## 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>
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)
```
<!-- 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?
Nice to have functionality
## Related issue number
Closes#6060
## 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.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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
- [ ] 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.
Added support for structured message component using the Json to
Pydantic utility functions. Note: also adding the ability to use a
format string for structured messages.
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Token limited model context is currently broken because it is importing
from extensions.
This fix removed the imports and updated the model context
implementation to use model client directly.
In the future, the model client's token counting should cache results
from model API to provide accurate counting.
Resolves#5745
Also made sure to log LLMCallEvent from all builtin model clients, and
added unit test for coverage.
---------
Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
Fixes#4821 by adding a `close()` method to all clients.
Additionally:
* The m1 CLI is updated to close the client before exiting.
* The playwrightcontroller is updated to suppress some other unrelated
chatty warnings (e.g,, produced by markitdown when encountering
conversions that require external utilities)
AutoGen was passing raw dictionaries to functions instead of
constructing Pydantic model or dataclass instances. If a tool function’s
parameter was a Pydantic BaseModel or a dataclass, the function would
receive a dict and likely throw an error or behave incorrectly (since it
expected an object of that type).
This PR addresses problem in AutoGen where tool functions expecting
structured inputs (Pydantic models or dataclasses) were receiving raw
dictionaries. It ensures that structured inputs are automatically
validated and instantiated before function calls. Complete details are
in Issue #5736
[Reproducible Example Code - Failing
Case](https://colab.research.google.com/drive/1hgoP-cGdSZ1-OqQLpwYmlmcExgftDqlO?usp=sharing)
<!-- Please give a short summary of the change and the problem this
solves. -->
## Changes Made:
- Inspect function signatures for Pydantic BaseModel and dataclass
annotations.
- Convert input dictionaries into properly instantiated objects using
BaseModel.model_validate() for Pydantic models or standard instantiation
for dataclasses.
- Raise descriptive errors when validation or instantiation fails.
- Unit tests have been added to cover all scenarios
Now structured inputs are automatically validated and instantiated
before function calls.
- **Updated Conversion Logic:**
In the `run()` method, we now inspect the function’s signature and
convert input dictionaries to structured objects. For parameters
annotated with a Pydantic model, we use `model_validate()` to create an
instance; for those annotated with a dataclass, we instantiate the
object using the dataclass constructor. For example:
```python
# Get the function signature.
sig = inspect.signature(self._func)
raw_kwargs = args.model_dump()
kwargs = {}
# Iterate over the parameters expected by the function.
for name, param in sig.parameters.items():
if name in raw_kwargs:
expected_type = param.annotation
value = raw_kwargs[name]
# If expected type is a subclass of BaseModel, perform conversion.
if inspect.isclass(expected_type) and issubclass(expected_type,
BaseModel):
try:
kwargs[name] = expected_type.model_validate(value)
except ValidationError as e:
raise ValueError(
f"Error validating parameter '{name}' for function
'{self._func.__name__}': {e}"
) from e
# If it's a dataclass, instantiate it.
elif is_dataclass(expected_type):
try:
cls = expected_type if isinstance(expected_type, type) else
type(expected_type)
kwargs[name] = cls(**value)
except Exception as e:
raise ValueError(
f"Error instantiating dataclass parameter '{name}' for function
'{self._func.__name__}': {e}"
) from e
else:
kwargs[name] = value
```
- **Error Handling Improvements:**
Conversion steps are wrapped in try/except blocks to raise descriptive
errors when instantiation fails, aiding in debugging invalid inputs.
- **Testing:**
Unit tests have been added to simulate tool calls (e.g., an `add` tool)
to ensure that with input like:
```json
{"input": {"x": 2, "y": 3}}
```
The tool function receives an instance of the expected type and returns
the correct result.
## Related issue number
Closes#5736
## 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.
<!-- 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. -->
The PR introduces two changes.
The first change is adding a name attribute to
`FunctionExecutionResult`. The motivation is that semantic kernel
requires it for their function result interface and it seemed like a
easy modification as `FunctionExecutionResult` is always created in the
context of a `FunctionCall` which will contain the name. I'm unsure if
there was a motivation to keep it out but this change makes it easier to
trace which tool the result refers to and also increases api
compatibility with SK.
The second change is an update to how messages are mapped from autogen
to semantic kernel, which includes an update/fix in the processing of
function results.
## Related issue number
<!-- For example: "Closes #1234" -->
Related to #5675 but wont fix the underlying issue of anthropic
requiring tools during AssistantAgent reflection.
## 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.
---------
Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>
Closes#4904
Does not change default behavior in core.
In agentchat, this change will mean that exceptions that used to be
ignored and result in bugs like the group chat stopping are now reported
out to the user application.
---------
Co-authored-by: Ben Constable <benconstable@microsoft.com>
Co-authored-by: Ryan Sweet <rysweet@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?
Currently the way to accomplish RAG behavior with agent chat,
specifically assistant agents is with the memory interface, however
there is no way to configure it via the declarative API.
<!-- 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://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.
---------
Co-authored-by: Victor Dibia <chuvidi2003@gmail.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.
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assign them to your PR. -->
## Why are these changes needed?
FunctionTool supports passing in a partial
## Related issue number
Closes#5151
## Checks
- [x] 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.
- [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.
<!-- 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?
It is currently hard to add a description to a component (defaults to
None also) .. you have to call super.dump() modify and return. This PR
makes the experience better.
- allows you specify `component_description` and `component_label` as an
optional class var. label is an optional human readable name for the the
component.
- will use component_description if provided int he description field
when dumped if there is no description, will use the first line of class
docstring. Takes advantage of all the good practices we have in writing
good docstrings. label defaults to component type.
For example
```python
model_client=OpenAIChatCompletionClient( model="gpt-4o-2024-08-06" )
config = model_client.dump_component()
print(config.model_dump_json())
```
Note the description field below is no longer None and there is a label
```python
{
"provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
"component_type": "model",
"version": 1,
"component_version": 1,
"description": "Chat completion client for OpenAI hosted models.",
"label": "OpenAIChatCompletionClient",
"config": { "model": "gpt-4o-2024-08-06" }
}
```
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
None, felt faster to fix.
## Checks
- [x] 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.
- [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.
* initial pass on making group chats declarative
* update group chat tests
* update impl to include participant serialization for all teams
* v1 making soc declarative
* update memory test
* update chatagent and team base classes
* update serialization doc notebook
* fomating updates
* vi1 for declarative tools
* make functtools declarative
* add tests
* update imports
* update formatting
* move tests, format fixes
* format updates
* update test
* add user warning to _from_config
* add warning on load_component to docs
---------
Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
* Add ChatCompletionCache along with AbstractStore for caching completions
* Addressing comments
* Improve interface for cachestore
* Improve documentation & revert protocol
* Make cache store typed, and improve docs
* remove unnecessary casts
* initial base memroy impl
* update, add example with chromadb
* include mimetype consideration
* add transform method
* update to address feedback, will update after 4681 is merged
* update memory impl,
* remove chroma db, typing fixes
* format, add test
* update uv lock
* update docs
* format updates
* update notebook
* add memoryqueryevent message, yield message for observability.
* minor fixes, make score optional/none
* Update python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
* update tests to improve cov
* refactor, move memory to core.
* format fixxes
* format updates
* format updates
* fix azure notebook import, other fixes
* update notebook, support str query in Memory protocol
* update test
* update cells
* add specific extensible return types to memory query and update_context
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
* Split apart component infra to allow for abstract class integration
* fix is_component_class check
* make is_ functions type guards
* Simplify component creation
* undo changes
* Format
* Instantiate and call activate/deactivate on agents
* autoformatting
* remove activate. Rename deactivate to close
* remove unneeded import
* create close fn in runtime
* change runtime close behavior
* uv.lock
---------
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
* Decouple model_context from AssistantAgent
* add UnboundedBufferedChatCompletionContext to mimic pervious model_context behaviour on AssistantAgent
* moving unbounded buffered chat to a different file
* fix model_context assertions in test_group_chat
* Refactor model context, introduce states
* fixes
* update
---------
Co-authored-by: aditya.kurniawan <aditya.kurniawan@core42.ai>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
