Aegis dag

[abhinav-aegis]

Why are these changes needed?

Related issue number

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.

Helps close #4623 and #5131. I am creating a pull requested as suggested by @lspinheiro to be able to compare changes and provide comments. The code itself is not ready for merging.

You can find the different Graph Execution patterns in the test files: https://github.com/abhinav-aegis/autogen/blob/7ddfb088ac5a7da37d5af59dad92d6f216426169/python/packages/autogen-agentchat/tests/test_digraph_group_chat.py#L596

Message filtering is implemented here: https://github.com/abhinav-aegis/autogen/blob/7ddfb088ac5a7da37d5af59dad92d6f216426169/python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_chat_agent_container.py#L116

Structured message schema deserialization is here: https://github.com/abhinav-aegis/autogen/blob/aegis-dag/python/packages/autogen-agentchat/src/autogen_agentchat/utils/_structured_message_utils.py

See several tests for the deserialization here: https://github.com/abhinav-aegis/autogen/blob/aegis-dag/python/packages/autogen-agentchat/tests/test_structured_message_utils.py

See StructuredMessageComponent here: https://github.com/abhinav-aegis/autogen/blob/7ddfb088ac5a7da37d5af59dad92d6f216426169/python/packages/autogen-agentchat/src/autogen_agentchat/messages.py#L214

See serialization tests here: https://github.com/abhinav-aegis/autogen/blob/7ddfb088ac5a7da37d5af59dad92d6f216426169/python/packages/autogen-agentchat/tests/test_messages.py#L56

[victordibia]

Hi @abhinav-aegis ,

Thanks for putting this together, much appreciated. I am personally excited to see this take shape and ideally, it would be great to see it get to a point where we support it in AutoGen Studio.

That said, as we improve it, what is a good minimum testable example we can use to help readers of this thread get a good sense of what is being accomplished. Will also provide some framework for expected behaviour.

Perhaps something like the below (B and C below seem to not be responding with )?

from autogen_ext.models.openai._openai_client import OpenAIChatCompletionClient
from autogen_ext.models.openai._openai_client import OpenAIChatCompletionClient
from autogen_agentchat.agents import (
    AssistantAgent,
)
from autogen_agentchat.conditions import MaxMessageTermination
from autogen_agentchat.teams._group_chat._digraph_group_chat import DiGraphGroupChat, DiGraph, DiGraphNode, DiGraphEdge 


model_client = OpenAIChatCompletionClient(model="gpt-4o-mini")
agent_a = AssistantAgent("A", model_client=model_client, system_message="You are a helpful assistant.")
agent_b = AssistantAgent("B", model_client=model_client, system_message="You are a helpful spanish translator. Whenever you receive a message, translate it to Spanish and respond with the translation.")
agent_c = AssistantAgent("C", model_client=model_client, system_message="You are a helpful assistant markdown assistant. Whenever you receieve a message format it as markdown (use tables where appropriate) and respond with the formatted message.")

graph = DiGraph(
    nodes={
        "A": DiGraphNode(name="A", edges=[DiGraphEdge(target="B")]),
        "B": DiGraphNode(name="B", edges=[DiGraphEdge(target="C")]),
        "C": DiGraphNode(name="C", edges=[]),
    }
)

team = DiGraphGroupChat(
    participants=[agent_a, agent_b, agent_c],
    graph=graph,
    termination_condition=MaxMessageTermination(5),
)
 
stream =  team.run_stream(task="Write a 3 line haiku poem about the amount of rainfail each month for california.")
async for message in stream:
    print("********",message) 

Result

TaskResult(messages=[TextMessage(source='user', models_usage=None, metadata={}, content='Write a 3 line haiku poem about the amount of rainfail each month for california.', type='TextMessage'), TextMessage(source='A', models_usage=RequestUsage(prompt_tokens=37, completion_tokens=21), metadata={}, content="Winter's soft whispers,  \nSpring's vibrant blooms drink deeply,  \nSummer's drought holds sway.", type='TextMessage'), TextMessage(source='B', models_usage=RequestUsage(prompt_tokens=79, completion_tokens=27), metadata={}, content='Susurros de invierno,  \nLas flores vibrantes de primavera beben profundamente,  \nLa sequía del verano prevalece.', type='TextMessage'), TextMessage(source='C', models_usage=RequestUsage(prompt_tokens=118, completion_tokens=64), metadata={}, content="### Haiku about California Rainfall\n\n**English:**\n\nWinter's soft whispers,  \nSpring's vibrant blooms drink deeply,  \nSummer's drought holds sway.\n\n---\n\n**Spanish:**\n\nSusurros de invierno,  \nLas flores vibrantes de primavera beben profundamente,  \nLa sequía del verano prevalece.", type='TextMessage')], stop_reason='The DiGraph chat has finished executing.')

[abhinav-aegis]

Hi @abhinav-aegis ,

Thanks for putting this together, much appreciated. I am personally excited to see this take shape and ideally, it would be great to see it get to a point where we support it in AutoGen Studio.

That said, as we improve it, what is a good minimum testable example we can use to help readers of this thread get a good sense of what is being accomplished. Will also provide some framework for expected behaviour.

Perhaps something like the below (B and C below seem to not be responding with )?

from autogen_ext.models.openai._openai_client import OpenAIChatCompletionClient
from autogen_ext.models.openai._openai_client import OpenAIChatCompletionClient
from autogen_agentchat.agents import (
    AssistantAgent,
)
from autogen_agentchat.conditions import MaxMessageTermination
from autogen_agentchat.teams._group_chat._digraph_group_chat import DiGraphGroupChat, DiGraph, DiGraphNode, DiGraphEdge 


model_client = OpenAIChatCompletionClient(model="gpt-4o-mini")
agent_a = AssistantAgent("A", model_client=model_client, system_message="You are a helpful assistant.")
agent_b = AssistantAgent("B", model_client=model_client, system_message="You are a helpful spanish translator. Whenever you receive a message, translate it to Spanish and respond with the translation.")
agent_c = AssistantAgent("C", model_client=model_client, system_message="You are a helpful assistant markdown assistant. Whenever you receieve a message format it as markdown (use tables where appropriate) and respond with the formatted message.")

graph = DiGraph(
    nodes={
        "A": DiGraphNode(name="A", edges=[DiGraphEdge(target="B")]),
        "B": DiGraphNode(name="B", edges=[DiGraphEdge(target="C")]),
        "C": DiGraphNode(name="C", edges=[]),
    }
)

team = DiGraphGroupChat(
    participants=[agent_a, agent_b, agent_c],
    graph=graph,
    termination_condition=MaxMessageTermination(5),
)
 
stream =  team.run_stream(task="Write a 3 line haiku poem about the amount of rainfail each month for california.")
async for message in stream:
    print("********",message) 

Result

TaskResult(messages=[TextMessage(source='user', models_usage=None, metadata={}, content='Write a 3 line haiku poem about the amount of rainfail each month for california.', type='TextMessage'), TextMessage(source='A', models_usage=RequestUsage(prompt_tokens=37, completion_tokens=21), metadata={}, content="Winter's soft whispers,  \nSpring's vibrant blooms drink deeply,  \nSummer's drought holds sway.", type='TextMessage'), TextMessage(source='B', models_usage=RequestUsage(prompt_tokens=79, completion_tokens=27), metadata={}, content='Susurros de invierno,  \nLas flores vibrantes de primavera beben profundamente,  \nLa sequía del verano prevalece.', type='TextMessage'), TextMessage(source='C', models_usage=RequestUsage(prompt_tokens=118, completion_tokens=64), metadata={}, content="### Haiku about California Rainfall\n\n**English:**\n\nWinter's soft whispers,  \nSpring's vibrant blooms drink deeply,  \nSummer's drought holds sway.\n\n---\n\n**Spanish:**\n\nSusurros de invierno,  \nLas flores vibrantes de primavera beben profundamente,  \nLa sequía del verano prevalece.", type='TextMessage')], stop_reason='The DiGraph chat has finished executing.')

@victordibia Thanks a lot for your feedback. I will definitely include such an example. I think the decision last week at Office Hours was to create an extension and maintain this library as an extension. I will get to that later this week and when I do that, I will be sure to include such an example in the Documentation.

[ekzhu]

@abhinav-aegis, @victordibia and I discussed and we think it maybe good for us to create an experimental module in AgentChat instead.

[abhinav-aegis]

@abhinav-aegis, @victordibia and I discussed and we think it maybe good for us to create an experimental module in AgentChat instead.

I am okay either ways - as a community extension or an experimental module. I will respond in Discord - easier to have a quick conversation there.

[codecov]

Codecov Report

Attention: Patch coverage is 88.88889% with 41 lines in your changes missing coverage. Please review.

Project coverage is 77.53%. Comparing base (71b7429) to head (754a20c).

Files with missing lines	Patch %	Lines
...agentchat/teams/_group_chat/_digraph_group_chat.py	85.45%	32 Missing ⚠️
...togen_agentchat/utils/_structured_message_utils.py	94.31%	5 Missing ⚠️
...utogen-agentchat/src/autogen_agentchat/messages.py	92.85%	2 Missing ⚠️
...chat/teams/_group_chat/_base_group_chat_manager.py	92.00%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #6197      +/-   ##
==========================================
+ Coverage   73.02%   77.53%   +4.51%     
==========================================
  Files         306      202     -104     
  Lines       17591    14816    -2775     
  Branches      406        0     -406     
==========================================
- Hits        12845    11487    -1358     
+ Misses       4473     3329    -1144     
+ Partials      273        0     -273     

Flag	Coverage Δ
unittests	77.53% <88.88%> (+4.51%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.