9H/rCOJikYz67o0a2Tw2hGRPOG2Y1R2dg7brRe1uG0yaNQDHu+TO/uQPF/5eCapvYSmHUjt7JQ==

-eslint@^9.33.0:
+"eslint@^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 || ^7.0.0 || ^8.0.0-0 || ^9.0.0", "eslint@^6.0.0 || ^7.0.0 || >=8.0.0", "eslint@^8.57.0 || ^9.0.0", eslint@^9.33.0, eslint@>=8.40:
  version "9.33.0"
  resolved "https://registry.npmjs.org/eslint/-/eslint-9.33.0.tgz"
  integrity sha512-TS9bTNIryDzStCpJN93aC5VRSW3uTx9sClUn4B87pwiCaJh220otoI0X8mJKr+VcPtniMdN8GKjlwgWGUv5ZKA==
@@ -1866,7 +1564,7 @@ isexe@^2.0.0:
  resolved "https://registry.npmjs.org/isexe/-/isexe-2.0.0.tgz"
  integrity sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw==

-jiti@^2.5.1:
+jiti@*, jiti@^2.5.1, jiti@>=1.21.0:
  version "2.5.1"
  resolved "https://registry.npmjs.org/jiti/-/jiti-2.5.1.tgz"
  integrity sha512-twQoecYPiVA5K/h6SxtORw/Bs3ar+mLUtoPSc7iMXzQzK8d7eJ/R09wmTwAjiamETn1cXYPGfNnu7DMoHgu12w==
@@ -1877,9 +1575,7 @@ js-tokens@^4.0.0:
  integrity sha512-RdJUflcE3cUzKiMqQgsCu06FPu9UdIJO0beYbPhHN4k6apgJtifcoCtT9bcxOpYBtpD2kCM6Sbzg4CausW/PKQ==

 js-yaml@^4.1.0:
-  version "4.1.1"
-  resolved "https://registry.yarnpkg.com/js-yaml/-/js-yaml-4.1.1.tgz#854c292467705b699476e1a2decc0c8a3458806b"
-  integrity sha512-qQKT4zQxXl8lLwBtHMWwaTcGfFOZviOJet3Oy/xmGk2gZH677CJM9EvtfdSkgWcATZhj/55JZ0rmy3myCT5lsA==
+  version "4.1.0"
  dependencies:
    argparse "^2.0.1"

@@ -1925,55 +1621,10 @@ levn@^0.4.1:

 lightningcss-darwin-arm64@1.30.1:
  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-darwin-arm64/-/lightningcss-darwin-arm64-1.30.1.tgz#3d47ce5e221b9567c703950edf2529ca4a3700ae"
+  resolved "https://registry.npmjs.org/lightningcss-darwin-arm64/-/lightningcss-darwin-arm64-1.30.1.tgz"
  integrity sha512-c8JK7hyE65X1MHMN+Viq9n11RRC7hgin3HhYKhrMyaXflk5GVplZ60IxyoVtzILeKr+xAJwg6zK6sjTBJ0FKYQ==

-lightningcss-darwin-x64@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-darwin-x64/-/lightningcss-darwin-x64-1.30.1.tgz#e81105d3fd6330860c15fe860f64d39cff5fbd22"
-  integrity sha512-k1EvjakfumAQoTfcXUcHQZhSpLlkAuEkdMBsI/ivWw9hL+7FtilQc0Cy3hrx0AAQrVtQAbMI7YjCgYgvn37PzA==
-
-lightningcss-freebsd-x64@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-freebsd-x64/-/lightningcss-freebsd-x64-1.30.1.tgz#a0e732031083ff9d625c5db021d09eb085af8be4"
-  integrity sha512-kmW6UGCGg2PcyUE59K5r0kWfKPAVy4SltVeut+umLCFoJ53RdCUWxcRDzO1eTaxf/7Q2H7LTquFHPL5R+Gjyig==
-
-lightningcss-linux-arm-gnueabihf@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-linux-arm-gnueabihf/-/lightningcss-linux-arm-gnueabihf-1.30.1.tgz#1f5ecca6095528ddb649f9304ba2560c72474908"
-  integrity sha512-MjxUShl1v8pit+6D/zSPq9S9dQ2NPFSQwGvxBCYaBYLPlCWuPh9/t1MRS8iUaR8i+a6w7aps+B4N0S1TYP/R+Q==
-
-lightningcss-linux-arm64-gnu@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-linux-arm64-gnu/-/lightningcss-linux-arm64-gnu-1.30.1.tgz#eee7799726103bffff1e88993df726f6911ec009"
-  integrity sha512-gB72maP8rmrKsnKYy8XUuXi/4OctJiuQjcuqWNlJQ6jZiWqtPvqFziskH3hnajfvKB27ynbVCucKSm2rkQp4Bw==
-
-lightningcss-linux-arm64-musl@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-linux-arm64-musl/-/lightningcss-linux-arm64-musl-1.30.1.tgz#f2e4b53f42892feeef8f620cbb889f7c064a7dfe"
-  integrity sha512-jmUQVx4331m6LIX+0wUhBbmMX7TCfjF5FoOH6SD1CttzuYlGNVpA7QnrmLxrsub43ClTINfGSYyHe2HWeLl5CQ==
-
-lightningcss-linux-x64-gnu@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-linux-x64-gnu/-/lightningcss-linux-x64-gnu-1.30.1.tgz#2fc7096224bc000ebb97eea94aea248c5b0eb157"
-  integrity sha512-piWx3z4wN8J8z3+O5kO74+yr6ze/dKmPnI7vLqfSqI8bccaTGY5xiSGVIJBDd5K5BHlvVLpUB3S2YCfelyJ1bw==
-
-lightningcss-linux-x64-musl@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.30.1.tgz#66dca2b159fd819ea832c44895d07e5b31d75f26"
-  integrity sha512-rRomAK7eIkL+tHY0YPxbc5Dra2gXlI63HL+v1Pdi1a3sC+tJTcFrHX+E86sulgAXeI7rSzDYhPSeHHjqFhqfeQ==
-
-lightningcss-win32-arm64-msvc@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.yarnpkg.com/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.30.1.tgz#7d8110a19d7c2d22bfdf2f2bb8be68e7d1b69039"
-  integrity sha512-mSL4rqPi4iXq5YVqzSsJgMVFENoa4nGTT/GjO2c0Yl9OuQfPsIfncvLrEW6RbbB24WtZ3xP/2CCmI3tNkNV4oA==
-
-lightningcss-win32-x64-msvc@1.30.1:
-  version "1.30.1"
-  resolved "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.30.1.tgz"
-  integrity sha512-PVqXh48wh4T53F/1CCu8PIPCxLzWyCnn/9T5W1Jpmdy5h9Cwd+0YQS6/LwhHXSafuc61/xg9Lv5OrCby6a++jg==
-
-lightningcss@1.30.1:
+lightningcss@^1.21.0, lightningcss@1.30.1:
  version "1.30.1"
  resolved "https://registry.npmjs.org/lightningcss/-/lightningcss-1.30.1.tgz"
  integrity sha512-xi6IyHML+c9+Q3W0S4fCQJOym42pyurFiJUHEcEyHS0CeKzia4yZDEsLlqOFykxOdHpNy0NmvVO31vcSqAxJCg==
@@ -2144,7 +1795,7 @@ picomatch@^2.3.1:
  resolved "https://registry.npmjs.org/picomatch/-/picomatch-2.3.1.tgz"
  integrity sha512-JU3teHTNjmE2VCGFzuY8EXzCDVwEqB2a8fsIvwaStHhAWJEeVd1o1QD80CU6+ZdEXXSLbSsuLwJjkCBWqRQUVA==

-picomatch@^4.0.3:
+"picomatch@^3 || ^4", picomatch@^4.0.3:
  version "4.0.3"
  resolved "https://registry.npmjs.org/picomatch/-/picomatch-4.0.3.tgz"
  integrity sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==
@@ -2173,7 +1824,7 @@ queue-microtask@^1.2.2:
  resolved "https://registry.npmjs.org/queue-microtask/-/queue-microtask-1.2.3.tgz"
  integrity sha512-NuaNSa6flKT5JaSYQzJok04JzTL1CA6aGhv5rfLW3PgqA+M2ChpZQnAC8h8i4ZFkBS8X5RqkDBHA7r4hej3K9A==

-react-dom@^19.1.1:
+"react-dom@^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc", "react-dom@^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", react-dom@^19.1.1, react-dom@>=16.8.0, react-dom@>=17:
  version "19.1.1"
  resolved "https://registry.npmjs.org/react-dom/-/react-dom-19.1.1.tgz"
  integrity sha512-Dlq/5LAZgF0Gaz6yiqZCf6VCcZs1ghAJyrsu84Q/GT0gV+mCxbfmKNoGRKBYMJ8IEdGPqu49YWXD02GCknEDkw==
@@ -2212,7 +1863,7 @@ react-style-singleton@^2.2.2, react-style-singleton@^2.2.3:
    get-nonce "^1.0.0"
    tslib "^2.0.0"

-react@^19.1.1:
+"react@^16.5.1 || ^17.0.0 || ^18.0.0 || ^19.0.0", "react@^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc", "react@^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react@^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0", "react@^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc", react@^19.1.1, react@>=16.8, react@>=16.8.0, react@>=17, react@>=18.0.0:
  version "19.1.1"
  resolved "https://registry.npmjs.org/react/-/react-19.1.1.tgz"
  integrity sha512-w8nqGImo45dmMIfljjMwOGtbmC/mk4CMYhWIicdSflH91J9TyCyczcPFXJzrZ/ZXcgGRFeP6BU0BEJTw6tZdfQ==
@@ -2312,7 +1963,7 @@ tailwind-merge@^3.3.1:
  resolved "https://registry.npmjs.org/tailwind-merge/-/tailwind-merge-3.3.1.tgz"
  integrity sha512-gBXpgUm/3rp1lMZZrM/w7D8GKqshif0zAymAhbCyIt8KMe+0v9DQ7cdYLR4FHH/cKpdTXb+A/tKKU3eolfsI+g==

-tailwindcss@4.1.12, tailwindcss@^4.1.12:
+tailwindcss@^4.1.12, tailwindcss@4.1.12:
  version "4.1.12"
  resolved "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.12.tgz"
  integrity sha512-DzFtxOi+7NsFf7DBtI3BJsynR+0Yp6etH+nRPTbpWnS2pZBaSksv/JGctNwSWzbFjp0vxSqknaUylseZqMDGrA==
@@ -2354,7 +2005,7 @@ ts-api-utils@^2.1.0:
  resolved "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-2.1.0.tgz"
  integrity sha512-CUgTZL1irw8u29bzrOD/nH85jqyc74D6SshFgujOIA7osm2Rz7dYH77agkx7H4FBNxDq7Cjf+IjaX/8zwFW+ZQ==

-tslib@^2.0.0, tslib@^2.1.0, tslib@^2.4.0, tslib@^2.8.0:
+tslib@^2.0.0, tslib@^2.1.0:
  version "2.8.1"
  resolved "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz"
  integrity sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==
@@ -2381,7 +2032,7 @@ typescript-eslint@^8.39.1:
    "@typescript-eslint/typescript-estree" "8.40.0"
    "@typescript-eslint/utils" "8.40.0"

-typescript@~5.8.3:
+typescript@>=4.8.4, "typescript@>=4.8.4 <6.0.0", typescript@~5.8.3:
  version "5.8.3"
  resolved "https://registry.npmjs.org/typescript/-/typescript-5.8.3.tgz"
  integrity sha512-p1diW6TqL9L07nNxvRMM7hMMw4c5XOo/1ibL4aAIGmSAt9slTE1Xgw5KWuof2uTOvCg9BY7ZRi+GaF+7sfgPeQ==
@@ -2421,12 +2072,12 @@ use-sidecar@^1.1.3:
    detect-node-es "^1.1.0"
    tslib "^2.0.0"

-use-sync-external-store@^1.2.2:
+use-sync-external-store@^1.2.2, use-sync-external-store@>=1.2.0:
  version "1.5.0"
  resolved "https://registry.npmjs.org/use-sync-external-store/-/use-sync-external-store-1.5.0.tgz"
  integrity sha512-Rb46I4cGGVBmjamjphe8L/UnvJD+uPPtTkNvX5mZgqdbavhI4EbgIWJiIHXJ8bc/i9EQGPRh4DwEURJ552Do0A==

-vite@^7.1.11:
+"vite@^4.2.0 || ^5.0.0 || ^6.0.0 || ^7.0.0", "vite@^5.2.0 || ^6 || ^7", vite@^7.1.11:
  version "7.1.12"
  resolved "https://registry.npmjs.org/vite/-/vite-7.1.12.tgz"
  integrity sha512-ZWyE8YXEXqJrrSLvYgrRP7p62OziLW7xI5HYGWFzOvupfAlrLvURSzv/FyGyy0eidogEM3ujU+kUG1zuHgb6Ug==
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://github.com/microsoft/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -8,8 +8,10 @@ import pytest
 from agent_framework import (
    Executor,
    InMemoryCheckpointStorage,
+    RequestInfoEvent,
    WorkflowBuilder,
    WorkflowContext,
+    WorkflowStatusEvent,
    handler,
    response_handler,
 )
@@ -426,14 +428,11 @@ class TestIntegration:
        # Run workflow until it reaches IDLE_WITH_PENDING_REQUESTS (after checkpoint is created)
        saw_request_event = False
        async for event in test_workflow.run_stream(WorkflowTestData(value="test")):
-            if hasattr(event, "__class__"):
-                if event.__class__.__name__ == "RequestInfoEvent":
-                    saw_request_event = True
-                # Wait for IDLE_WITH_PENDING_REQUESTS status (comes after checkpoint creation)
-                is_status_event = event.__class__.__name__ == "WorkflowStatusEvent"
-                has_pending_status = hasattr(event, "status") and "IDLE_WITH_PENDING_REQUESTS" in str(event.status)
-                if is_status_event and has_pending_status:
-                    break
+            if isinstance(event, RequestInfoEvent):
+                saw_request_event = True
+            # Wait for IDLE_WITH_PENDING_REQUESTS status (comes after checkpoint creation)
+            if isinstance(event, WorkflowStatusEvent) and "IDLE_WITH_PENDING_REQUESTS" in str(event.state):
+                break

        assert saw_request_event, "Test workflow should have emitted RequestInfoEvent"

@@ -234,7 +234,7 @@ async def test_list_items_converts_function_calls():
                {
                    "type": "function_result",
                    "call_id": "call_test123",
-                    "output": '{"temperature": 65, "condition": "sunny"}',
+                    "result": '{"temperature": 65, "condition": "sunny"}',
                }
            ],
        ),
@@ -441,73 +441,119 @@ async def test_workflow_status_event(mapper: MessageMapper, test_request: AgentF


 # =============================================================================
-# MagenticAgentDeltaEvent Tests
+# Magentic Event Tests - Testing REAL AgentRunUpdateEvent with additional_properties
 # =============================================================================


-async def test_magentic_agent_delta_creates_message_container(
+async def test_magentic_agent_run_update_event_with_agent_delta_metadata(
    mapper: MessageMapper, test_request: AgentFrameworkRequest
 ) -> None:
-    """Test that MagenticAgentDeltaEvent creates message containers when no executor context."""
-    from dataclasses import dataclass
+    """Test that AgentRunUpdateEvent with magentic_event_type='agent_delta' is handled correctly.

-    from agent_framework import WorkflowEvent
+    This tests the ACTUAL event format Magentic emits - not a fake MagenticAgentDeltaEvent class.
+    Magentic uses AgentRunUpdateEvent with additional_properties containing magentic_event_type.
+    """
+    from agent_framework._types import AgentRunResponseUpdate, Role, TextContent
+    from agent_framework._workflows._events import AgentRunUpdateEvent

-    @dataclass
-    class MagenticAgentDeltaEvent(WorkflowEvent):
-        agent_id: str
-        text: str | None = None
+    # Create the REAL event format that Magentic emits
+    update = AgentRunResponseUpdate(
+        contents=[TextContent(text="Hello from agent")],
+        role=Role.ASSISTANT,
+        author_name="Writer",
+        additional_properties={
+            "magentic_event_type": "agent_delta",
+            "agent_id": "writer_agent",
+        },
+    )
+    event = AgentRunUpdateEvent(executor_id="magentic_executor", data=update)

-    # First delta should create message container
-    first_delta = MagenticAgentDeltaEvent(agent_id="test_agent", text="Hello ")
-    events = await mapper.convert_event(first_delta, test_request)
+    events = await mapper.convert_event(event, test_request)

-    # Should emit 3 events: message container, content part, and text delta
-    assert len(events) == 3
-    assert events[0].type == "response.output_item.added"
-    assert events[0].item.type == "message"
-    assert events[0].item.metadata["agent_id"] == "test_agent"
-    message_id = events[0].item.id
-
-    # Second delta should NOT create new container
-    second_delta = MagenticAgentDeltaEvent(agent_id="test_agent", text="world!")
-    events = await mapper.convert_event(second_delta, test_request)
-
-    assert len(events) == 1
-    assert events[0].type == "response.output_text.delta"
-    assert events[0].item_id == message_id
+    # Should be treated as a regular AgentRunUpdateEvent with text content
+    # The mapper should emit text delta events
+    assert len(events) >= 1
+    text_events = [e for e in events if getattr(e, "type", "") == "response.output_text.delta"]
+    assert len(text_events) >= 1
+    assert text_events[0].delta == "Hello from agent"


-async def test_magentic_agent_delta_routes_to_executor_item(
+async def test_magentic_orchestrator_message_event(mapper: MessageMapper, test_request: AgentFrameworkRequest) -> None:
+    """Test that AgentRunUpdateEvent with magentic_event_type='orchestrator_message' is handled.
+
+    Magentic emits orchestrator planning/instruction messages using AgentRunUpdateEvent
+    with additional_properties containing magentic_event_type='orchestrator_message'.
+    """
+    from agent_framework._types import AgentRunResponseUpdate, Role, TextContent
+    from agent_framework._workflows._events import AgentRunUpdateEvent
+
+    # Create orchestrator message event (REAL format from Magentic)
+    update = AgentRunResponseUpdate(
+        contents=[TextContent(text="Planning: First, the writer will create content...")],
+        role=Role.ASSISTANT,
+        author_name="Orchestrator",
+        additional_properties={
+            "magentic_event_type": "orchestrator_message",
+            "orchestrator_message_kind": "task_ledger",
+            "orchestrator_id": "magentic_orchestrator",
+        },
+    )
+    event = AgentRunUpdateEvent(executor_id="magentic_orchestrator", data=update)
+
+    events = await mapper.convert_event(event, test_request)
+
+    # Currently, mapper treats this as regular AgentRunUpdateEvent (no special handling)
+    # This test documents the current behavior
+    assert len(events) >= 1
+    text_events = [e for e in events if getattr(e, "type", "") == "response.output_text.delta"]
+    assert len(text_events) >= 1
+    assert "Planning:" in text_events[0].delta
+
+
+async def test_magentic_events_use_same_event_class_as_other_workflows(
    mapper: MessageMapper, test_request: AgentFrameworkRequest
 ) -> None:
-    """Test that MagenticAgentDeltaEvent routes to executor item when executor context is present."""
-    from dataclasses import dataclass
+    """Verify Magentic uses the same AgentRunUpdateEvent class as other workflows.

-    from agent_framework import WorkflowEvent
+    This test documents that Magentic does NOT define separate event classes like
+    MagenticAgentDeltaEvent - it reuses AgentRunUpdateEvent with metadata in
+    additional_properties. Any mapper code checking for 'MagenticAgentDeltaEvent'
+    class names is dead code.
+    """
+    from agent_framework._types import AgentRunResponseUpdate, Role, TextContent
+    from agent_framework._workflows._events import AgentRunUpdateEvent

-    @dataclass
-    class MagenticAgentDeltaEvent(WorkflowEvent):
-        agent_id: str
-        text: str | None = None
+    # Create events the way different workflows do it
+    # 1. Regular workflow (no additional_properties)
+    regular_update = AgentRunResponseUpdate(
+        contents=[TextContent(text="Regular workflow response")],
+        role=Role.ASSISTANT,
+    )
+    regular_event = AgentRunUpdateEvent(executor_id="regular_executor", data=regular_update)

-    # First, invoke an executor (sets current_executor_id in context)
-    executor_event = create_executor_invoked_event(executor_id="agent_writer")
-    executor_events = await mapper.convert_event(executor_event, test_request)
+    # 2. Magentic workflow (with additional_properties)
+    magentic_update = AgentRunResponseUpdate(
+        contents=[TextContent(text="Magentic workflow response")],
+        role=Role.ASSISTANT,
+        additional_properties={"magentic_event_type": "agent_delta"},
+    )
+    magentic_event = AgentRunUpdateEvent(executor_id="magentic_executor", data=magentic_update)

-    assert len(executor_events) == 1
-    assert executor_events[0].type == "response.output_item.added"
-    executor_item_id = executor_events[0].item.id
+    # Both should be the SAME class
+    assert type(regular_event) is type(magentic_event)
+    assert isinstance(regular_event, AgentRunUpdateEvent)
+    assert isinstance(magentic_event, AgentRunUpdateEvent)

-    # Now send Magentic delta - should route to executor's item
-    delta = MagenticAgentDeltaEvent(agent_id="writer", text="Hello world")
-    delta_events = await mapper.convert_event(delta, test_request)
+    # Both should be handled by the same isinstance check in mapper
+    regular_events = await mapper.convert_event(regular_event, test_request)
+    magentic_events = await mapper.convert_event(magentic_event, test_request)

-    # Should only emit 1 event: text delta routed to executor's item
-    assert len(delta_events) == 1
-    assert delta_events[0].type == "response.output_text.delta"
-    assert delta_events[0].item_id == executor_item_id
-    assert delta_events[0].delta == "Hello world"
+    # Both produce text delta events
+    regular_text = [e for e in regular_events if getattr(e, "type", "") == "response.output_text.delta"]
+    magentic_text = [e for e in magentic_events if getattr(e, "type", "") == "response.output_text.delta"]
+
+    assert len(regular_text) >= 1
+    assert len(magentic_text) >= 1


 # =============================================================================
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://learn.microsoft.com/en-us/agent-framework/"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://github.com/microsoft/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -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 = "1.0.0b251223"
+version = "1.0.0b260106"
 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]==1.0.0b251223",
+    "agent-framework-core[all]==1.0.0b260106",
 ]

 [dependency-groups]
@@ -236,7 +236,7 @@ The recommended way to use Ollama is via the native `OllamaChatClient` from the
 |--------|-------------|
 | [`getting_started/azure_functions/01_single_agent/`](./getting_started/azure_functions/01_single_agent/) | Host a single agent in Azure Functions with Durable Extension HTTP endpoints and per-session state. |
 | [`getting_started/azure_functions/02_multi_agent/`](./getting_started/azure_functions/02_multi_agent/) | Register multiple agents in one function app with dedicated run routes and a health check endpoint. |
-| [`getting_started/azure_functions/03_callbacks/`](./getting_started/azure_functions/03_callbacks/) | Capture streaming response telemetry via Durable Extension callbacks exposed through HTTP APIs. |
+| [`getting_started/azure_functions/03_reliable_streaming/`](./getting_started/azure_functions/03_reliable_streaming/) | Implement reliable streaming for durable agents using Redis Streams with cursor-based resumption. |
 | [`getting_started/azure_functions/04_single_agent_orchestration_chaining/`](./getting_started/azure_functions/04_single_agent_orchestration_chaining/) | Chain sequential agent executions inside a durable orchestration while preserving the shared thread context. |
 | [`getting_started/azure_functions/05_multi_agent_orchestration_concurrency/`](./getting_started/azure_functions/05_multi_agent_orchestration_concurrency/) | Run two agents concurrently within a durable orchestration and combine their domain-specific outputs. |
 | [`getting_started/azure_functions/06_multi_agent_orchestration_conditionals/`](./getting_started/azure_functions/06_multi_agent_orchestration_conditionals/) | Route orchestration logic based on structured agent responses for spam detection and reply drafting. |
@@ -1,83 +0,0 @@
-# Callback Telemetry Sample
-
-This sample demonstrates how to use the Durable Extension for Agent Framework's response callbacks to observe
-streaming updates and final agent responses in real time. The `ConversationAuditTrail` callback
-records each chunk received from the Azure OpenAI agent and exposes the collected events through
-an HTTP API that can be polled by a web client or dashboard.
-
-## Highlights
-
- Registers a default `AgentResponseCallbackProtocol` implementation that logs streaming and final
-  responses.
- Persists callback events in an in-memory store and exposes them via
-  `GET /api/agents/{agentName}/callbacks/{thread_id}`.
- Shows how to reset stored callback events with `DELETE /api/agents/{agentName}/callbacks/{thread_id}`.
- Works alongside the standard `/api/agents/{agentName}/run` endpoint so you can correlate callback
-  telemetry with agent responses.
-
-## Prerequisites
-
-Complete the shared environment setup steps in `../README.md`, including creating a virtual environment, installing dependencies, and configuring Azure OpenAI credentials and storage settings.
-
-> **Note:** This is a streaming example that currently uses a local in-memory store for simplicity.
-> For distributed environments, consider using Redis, Service Bus, or another pub/sub mechanism for
-> callback coordination.
-
-## Running the Sample
-
-Send a prompt to the agent:
-
-```bash
-curl -X POST http://localhost:7071/api/agents/CallbackAgent/run \
-   -H "Content-Type: application/json" \
-   -d '{"message": "Tell me a short joke"}'
-```
-
-> **Note:** The run endpoint waits for the agent response by default. To return immediately, set the `x-ms-wait-for-response` header or include `"wait_for_response": false` in the request body.
-
-Poll callback telemetry (replace `<conversationId>` with the value from the POST response):
-
-```bash
-curl http://localhost:7071/api/agents/CallbackAgent/callbacks/<conversationId>
-```
-
-Reset stored events:
-
-```bash
-curl -X DELETE http://localhost:7071/api/agents/CallbackAgent/callbacks/<conversationId>
-```
-
-## Expected Output
-
-When you call `GET /api/agents/CallbackAgent/callbacks/{thread_id}` after sending a request to the agent,
-the API returns a list of streaming and final callback events similar to the following:
-
-```json
-[
-  {
-    "timestamp": "2024-01-01T00:00:00Z",
-    "agent_name": "CallbackAgent",
-    "thread_id": "<thread_id>",
-    "correlation_id": "<guid>",
-    "request_message": "Tell me a short joke",
-    "event_type": "stream",
-    "update_kind": "text",
-    "text": "Sure, here's a joke..."
-  },
-  {
-    "timestamp": "2024-01-01T00:00:01Z",
-    "agent_name": "CallbackAgent",
-    "thread_id": "<thread_id>",
-    "correlation_id": "<guid>",
-    "request_message": "Tell me a short joke",
-    "event_type": "final",
-    "response_text": "Why did the cloud...",
-    "usage": {
-      "type": "usage_details",
-      "input_token_count": 159,
-      "output_token_count": 29,
-      "total_token_count": 188
-    }
-  }
-]
-```
@@ -1,30 +0,0 @@
-### Callback Sample - API Tests
-### Use with VS Code REST Client or another HTTP testing tool.
-###
-### Endpoints introduced in this sample:
-### - POST /api/agents/{agentName}/run                          : send a message to the agent
-### - GET  /api/agents/{agentName}/callbacks/{thread_id}   : retrieve callback telemetry
-### - DELETE /api/agents/{agentName}/callbacks/{thread_id} : clear stored callback events
-
-@baseUrl = http://localhost:7071
-@agentName = CallbackAgent
-@agentRoute = {{baseUrl}}/api/agents/{{agentName}}
-@thread_id = test-thread-00
-
-### Health Check
-GET {{baseUrl}}/api/health
-
-### Send message (callbacks will capture streaming + final response)
-POST {{agentRoute}}/run
-Content-Type: application/json
-
-{
-  "message": "Generate a short weather update for Paris and mention streaming callbacks.",
-  "thread_id": "{{thread_id}}"
-}
-
-### Inspect callback telemetry
-GET {{agentRoute}}/callbacks/{{thread_id}}
-
-### Clear stored callback telemetry for the thread
-DELETE {{agentRoute}}/callbacks/{{thread_id}}
@@ -1,185 +0,0 @@
-"""Capture agent response callbacks inside Azure Functions.
-
-Components used in this sample:
- AzureOpenAIChatClient to build an agent that streams interim updates.
- AgentFunctionApp with a default AgentResponseCallbackProtocol implementation.
- Azure Functions HTTP triggers that expose callback telemetry via REST.
-
-Prerequisites: set `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_CHAT_DEPLOYMENT_NAME`, and either
-`AZURE_OPENAI_API_KEY` or authenticate with Azure CLI before starting the Functions host."""
-
-import json
-import logging
-from collections import defaultdict
-from datetime import datetime, timezone
-from typing import Any, DefaultDict
-
-import azure.functions as func
-from agent_framework import AgentRunResponseUpdate
-from agent_framework.azure import (
-    AgentCallbackContext,
-    AgentFunctionApp,
-    AgentResponseCallbackProtocol,
-    AzureOpenAIChatClient,
-)
-from azure.identity import AzureCliCredential
-
-logger = logging.getLogger(__name__)
-
-
-# 1. Maintain an in-memory store for callback events keyed by thread ID.
-# NOTE: This is a streaming example using a local console logger. For distributed environments,
-# consider using Redis or Service Bus for callback coordination across multiple instances.
-CallbackStore = DefaultDict[str, list[dict[str, Any]]]
-callback_events: CallbackStore = defaultdict(list)
-
-
-def _serialize_usage(usage: Any) -> Any:
-    """Best-effort serialization for agent usage metadata."""
-
-    if usage is None:
-        return None
-
-    model_dump = getattr(usage, "model_dump", None)
-    if callable(model_dump):
-        return model_dump()
-
-    to_dict = getattr(usage, "to_dict", None)
-    if callable(to_dict):
-        return to_dict()
-
-    return str(usage)
-
-
-class ConversationAuditTrail(AgentResponseCallbackProtocol):
-    """Callback that records streaming chunks and final responses for later inspection."""
-
-    def __init__(self) -> None:
-        self._logger = logging.getLogger("durableagent.samples.callbacks.audit")
-
-    async def on_streaming_response_update(
-        self,
-        update: AgentRunResponseUpdate,
-        context: AgentCallbackContext,
-    ) -> None:
-        event = self._build_base_event(context)
-        event.update(
-            {
-                "event_type": "stream",
-                "update_kind": getattr(update, "kind", "text"),
-                "text": getattr(update, "text", None),
-            }
-        )
-        thread_id = context.thread_id or ""
-        callback_events[thread_id].append(event)
-
-        preview = event.get("text") or event.get("update_kind")
-        self._logger.info(
-            "[%s][%s] streaming chunk: %s",
-            context.agent_name,
-            context.correlation_id,
-            preview,
-        )
-
-    async def on_agent_response(self, response, context: AgentCallbackContext) -> None:
-        event = self._build_base_event(context)
-        event.update(
-            {
-                "event_type": "final",
-                "response_text": getattr(response, "text", None),
-                "usage": _serialize_usage(getattr(response, "usage_details", None)),
-            }
-        )
-        thread_id = context.thread_id or ""
-        callback_events[thread_id].append(event)
-
-        self._logger.info(
-            "[%s][%s] final response recorded",
-            context.agent_name,
-            context.correlation_id,
-        )
-
-    @staticmethod
-    def _build_base_event(context: AgentCallbackContext) -> dict[str, Any]:
-        thread_id = context.thread_id
-        return {
-            "timestamp": datetime.now(timezone.utc).isoformat(),
-            "agent_name": context.agent_name,
-            "thread_id": thread_id,
-            "correlation_id": context.correlation_id,
-            "request_message": context.request_message,
-        }
-
-
-# 2. Create the agent that will emit streaming updates and final responses.
-callback_agent = AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
-    name="CallbackAgent",
-    instructions=(
-        "You are a friendly assistant that narrates actions while responding. "
-        "Keep answers concise and acknowledge when callbacks capture streaming updates."
-    ),
-)
-
-
-# 3. Register the agent inside AgentFunctionApp with a default callback instance.
-audit_callback = ConversationAuditTrail()
-app = AgentFunctionApp(enable_health_check=True, default_callback=audit_callback)
-app.add_agent(callback_agent)
-
-
-@app.function_name("get_callback_events")
-@app.route(route="agents/{agent_name}/callbacks/{thread_id}", methods=["GET"])
-async def get_callback_events(req: func.HttpRequest) -> func.HttpResponse:
-    """Return all callback events collected for a thread."""
-
-    thread_id = req.route_params.get("thread_id", "")
-    events = callback_events.get(thread_id, [])
-    return func.HttpResponse(
-        json.dumps(events, indent=2),
-        status_code=200,
-        mimetype="application/json",
-    )
-
-
-@app.function_name("reset_callback_events")
-@app.route(route="agents/{agent_name}/callbacks/{thread_id}", methods=["DELETE"])
-async def reset_callback_events(req: func.HttpRequest) -> func.HttpResponse:
-    """Clear the stored callback events for a thread."""
-
-    thread_id = req.route_params.get("thread_id", "")
-    callback_events.pop(thread_id, None)
-    return func.HttpResponse(status_code=204)
-
-
-"""
-Expected output when querying `GET /api/agents/CallbackAgent/callbacks/{thread_id}`:
-
-HTTP/1.1 200 OK
-[
-    {
-        "timestamp": "2024-01-01T00:00:00Z",
-        "agent_name": "CallbackAgent",
-        "thread_id": "<thread_id>",
-        "correlation_id": "<guid>",
-        "request_message": "Tell me a short joke",
-        "event_type": "stream",
-        "update_kind": "text",
-        "text": "Sure, here's a joke..."
-    },
-    {
-        "timestamp": "2024-01-01T00:00:01Z",
-        "agent_name": "CallbackAgent",
-        "thread_id": "<thread_id>",
-        "correlation_id": "<guid>",
-        "request_message": "Tell me a short joke",
-        "event_type": "final",
-        "response_text": "Why did the cloud...",
-        "usage": {
-            "type": "usage_details",
-            "input_token_count": 159,
-            "output_token_count": 29,
-            "total_token_count": 188
-        }
-    }
-]
-"""
@@ -0,0 +1,132 @@
+# Agent Response Callbacks with Redis Streaming
+
+This sample demonstrates how to use Redis Streams with agent response callbacks to enable reliable, resumable streaming for durable agents. Clients can disconnect and reconnect without losing messages by using cursor-based pagination.
+
+## Key Concepts Demonstrated
+
+- Using `AgentResponseCallbackProtocol` to capture streaming agent responses
+- Persisting streaming chunks to Redis Streams for reliable delivery
+- Building a custom HTTP endpoint to read from Redis with Server-Sent Events (SSE) format
+- Supporting cursor-based resumption for disconnected clients
+- Managing Redis client lifecycle with async context managers
+
+## Prerequisites
+
+In addition to the common setup steps in `../README.md`, this sample requires Redis:
+
+```bash
+# Start Redis
+docker run -d --name redis -p 6379:6379 redis:latest
+```
+
+Update `local.settings.json` with your Redis connection string:
+
+```json
+{
+  "Values": {
+    "REDIS_CONNECTION_STRING": "redis://localhost:6379"
+  }
+}
+```
+
+## Running the Sample
+
+### Start the agent run
+
+The agent executes in the background via durable orchestration. The `RedisStreamCallback` persists streaming chunks to Redis:
+
+```bash
+curl -X POST http://localhost:7071/api/agents/TravelPlanner/run \
+  -H "Content-Type: text/plain" \
+  -d "Plan a 3-day trip to Tokyo"
+```
+
+Response (202 Accepted):
+```json
+{
+  "status": "accepted",
+  "response": "Agent request accepted",
+  "conversation_id": "abc-123-def-456",
+  "correlation_id": "xyz-789"
+}
+```
+
+### Stream the response from Redis
+
+Use the custom `/api/agent/stream/{conversation_id}` endpoint to read persisted chunks:
+
+```bash
+curl http://localhost:7071/api/agent/stream/abc-123-def-456 \
+  -H "Accept: text/event-stream"
+```
+
+Response (SSE format):
+```
+id: 1734649123456-0
+event: message
+data: Here's a wonderful 3-day Tokyo itinerary...
+
+id: 1734649123789-0
+event: message
+data: Day 1: Arrival and Shibuya...
+
+id: 1734649124012-0
+event: done
+data: [DONE]
+```
+
+### Resume from a cursor
+
+Use a cursor ID from an SSE event to skip already-processed messages:
+
+```bash
+curl "http://localhost:7071/api/agent/stream/abc-123-def-456?cursor=1734649123456-0" \
+  -H "Accept: text/event-stream"
+```
+
+## How It Works
+
+### 1. Redis Callback
+
+The `RedisStreamCallback` class implements `AgentResponseCallbackProtocol` to capture streaming updates:
+
+```python
+class RedisStreamCallback(AgentResponseCallbackProtocol):
+    async def on_streaming_response_update(self, update, context):
+        # Write chunk to Redis Stream
+        async with await get_stream_handler() as handler:
+            await handler.write_chunk(thread_id, update.text, sequence)
+
+    async def on_agent_response(self, response, context):
+        # Write end-of-stream marker
+        async with await get_stream_handler() as handler:
+            await handler.write_completion(thread_id, sequence)
+```
+
+### 2. Custom Streaming Endpoint
+
+The `/api/agent/stream/{conversation_id}` endpoint reads from Redis:
+
+```python
+@app.route(route="agent/stream/{conversation_id}", methods=["GET"])
+async def stream(req):
+    conversation_id = req.route_params.get("conversation_id")
+    cursor = req.params.get("cursor")  # Optional
+
+    async with await get_stream_handler() as handler:
+        async for chunk in handler.read_stream(conversation_id, cursor):
+            # Format and return chunks
+```
+
+### 3. Redis Streams
+
+Messages are stored in Redis Streams with automatic TTL (default: 10 minutes):
+
+```
+Stream Key: agent-stream:{conversation_id}
+Entry: {
+  "text": "chunk content",
+  "sequence": "0",
+  "timestamp": "1734649123456"
+}
+```
@@ -0,0 +1,55 @@
+### Reliable Streaming with Redis - Demo HTTP Requests
+### Use with the VS Code REST Client extension or any HTTP client
+###
+### Workflow:
+### 1. POST /api/agents/{agentName}/run  -> Start durable agent (returns conversation_id)
+### 2. GET  /api/agent/stream/{id}       -> Read chunks from Redis (SSE or plain text)
+### 3. Add ?cursor={id} to resume from a specific point
+###
+### Prerequisites:
+### - Redis: docker run -d --name redis -p 6379:6379 redis:latest
+### - Start function app: func start
+
+### Variables
+@baseUrl = http://localhost:7071
+@agentName = TravelPlanner
+
+### Health Check
+GET {{baseUrl}}/api/health
+
+###
+
+### Start Agent Run
+# Starts the agent in the background via durable orchestration.
+# The RedisStreamCallback persists streaming chunks to Redis.
+# @name trip
+POST {{baseUrl}}/api/agents/{{agentName}}/run
+Content-Type: text/plain
+
+Plan a 3-day trip to Tokyo
+
+###
+
+### Stream from Redis (SSE format)
+# Reads persisted chunks from Redis using cursor-based pagination.
+# The conversation_id is automatically captured from the previous request.
+@conversationId = {{trip.response.body.$.conversation_id}}
+GET {{baseUrl}}/api/agent/stream/{{conversationId}}
+Accept: text/event-stream
+
+###
+
+### Stream from Redis (plain text)
+# Same as above, but returns plain text instead of SSE format
+GET {{baseUrl}}/api/agent/stream/{{conversationId}}
+Accept: text/plain
+
+###
+
+### Resume from cursor
+# Use a cursor ID from an SSE event to skip already-processed messages
+# Replace {cursor_id} with an actual entry ID from the SSE stream
+GET {{baseUrl}}/api/agent/stream/{{conversationId}}?cursor={cursor_id}
+Accept: text/event-stream
+
+###
@@ -0,0 +1,322 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Reliable streaming for durable agents using Redis Streams.
+
+This sample demonstrates how to implement reliable streaming for durable agents using Redis Streams.
+
+Components used in this sample:
+- AzureOpenAIChatClient to create the travel planner agent with tools.
+- AgentFunctionApp with a Redis-based callback for persistent streaming.
+- Custom HTTP endpoint to resume streaming from any point using cursor-based pagination.
+
+Prerequisites:
+- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_CHAT_DEPLOYMENT_NAME
+- Redis running (docker run -d --name redis -p 6379:6379 redis:latest)
+- DTS and Azurite running (see parent README)
+"""
+
+import logging
+import os
+from datetime import timedelta
+
+import redis.asyncio as aioredis
+from agent_framework import AgentRunResponseUpdate
+import azure.functions as func
+from agent_framework.azure import (
+    AgentCallbackContext,
+    AgentFunctionApp,
+    AgentResponseCallbackProtocol,
+    AzureOpenAIChatClient,
+)
+from azure.identity import AzureCliCredential
+
+from redis_stream_response_handler import RedisStreamResponseHandler, StreamChunk
+from tools import get_local_events, get_weather_forecast
+
+logger = logging.getLogger(__name__)
+
+# Configuration
+REDIS_CONNECTION_STRING = os.environ.get("REDIS_CONNECTION_STRING", "redis://localhost:6379")
+REDIS_STREAM_TTL_MINUTES = int(os.environ.get("REDIS_STREAM_TTL_MINUTES", "10"))
+
+async def get_stream_handler() -> RedisStreamResponseHandler:
+    """Create a new Redis stream handler for each request.
+
+    This avoids event loop conflicts in Azure Functions by creating
+    a fresh Redis client in the current event loop context.
+    """
+    # Create a new Redis client in the current event loop
+    redis_client = aioredis.from_url(
+        REDIS_CONNECTION_STRING,
+        encoding="utf-8",
+        decode_responses=False,
+    )
+
+    return RedisStreamResponseHandler(
+        redis_client=redis_client,
+        stream_ttl=timedelta(minutes=REDIS_STREAM_TTL_MINUTES),
+    )
+
+
+class RedisStreamCallback(AgentResponseCallbackProtocol):
+    """Callback that writes streaming updates to Redis Streams for reliable delivery.
+
+    This enables clients to disconnect and reconnect without losing messages.
+    """
+
+    def __init__(self) -> None:
+        self._logger = logging.getLogger("durableagent.samples.redis_streaming")
+        self._sequence_numbers = {}  # Track sequence per thread
+
+    async def on_streaming_response_update(
+        self,
+        update: AgentRunResponseUpdate,
+        context: AgentCallbackContext,
+    ) -> None:
+        """Write streaming update to Redis Stream.
+
+        Args:
+            update: The streaming response update chunk.
+            context: The callback context with thread_id, agent_name, etc.
+        """
+        thread_id = context.thread_id
+        if not thread_id:
+            self._logger.warning("No thread_id available for streaming update")
+            return
+
+        if not update.text:
+            return
+
+        text = update.text
+
+        # Get or initialize sequence number for this thread
+        if thread_id not in self._sequence_numbers:
+            self._sequence_numbers[thread_id] = 0
+
+        sequence = self._sequence_numbers[thread_id]
+
+        try:
+            # Use context manager to ensure Redis client is properly closed
+            async with await get_stream_handler() as stream_handler:
+                # Write chunk to Redis Stream using public API
+                await stream_handler.write_chunk(thread_id, text, sequence)
+
+                self._sequence_numbers[thread_id] += 1
+
+                self._logger.info(
+                    "[%s][%s] Wrote chunk to Redis: seq=%d, text=%s",
+                    context.agent_name,
+                    thread_id[:8],
+                    sequence,
+                    text,
+                )
+        except Exception as ex:
+            self._logger.error(f"Error writing to Redis stream: {ex}", exc_info=True)
+
+    async def on_agent_response(self, response, context: AgentCallbackContext) -> None:
+        """Write end-of-stream marker when agent completes.
+
+        Args:
+            response: The final agent response.
+            context: The callback context.
+        """
+        thread_id = context.thread_id
+        if not thread_id:
+            return
+
+        sequence = self._sequence_numbers.get(thread_id, 0)
+
+        try:
+            # Use context manager to ensure Redis client is properly closed
+            async with await get_stream_handler() as stream_handler:
+                # Write end-of-stream marker using public API
+                await stream_handler.write_completion(thread_id, sequence)
+
+                self._logger.info(
+                    "[%s][%s] Agent completed, wrote end-of-stream marker",
+                    context.agent_name,
+                    thread_id[:8],
+                )
+
+                # Clean up sequence tracker
+                self._sequence_numbers.pop(thread_id, None)
+        except Exception as ex:
+            self._logger.error(f"Error writing end-of-stream marker: {ex}", exc_info=True)
+
+
+# Create the Redis streaming callback
+redis_callback = RedisStreamCallback()
+
+
+# Create the travel planner agent
+def create_travel_agent():
+    """Create the TravelPlanner agent with tools."""
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
+        name="TravelPlanner",
+        instructions="""You are an expert travel planner who creates detailed, personalized travel itineraries.
+When asked to plan a trip, you should:
+1. Create a comprehensive day-by-day itinerary
+2. Include specific recommendations for activities, restaurants, and attractions
+3. Provide practical tips for each destination
+4. Consider weather and local events when making recommendations
+5. Include estimated times and logistics between activities
+
+Always use the available tools to get current weather forecasts and local events
+for the destination to make your recommendations more relevant and timely.
+
+Format your response with clear headings for each day and include emoji icons
+to make the itinerary easy to scan and visually appealing.""",
+        tools=[get_weather_forecast, get_local_events],
+    )
+
+
+# Create AgentFunctionApp with the Redis callback
+app = AgentFunctionApp(
+    agents=[create_travel_agent()],
+    enable_health_check=True,
+    default_callback=redis_callback,
+    max_poll_retries=100,  # Increase for longer-running agents
+)
+
+
+# Custom streaming endpoint for reading from Redis
+# Use the standard /api/agents/TravelPlanner/run endpoint to start agent runs
+
+
+@app.function_name("stream")
+@app.route(route="agent/stream/{conversation_id}", methods=["GET"])
+async def stream(req: func.HttpRequest) -> func.HttpResponse:
+    """Resume streaming from a specific cursor position for an existing session.
+
+    This endpoint reads all currently available chunks from Redis for the given
+    conversation ID, starting from the specified cursor (or beginning if no cursor).
+
+    Use this endpoint to resume a stream after disconnection. Pass the conversation ID
+    and optionally a cursor (Redis entry ID) to continue from where you left off.
+
+    Query Parameters:
+        cursor (optional): Redis stream entry ID to resume from. If not provided, starts from beginning.
+
+    Response Headers:
+        Content-Type: text/event-stream or text/plain based on Accept header
+        x-conversation-id: The conversation/thread ID
+
+    SSE Event Fields (when Accept: text/event-stream):
+        id: Redis stream entry ID (use as cursor for resumption)
+        event: "message" for content, "done" for completion, "error" for errors
+        data: The text content or status message
+    """
+    try:
+        conversation_id = req.route_params.get("conversation_id")
+        if not conversation_id:
+            return func.HttpResponse(
+                "Conversation ID is required.",
+                status_code=400,
+            )
+
+        # Get optional cursor from query string
+        cursor = req.params.get("cursor")
+
+        logger.info(
+            f"Resuming stream for conversation {conversation_id} from cursor: {cursor or '(beginning)'}"
+        )
+
+        # Check Accept header to determine response format
+        accept_header = req.headers.get("Accept", "")
+        use_sse_format = "text/plain" not in accept_header.lower()
+
+        # Stream chunks from Redis
+        return await _stream_to_client(conversation_id, cursor, use_sse_format)
+
+    except Exception as ex:
+        logger.error(f"Error in stream endpoint: {ex}", exc_info=True)
+        return func.HttpResponse(
+            f"Internal server error: {str(ex)}",
+            status_code=500,
+        )
+
+
+async def _stream_to_client(
+    conversation_id: str,
+    cursor: str | None,
+    use_sse_format: bool,
+) -> func.HttpResponse:
+    """Stream chunks from Redis to the HTTP response.
+
+    Args:
+        conversation_id: The conversation ID to stream from.
+        cursor: Optional cursor to resume from. If None, streams from the beginning.
+        use_sse_format: True to use SSE format, false for plain text.
+
+    Returns:
+        HTTP response with all currently available chunks.
+    """
+    chunks = []
+
+    # Use context manager to ensure Redis client is properly closed
+    async with await get_stream_handler() as stream_handler:
+        try:
+            async for chunk in stream_handler.read_stream(conversation_id, cursor):
+                if chunk.error:
+                    logger.warning(f"Stream error for {conversation_id}: {chunk.error}")
+                    chunks.append(_format_error(chunk.error, use_sse_format))
+                    break
+
+                if chunk.is_done:
+                    chunks.append(_format_end_of_stream(chunk.entry_id, use_sse_format))
+                    break
+
+                if chunk.text:
+                    chunks.append(_format_chunk(chunk, use_sse_format))
+
+        except Exception as ex:
+            logger.error(f"Error reading from Redis: {ex}", exc_info=True)
+            chunks.append(_format_error(str(ex), use_sse_format))
+
+    # Return all chunks
+    response_body = "".join(chunks)
+
+    return func.HttpResponse(
+        body=response_body,
+        mimetype="text/event-stream" if use_sse_format else "text/plain; charset=utf-8",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "x-conversation-id": conversation_id,
+        },
+    )
+
+
+def _format_chunk(chunk: StreamChunk, use_sse_format: bool) -> str:
+    """Format a text chunk."""
+    if use_sse_format:
+        return _format_sse_event("message", chunk.text, chunk.entry_id)
+    else:
+        return chunk.text
+
+
+def _format_end_of_stream(entry_id: str, use_sse_format: bool) -> str:
+    """Format end-of-stream marker."""
+    if use_sse_format:
+        return _format_sse_event("done", "[DONE]", entry_id)
+    else:
+        return "\n"
+
+
+def _format_error(error: str, use_sse_format: bool) -> str:
+    """Format error message."""
+    if use_sse_format:
+        return _format_sse_event("error", error, None)
+    else:
+        return f"\n[Error: {error}]\n"
+
+
+def _format_sse_event(event_type: str, data: str, event_id: str | None = None) -> str:
+    """Format a Server-Sent Event."""
+    lines = []
+    if event_id:
+        lines.append(f"id: {event_id}")
+    lines.append(f"event: {event_type}")
+    lines.append(f"data: {data}")
+    lines.append("")
+    return "\n".join(lines) + "\n"
@@ -7,6 +7,8 @@
    "TASKHUB_NAME": "default",
    "AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
    "AZURE_OPENAI_CHAT_DEPLOYMENT_NAME": "<AZURE_OPENAI_CHAT_DEPLOYMENT_NAME>",
-    "AZURE_OPENAI_API_KEY": "<AZURE_OPENAI_API_KEY>"
+    "AZURE_OPENAI_API_KEY": "<AZURE_OPENAI_API_KEY>",
+    "REDIS_CONNECTION_STRING": "redis://localhost:6379",
+    "REDIS_STREAM_TTL_MINUTES": "10"
  }
 }
@@ -0,0 +1,200 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Redis-based streaming response handler for durable agents.
+
+This module provides reliable, resumable streaming of agent responses using Redis Streams
+as a message broker. It enables clients to disconnect and reconnect without losing messages.
+"""
+
+import asyncio
+import time
+from dataclasses import dataclass
+from datetime import timedelta
+from collections.abc import AsyncIterator
+
+import redis.asyncio as aioredis
+
+
+@dataclass
+class StreamChunk:
+    """Represents a chunk of streamed data from Redis.
+
+    Attributes:
+        entry_id: The Redis stream entry ID (used as cursor for resumption).
+        text: The text content of the chunk, if any.
+        is_done: Whether this is the final chunk in the stream.
+        error: Error message if an error occurred, otherwise None.
+    """
+    entry_id: str
+    text: str | None = None
+    is_done: bool = False
+    error: str | None = None
+
+
+class RedisStreamResponseHandler:
+    """Handles agent responses by persisting them to Redis Streams.
+
+    This handler writes agent response updates to Redis Streams, enabling reliable,
+    resumable streaming delivery to clients. Clients can disconnect and reconnect
+    at any point using cursor-based pagination.
+
+    Attributes:
+        MAX_EMPTY_READS: Maximum number of empty reads before timing out.
+        POLL_INTERVAL_MS: Interval in milliseconds between polling attempts.
+    """
+
+    MAX_EMPTY_READS = 300
+    POLL_INTERVAL_MS = 1000
+
+    def __init__(self, redis_client: aioredis.Redis, stream_ttl: timedelta):
+        """Initialize the Redis stream response handler.
+
+        Args:
+            redis_client: The async Redis client instance.
+            stream_ttl: Time-to-live for stream entries in Redis.
+        """
+        self._redis = redis_client
+        self._stream_ttl = stream_ttl
+
+    async def __aenter__(self):
+        """Enter async context manager."""
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        """Exit async context manager and close Redis connection."""
+        await self._redis.aclose()
+
+    async def write_chunk(
+        self,
+        conversation_id: str,
+        text: str,
+        sequence: int,
+    ) -> None:
+        """Write a single text chunk to the Redis Stream.
+
+        Args:
+            conversation_id: The conversation ID for this agent run.
+            text: The text content to write.
+            sequence: The sequence number for ordering.
+        """
+        stream_key = self._get_stream_key(conversation_id)
+        await self._redis.xadd(
+            stream_key,
+            {
+                "text": text,
+                "sequence": str(sequence),
+                "timestamp": str(int(time.time() * 1000)),
+            }
+        )
+        await self._redis.expire(stream_key, self._stream_ttl)
+
+    async def write_completion(
+        self,
+        conversation_id: str,
+        sequence: int,
+    ) -> None:
+        """Write an end-of-stream marker to the Redis Stream.
+
+        Args:
+            conversation_id: The conversation ID for this agent run.
+            sequence: The final sequence number.
+        """
+        stream_key = self._get_stream_key(conversation_id)
+        await self._redis.xadd(
+            stream_key,
+            {
+                "text": "",
+                "sequence": str(sequence),
+                "timestamp": str(int(time.time() * 1000)),
+                "done": "true",
+            }
+        )
+        await self._redis.expire(stream_key, self._stream_ttl)
+
+    async def read_stream(
+        self,
+        conversation_id: str,
+        cursor: str | None = None,
+    ) -> AsyncIterator[StreamChunk]:
+        """Read entries from a Redis Stream with cursor-based pagination.
+
+        This method polls the Redis Stream for new entries, yielding chunks as they
+        become available. Clients can resume from any point using the entry_id from
+        a previous chunk.
+
+        Args:
+            conversation_id: The conversation ID to read from.
+            cursor: Optional cursor to resume from. If None, starts from beginning.
+
+        Yields:
+            StreamChunk instances containing text content or status markers.
+        """
+        stream_key = self._get_stream_key(conversation_id)
+        start_id = cursor if cursor else "0-0"
+
+        empty_read_count = 0
+        has_seen_data = False
+
+        while True:
+            try:
+                # Read up to 100 entries from the stream
+                entries = await self._redis.xread(
+                    {stream_key: start_id},
+                    count=100,
+                    block=None,
+                )
+
+                if not entries:
+                    # No entries found
+                    if not has_seen_data:
+                        empty_read_count += 1
+                        if empty_read_count >= self.MAX_EMPTY_READS:
+                            timeout_seconds = self.MAX_EMPTY_READS * self.POLL_INTERVAL_MS / 1000
+                            yield StreamChunk(
+                                entry_id=start_id,
+                                error=f"Stream not found or timed out after {timeout_seconds} seconds"
+                            )
+                            return
+
+                    # Wait before polling again
+                    await asyncio.sleep(self.POLL_INTERVAL_MS / 1000)
+                    continue
+
+                has_seen_data = True
+
+                # Process entries from the stream
+                for stream_name, stream_entries in entries:
+                    for entry_id, entry_data in stream_entries:
+                        start_id = entry_id.decode() if isinstance(entry_id, bytes) else entry_id
+
+                        # Decode entry data
+                        text = entry_data.get(b"text", b"").decode() if b"text" in entry_data else None
+                        done = entry_data.get(b"done", b"").decode() if b"done" in entry_data else None
+                        error = entry_data.get(b"error", b"").decode() if b"error" in entry_data else None
+
+                        if error:
+                            yield StreamChunk(entry_id=start_id, error=error)
+                            return
+
+                        if done == "true":
+                            yield StreamChunk(entry_id=start_id, is_done=True)
+                            return
+
+                        if text:
+                            yield StreamChunk(entry_id=start_id, text=text)
+
+            except Exception as ex:
+                yield StreamChunk(entry_id=start_id, error=str(ex))
+                return
+
+    @staticmethod
+    def _get_stream_key(conversation_id: str) -> str:
+        """Generate the Redis key for a conversation's stream.
+
+        Args:
+            conversation_id: The conversation ID.
+
+        Returns:
+            The Redis stream key.
+        """
+        return f"agent-stream:{conversation_id}"
@@ -1,2 +1,3 @@
 agent-framework-azurefunctions
-azure-identity
+azure-identity
+redis
@@ -0,0 +1,165 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Mock travel tools for demonstration purposes.
+
+In a real application, these would call actual weather and events APIs.
+"""
+
+from typing import Annotated
+
+
+def get_weather_forecast(
+    destination: Annotated[str, "The destination city or location"],
+    date: Annotated[str, 'The date for the forecast (e.g., "2025-01-15" or "next Monday")'],
+) -> str:
+    """Get the weather forecast for a destination on a specific date.
+
+    Use this to provide weather-aware recommendations in the itinerary.
+
+    Args:
+        destination: The destination city or location.
+        date: The date for the forecast.
+
+    Returns:
+        A weather forecast summary.
+    """
+    # Mock weather data based on destination for realistic responses
+    weather_by_region = {
+        "Tokyo": ("Partly cloudy with a chance of light rain", 58, 45),
+        "Paris": ("Overcast with occasional drizzle", 52, 41),
+        "New York": ("Clear and cold", 42, 28),
+        "London": ("Foggy morning, clearing in afternoon", 48, 38),
+        "Sydney": ("Sunny and warm", 82, 68),
+        "Rome": ("Sunny with light breeze", 62, 48),
+        "Barcelona": ("Partly sunny", 59, 47),
+        "Amsterdam": ("Cloudy with light rain", 46, 38),
+        "Dubai": ("Sunny and hot", 85, 72),
+        "Singapore": ("Tropical thunderstorms in afternoon", 88, 77),
+        "Bangkok": ("Hot and humid, afternoon showers", 91, 78),
+        "Los Angeles": ("Sunny and pleasant", 72, 55),
+        "San Francisco": ("Morning fog, afternoon sun", 62, 52),
+        "Seattle": ("Rainy with breaks", 48, 40),
+        "Miami": ("Warm and sunny", 78, 65),
+        "Honolulu": ("Tropical paradise weather", 82, 72),
+    }
+
+    # Find a matching destination or use a default
+    forecast = ("Partly cloudy", 65, 50)
+    for city, weather in weather_by_region.items():
+        if city.lower() in destination.lower():
+            forecast = weather
+            break
+
+    condition, high_f, low_f = forecast
+    high_c = (high_f - 32) * 5 // 9
+    low_c = (low_f - 32) * 5 // 9
+
+    recommendation = _get_weather_recommendation(condition)
+
+    return f"""Weather forecast for {destination} on {date}:
+Conditions: {condition}
+High: {high_f}°F ({high_c}°C)
+Low: {low_f}°F ({low_c}°C)
+
+Recommendation: {recommendation}"""
+
+
+def get_local_events(
+    destination: Annotated[str, "The destination city or location"],
+    date: Annotated[str, 'The date to search for events (e.g., "2025-01-15" or "next week")'],
+) -> str:
+    """Get local events and activities happening at a destination around a specific date.
+
+    Use this to suggest timely activities and experiences.
+
+    Args:
+        destination: The destination city or location.
+        date: The date to search for events.
+
+    Returns:
+        A list of local events and activities.
+    """
+    # Mock events data based on destination
+    events_by_city = {
+        "Tokyo": [
+            "🎭 Kabuki Theater Performance at Kabukiza Theatre - Traditional Japanese drama",
+            "🌸 Winter Illuminations at Yoyogi Park - Spectacular light displays",
+            "🍜 Ramen Festival at Tokyo Station - Sample ramen from across Japan",
+            "🎮 Gaming Expo at Tokyo Big Sight - Latest video games and technology",
+        ],
+        "Paris": [
+            "🎨 Impressionist Exhibition at Musée d'Orsay - Extended evening hours",
+            "🍷 Wine Tasting Tour in Le Marais - Local sommelier guided",
+            "🎵 Jazz Night at Le Caveau de la Huchette - Historic jazz club",
+            "🥐 French Pastry Workshop - Learn from master pâtissiers",
+        ],
+        "New York": [
+            "🎭 Broadway Show: Hamilton - Limited engagement performances",
+            "🏀 Knicks vs Lakers at Madison Square Garden",
+            "🎨 Modern Art Exhibit at MoMA - New installations",
+            "🍕 Pizza Walking Tour of Brooklyn - Artisan pizzerias",
+        ],
+        "London": [
+            "👑 Royal Collection Exhibition at Buckingham Palace",
+            "🎭 West End Musical: The Phantom of the Opera",
+            "🍺 Craft Beer Festival at Brick Lane",
+            "🎪 Winter Wonderland at Hyde Park - Rides and markets",
+        ],
+        "Sydney": [
+            "🏄 Pro Surfing Competition at Bondi Beach",
+            "🎵 Opera at Sydney Opera House - La Bohème",
+            "🦘 Wildlife Night Safari at Taronga Zoo",
+            "🍽️ Harbor Dinner Cruise with fireworks",
+        ],
+        "Rome": [
+            "🏛️ After-Hours Vatican Tour - Skip the crowds",
+            "🍝 Pasta Making Class in Trastevere",
+            "🎵 Classical Concert at Borghese Gallery",
+            "🍷 Wine Tasting in Roman Cellars",
+        ],
+    }
+
+    # Find events for the destination or use generic events
+    events = [
+        "🎭 Local theater performance",
+        "🍽️ Food and wine festival",
+        "🎨 Art gallery opening",
+        "🎵 Live music at local venues",
+    ]
+
+    for city, city_events in events_by_city.items():
+        if city.lower() in destination.lower():
+            events = city_events
+            break
+
+    event_list = "\n• ".join(events)
+    return f"""Local events in {destination} around {date}:
+
+• {event_list}
+
+💡 Tip: Book popular events in advance as they may sell out quickly!"""
+
+
+def _get_weather_recommendation(condition: str) -> str:
+    """Get a recommendation based on weather conditions.
+
+    Args:
+        condition: The weather condition description.
+
+    Returns:
+        A recommendation string.
+    """
+    condition_lower = condition.lower()
+
+    if "rain" in condition_lower or "drizzle" in condition_lower:
+        return "Bring an umbrella and waterproof jacket. Consider indoor activities for backup."
+    elif "fog" in condition_lower:
+        return "Morning visibility may be limited. Plan outdoor sightseeing for afternoon."
+    elif "cold" in condition_lower:
+        return "Layer up with warm clothing. Hot drinks and cozy cafés recommended."
+    elif "hot" in condition_lower or "warm" in condition_lower:
+        return "Stay hydrated and use sunscreen. Plan strenuous activities for cooler morning hours."
+    elif "thunder" in condition_lower or "storm" in condition_lower:
+        return "Keep an eye on weather updates. Have indoor alternatives ready."
+    else:
+        return "Pleasant conditions expected. Great day for outdoor exploration!"
Author	SHA1	Message	Date
Evan MattsonandGitHub	e9d97ce6b7	Python: fix(azure-ai): Fix response_format handling for structured outputs (#3114 ) * fix(azure-ai): read response_format from chat_options instead of run_options * refactor: use explicit None checks for response_format * Fix mypy error * Mypy fix	2026-01-07 23:11:28 +00:00
Gavin AguiarandGitHub	f4ab586f11	Python: Streaming sample for azurefunctions (#3057 ) * Streaming sample for azurefunctions * Fixed links and sample name * Addressed feedback * Addressed feedback * Fixed integration tests * Updated test	2026-01-07 22:20:42 +00:00
Eduard van ValkenburgandGitHub	a118fd5c07	updated templates (#3106 ) * updated templates * enabled blank and fixed triage * made language optional and moved to the bottom for features	2026-01-07 15:39:31 +00:00
Mark WallaceandGitHub	521f04632d	Enable blank issues in issue template configuration Need to re-enable creating blank issues	2026-01-07 14:55:43 +00:00
westey GitHub Copilot	dd69cabc67	.NET: Seal factory contexts and add non JSO deserialize overloads (#3066 ) * Seal factory contexts and add non JSO deserialize overloads * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>	2026-01-07 11:40:39 +00:00
Victor DibiaandGitHub	2e1189ca65	Python: Improve DevUI, add Context Inspector view as new tab under traces (#2742 ) * Improve DevUI, add Context Inspector view as new tab under traces * fix mypy errors * fix: Handle stale MCP connections in DevUI executor MCP tools can become stale when HTTP streaming responses end - the underlying stdio streams close but `is_connected` remains True. This causes subsequent requests to fail with `ClosedResourceError`. Add `_ensure_mcp_connections()` to detect and reconnect stale MCP tools before agent execution. This is a workaround for an upstream Agent Framework issue where connection state isn't properly tracked. Fixes MCP tools failing on second HTTP request in DevUI. fixes #1476 #1515 #2865 * fix #1572 report import dependency errors more clearly * Ensure there is streaming toggle where users can select streaming vs non streaming mode in devui . Fixes .NET: [Python] DevUI tool call rendering in non-streaming mode? * remove unused dead code * improve ux - workflows with agents show a chat component in execution timelien, also ensure magentic final output shows correctly * update ui build * update devui to use instrumentation instead of tracing, other instrumentation and type/instance check fixes	2026-01-07 08:26:08 +00:00
claude89757andGitHub	db283cd396	Python: Fix MCP tool result serialization for list[TextContent] (#2523 ) * Fix MCP tool result serialization for list[TextContent] When MCP tools return results containing list[TextContent], they were incorrectly serialized to object repr strings like: '[<agent_framework._types.TextContent object at 0x...>]' This fix properly extracts text content from list items by: 1. Checking if items have a 'text' attribute (TextContent) 2. Using model_dump() for items that support it 3. Falling back to str() for other types 4. Joining single items as plain text, multiple items as JSON array Fixes #2509 * Address PR review feedback for MCP tool result serialization - Extract serialize_content_result() to shared _utils.py - Fix logic: use texts[0] instead of join for single item - Add type annotation: texts: list[str] = [] - Return empty string for empty list instead of '[]' - Move import json to file top level - Add comprehensive unit tests for serialization * Address PR review feedback: fix type checking and double serialization - Add isinstance(item.text, str) check to ensure text attribute is a string - Fix double-serialization issue by keeping model_dump results as dicts until final json.dumps (removes escaped JSON strings in arrays) - Improve docstring with detailed return value documentation - Add test for non-string text attribute handling - Add tests for list type tool results in _events.py path * Simplify PR: minimal changes to fix MCP tool result serialization Addresses reviewer feedback about excessive refactoring: - Reset _events.py to original structure - Only add import and use serialize_content_result in one location - All review comments addressed in serialize_content_result(): - Added isinstance(item.text, str) check - Use model_dump(mode="json") to avoid double-serialization - Improved docstring with explicit return value documentation - Empty list returns "" instead of "[]" * Refactor: Move MCP TextContent serialization to core prepare_function_call_results Per reviewer feedback, moved the TextContent serialization logic from ag-ui's serialize_content_result to the core package's prepare_function_call_results function. Changes: - Added handling for objects with 'text' attribute (like MCP TextContent) in _prepare_function_call_results_as_dumpable - Removed serialize_content_result from ag-ui/_utils.py - Updated _events.py and _message_adapters.py to use prepare_function_call_results from core package - Updated tests to match the core function's behavior * Fix failing tests for prepare_function_call_results behavior - test_tool_result_with_none: Update expected value to 'null' (JSON serialization of None) - test_tool_result_with_model_dump_objects: Use Pydantic BaseModel instead of plain class * Fix B903 linter error: Convert MockTextContent to dataclass The ruff linter was reporting B903 (class could be dataclass or namedtuple) for the MockTextContent test helper classes. This commit converts them to dataclasses to satisfy the linter check.	2026-01-07 00:47:26 +00:00
Evan MattsonandGitHub	f49e537721	Bump Bedrock version to latest (#3110 )	2026-01-07 09:34:02 +09:00
Evan MattsonandGitHub	202f557c71	Bump versions to 1.0.0b260106 for a release. Update CHANGELOG.md (#3109 )	2026-01-07 00:09:49 +00:00