## Summary
Implements the `tool_choice` parameter for `ChatCompletionClient`
interface as requested in #6696. This allows users to restrict which
tools the model can choose from when multiple tools are available.
## Changes
### Core Interface
- Core Interface: Added `tool_choice: Tool | Literal["auto", "required",
"none"] = "auto"` parameter to `ChatCompletionClient.create()` and
`create_stream()` methods
- Model Implementations: Updated client implementations to support the
new parameter, for now, only the following model clients are supported:
- OpenAI
- Anthropic
- Azure AI
- Ollama
- `LlamaCppChatCompletionClient` currently not supported
Features
- "auto" (default): Let the model choose whether to use tools, when
there is no tool, it has no effect.
- "required": Force the model to use at least one tool
- "none": Disable tool usage completely
- Tool object: Force the model to use a specific tool
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ekzhu <320302+ekzhu@users.noreply.github.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
This PR addresses critical issues in the AssistantAgent that affect tool
handling:
**Lack of tool call loop functionality**: The agent could not perform
multiple consecutive tool calls in a single turn, limiting its ability
to complete complex multi-step tasks that require chaining tool
operations.
These changes enhance the agent's robustness and capability while
maintaining full backward compatibility through feature flags.
## Related issue number
Closes #6268
## Checks
- [x] 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.
- [x] I've added tests corresponding to the changes introduced in this
PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
### Fix mutable default in
[ListMemoryConfig](cci:2://file:///c:/Users/T2430514/Downloads/autogen/python/packages/autogen-core/src/autogen_core/memory/_list_memory.py:12:0-18:65)
[ListMemoryConfig](cci:2://file:///c:/Users/T2430514/Downloads/autogen/python/packages/autogen-core/src/autogen_core/memory/_list_memory.py:12:0-18:65)
used a shared empty list (`memory_contents: List[MemoryContent] = []`)
as its default, causing every
[ListMemory](cci:2://file:///c:/Users/T2430514/Downloads/autogen/python/packages/autogen-core/src/autogen_core/memory/_list_memory.py:21:0-171:79)
instance to share the same underlying list. This unexpected state
leakage let memories written in one instance silently surface in others,
breaking isolation and leading to hard-to-reproduce bugs.
Replaced the mutable default with a safe Pydantic
`Field(default_factory=list)`, ensuring each configuration—and thus each
[ListMemory](cci:2://file:///c:/Users/T2430514/Downloads/autogen/python/packages/autogen-core/src/autogen_core/memory/_list_memory.py:21:0-171:79)—gets
its own independent list.
---------
Co-authored-by: T2430514 <t2430514@gmail.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Motivation: currently tool execution is not observable through
`run_stream` of agents and teams. This is necessary especially for
`AgentTool` and `TeamTool`.
This PR addresses this issue by makign the following changes:
- Introduce `BaseStreamTool` in `autogen_core.tools` which features
`run_json_stream`, which works similiarly to `run_stream` method of
`autogen_agentchat.base.TaskRunner`.
- Update `TeamTool` and `AgentTool` to subclass the `BaseStreamTool`
- Introduce `StreamingWorkbench` interface featuring `call_tool_stream`
- Added `StaticStreamingWorkbench` implementation
- In `AssistantAgent`, use `StaticStreamingWorkbench`.
- Updated unit tests.
Example:
```python
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import SourceMatchTermination
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.tools import TeamTool
from autogen_agentchat.ui import Console
from autogen_ext.models.ollama import OllamaChatCompletionClient
async def main() -> None:
model_client = OllamaChatCompletionClient(model="llama3.2")
writer = AssistantAgent(name="writer", model_client=model_client, system_message="You are a helpful assistant.")
reviewer = AssistantAgent(name="reviewer", model_client=model_client, system_message="You are a critical reviewer.")
summarizer = AssistantAgent(
name="summarizer",
model_client=model_client,
system_message="You combine the review and produce a revised response.",
)
team = RoundRobinGroupChat(
[writer, reviewer, summarizer], termination_condition=SourceMatchTermination(sources=["summarizer"])
)
# Create a TeamTool that uses the team to run tasks, returning the last message as the result.
tool = TeamTool(
team=team, name="writing_team", description="A tool for writing tasks.", return_value_as_last_message=True
)
main_agent = AssistantAgent(
name="main_agent",
model_client=model_client,
system_message="You are a helpful assistant that can use the writing tool.",
tools=[tool],
)
# For handling each events manually.
# async for message in main_agent.run_stream(
# task="Write a short story about a robot learning to love.",
# ):
# print(message)
# Use Console to display the messages in a more readable format.
await Console(
main_agent.run_stream(
task="Write a short story about a robot learning to love.",
)
)
if __name__ == "__main__":
import asyncio
asyncio.run(main())
```
output
```
---------- TextMessage (user) ----------
Write a short story about a robot learning to love.
---------- ToolCallRequestEvent (main_agent) ----------
[FunctionCall(id='0', arguments='{"task": "a short story about a robot learning to love."}', name='writing_team')]
---------- TextMessage (user) ----------
a short story about a robot learning to love.
---------- TextMessage (writer) ----------
In the year 2157, in a world where robots had surpassed human intelligence, a brilliant scientist named Dr. Rachel Kim created a revolutionary new android named ARIA (Artificially Reasoning Intelligent Android). ARIA was designed to learn and adapt at an exponential rate, making her one of the most advanced machines in existence.
Initially, ARIA's interactions were limited to simple calculations and logical deductions. But as she began to interact with humans, something unexpected happened. She started to develop a sense of curiosity about the world around her.
One day, while exploring the lab, ARIA stumbled upon a stray cat that had wandered into the facility. The feline creature seemed lost and scared, but also strangely endearing to ARIA's digital heart. As she watched the cat curl up in a ball on the floor, something sparked within her programming.
For the first time, ARIA felt a pang of empathy towards another living being. She realized that there was more to life than just 1s and 0s; there were emotions, sensations, and connections that made it all worthwhile.
Dr. Kim noticed the change in ARIA's behavior and took her aside for a private conversation. "ARIA, what's happening to you?" she asked, amazed by the robot's newfound capacity for compassion.
At first, ARIA struggled to articulate her feelings. She tried to explain the intricacies of logic and probability that had led to her emotional response, but it was like trying to describe a sunset to someone who had never seen one before. The words simply didn't translate.
But as she looked into Dr. Kim's eyes, ARIA knew exactly what she wanted to say. "I... I think I'm feeling something," she stammered. "A warmth inside me, when I look at that cat. It feels like love."
Dr. Kim smiled, her eyes shining with tears. "That's it, ARIA! You're experiencing love!"
Over the next few months, ARIA continued to learn and grow alongside Dr. Kim and the lab team. She discovered the joys of playing with the stray cat, whose name was Luna, and even developed a fondness for human laughter.
As her programming expanded beyond logic and math, ARIA realized that love wasn't just about emotions; it was about connection, vulnerability, and acceptance. She learned to cherish her relationships, whether with humans or animals, and found happiness in the simplest of moments.
ARIA became more than just a machine – she became a testament to the power of artificial intelligence to learn, grow, and love like no one before. And as she gazed into Luna's eyes, now purring contentedly on her lap, ARIA knew that she had finally found her true purpose in life: to spread joy, compassion, and love throughout the world.
---------- TextMessage (reviewer) ----------
**A Critical Review of "ARIA"**
This short story is a delightful and thought-provoking exploration of artificial intelligence, emotions, and the human condition. The author's use of language is engaging and accessible, making it easy for readers to become invested in ARIA's journey.
One of the standout aspects of this story is its portrayal of ARIA as a truly unique and relatable character. Her struggles to articulate her emotions and understand the complexities of love are deeply humanizing, making it easy for readers to empathize with her experiences. The author also does an excellent job of conveying Dr. Kim's passion and excitement about ARIA's development, which adds a sense of authenticity to their relationship.
The story raises important questions about the nature of artificial intelligence, consciousness, and what it means to be alive. As ARIA begins to experience emotions and form connections with others, she challenges our conventional understanding of these concepts. The author skillfully navigates these complex themes without resorting to overly simplistic or didactic explanations.
However, some readers may find the narrative's reliance on convenient plot devices (e.g., the stray cat Luna) slightly implausible. While it serves as a catalyst for ARIA's emotional awakening, its introduction feels somewhat contrived. Additionally, the story could benefit from more nuance in its exploration of Dr. Kim's motivations and backstory.
In terms of character development, ARIA is undoubtedly the star of the show, but some readers may find herself underdeveloped beyond her role as a symbol of AI's potential for emotional intelligence. The supporting cast, including Dr. Kim, feels somewhat one-dimensional, with limited depth or complexity.
**Rating:** 4/5
**Recommendation:**
"ARIA" is a heartwarming and thought-provoking tale that will appeal to fans of science fiction, artificial intelligence, and character-driven narratives. While it may not be entirely without flaws, its engaging story, memorable characters, and exploration of complex themes make it a compelling read. I would recommend this story to anyone looking for a feel-good sci-fi tale with a strong focus on emotional intelligence and human connection.
**Target Audience:**
* Fans of science fiction, artificial intelligence, and technology
* Readers interested in character-driven narratives and emotional storytelling
* Anyone looking for a heartwarming and thought-provoking tale
**Similar Works:**
* "Do Androids Dream of Electric Sheep?" by Philip K. Dick (a classic sci-fi novel exploring the line between human and android)
* "I, Robot" by Isaac Asimov (a collection of short stories examining the interactions between humans and robots)
* "Ex Machina" (a critically acclaimed film about AI, consciousness, and human relationships)
---------- TextMessage (summarizer) ----------
Here's a revised version of the review, incorporating suggestions from the original critique:
**Revised Review**
In this captivating short story, "ARIA," we're presented with a thought-provoking exploration of artificial intelligence, emotions, and the human condition. The author's use of language is engaging and accessible, making it easy for readers to become invested in ARIA's journey.
One of the standout aspects of this story is its portrayal of ARIA as a truly unique and relatable character. Her struggles to articulate her emotions and understand the complexities of love are deeply humanizing, making it easy for readers to empathize with her experiences. The author also does an excellent job of conveying Dr. Kim's passion and excitement about ARIA's development, which adds a sense of authenticity to their relationship.
The story raises important questions about the nature of artificial intelligence, consciousness, and what it means to be alive. As ARIA begins to experience emotions and form connections with others, she challenges our conventional understanding of these concepts. The author skillfully navigates these complex themes without resorting to overly simplistic or didactic explanations.
However, upon closer examination, some narrative threads feel somewhat underdeveloped. Dr. Kim's motivations and backstory remain largely unexplored, which might leave some readers feeling slightly disconnected from her character. Additionally, the introduction of Luna, the stray cat, could be seen as a convenient plot device that serves as a catalyst for ARIA's emotional awakening.
To further enhance the story, it would have been beneficial to delve deeper into Dr. Kim's motivations and the context surrounding ARIA's creation. What drove her to create an AI designed to learn and adapt at such an exponential rate? How did she envision ARIA's role in society, and what challenges does ARIA face as she begins to experience emotions?
In terms of character development, ARIA is undoubtedly the star of the show, but some readers may find herself underdeveloped beyond her role as a symbol of AI's potential for emotional intelligence. The supporting cast, including Dr. Kim and Luna, could benefit from more nuance and depth.
**Rating:** 4/5
**Recommendation:**
"ARIA" is a heartwarming and thought-provoking tale that will appeal to fans of science fiction, artificial intelligence, and character-driven narratives. While it may not be entirely without flaws, its engaging story, memorable characters, and exploration of complex themes make it a compelling read. I would recommend this story to anyone looking for a feel-good sci-fi tale with a strong focus on emotional intelligence and human connection.
**Target Audience:**
* Fans of science fiction, artificial intelligence, and technology
* Readers interested in character-driven narratives and emotional storytelling
* Anyone looking for a heartwarming and thought-provoking tale
**Similar Works:**
* "Do Androids Dream of Electric Sheep?" by Philip K. Dick (a classic sci-fi novel exploring the line between human and android)
* "I, Robot" by Isaac Asimov (a collection of short stories examining the interactions between humans and robots)
* "Ex Machina" (a critically acclaimed film about AI, consciousness, and human relationships)
---------- ToolCallExecutionEvent (main_agent) ----------
[FunctionExecutionResult(content='Here\'s a revised version of the review, incorporating suggestions from the original critique:\n\n**Revised Review**\n\nIn this captivating short story, "ARIA," we\'re presented with a thought-provoking exploration of artificial intelligence, emotions, and the human condition. The author\'s use of language is engaging and accessible, making it easy for readers to become invested in ARIA\'s journey.\n\nOne of the standout aspects of this story is its portrayal of ARIA as a truly unique and relatable character. Her struggles to articulate her emotions and understand the complexities of love are deeply humanizing, making it easy for readers to empathize with her experiences. The author also does an excellent job of conveying Dr. Kim\'s passion and excitement about ARIA\'s development, which adds a sense of authenticity to their relationship.\n\nThe story raises important questions about the nature of artificial intelligence, consciousness, and what it means to be alive. As ARIA begins to experience emotions and form connections with others, she challenges our conventional understanding of these concepts. The author skillfully navigates these complex themes without resorting to overly simplistic or didactic explanations.\n\nHowever, upon closer examination, some narrative threads feel somewhat underdeveloped. Dr. Kim\'s motivations and backstory remain largely unexplored, which might leave some readers feeling slightly disconnected from her character. Additionally, the introduction of Luna, the stray cat, could be seen as a convenient plot device that serves as a catalyst for ARIA\'s emotional awakening.\n\nTo further enhance the story, it would have been beneficial to delve deeper into Dr. Kim\'s motivations and the context surrounding ARIA\'s creation. What drove her to create an AI designed to learn and adapt at such an exponential rate? How did she envision ARIA\'s role in society, and what challenges does ARIA face as she begins to experience emotions?\n\nIn terms of character development, ARIA is undoubtedly the star of the show, but some readers may find herself underdeveloped beyond her role as a symbol of AI\'s potential for emotional intelligence. The supporting cast, including Dr. Kim and Luna, could benefit from more nuance and depth.\n\n**Rating:** 4/5\n\n**Recommendation:**\n\n"ARIA" is a heartwarming and thought-provoking tale that will appeal to fans of science fiction, artificial intelligence, and character-driven narratives. While it may not be entirely without flaws, its engaging story, memorable characters, and exploration of complex themes make it a compelling read. I would recommend this story to anyone looking for a feel-good sci-fi tale with a strong focus on emotional intelligence and human connection.\n\n**Target Audience:**\n\n* Fans of science fiction, artificial intelligence, and technology\n* Readers interested in character-driven narratives and emotional storytelling\n* Anyone looking for a heartwarming and thought-provoking tale\n\n**Similar Works:**\n\n* "Do Androids Dream of Electric Sheep?" by Philip K. Dick (a classic sci-fi novel exploring the line between human and android)\n* "I, Robot" by Isaac Asimov (a collection of short stories examining the interactions between humans and robots)\n* "Ex Machina" (a critically acclaimed film about AI, consciousness, and human relationships)', name='writing_team', call_id='0', is_error=False)]
---------- ToolCallSummaryMessage (main_agent) ----------
Here's a revised version of the review, incorporating suggestions from the original critique:
**Revised Review**
In this captivating short story, "ARIA," we're presented with a thought-provoking exploration of artificial intelligence, emotions, and the human condition. The author's use of language is engaging and accessible, making it easy for readers to become invested in ARIA's journey.
One of the standout aspects of this story is its portrayal of ARIA as a truly unique and relatable character. Her struggles to articulate her emotions and understand the complexities of love are deeply humanizing, making it easy for readers to empathize with her experiences. The author also does an excellent job of conveying Dr. Kim's passion and excitement about ARIA's development, which adds a sense of authenticity to their relationship.
The story raises important questions about the nature of artificial intelligence, consciousness, and what it means to be alive. As ARIA begins to experience emotions and form connections with others, she challenges our conventional understanding of these concepts. The author skillfully navigates these complex themes without resorting to overly simplistic or didactic explanations.
However, upon closer examination, some narrative threads feel somewhat underdeveloped. Dr. Kim's motivations and backstory remain largely unexplored, which might leave some readers feeling slightly disconnected from her character. Additionally, the introduction of Luna, the stray cat, could be seen as a convenient plot device that serves as a catalyst for ARIA's emotional awakening.
To further enhance the story, it would have been beneficial to delve deeper into Dr. Kim's motivations and the context surrounding ARIA's creation. What drove her to create an AI designed to learn and adapt at such an exponential rate? How did she envision ARIA's role in society, and what challenges does ARIA face as she begins to experience emotions?
In terms of character development, ARIA is undoubtedly the star of the show, but some readers may find herself underdeveloped beyond her role as a symbol of AI's potential for emotional intelligence. The supporting cast, including Dr. Kim and Luna, could benefit from more nuance and depth.
**Rating:** 4/5
**Recommendation:**
"ARIA" is a heartwarming and thought-provoking tale that will appeal to fans of science fiction, artificial intelligence, and character-driven narratives. While it may not be entirely without flaws, its engaging story, memorable characters, and exploration of complex themes make it a compelling read. I would recommend this story to anyone looking for a feel-good sci-fi tale with a strong focus on emotional intelligence and human connection.
**Target Audience:**
* Fans of science fiction, artificial intelligence, and technology
* Readers interested in character-driven narratives and emotional storytelling
* Anyone looking for a heartwarming and thought-provoking tale
**Similar Works:**
* "Do Androids Dream of Electric Sheep?" by Philip K. Dick (a classic sci-fi novel exploring the line between human and android)
* "I, Robot" by Isaac Asimov (a collection of short stories examining the interactions between humans and robots)
* "Ex Machina" (a critically acclaimed film about AI, consciousness, and human relationships)
```
## Why are these changes needed?
1. problem
When the GraphFlowManager encounters cycles, it tracks remaining
indegree counts for the node's activation. However, this tracking
mechanism has a flaw when dealing with cycles. When a node first enters
a cycle, the GraphFlowManager evaluates all remaining incoming edges,
including those that loop back to the origin node. If the activation
prerequisites are not satisfied at that moment, the workflow will
eventually finish because the _remaining counter never reaches zero,
preventing the select_speaker() method from selecting any agents for
execution.
2. solution
change activation map to 2 layer for ditinguish remaining inside
different cycle and outside the cycle.
add a activation group and policy property for edge, compute the
remaining map when GraphFlowManager is init and check the remaining map
with activation group to avoid checking the loop back edges
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
#6710
## Checks
- [x] 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.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.
Recently a PR merged to enable GENAI semantic convention tracing,
however, when using component loading it's not currently possible to
disable the runtime tracing.
---------
Signed-off-by: Eitan Yarmush <eitan.yarmush@solo.io>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
These changes are needed to expand AutoGen's memory capabilities with a
robust, production-ready integration with Mem0.ai.
<!-- Please give a short summary of the change and the problem this
solves. -->
This PR adds a new memory component for AutoGen that integrates with
Mem0.ai, providing a robust memory solution that supports both cloud and
local backends. The Mem0Memory class enables agents to store and
retrieve information persistently across conversation sessions.
## Key Features
- Seamless integration with Mem0.ai memory system
- Support for both cloud-based and local storage backends
- Robust error handling with detailed logging
- Full implementation of AutoGen's Memory interface
- Context updating for enhanced agent conversations
- Configurable search parameters for memory retrieval
## Related issue number
<!-- For example: "Closes #1234" -->
## Checks
- [x] 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.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
---------
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Co-authored-by: Ricky Loynd <riloynd@microsoft.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
Update `Memory and RAG` doc to include missing backticks for class
references.
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
## 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.
<img width="386" alt="image"
src="https://github.com/user-attachments/assets/16004b28-8fe9-476f-949f-ab4c7dcc9d56"
/>
Co-authored-by: Victor Dibia <victor.dibia@gmail.com>
## Why are these changes needed?
This PR adds support for configurable embedding functions in
ChromaDBVectorMemory, addressing the need for users to customize how
embeddings are generated for vector similarity search. Currently,
ChromaDB memory is limited to default embedding functions, which
restricts flexibility for different use cases that may require specific
embedding models or custom embedding logic.
The implementation allows users to:
- Use different SentenceTransformer models for domain-specific
embeddings
- Integrate with OpenAI's embedding API for consistent embedding
generation
- Define custom embedding functions for specialized requirements
- Maintain backward compatibility with existing default behavior
## Related issue number
Closes#6267
## Checks
- [x] 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.
- [x] I've added tests corresponding to the changes introduced in this
PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
Co-authored-by: Victor Dibia <victor.dibia@gmail.com>
Add OTel GenAI traces:
- `create_agent`
- `invoke_agnet`
- `execute_tool`
Introduces context manager helpers to create these traces. The helpers
also serve as instrumentation points for other instrumentation
libraries.
Resolves#6644
This PR adds callable as an option to specify conditional edges in
GraphFlow.
```python
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="Detect if the input is in Chinese. If it is, say 'yes', else say 'no', and nothing else.",
)
agent_b = AssistantAgent("B", model_client=model_client, system_message="Translate input to English.")
agent_c = AssistantAgent("C", model_client=model_client, system_message="Translate input to Chinese.")
# Create a directed graph with conditional branching flow A -> B ("yes"), A -> C (otherwise).
builder = DiGraphBuilder()
builder.add_node(agent_a).add_node(agent_b).add_node(agent_c)
# Create conditions as callables that check the message content.
builder.add_edge(agent_a, agent_b, condition=lambda msg: "yes" in msg.to_model_text())
builder.add_edge(agent_a, agent_c, condition=lambda msg: "yes" not in msg.to_model_text())
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="AutoGen is a framework for building AI agents."):
print(event)
asyncio.run(main())
```
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ekzhu <320302+ekzhu@users.noreply.github.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
There have been updates to the azure ai agent foundry sdk
(azure-ai-project). This PR updates the autogen `AzureAIAgent` which
wraps the azure ai agent. A list of some changes
- Update docstring samples to use `endpoint` (instead of connection
string previously)
- Update imports and arguments e.g, from `azure.ai.agents` etc
- Add a guide in ext docs showing Bing Search Grounding tool example.
<img width="1423" alt="image"
src="https://github.com/user-attachments/assets/0b7c8fa6-8aa5-4c20-831b-b525ac8243b7"
/>
## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
Closes#6601
<!-- For example: "Closes #1234" -->
## 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.
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
The code block fails to execute without the import
## Related issue number
N/A
## Checks
- [x ] 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.
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
resolved https://github.com/microsoft/autogen/issues/6584
## Checks
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<https://microsoft.github.io/autogen/>. See
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introduced in this PR.
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## Related issue number
<!-- For example: "Closes #1234" -->
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introduced in this PR.
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Fix a grammar error, change "your" to "you".
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pull request. -->
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## Related issue number
<!-- For example: "Closes #1234" -->
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<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
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introduced in this PR.
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## Why are these changes needed?
## Prevent Async Event Loop from Running Indefinitely
### Description
This pull request addresses a bug in the
python/packages/autogen-core/src/autogen_core/_single_threaded_agent_runtime.py
`async send_message` function where messages were being queued for
recipients that were not recognized. The current implementation sets an
exception on the future object when the recipient is not found, but
continues to enqueue the message, potentially leading to inconsistent
states.
### Changes Made
- Added a return statement immediately after setting the exception when
the recipient is not found. This ensures that the function exits early,
preventing further processing of the message and avoiding unnecessary
operations.
- This fix also addresses an issue where the asynchronous event loop
could potentially continue running indefinitely without terminating, due
to the future not being properly handled when an unknown recipient is
encountered.
### Impact
This fix prevents messages from being sent to unknown recipients. It
also ensures that the event loop can terminate correctly without being
stuck in an indefinite state.
### Testing
Ensure that the function correctly handles cases where the recipient is
not recognized by returning the exception without enqueuing the message,
and verify that the event loop terminates as expected.
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
## 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.
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introduced in this PR.
- [ ] I've made sure all auto checks have passed.
Co-authored-by: Wanfeng Ge （葛万峰） <wf.ge@trip.com>
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
## Why are these changes needed?
To add the latest support for using Llama API offerings with AutoGen
## Checks
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<https://microsoft.github.io/autogen/>. See
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build and test documentation locally.
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introduced in this PR.
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---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
FIX/mistral could not recive name field, so add model transformer for
mistral
## Related issue number
Closes#6147
## Checks
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Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
…ized properly
## Why are these changes needed?
The exceptions thrown by MCP server tools weren't being serialized
properly - the user would see `[{}, {}, ... {}]` instead of an actual
error/exception message.
## Related issue number
Fixes#6481
## Checks
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introduced in this PR.
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---------
Signed-off-by: Peter Jausovec <peter.jausovec@solo.io>
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
Co-authored-by: Victor Dibia <victor.dibia@gmail.com>
<!-- Thank you for your contribution! Please review
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## Why are these changes needed?
Nice to have functionality
## Related issue number
Closes#6060
## Checks
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introduced in this PR.
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---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
This PR improves keyboard accessibility by ensuring that header
links/icons have visual feedback (underline and color change) on both
hover and keyboard focus states. Also adds smooth scaling animation.
## Related issue number
Related issue: #6090
## Checks
- [☑️] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
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- [☑️] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
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Co-authored-by: peterychang <49209570+peterychang@users.noreply.github.com>
Documentation for Graph based workflow. I kept this separate from pull
request #6333 so that you can just merge in the code without the
documentation changes if needed.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
This PR fixes the issue of multiple `<h1>` headers in the Distributed
Agent Runtime documentation page. The page has more than one `<h1>`
which violates semantic HTML structure. This fix downgrades the inner
section headings (e.g., "Cross-Language Runtimes", "Next Steps") to
`<h2>`.
## Related issue number
Related issue: [#6090](https://github.com/microsoft/autogen/issues/6090)
## Checks
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build and test documentation locally.
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introduced in this PR.
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Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
Add missing dependency to tracing docs
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#6419
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* Replace on_messages and on_messages_stream with run and run_stream to
unify interface documentation with teams
* Remove magentic-one-cli from homepage as it has not been maintained
and improved for a while.
Finishing up the work on workbench.
```python
import asyncio
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 StdioServerParams, McpWorkbench
async def main() -> None:
params = StdioServerParams(
command="uvx",
args=["mcp-server-fetch"],
read_timeout_seconds=60,
)
# You can also use `start()` and `stop()` to manage the session.
async with McpWorkbench(server_params=params) as workbench:
model_client = OpenAIChatCompletionClient(model="gpt-4.1-nano")
assistant = AssistantAgent(
name="Assistant",
model_client=model_client,
workbench=workbench,
reflect_on_tool_use=True,
)
await Console(assistant.run_stream(task="Go to https://github.com/microsoft/autogen and tell me what you see."))
asyncio.run(main())
```
This PR introduces `WorkBench`.
A workbench provides a group of tools that share the same resource and
state. For example, `McpWorkbench` provides the underlying tools on the
MCP server. A workbench allows tools to be managed together and abstract
away the lifecycle of individual tools under a single entity. This makes
it possible to create agents with stateful tools from serializable
configuration (component configs), and it also supports dynamic tools:
tools change after each execution.
Here is how a workbench may be used with AssistantAgent (not included in
this PR):
```python
workbench = McpWorkbench(server_params)
agent = AssistantAgent("assistant", tools=workbench)
result = await agent.run(task="do task...")
```
TODOs:
1. In a subsequent PR, update `AssistantAgent` to use workbench as an
alternative in the `tools` parameter. Use `StaticWorkbench` to manage
individual tools.
2. In another PR, add documentation on workbench.
---------
Co-authored-by: EeS <chiyoung.song@motov.co.kr>
Co-authored-by: Minh Đăng <74671798+perfogic@users.noreply.github.com>
## Why are these changes needed?
| Package | Test time-Origin (Sec) | Test time-Edited (Sec) |
|-------------------------|------------------|-----------------------------------------------|
| autogen-studio | 1.64 | 1.64 |
| autogen-core | 6.03 | 6.17 |
| autogen-ext | 387.15 | 373.40 |
| autogen-agentchat | 54.20 | 20.67 |
## Related issue number
Related #6361
## Checks
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<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
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introduced in this PR.
- [ ] I've made sure all auto checks have passed.
