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python-v0.6.4

09 Jul 17:52
@ekzhu ekzhu
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What's New

More helps from @copilot-swe-agent for this release.

Improvements to GraphFlow

Now it behaves the same way as RoundRobinGroupChat, SelectorGroupChat and others after termination condition hits -- it retains its execution state and can be resumed with a new task or empty task. Only when the graph finishes execution i.e., no more next available agent to choose from, the execution state will be reset.

Also, the inner StopAgent has been removed and there will be no last message coming from the StopAgent. Instead, the stop_reason field in the TaskResult will carry the stop message.

Improvements to Workbench implementations

McpWorkbench and StaticWorkbench now supports overriding tool names and descriptions. This allows client-side optimization of the server-side tools, for better adaptability.

All Changes

New Contributors

Full Changelog: python-v0.6.2...python-v0.6.4

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marcos-muino-garcia, ekzhu, and 6 other contributors
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python-v0.6.2

01 Jul 00:09
@ekzhu ekzhu
python-v0.6.2
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What's New

Streaming Tools

This release introduces streaming tools and updates AgentTool and TeamTool to support run_json_stream. The new interface exposes the inner events of tools when calling run_stream of agents and teams. AssistantAgent is also updated to use run_json_stream when the tool supports streaming. So, when using AgentTool or TeamTool with AssistantAgent, you can receive the inner agent's or team's events through the main agent.

To create new streaming tools, subclass autogen_core.tools.BaseStreamTool and implement run_stream. To create new streaming workbench, subclass autogen_core.tools.StreamWorkbench and implement call_tool_stream.

  • Introduce streaming tool and support streaming for AgentTool and TeamTool. by @ekzhu in #6712

tool_choice parameter for ChatCompletionClient and subclasses

Introduces a new parameter tool_choice to the ChatCompletionClients create and create_stream methods.

This is also the first PR by @copliot-swe-agent!

  • Add tool_choice parameter to ChatCompletionClient create and create_stream methods by @copilot-swe-agent in #6697

AssistantAgent's inner tool calling loop

Now you can enable AssistantAgent with an inner tool calling loop by setting the max_tool_iterations parameter through its constructor. The new implementation calls the model and executes tools until (1) the model stops generating tool calls, or (2) max_tool_iterations has been reached. This change simplies the usage of AssistantAgent.

OpenTelemetry GenAI Traces

This releases added new traces create_agent, invoke_agent, execute_tool from the GenAI Semantic Convention.

  • OTel GenAI Traces for Agent and Tool by @ekzhu in #6653

You can also disable agent runtime traces by setting the environment variable AUTOGEN_DISABLE_RUNTIME_TRACING=true.

output_task_messages flag for run and run_stream

You can use the new flag to customize whether the input task messages get emitted as part of run_stream of agents and teams.

Mem0 Extension

Added Mem0 memory extension so you can use it as memory for AutoGen agents.

Improvement to GraphFlow

  • Add activation group for workflow with multiple cycles by @ZenWayne in #6711

uv update

We have removed the uv version limit so you can use the latest version to develop AutoGen.

  • Unpin uv version to use the latest version by @ekzhu in #6713

Other Python Related Changes

New Contributors

Full Changelog: python-v0.6.1...python-v0.6.2

Contributors

ekzhu, victordibia, and 13 other contributors
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python-v0.6.1

05 Jun 05:58
@ekzhu ekzhu
python-v0.6.1
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Bug Fixes

  • Fix bug in GraphFlow cycle check by @ekzhu in #6629
  • Fix graph validation logic and add tests by @ekzhu in #6630

Others

  • Add list of function calls and results in ToolCallSummaryMessage by @ekzhu in #6626

Full Changelog: python-v0.6.0...python-v0.6.1

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ekzhu
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python-v0.6.0

05 Jun 00:37
@ekzhu ekzhu
python-v0.6.0
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What's New

Change to BaseGroupChatManager.select_speaker and support for concurrent agents in GraphFlow

We made a type hint change to the select_speaker method of BaseGroupChatManager to allow for a list of agent names as a return value. This makes it possible to support concurrent agents in GraphFlow, such as in a fan-out-fan-in pattern.
 

# Original signature:
async def select_speaker(self, thread: Sequence[BaseAgentEvent | BaseChatMessage]) -> str:
  ...

# New signature:
async def select_speaker(self, thread: Sequence[BaseAgentEvent | BaseChatMessage]) -> List[str] | str:
  ...

Now you can run GraphFlow with concurrent agents as follows:

import asyncio

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import MaxMessageTermination
from autogen_agentchat.teams import DiGraphBuilder, GraphFlow
from autogen_ext.models.openai import OpenAIChatCompletionClient


async def main():
    # Initialize agents with OpenAI model clients.
    model_client = OpenAIChatCompletionClient(model="gpt-4.1-nano")
    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="Translate input to Chinese.")
    agent_c = AssistantAgent("C", model_client=model_client, system_message="Translate input to Japanese.")

    # Create a directed graph with fan-out flow A -> (B, C).
    builder = DiGraphBuilder()
    builder.add_node(agent_a).add_node(agent_b).add_node(agent_c)
    builder.add_edge(agent_a, agent_b).add_edge(agent_a, agent_c)
    graph = builder.build()

    # Create a GraphFlow team with the directed graph.
    team = GraphFlow(
        participants=[agent_a, agent_b, agent_c],
        graph=graph,
        termination_condition=MaxMessageTermination(5),
    )

    # Run the team and print the events.
    async for event in team.run_stream(task="Write a short story about a cat."):
        print(event)


asyncio.run(main())

Agent B and C will run concurrently in separate coroutines.

  • Enable concurrent execution of agents in GraphFlow by @ekzhu in #6545

Callable conditions for GraphFlow edges

Now you can use lambda functions or other callables to specify edge conditions in GraphFlow. This addresses the issue of the keyword substring-based conditions cannot cover all possibilities and leading to "cannot find next agent" bug.

NOTE: callable conditions are currently experimental, and it cannot be serialized with the graph.

  • Add callable condition for GraphFlow edges by @ekzhu in #6623

New Agent: OpenAIAgent

  • Feature: Add OpenAIAgent backed by OpenAI Response API by @jay-thakur in #6418

MCP Improvement

AssistantAgent Improvement

Code Executors Improvement

  • Add option to auto-delete temporary files in LocalCommandLineCodeExecutor by @holtvogt in #6556
  • Include all output to error output in docker jupyter code executor by @ekzhu in #6572

OpenAIChatCompletionClient Improvement

OllamaChatCompletionClient Improvement

AnthropicBedrockChatCompletionClient Improvement

MagenticOneGroupChat Improvement

  • Use structured output for m1 orchestrator by @ekzhu in #6540

Other Changes

New Contributors

Full Changelog: python-v0.5.7...python-v0.6.0

Contributors

ekzhu, victordibia, and 19 other contributors
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python-v0.5.7

14 May 05:02
@ekzhu ekzhu
python-v0.5.7
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What's New

AzureAISearchTool Improvements

The Azure AI Search Tool API now features unified methods:

  • create_full_text_search() (supporting "simple", "full", and "semantic" query types)
  • create_vector_search() and
  • create_hybrid_search()
    We also added support for client-side embeddings, while defaults to service embeddings when client embeddings aren't provided.

If you have been using create_keyword_search(), update your code to use create_full_text_search() with "simple" query type.

SelectorGroupChat Improvements

To support long context for the model-based selector in SelectorGroupChat, you can pass in a model context object through the new model_context parameter to customize the messages sent to the model client when selecting the next speaker.

  • Add model_context to SelectorGroupChat for enhanced speaker selection by @Ethan0456 in #6330

OTEL Tracing Improvements

We added new metadata and message content fields to the OTEL traces emitted by the SingleThreadedAgentRuntime.

Agent Runtime Improvements

Other Python Related Changes

New Contributors

Full Changelog: python-v0.5.6...python-v0.5.7

Contributors

ekzhu, victordibia, and 9 other contributors
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python-v0.5.6

02 May 22:55
@ekzhu ekzhu
python-v0.5.6
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python-v0.5.6

What's New

GraphFlow: customized workflows using directed graph

Should I say finally? Yes, finally, we have workflows in AutoGen. GraphFlow is a new team class as part of the AgentChat API. One way to think of GraphFlow is that it is a version of SelectorGroupChat but with a directed graph as the selector_func. However, it is actually more powerful, because the abstraction also supports concurrent agents.

Note: GraphFlow is still an experimental API. Watch out for changes in the future releases.

For more details, see our newly added user guide on GraphFlow.

If you are in a hurry, here is an example of creating a fan-out-fan-in workflow:

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import DiGraphBuilder, GraphFlow
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient


async def main() -> None:
    # Create an OpenAI model client
    client = OpenAIChatCompletionClient(model="gpt-4.1-nano")

    # Create the writer agent
    writer = AssistantAgent(
        "writer",
        model_client=client,
        system_message="Draft a short paragraph on climate change.",
    )

    # Create two editor agents
    editor1 = AssistantAgent(
        "editor1", model_client=client, system_message="Edit the paragraph for grammar."
    )

    editor2 = AssistantAgent(
        "editor2", model_client=client, system_message="Edit the paragraph for style."
    )

    # Create the final reviewer agent
    final_reviewer = AssistantAgent(
        "final_reviewer",
        model_client=client,
        system_message="Consolidate the grammar and style edits into a final version.",
    )

    # Build the workflow graph
    builder = DiGraphBuilder()
    builder.add_node(writer).add_node(editor1).add_node(editor2).add_node(
        final_reviewer
    )

    # Fan-out from writer to editor1 and editor2
    builder.add_edge(writer, editor1)
    builder.add_edge(writer, editor2)

    # Fan-in both editors into final reviewer
    builder.add_edge(editor1, final_reviewer)
    builder.add_edge(editor2, final_reviewer)

    # Build and validate the graph
    graph = builder.build()

    # Create the flow
    flow = GraphFlow(
        participants=builder.get_participants(),
        graph=graph,
    )

    # Run the workflow
    await Console(flow.run_stream(task="Write a short biography of Steve Jobs."))

asyncio.run(main())

Major thanks to @abhinav-aegis for the initial design and implementation of this amazing feature!

Azure AI Agent Improvement

New Sample

  • A multi-agent PostgreSQL data management example by @mehrsa in #6443

Bug Fixes:

Dev Improvement

Other Python Related Changes

New Contributors

Full Changelog: python-v0.5.5...python-v0.5.6

Contributors

abdomohamed, ekzhu, and 9 other contributors
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python-v0.5.5

25 Apr 23:56
@ekzhu ekzhu
python-v0.5.5
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What's New

Introduce Workbench

A workbench is a collection of tools that share state and resource. For example, you can now use MCP server through McpWorkbench rather than using tool adapters. This makes it possible to use MCP servers that requires a shared session among the tools (e.g., login session).

Here is an example of using AssistantAgent with GitHub MCP Server.

import asyncio
import os
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StdioServerParams

async def main() -> None:
    model_client = OpenAIChatCompletionClient(model="gpt-4.1-nano")
    server_params = StdioServerParams(
        command="docker",
        args=[
            "run",
            "-i",
            "--rm",
            "-e",
            "GITHUB_PERSONAL_ACCESS_TOKEN",
            "ghcr.io/github/github-mcp-server",
        ],
        env={
            "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
        }
    )
    async with McpWorkbench(server_params) as mcp:
        agent = AssistantAgent(
            "github_assistant",
            model_client=model_client,
            workbench=mcp,
            reflect_on_tool_use=True,
            model_client_stream=True,
        )
        await Console(agent.run_stream(task="Is there a repository named Autogen"))
    
asyncio.run(main())

Here is another example showing a web browsing agent using Playwright MCP Server, AssistantAgent and RoundRobinGroupChat.

# First run `npm install -g @playwright/mcp@latest` to install the MCP server.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.conditions import TextMessageTermination
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StdioServerParams

async def main() -> None:
    model_client = OpenAIChatCompletionClient(model="gpt-4.1-nano")
    server_params = StdioServerParams(
        command="npx",
        args=[
            "@playwright/mcp@latest",
            "--headless",
        ],
    )
    async with McpWorkbench(server_params) as mcp:
        agent = AssistantAgent(
            "web_browsing_assistant",
            model_client=model_client,
            workbench=mcp,
            model_client_stream=True,
        )
        team = RoundRobinGroupChat(
            [agent],
            termination_condition=TextMessageTermination(source="web_browsing_assistant"),
        )
        await Console(team.run_stream(task="Find out how many contributors for the microsoft/autogen repository"))
    
asyncio.run(main())

Read more:

New Sample: AutoGen and FastAPI with Streaming

  • Add example using autogen-core and FastAPI for handoff multi-agent design pattern with streaming and UI by @amith-ajith in #6391

New Termination Condition: FunctionalTermination

  • Support using a function expression to create a termination condition for teams. by @ekzhu in #6398

Other Python Related Changes

  • update website version by @ekzhu in #6364
  • TEST/change gpt4, gpt4o serise to gpt4.1nano by @SongChiYoung in #6375
  • Remove name field from OpenAI Assistant Message by @ekzhu in #6388
  • Add guide for workbench and mcp & bug fixes for create_mcp_server_session by @ekzhu in #6392
  • TEST: skip when macos+uv and adding uv venv tests by @SongChiYoung in #6387
  • AssistantAgent to support Workbench by @ekzhu in #6393
  • Update agent documentation by @ekzhu in #6394
  • Update version to 0.5.5 by @ekzhu in #6397
  • Update: implement return_value_as_string for McpToolAdapter by @perfogic in #6380
  • [doc] Clarify selector prompt for SelectorGroupChat by @ekzhu in #6399
  • Document custom message types in teams API docs by @ekzhu in #6400

New Contributors

Full Changelog: python-v0.5.4...python-v0.5.5

Contributors

ekzhu, SongChiYoung, and 2 other contributors
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python-v0.5.4

22 Apr 17:51
@ekzhu ekzhu
python-v0.5.4
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python-v0.5.4

What's New

Agent and Team as Tools

You can use AgentTool and TeamTool to wrap agent and team into tools to be used by other agents.

import asyncio

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.tools import AgentTool
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient


async def main() -> None:
    model_client = OpenAIChatCompletionClient(model="gpt-4")
    writer = AssistantAgent(
        name="writer",
        description="A writer agent for generating text.",
        model_client=model_client,
        system_message="Write well.",
    )
    writer_tool = AgentTool(agent=writer)
    assistant = AssistantAgent(
        name="assistant",
        model_client=model_client,
        tools=[writer_tool],
        system_message="You are a helpful assistant.",
    )
    await Console(assistant.run_stream(task="Write a poem about the sea."))


asyncio.run(main())

See AgentChat Tools API for more information.

Azure AI Agent

Introducing adapter for Azure AI Agent, with support for file search, code interpreter, and more. See our Azure AI Agent Extension API.

Docker Jupyter Code Executor

Thinking about sandboxing your local Jupyter execution environment? We just added a new code executor to our family of code executors. See Docker Jupyter Code Executor Extension API.

  • Make Docker Jupyter support to the Version 0.4 as Version 0.2 by @masquerlin in #6231

Canvas Memory

Shared "whiteboard" memory can be useful for agents to collaborate on a common artifact such code, document, or illustration. Canvas Memory is an experimental extension for sharing memory and exposing tools for agents to operate on the shared memory.

New Community Extensions

Updated links to new community extensions. Notably, autogen-contextplus provides advanced model context implementations with ability to automatically summarize, truncate the model context used by agents.

SelectorGroupChat Update

SelectorGroupChat now works with models that only support streaming mode (e.g., QwQ). It can also optionally emit the inner reasoning of the model used in the selector. Set emit_team_events=True and model_client_streaming=True when creating SelectorGroupChat.

  • FEAT: SelectorGroupChat could using stream inner select_prompt by @SongChiYoung in #6286

CodeExecutorAgent Update

CodeExecutorAgent just got another refresh: it now supports max_retries_on_error parameter. You can specify how many times it can retry and self-debug in case there is error in the code execution.

ModelInfo Update

New Sample: AutoGen Core + FastAPI with Streaming

  • Add an example using autogen-core and FastAPI to create streaming responses by @ToryPan in #6335

AGBench Update

Bug Fixes

  • Bugfix: Azure AI Search Tool - fix query type by @jay-thakur in #6331
  • fix: ensure serialized messages are passed to LLMStreamStartEvent by @peterj in #6344
  • fix: ollama fails when tools use optional args by @peterj in #6343
  • Avoid re-registering a message type already registered by @jorge-wonolo in #6354
  • Fix: deserialize model_context in AssistantAgent and SocietyOfMindAgent and CodeExecutorAgent by @SongChiYoung in #6337

What's Changed

  • Update website 0.5.3 by @ekzhu in #6320
  • Update version 0.5.4 by @ekzhu in #6334
  • Generalize Continuous SystemMessage merging via model_info[“multiple_system_messages”] instead of startswith("gemini-") by @SongChiYoung in #6345
  • Add experimental notice to canvas by @ekzhu in #6349
  • Added support for exposing GPUs to docker code executor by @millerh1 in #6339

New Contributors

Full Changelog: python-v0.5.3...python-v0.5.4

Contributors

abdomohamed, ekzhu, and 11 other contributors
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python-v0.5.3

17 Apr 03:36
@ekzhu ekzhu
python-v0.5.3
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python-v0.5.3

What's New

CodeExecutorAgent Update

Now the CodeExecutorAgent can generate and execute code in the same invocation. See API doc for examples.

AssistantAgent Improvement

Now AssistantAgent can be serialized when output_content_type is set, thanks @abhinav-aegis's new built-in utility module autogen_core.utils for working with JSON schema.

Team Improvement

Added an optional parameter emit_team_events to configure whether team events like SelectorSpeakerEvent are emitted through run_stream.

  • [FEATURE] Option to emit group chat manager messages in AgentChat by @SongChiYoung in #6303

MCP Improvement

Now mcp_server_tools factory can reuse a shared session. See example of AssistantAgent using Playwright MCP server in the API Doc.

  • Make shared session possible for MCP tool by @ekzhu in #6312

Console Improvement

Bug Fixes

  • Fix: Azure AI Search Tool Client Lifetime Management by @jay-thakur in #6316
  • Make sure thought content is included in handoff context by @ekzhu in #6319

Python Related Changes

New Contributors

Full Changelog: python-v0.5.2...python-v0.5.3

Contributors

ekzhu, jay-thakur, and 7 other contributors
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python-v0.5.2

15 Apr 03:24
@ekzhu ekzhu
python-v0.5.2
3500170
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Python Related Changes

New Contributors

Full Changelog: python-v0.5.1...python-v0.5.2

Contributors

ekzhu, scovetta, and 13 other contributors
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