## Why are these changes needed?

The existing run_stream methods used fragile count-based logic (count <=
len(task)) to skip task messages during streaming. This approach was
brittle and broke when team structure changed or task composition
varied, particularly affecting SocietyOfMindAgent's ability to properly
encapsulate inner team messages.

This PR adds an output_task_messages parameter to run_stream methods to
provide explicit control over task message inclusion in streams,
replacing the fragile count-based logic with robust message filtering.

## Related issue number

Closes #6150

## Checks

- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests corresponding to the changes introduced in this
PR.
- [x] I've made sure all auto checks have passed.

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

## Why are these changes needed?

I added `created_at` to both BaseChatMessage and BaseAgentEvent classes
that store the time these Pydantic model instances are generated. And
then users will be able to use `created_at` to build up a customized
external persisting state management layer for their case.

## Related issue number


https://github.com/microsoft/autogen/discussions/6169#discussioncomment-13151540

## Checks

- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.

---------

Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->

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If you don't have the access to it, we will shortly find a reviewer and
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## Why are these changes needed?

Will the changes made in
https://github.com/microsoft/autogen/pull/5853/files and this PR need to
be ported to the worker_runtime as well?
Resolves https://github.com/microsoft/autogen/issues/5894

## Related issue number

https://github.com/microsoft/autogen/issues/5894

## Checks

- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.

## Why are these changes needed?
This PR enhances the `SelectorGroupChat` class by introducing a new
`model_context` parameter to support more context-aware speaker
selection.

### Changes
- Added a `model_context: ChatCompletionContext | None` parameter to
`SelectorGroupChat`.
- Defaulted to `UnboundedChatCompletionContext` when None is provided
like `AssistantAgent`.
- Updated `_select_speaker` to prepend context messages from
`model_context` to the main thread history.
- Refactored history construction into a helper method
`construct_message_history`.

## Related issue number
Closes [Issue #6301](https://github.com/org/repo/issues/6301), enabling
the group chat manager to utilize `model_context` for richer, more
informed speaker selection decisions.

## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.

---------

Signed-off-by: Abhijeetsingh Meena <abhijeet040403@gmail.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

## Why are these changes needed?

| Package | Test time-Origin (Sec) | Test time-Edited (Sec) |

|-------------------------|------------------|-----------------------------------------------|
| autogen-studio          | 1.64             | 1.64 |
| autogen-core            | 6.03             | 6.17 |
| autogen-ext             | 387.15           | 373.40 |
| autogen-agentchat       | 54.20            | 20.67 |


## Related issue number

Related #6361 

## Checks

- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.

## Why are these changes needed?

This PR updates `SelectorGroupChat` to support streaming mode for
`select_speaker`.
It introduces a `streaming` argument — when set to `True`,
`select_speaker` will use `create_streaming()` instead of `create()`.

## Additional context

Some models (e.g., QwQ) only work properly in streaming mode.  
To support them, the prompt selection step in `SelectorGroupChat` must
also run with `streaming=True`.

## Related issue number

Closes #6145

## Checks

- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Add an option emit_team_events to BaseGroupChat to emit events from
group chat manager through run_stream.
SpeakerSelectedEvent from group chat speaker selection.

Closes #6161

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Added support for structured message component using the Json to
Pydantic utility functions. Note: also adding the ability to use a
format string for structured messages.

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Resolves #5851

* Added GroupChatError event type and terminate a run when an error
occurs in either a participant or the group chat manager
* Raise a RuntimeError from the error message within the group chat run

Rename the `ChatMessage` and `AgentEvent` base classes to `BaseChatMessage` and `BaseAgentEvent`. 

Bring back the `ChatMessage` and `AgentEvent` as union of built-in concrete types to avoid breaking existing applications that depends on Pydantic serialization. 

Why?

Many existing code uses containers like this:

```python
class AppMessage(BaseModel):
   name: str
   message: ChatMessage 

# Serialization is this:
m = AppMessage(...)
m.model_dump_json()

# Fields like HandoffMessage.target will be lost because it is now treated as a base class without content or target fields.
```

The assumption on `ChatMessage` or `AgentEvent` to be a union of concrete types could be in many existing code bases. So this PR brings back the union types, while keep method type hints such as those on `on_messages` to use the `BaseChatMessage` and `BaseAgentEvent` base classes for flexibility.

This PR refactored `AgentEvent` and `ChatMessage` union types to
abstract base classes. This allows for user-defined message types that
subclass one of the base classes to be used in AgentChat.

To support a unified interface for working with the messages, the base
classes added abstract methods for:
- Convert content to string
- Convert content to a `UserMessage` for model client
- Convert content for rendering in console.
- Dump into a dictionary
- Load and create a new instance from a dictionary

This way, all agents such as `AssistantAgent` and `SocietyOfMindAgent`
can utilize the unified interface to work with any built-in and
user-defined message type.

This PR also introduces a new message type, `StructuredMessage` for
AgentChat (Resolves #5131), which is a generic type that requires a
user-specified content type.

You can create a `StructuredMessage` as follow:

```python

class MessageType(BaseModel):
  data: str
  references: List[str]

message = StructuredMessage[MessageType](content=MessageType(data="data", references=["a", "b"]), source="user")

# message.content is of type `MessageType`. 
```

This PR addresses the receving side of this message type. To produce
this message type from `AssistantAgent`, the work continue in #5934.

Added unit tests to verify this message type works with agents and
teams.

## Summary of Changes
- Added 'candidate_func' to 'SelectorGroupChat' to narrow-down the pool
of candidate speakers.
- Introduced a test in tests/test_group_chat_endpoint.py to validate its
functionality.
- Updated the selector group chat user guide with an example
demonstrating 'candidate_func'.

## Why are these changes needed?
- These changes adds a new parameter `candidate_func` to
`SelectorGroupChat` that helps user narrow-down the set of agents for
speaker selection, allowing users to automatically select next speaker
from a smaller pool of agents.

## Related issue number
Closes #5828

## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.

---------

Signed-off-by: Abhijeetsingh Meena <abhijeet040403@gmail.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Resolves #4075

1. Introduce custom runtime parameter for all AgentChat teams
(RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making
sure each team's topics are isolated from other teams, and decoupling
state from agent identities. Also, I removed the closure agent from the
BaseGroupChat and use the group chat manager agent to relay messages to
the output message queue.
2. Added unit tests to test scenarios with custom runtimes by using
pytest fixture
3. Refactored existing unit tests to use ReplayChatCompletionClient with
a few improvements to the client.
4. Fix a one-liner bug in AssistantAgent that caused deserialized agent
to have handoffs.

How to use it? 

```python
import asyncio
from autogen_core import SingleThreadedAgentRuntime
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.conditions import TextMentionTermination
from autogen_ext.models.replay import ReplayChatCompletionClient

async def main() -> None:
    # Create a runtime
    runtime = SingleThreadedAgentRuntime()
    runtime.start()

    # Create a model client.
    model_client = ReplayChatCompletionClient(
        ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"],
    )

    # Create agents
    agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.")
    agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.")

    # Create a termination condition
    termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"])

    # Create a team
    team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition)

    # Run the team
    stream = team.run_stream(task="Count to 10.")
    async for message in stream:
        print(message)
    
    # Save the state.
    state = await team.save_state()

    # Load the state to an existing team.
    await team.load_state(state)

    # Run the team again
    model_client.reset()
    stream = team.run_stream(task="Count to 10.")
    async for message in stream:
        print(message)

    # Create a new team, with the same agent names.
    agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.")
    agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.")
    new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition)

    # Load the state to the new team.
    await new_team.load_state(state)

    # Run the new team
    model_client.reset()
    new_stream = new_team.run_stream(task="Count to 10.")
    async for message in new_stream:
        print(message)
    
    # Stop the runtime
    await runtime.stop()

asyncio.run(main())
```

TODOs as future PRs:
1. Documentation.
2. How to handle errors in custom runtime when the agent has exception?

---------

Co-authored-by: Ryan Sweet <rysweet@microsoft.com>

<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->

<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->

## Why are these changes needed?

<!-- Please give a short summary of the change and the problem this
solves. -->

The PR introduces two changes.

The first change is adding a name attribute to
`FunctionExecutionResult`. The motivation is that semantic kernel
requires it for their function result interface and it seemed like a
easy modification as `FunctionExecutionResult` is always created in the
context of a `FunctionCall` which will contain the name. I'm unsure if
there was a motivation to keep it out but this change makes it easier to
trace which tool the result refers to and also increases api
compatibility with SK.

The second change is an update to how messages are mapped from autogen
to semantic kernel, which includes an update/fix in the processing of
function results.

## Related issue number

<!-- For example: "Closes #1234" -->

Related to #5675 but wont fix the underlying issue of anthropic
requiring tools during AssistantAgent reflection.

## Checks

- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.

---------

Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>

Closes #4904 

Does not change default behavior in core.

In agentchat, this change will mean that exceptions that used to be
ignored and result in bugs like the group chat stopping are now reported
out to the user application.

---------

Co-authored-by: Ben Constable <benconstable@microsoft.com>
Co-authored-by: Ryan Sweet <rysweet@microsoft.com>

Some LLMs recieve an explicit signal about tool use failures. 

Closes #5273

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Don't throw an exception when model makes a mistake. Use retries, and if
not succeeding after a fixed attempts, fall back to the previous sepaker
if available, or the first participant.

Resolves #5453

* initial pass on making group chats declarative

* update group chat tests

* update impl to include participant serialization for all teams

* v1 making soc declarative

* update memory test

* update chatagent and team base classes

* update serialization doc notebook

* fomating updates

* Pass context between AssistantAgent for handoffs

* Add parallel tool call test

---------

Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>

* Refine types in agentchat

* importg

* fix mypy

* Decouple model_context from AssistantAgent

* add UnboundedBufferedChatCompletionContext to mimic pervious model_context behaviour on AssistantAgent

* moving unbounded buffered chat to a different file

* fix model_context assertions in test_group_chat

* Refactor model context, introduce states

* fixes

* update

---------

Co-authored-by: aditya.kurniawan <aditya.kurniawan@core42.ai>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Co-authored-by: Victor Dibia <victordibia@microsoft.com>

* Adding ToolCallResultSummaryMessage

* Support for ToolCallResultSummaryMessage

* Added ToolCallSummaryMessage

* ruff format

* Add ToolCallSummaryMessage to ChatMessage

* typing and tests for ToolCallSummaryMessage

* PR Feedback

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Co-authored-by: Hussein Mozannar <hmozannar@microsoft.com>

* Define AgentEvent, rename tool call messages to events.

* update doc

* Use AgentEvent | ChatMessage to replace AgentMessage

* Update docs

* update deprecation notice

* remove unused

* fix doc

* format

* feat: add support for list of messages as team task input
* Update society of mind agent to use the list input task
---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* add models.openai namespace

* refactor tools namespace

* update lock file

* revert pyproject changes

* update docs and add cast

* update ext models doc ref

* increase underline

* add reply models namespace

* update imports

* fix test

* linting

* fix missing conflicts

* revert pydantic changes

* rename to replay

* replay

* fix reply

* Fix test

* formatting

* example

---------

Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>
Co-authored-by: Jack Gerrits <jack@jackgerrits.com>
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>

* 1 tool call iteration default

* handoff first

* return_only_response

* add and remove tools

* print out tool calls

* pass checks

* fix issues

* add test

* add unit tests

* remove extra print

* Update python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* documentation and none max_tools_calls

* Always limit # tool call to 1

* Update notebooks for the changing behavior of assistant agent.

* Merge branch 'main' into assistant_Agent_tools

* add reflect_on_tool_use parameter to format the tool call result

* wip

* wip

* fix pyright

* Add unit tests

* Merge remote-tracking branch 'origin/main' into assistant_Agent_tools

* Update with custom formatting of tool call summary

* format

* Merge branch 'main' into assistant_Agent_tools

* Move model context out of components

* move models out of components

* rename docs file

1. convert dataclass types to pydantic basemodel 
2. add save_state and load_state for ChatAgent
3. state types for AgentChat
---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Flatten core base and components

* remove extra files

* dont export from deprecated locations

* format

* fmt

* Propagate team cancellation token in agentchat

* Docs

---------

Co-authored-by: Ryan Sweet <rysweet@microsoft.com>

* Console to return last processed (#4277)

* Preserve input generator type

* Add tests

* format

---------

Co-authored-by: Jack Gerrits <jack@jackgerrits.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* task can be ChatMessage; add group chat state validation step, and address swarm state valiation; change handling of start and reset to RPC to capture any error.

* Update tutorial note

* fix select speaker for swarm

* Fix max-turn = 1 for swarm

* Max turn parameter for group chats

* Add note no usage

* Add task type that are messages to enable multi-modal tasks.

* fix test

* AgentChat pause and resume a task
Resolves #3859

* Add

* Update usage

* Update usage

* WIP to address stateful group chat

* Refactor group chat to add reset and flags for running

* documentation

* Agentchat refactor

* Move termination stop message to a separate field in task result

* Update quick start example

* Use string stop reason instead of stop message in task result for simpler API

* Use main function

* Termination condition as part of constructor

* Update doc

* Update notebooks

* AssistantAgent no longer sends out StopMessage. We use TextMentionTermination("TERMINATE") on the team instead for default setting.

* Fix test