Introduce validation for the ModelInfo dictionary to ensure required
fields are present.

Resolves #5501

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## Why are these changes needed?

Make
[PythonCodeExecutionTool](https://github.com/microsoft/autogen/blob/main/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/_code_execution.py)
declarative so it can be used in tools like AGS

Summary of changes

- Make CodeExecutor declarative (convert from Protocol to ABC, inherit
from ComponentBase)
- Make LocalCommandLineCodeExecutor, JupyterCodeExecutor and
DockerCommandLineCodeExecutor declarative , best effort. Not all fields
are serialized, warnings are shown where appropriate.
- Make PythonCodeExecutionTool declarative.

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## Related issue number

Closes #5526 
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Resolves #4447

For `openai` client's structured output support is through its beta
client, which requires the function JSON schema to be strict when in
structured output mode.

Reference:
https://platform.openai.com/docs/guides/function-calling#strict-mode

Right now we rely on opening the channel to associate a ClientId with an
entry on the gateway side. This causes a race when the channel is being
opened in the background while an RPC (e.g. MyAgent.register()) is
invoked.

If the RPC is processed first, the gateway rejects it due to "invalid"
clientId.

This fix makes this condition less likely to trigger, but there is still
a piece of the puzzle that needs to be solved on the Gateway side.

Closes #5297

---------

Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
Co-authored-by: Jacob Alber <jaalber@microsoft.com>
Co-authored-by: Jacob Alber <jacob.alber@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Add the following additional configuration options to
DockerCommandLineCodeExectutor:

- **extra_volumes** (Optional[Dict[str, Dict[str, str]]], optional): A
dictionary of extra volumes (beyond the work_dir) to mount to the
container. Defaults to None.
- **extra_hosts** (Optional[Dict[str, str]], optional): A dictionary of
host mappings to add to the container. (See Docker docs on extra_hosts)
Defaults to None.
- **init_command** (Optional[str], optional): A shell command to run
before each shell operation execution. Defaults to None. 

## Why are these changes needed?

See linked issue below.

In summary: Enable the agents to:
- work with a richer set of sys admin tools on top of code execution
- add support for a 'project' directory the agents can interact on
that's accessible by bash tools and custom scripts

## Related issue number

Closes #5363

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introduced in this PR.
- [x] I've made sure all auto checks have passed.

This PR improves documentation on custom agents 

- Shows example on how to create a custom agent that directly uses a
model client. In this case an example of a GeminiAssistantAgent that
directly uses the Gemini SDK model client.
- Shows that that CustomAgent can be easily added to any agentchat team 
- Shows how the same CustomAgent can be made declarative by inheriting
the Component interface and implementing the required methods.

Closes #5450

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

## Why are these changes needed?
These changes are needed because currently there's no generic way to add
`tools` to autogen studio workflows using the existing DSL and schema
other than inline python.

This API will be quite verbose, and lacks a discovery mechanism, but it
unlocks a lot of programmatic use-cases.

## Related issue number
https://github.com/microsoft/autogen/issues/5170

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

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## Why are these changes needed?

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solves. -->
The current implementation tries to recreate the metadata but it does it
in an incomplete way. This PR uses SK built-in kernel from function
decorator to infer the callable from the `run_json` and makes better use
of the pydantic schemas for the input and output to infer the schema of
the kernel function.

## Related issue number

<!-- For example: "Closes #1234" -->
Closes #5458 

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introduced in this PR.
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---------

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

Some LLMs recieve an explicit signal about tool use failures. 

Closes #5273

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

Resolves #5358

---------

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

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

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## Why are these changes needed?

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solves. -->

The current stream processing of SK model adapter returns on the first
function call chunk but this behavior is incorrect end ends up returning
with an incomplete function call. The observed behavior is that the
function name and arguments are split into different chunks and this
update correctly processes the chunks in this way.

## Related issue number

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Fixes the reply in #5420 

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---------

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

Mitigates #5401 by optionally prepending names to messages.

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

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## Why are these changes needed?

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solves. -->

Semantic kernel prepends the plugin name to the tool name when passing
the tools to model clients and this is causing a mismatch between tool
names in SK and the AssistantAgent. Since plugin names are optional, we
have opted to remove it.

## Related issue number

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

Closes #5420 

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---------

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

Presently MagenticOne and the m1 CLI use the LocalCommandLineExecutor
(presumably copied from the agbench code, which already runs in Docker).

This pr defaults m1 to Docker, and adds a code_executor parameter to
MagenticOne, which defaults to local for now to maintain backward
compatibility -- but this behavior is immediately deprecated.

Fix: Prevent empty messages accumulation in streaming mode

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

Resolves #5414

A series of changes to the
`python/packages/autogen-ext/src/autogen_ext/agents/web_surfer/_multimodal_web_surfer.py`
file have been made to better support smaller models.

This includes changes to the prompts, state descriptions, and ordering
of messages.

Regression tasks with OpenAI models shows no change in GAIA scores,
while scores for Llama are significantly improved.

This PR fixes:

A prompting bug when no control had focus.
Awkward prompt phrasing.
Renamed page_down to scroll_down to better match other prompting and
agent descriptions.

Some agent descriptions were split over multiple lines in the M1
orchestrator. This PR ensures that each description appears on one, and
only one, line. This makes it easier for smaller models to understand.

WebSurfer's summarize_page was failing when the model was text-only, or
unknown.

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## Why are these changes needed?

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solves. -->

To allow serialization of OAI Assistant Agent.

## Related issue number

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Closes #5130 

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Modify M1 agents to support text-only settings.
This allows M1 to be used with models like o3-mini and Llama3.1+

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## Why are these changes needed?

Fix bug where the `model_info` field is not serialized for the
`OpenAIChatCompletionClient` class. This was because the `_raw_config`
field was based on a version of the args that had been sanitized
(model_info removed). We need the full model info field for non-openai
models

```python
from autogen_ext.agents.web_surfer import MultimodalWebSurfer
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_core.models import ModelInfo
mistral_vllm_model = OpenAIChatCompletionClient(
    model="TheBloke/Mistral-7B-Instruct-v0.2-GGUF",
    base_url="http://localhost:1234/v1",
    api_key="empty",
    model_info=ModelInfo(vision=False, function_calling=True, json_output=False, family="unkown"),
)
(mistral_vllm_model.dump_component().model_dump_json())
```

Before
```
{
  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
  "component_type": "model",
  "version": 1,
  "component_version": 1,
  "description": "Chat completion client for OpenAI hosted models.",
  "label": "OpenAIChatCompletionClient",
  "config": {
    "model": "TheBloke/Mistral-7B-Instruct-v0.2-GGUF",
    "api_key": "empty",
    "base_url": "http://localhost:1234/v1"
  }
}

```

After
```
{
  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
  "component_type": "model",
  "version": 1,
  "component_version": 1,
  "description": "Chat completion client for OpenAI hosted models.",
  "label": "OpenAIChatCompletionClient",
  "config": {
    "model": "TheBloke/Mistral-7B-Instruct-v0.2-GGUF",
    "api_key": "empty",
    "model_info": {
      "vision": false,
      "function_calling": true,
      "json_output": false,
      "family": "unkown"
    },
    "base_url": "http://localhost:1234/v1"
  }
}


```
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solves. -->

## Related issue number

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

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## Why are these changes needed?
This pull request introduces the 'o3' model family and adds support for
the 'o3-mini' model.

---------

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

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## Why are these changes needed?

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solves. -->

We are seeing this issue more often now, probably related to the load on
the API servers. Hence this PR:
1. Demotes the the `max_consecutive_empty_chunk_tolerance` parameter
from function to inline threshold
2. Change exception to a one time warning

## Related issue number

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---------

Signed-off-by: Mohammad Mazraeh <mazraeh.mohammad@gmail.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

Resolves #5322

This PR adds a method that approximately extracts the text visible in
the viewport of the web browser (as opposed to always printing the first
50 lines, or relying entirely on OCR).

Resolves #5179

Closes #5163
---------

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

Because.

Resolves #5281

Resolves #5255 

---------

Co-authored-by: afourney <adamfo@microsoft.com>

Removed the TERMINATE clause from the system prompt since M1 handles
termination via the Orchestrator, and it is just ignored.

Removed the clause about saving to a particular file name, since tmp_
files are created in the current CodeExecutors.

Partially address #5205 and #5226

Closes #5074

Signed-off-by: Mohammad Mazraeh <mazraeh.mohammad@gmail.com>

Resolves #3983

* introduce `model_client_stream` parameter in `AssistantAgent` to
enable token-level streaming output.
* introduce `ModelClientStreamingChunkEvent` as a type of `AgentEvent`
to pass the streaming chunks to the application via `run_stream` and
`on_messages_stream`. Although this will not affect the inner messages
list in the final `Response` or `TaskResult`.
* handle this new message type in `Console`.