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Claude 3.7 just came out. Its a pretty capable model and it would be
great to support it in Autogen.
This will could augment the already excellent support we have for
Anthropic via the SKAdapters in the following ways

- Based on the ChatCompletion API similar to the ollama and openai
client
- Configurable/serializable (can be dumped) .. this means it can be used
easily in AGS.

## What is Supported 

(video below shows the client being used in autogen studio)

https://github.com/user-attachments/assets/8fb7c17c-9f9c-4525-aa9c-f256aad0f40b



- streaming 
- tool callign / function calling 
- drop in integration with assistant agent. 
- multimodal support

```python

from dotenv import load_dotenv
import os 

load_dotenv()

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.models.anthropic import AnthropicChatCompletionClient 
model_client =   AnthropicChatCompletionClient(
        model="claude-3-7-sonnet-20250219" 
    )

async def get_weather(city: str) -> str:
    """Get the weather for a given city."""
    return f"The weather in {city} is 73 degrees and Sunny."

 
agent = AssistantAgent(
    name="weather_agent",
    model_client=model_client,
    tools=[get_weather],
    system_message="You are a helpful assistant.", 
    # model_client_stream=True,   
)

# Run the agent and stream the messages to the console.
async def main() -> None:
    await Console(agent.run_stream(task="What is the weather in New York?"))
await main()
```

result 

```
messages = [
    UserMessage(content="Write a very short story about a dragon.", source="user"),
]

# Create a stream.
stream = model_client.create_stream(messages=messages)

# Iterate over the stream and print the responses.
print("Streamed responses:")
async for response in stream:  # type: ignore
    if isinstance(response, str):
        # A partial response is a string.
        print(response, flush=True, end="")
    else:
        # The last response is a CreateResult object with the complete message.
        print("\n\n------------\n")
        print("The complete response:", flush=True)
        print(response.content, flush=True)
        print("\n\n------------\n")
        print("The token usage was:", flush=True)
        print(response.usage, flush=True)
```

 

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## Why are these changes needed?

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

## Related issue number

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

Closes #5205 
Closes #5708

## 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. 



cc @rohanthacker

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This PR has 3 main improvements. 

- Token streaming 
- Adds support for environment variables in the app settings 
- Updates AGS to persist Gallery entry in db.

## Adds Token Streaming in AGS.  

Agentchat now supports streaming of tokens via
`ModelClientStreamingChunkEvent `. This PR is to track progress on
supporting that in the AutoGen Studio UI.

If `model_client_stream` is enabled in an assitant agent, then token
will be streamed in UI.

```python
streaming_assistant = AssistantAgent(
    name="assistant",
    model_client=model_client,
    system_message="You are a helpful assistant.",
    model_client_stream=True,  # Enable streaming tokens.
)

```

https://github.com/user-attachments/assets/74d43d78-6359-40c3-a78e-c84dcb5e02a1


## Env Variables 
Also adds support for env variables in AGS Settings

You can set env variables that are loaded just before a team is run.
Handy to set variable to be used by tools etc.

<img width="1291" alt="image"
src="https://github.com/user-attachments/assets/437b9d90-ccee-42f7-be5d-94ab191afd67"
/>


> Note: the set variables are available to the server process.

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## Why are these changes needed?

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

## Related issue number

<!-- For example: "Closes #1234" -->
Closes #5627  
Closes #5662 
Closes #5619 

## 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.

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It is often helpful to inspect the raw request and response to/from an
LLM as agents act.
This PR, does the following:

- Updates TeamManager to yield LLMCallEvents from core library
- Run in an async background task to listen for LLMCallEvent JIT style
when a team is run
   - Add events to   an async queue and 
- yield those events in addition to whatever actual agentchat
team.run_stream yields.
- Update the AGS UI to show those LLMCallEvents in the messages section
as a team runs
   - Add settings panel to show/hide llm call events in messages. 
- Minor updates to default team

<img width="1539" alt="image"
src="https://github.com/user-attachments/assets/bfbb19fe-3560-4faa-b600-7dd244e0e974"
/>
<img width="1554" alt="image"
src="https://github.com/user-attachments/assets/775624f5-ba83-46e8-81ff-512bfeed6bab"
/>
<img width="1538" alt="image"
src="https://github.com/user-attachments/assets/3becbf85-b75a-4506-adb7-e5575ebbaec4"
/>


## Why are these changes needed?

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

## Related issue number

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

Closes #5440 

## Checks

- [ ] I've included any doc changes needed for
https://microsoft.github.io/autogen/. See
https://microsoft.github.io/autogen/docs/Contribute#documentation 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.

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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...


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

## Related issue number

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

## Checks

- [ ] I've included any doc changes needed for
https://microsoft.github.io/autogen/. See
https://microsoft.github.io/autogen/docs/Contribute#documentation 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.


cc @EItanya @nour-bouzid