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

Resolves #5501

- Add a section on how to use model client with tools
- Replace the obsecure pattern of using ToolAgent with a simpler
implementation of calling tool within the agent itself.

Resolves #5508

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

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Pulls the .NET Docs a bit more into the documentation website proper:

* Add a link from the 0.4-series Python docs to 
* Adds a transient redirect from /dotnet/ to /dotnet/dev/ to forward to
the dev docs until we do a non "-dev" release

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

Update AutoGen Studio link to stable page url

Fixed a wrong class name style in the document and removed trailing whitespace.

Co-authored-by: Wei Jen Lu <weijenlu@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

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Adds the following blurb to the model clients docs

## API Keys From Environment Variables

In the examples above, we show that you can provide the API key through
the `api_key` argument. Importantly, the OpenAI and Azure OpenAI clients
use the [openai
package](3f8d8205ae/src/openai/__init__.py (L260),)
which will automatically read an api key from the environment variable
if one is not provided.

- For OpenAI, you can set the `OPENAI_API_KEY` environment variable.  
- For Azure OpenAI, you can set the `AZURE_OPENAI_API_KEY` environment
variable.

This is a good practice to explore, as it avoids including sensitive api
keys in your code.



## Why are these changes needed?

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## Related issue number

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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.

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## Why are these changes needed?

It is useful to rapidly validate any changes to a team structure as
teams are built either via drag and drop or by modifying the underlying
spec

You can now “validate” your team. The key ideas are as follows
- Each team is based on some Component Config specification which is a
pedantic model underneath.
- Validation is 3 pronged based on a ValidatorService class 
    - Data model validation (validate component schema)
    - Instantiation validation (validate component can be instantiated)
- Provider validation, component_type validation (validate that provider
exists and can be imported)
- UX: each time a component is **loaded or saved**, it is automatically
validated and any errors shown (via a server endpoint). This way, the
developer immediately knows if updates to the configuration is wrong or
has errors.

> Note: this is different from actually running the component against a
task. Currently you can run the entire team. In a separate PR we will
implement ability to run/test other components.

<img width="1360" alt="image"
src="https://github.com/user-attachments/assets/d61095b7-0b07-463a-b4b2-5c50ded750f6"
/>

<img width="1368" alt="image"
src="https://github.com/user-attachments/assets/09a1677e-76e8-44a4-9749-15c27457efbb"
/>

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solves. -->

## Related issue number

Closes #4616 

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Fix the installation instruction and add comments to the code.

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>

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

## 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>

Have seen discussion on Discord regarding confusion about multi-modal
support in v0.4. This change adds a small note on how to use multi-modal
messages with agents.

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>

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Add clear notes on how to specify api key and modifying specifications
in AGS.
Add diagrams explaining how to switch between visual builder and JSON
mode

## Why are these changes needed?

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solves. -->


![teambuilder](https://github.com/user-attachments/assets/9eede334-7f60-4c87-bec6-cf41839ba231)


## Related issue number

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

@nour-bouzid 

## Checks

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

Added a websocket example and link to the sample directory.

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## Why are these changes needed?

- Add ability to test teams in Team Builder view 
- Update Gallery (add deep research default team, fix bug with gallery
serialization)
- UI fixes 
   -  improve drag drop component experience 
- improve new session experience (single click rather than 3 clicks to
create a session)
   - fix bug with stop reason not being shown in some cases

<img width="1738" alt="Image"
src="https://github.com/user-attachments/assets/4b895df2-3bad-474e-bec6-4fbcbf1c4346"
/>

<img width="1761" alt="Image"
src="https://github.com/user-attachments/assets/65f52eb9-e926-4168-88fb-d2496c159474"
/>

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solves. -->

## Related issue number

Closes #5392

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introduced in this PR.
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Added the Claude family of models to the `ModelFamily` class. 

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

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

Fix typo in Swarm doc

The Tuple class is never used in CountDownAgent class.

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## Why are these changes needed?

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## Related issue number

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Co-authored-by: Victor Dibia <victordibia@microsoft.com>

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## Why are these changes needed?

Currently the way to accomplish RAG behavior with agent chat,
specifically assistant agents is with the memory interface, however
there is no way to configure it via the declarative API.

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solves. -->

## Related issue number

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---------

Co-authored-by: Victor Dibia <chuvidi2003@gmail.com>

Just fix typo

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## Why are these changes needed?

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solves. -->

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Closes #5302

Resolves #5322

This PR removes the older `autogen_magentic_one` package, and directs
people to use the new AgentChat implementation.

Hopefully this eases confusion.

---------

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

Because.

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## Why are these changes needed?

This PR updates AGS to use the declarative config serialization native
to AgentChat.
The effect? You can build your teams/artifacts directly in python, run
`team.dump_component()` and immediately run it in AGS.

Some change details:

- Removes ComponentFactory. Instead TeamManager just loads team specs
directly using `Team.load_component`.
- Some fixes to the UI to simplify drag and drop experience.  
- Improve layout of nodes...


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solves. -->

## Related issue number

<!-- For example: "Closes #1234" -->
Closes #4439 
Closes #5172

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cc @EItanya @nour-bouzid

Resolves #5255 

---------

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

Partially address #5205 and #5226

Resolves #5248

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## Why are these changes needed?

FunctionTool supports passing in a partial

## Related issue number

Closes #5151 

## Checks

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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`.

Resolves #5046

Resolves #5043

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## Why are these changes needed?

It is currently hard to add a description to a component (defaults to
None also) .. you have to call super.dump() modify and return. This PR
makes the experience better.

- allows you specify `component_description` and `component_label` as an
optional class var. label is an optional human readable name for the the
component.
- will use component_description if provided int he description field
when dumped if there is no description, will use the first line of class
docstring. Takes advantage of all the good practices we have in writing
good docstrings. label defaults to component type.
 

For example 

```python
model_client=OpenAIChatCompletionClient( model="gpt-4o-2024-08-06" )
config = model_client.dump_component()
print(config.model_dump_json())
```
Note the description field below is no longer None and there is a label
```python
{
  "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": "gpt-4o-2024-08-06" }
}


```

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solves. -->

## Related issue number

<!-- For example: "Closes #1234" -->
None, felt faster to fix.

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Typo in Report Agent

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

Partially resolves: #5118

Once the extension page is ready, update the tutorial pages to reduce
duplication.

---------

Co-authored-by: Victor Dibia <victordibia@microsoft.com>