Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>

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## Why are these changes needed?



https://github.com/user-attachments/assets/e160f16d-f42d-49e2-a6c6-687e4e6786f4



Enable file upload/paste as a task in AGS. Enables tasks like

- Can you research and fact check the ideas in this screenshot?
- Summarize this file

Only text and images supported for now
Underneath, it constructs TextMessage and Multimodal messages as the
task.

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## Related issue number

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Closes #5773 

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---------

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

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.

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## Why are these changes needed?

Fix termination UI in AGS, ensure it can be edited correctly

<img width="1269" alt="image"
src="https://github.com/user-attachments/assets/eaa7a92f-a1ea-4ab4-a679-2894ac441311"
/>
<img width="1273" alt="image"
src="https://github.com/user-attachments/assets/6db81068-932f-4d4e-9512-279770c02bf2"
/>
<img width="1270" alt="image"
src="https://github.com/user-attachments/assets/5ca9df7d-b968-46c9-9d62-becd78809273"
/>


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## Related issue number

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Closes #5872
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Fix issue here in this discussion -
https://github.com/microsoft/autogen/discussions/4208#discussioncomment-12394408

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## Why are these changes needed?

Fix bug in AGS UI where frontend crashes because the default team config
is null

- update /teams endpoint to always return a default team if none is
found for the user
- update UI to check for team before rendering 
- also update run_id type to be autoincrement int (similar to team id)
instead of uuid. This helps side step the migration failed errors
related to UUID type when using an sqlite backend

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---------

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

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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?

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solves. -->

## Related issue number

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Closes #5205 
Closes #5708

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introduced in this PR.
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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?

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solves. -->

## Related issue number

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Closes #5627  
Closes #5662 
Closes #5619 

## Checks

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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?

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solves. -->

## Related issue number

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Closes #5440 

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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

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Closes #4439 
Closes #5172

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introduced in this PR.
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cc @EItanya @nour-bouzid