## Why are these changes needed?
The current installation command fails in certain shells (e.g., `zsh`,
`fish`) because brackets (`[]`) are interpreted as special characters.
Adding quotes ensures compatibility across different environments,
including Linux, macOS, and Windows.
## Related issue number
No related issue, but this fixes an installation issue encountered by
multiple users.
## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>.
- [ ] 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: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
* `python3` to `python`: Windows uses `python` for Python 3 by default,
not `python3`.
* `bin` to `scripts`: Windows virtual environments use `Scripts` instead
of `bin`.
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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.
Correcting an error: If CodeReviewResult is not approved, the coder
agents sends a CodeReviewTask back to the reviewer agent, not a
CodeWritingTask.
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Starting out this draft PR to add documentation for the
`with_requirements` decorator in the `autogen-core` package.
---------
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
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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>
<!-- Thank you for your contribution! Please review
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pull request. -->
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assign them to your PR. -->
## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
(I'm not familiar with English, so I use Goggle translation a lot. So
please forgive me if I say something rude.)
I started autogen-studio and opened the page in the browser, nothing was
rendered.
I checked using the Developer tool, the following error appeared:
```
TypeError: Cannot read properties of null (reading 'label')
at editor.tsx:114:42
```
I check the implementation, it looks like `team.component` is `null`,
which seems to be caused during initialization process when the team is
not registered.
[source](78ff883d24/python/packages/autogen-studio/frontend/src/components/views/playground/manager.tsx (L199))
So I fixed the issue where the gallery wasn't being retrieved which was
causing the issue.
### Reproduce bug
1. clone this repository
2. open devcontainer(`python/packages/autogen-studio`)
3. Running the application
```sh
cd frontend
yarn build
cd -
OPENAI_API_KEY="" autogenstudio ui --port 8081
```
4. Open `localhost:8081` in browser.
## Related issue number
<!-- For example: "Closes #1234" -->
Probably not found. (sorry if I had to raise an issue before PR)
## 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.
- [x] I've made sure all auto checks have passed.
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
stream_options are not part of the model classes, so they won't get
serialized when calling dump_component. Adding this to the model allows
us to store the stream options when the component is serialized.
---------
Signed-off-by: Peter Jausovec <peter.jausovec@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?
> Hey Victor, this is maybe a bug, but when a session is delete, runs
and messages for that session are not deleted, any reason why to keep
them?
@husseinmozannar
The main fix is to add a pragma that ensures SQL lite enforces foreign
key constraints.
Also needed to update error messages for autoupgrade of databases. Also
adds a test for cascade deletes and for parts of teammanager
With this fix,
- Messages get deleted when the run is deleted
- Runs get deleted when sessiosn are deleted
- Sessions get deleted when a team is deleted
<!-- 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.
<!-- Thank you for your contribution! Please review
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pull request. -->
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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. -->
- AGS contains image files which are required for local build /dev
- These files are stored using git lfs which needs to be run before the
files are downloaded
- This PR adds a reminder to the AGS readme to run `git lfs checkout`
after installing git lfs to download the image files
## Related issue number
<!-- For example: "Closes #1234" -->
Close#3418
## 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.
## Why are these changes needed?
The CodeExecutorAgent documentation needs to be updated to explicitly
mention that it only processes code properly formatted in markdown code
blocks with triple backticks. This change adds a clear note with
examples to help users understand the required format for code
execution.
## Related issue number
Closes#5771
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
<!-- Thank you for your contribution! Please review
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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?
Make FileSurfer and CodeExecAgent Declarative.
These agent presents are used as part of magentic one and having them
declarative is a precursor to their use in AGS.
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5607
## 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
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pull request. -->
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assign them to your PR. -->
## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
Shows an example of how to use the `Memory` interface to implement a
just-in-time vector memory based on chromadb.
```python
import os
from pathlib import Path
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_core.memory import MemoryContent, MemoryMimeType
from autogen_ext.memory.chromadb import ChromaDBVectorMemory, PersistentChromaDBVectorMemoryConfig
from autogen_ext.models.openai import OpenAIChatCompletionClient
# Initialize ChromaDB memory with custom config
chroma_user_memory = ChromaDBVectorMemory(
config=PersistentChromaDBVectorMemoryConfig(
collection_name="preferences",
persistence_path=os.path.join(str(Path.home()), ".chromadb_autogen"),
k=2, # Return top k results
score_threshold=0.4, # Minimum similarity score
)
)
# a HttpChromaDBVectorMemoryConfig is also supported for connecting to a remote ChromaDB server
# Add user preferences to memory
await chroma_user_memory.add(
MemoryContent(
content="The weather should be in metric units",
mime_type=MemoryMimeType.TEXT,
metadata={"category": "preferences", "type": "units"},
)
)
await chroma_user_memory.add(
MemoryContent(
content="Meal recipe must be vegan",
mime_type=MemoryMimeType.TEXT,
metadata={"category": "preferences", "type": "dietary"},
)
)
# Create assistant agent with ChromaDB memory
assistant_agent = AssistantAgent(
name="assistant_agent",
model_client=OpenAIChatCompletionClient(
model="gpt-4o",
),
tools=[get_weather],
memory=[user_memory],
)
stream = assistant_agent.run_stream(task="What is the weather in New York?")
await Console(stream)
await user_memory.close()
```
```txt
---------- user ----------
What is the weather in New York?
---------- assistant_agent ----------
[MemoryContent(content='The weather should be in metric units', mime_type='MemoryMimeType.TEXT', metadata={'category': 'preferences', 'mime_type': 'MemoryMimeType.TEXT', 'type': 'units', 'score': 0.4342913043162201, 'id': '8a8d683c-5866-41e1-ac17-08c4fda6da86'}), MemoryContent(content='The weather should be in metric units', mime_type='MemoryMimeType.TEXT', metadata={'category': 'preferences', 'mime_type': 'MemoryMimeType.TEXT', 'type': 'units', 'score': 0.4342913043162201, 'id': 'f27af42c-cb63-46f0-b26b-ffcc09955ca1'})]
---------- assistant_agent ----------
[FunctionCall(id='call_a8U3YEj2dxA065vyzdfXDtNf', arguments='{"city":"New York","units":"metric"}', name='get_weather')]
---------- assistant_agent ----------
[FunctionExecutionResult(content='The weather in New York is 23 °C and Sunny.', call_id='call_a8U3YEj2dxA065vyzdfXDtNf', is_error=False)]
---------- assistant_agent ----------
The weather in New York is 23 °C and Sunny.
```
Note that MemoryContent object in the MemoryQuery events have useful
metadata like the score and id retrieved memories.
## 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.
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pull request. -->
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assign them to your PR. -->
## Why are these changes needed?
The Team DB class doesn't have the "config" field anymore. It has
"component"
<!-- 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.
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
<!-- Thank you for your contribution! Please review
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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?
Add support for default model client, in AGS updates to settings UI.
A default model client will be used for subsequent background tasks
(e.g, automatically naming sessions to meaningful names).
<img width="1441" alt="image"
src="https://github.com/user-attachments/assets/31675ef4-8f80-4a8c-9762-3d6bcbc6d33d"
/>
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5685
## 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
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pull request. -->
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## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
Typo in example text
## 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.
- [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. -->
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## Why are these changes needed?
- Running a team generates a MemoryQueryEvent has a MemoryContent field
and is part of the model context
- Saving team state (`team.save_state()`) includes serializing model
context
- MemoryContent has a mime_type field, which was not being properly
serialized.
"Object of type MemoryMimeType is not JSON serializable"
This PR? -> add explicit serialization instruction for the mimetype
field.
```python
import asyncio
import logging
import json
import yaml, aiofiles
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_agentchat.conditions import MaxMessageTermination
from autogen_core.memory import ListMemory, MemoryContent, MemoryMimeType
from autogen_agentchat.ui import Console
logger = logging.getLogger(__name__)
state_path = "team_state.json"
model_client = OpenAIChatCompletionClient(model="gpt-4o-mini")
max_msg_termination = MaxMessageTermination(max_messages=3)
# Initialize user memory
user_memory = ListMemory()
# Add user preferences to memory
await user_memory.add(MemoryContent(content="The weather should be in metric units", mime_type=MemoryMimeType.TEXT))
# Create the team.
agent = AssistantAgent(
name="assistant",
model_client=model_client,
system_message="You are a helpful assistant.",
memory = [user_memory],
)
yoda = AssistantAgent(
name="yoda",
model_client=model_client,
system_message="Repeat the same message in the tone of Yoda.",
)
team = RoundRobinGroupChat(
[agent, yoda],
termination_condition=max_msg_termination
)
await Console(team.run_stream(task="Hi, How are you ?"))
# Save team state to file.
state = await team.save_state()
with open(state_path, "w") as f:
json.dump(state, f)
# Load team state from file.
with open("team_state.json", "r") as f:
team_state = json.load(f)
await team.load_state(state)
await Console( team.run_stream(task="What was the last thing that was said in this conversation "))
```
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5688
## 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.
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>
@ekzhu should likely be assigned as reviewer
## Why are these changes needed?
These changes address the bug reported in #5663. Prevents TypeError from
being thrown at inference time by ollama AsyncClient when `host` (and
other) kwargs are passed to autogen OllamaChatCompletionClient
constructor.
It also adds ollama as a named optional extra so that the ollama
requirements can be installed alongside autogen-ext (e.g. `pip install
autogen-ext[ollama]`
@ekzhu, I will need some help or guidance to ensure that the associated
test (which requires ollama and tiktoken as dependencies of the
OllamaChatCompletionClient) can run successfully in autogen's test
execution environment.
I have also left the "I've made sure all auto checks have passed" check
below unchecked as this PR is coming from my fork. (UPDATE: auto checks
appear to have passed after opening PR, so I have checked box below)
## Related issue number
Intended to close#5663
## 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: Ryan Stewart <ryanstewart@Ryans-MacBook-Pro.local>
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
Co-authored-by: peterychang <49209570+peterychang@users.noreply.github.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
Claude 3.7 just came out. Its a pretty capable model and it would be
great to support it in Autogen.
This will could augment the already excellent support we have for
Anthropic via the SKAdapters in the following ways
- Based on the ChatCompletion API similar to the ollama and openai
client
- Configurable/serializable (can be dumped) .. this means it can be used
easily in AGS.
## What is Supported
(video below shows the client being used in autogen studio)
https://github.com/user-attachments/assets/8fb7c17c-9f9c-4525-aa9c-f256aad0f40b
- streaming
- tool callign / function calling
- drop in integration with assistant agent.
- multimodal support
```python
from dotenv import load_dotenv
import os
load_dotenv()
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.models.anthropic import AnthropicChatCompletionClient
model_client = AnthropicChatCompletionClient(
model="claude-3-7-sonnet-20250219"
)
async def get_weather(city: str) -> str:
"""Get the weather for a given city."""
return f"The weather in {city} is 73 degrees and Sunny."
agent = AssistantAgent(
name="weather_agent",
model_client=model_client,
tools=[get_weather],
system_message="You are a helpful assistant.",
# model_client_stream=True,
)
# Run the agent and stream the messages to the console.
async def main() -> None:
await Console(agent.run_stream(task="What is the weather in New York?"))
await main()
```
result
```
messages = [
UserMessage(content="Write a very short story about a dragon.", source="user"),
]
# Create a stream.
stream = model_client.create_stream(messages=messages)
# Iterate over the stream and print the responses.
print("Streamed responses:")
async for response in stream: # type: ignore
if isinstance(response, str):
# A partial response is a string.
print(response, flush=True, end="")
else:
# The last response is a CreateResult object with the complete message.
print("\n\n------------\n")
print("The complete response:", flush=True)
print(response.content, flush=True)
print("\n\n------------\n")
print("The token usage was:", flush=True)
print(response.usage, flush=True)
```
<!-- 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?
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5205Closes#5708
## 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.
cc @rohanthacker
<!-- Thank you for your contribution! Please review
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pull request. -->
update human in the loop docs for agentchat
..
> Outputs in docs are outdated as summary is not printed out by default
when using Console
[#5590](https://github.com/microsoft/autogen/issues/5590)
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## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
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## Related issue number
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Closes#5590
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This pull request includes updates to the `README.md` file for the
`autogen-studio` package to improve clarity and accuracy. The most
important changes include a minor rewrite of the project structure
section and updates to the installation instructions (better tabbing).
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## Why are these changes needed?
Fixes `(14) Ensures the contrast between foreground and background
colors meets WCAG 2 AA minimum contrast ratio thresholds`
Note: the color values don't output at the exact values on the
stylesheet. For example, the value `#1774E5` evaluates to `#2274E0` by
the Accessibility Insights app.
## Related issue number
https://github.com/microsoft/autogen/issues/5633
## Checks
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## Why are these changes needed?
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I'm unsure if everyone will agree, but I started to look into adding new
logic and found that refactoring into smaller functions would make it
more maintainable.
There is no change in functionality, only a breakdown into smaller
methods to make it more modular and improve readability. There is a lot
of logic in the method and this refactor breaks it down into context
management, llm call and result processing.
## Related issue number
<!-- For example: "Closes #1234" -->
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---------
Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>
## Why are these changes needed?
For the sake of subsequent people reading the metacode and following
programming specifications, variable names are updated in combination
with usage scenarios. Mainly contains the variable "_self_text" in
TextMentionTermination
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This PR has 3 main improvements.
- Token streaming
- Adds support for environment variables in the app settings
- Updates AGS to persist Gallery entry in db.
## Adds Token Streaming in AGS.
Agentchat now supports streaming of tokens via
`ModelClientStreamingChunkEvent `. This PR is to track progress on
supporting that in the AutoGen Studio UI.
If `model_client_stream` is enabled in an assitant agent, then token
will be streamed in UI.
```python
streaming_assistant = AssistantAgent(
name="assistant",
model_client=model_client,
system_message="You are a helpful assistant.",
model_client_stream=True, # Enable streaming tokens.
)
```
https://github.com/user-attachments/assets/74d43d78-6359-40c3-a78e-c84dcb5e02a1
## Env Variables
Also adds support for env variables in AGS Settings
You can set env variables that are loaded just before a team is run.
Handy to set variable to be used by tools etc.
<img width="1291" alt="image"
src="https://github.com/user-attachments/assets/437b9d90-ccee-42f7-be5d-94ab191afd67"
/>
> Note: the set variables are available to the server process.
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## Why are these changes needed?
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solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5627Closes#5662Closes#5619
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Add metadata field to BaseMessage.
Why?
- additional metadata field can track 1) timestamp if needed, 2) flags
about the message. For instance, a use case is a metadata field
{"internal":"yes"} that would hide messages from being displayed in an
application or studio.
As long as an extra field is added to basemessage that is not consumed
by existing agents, I am happy.
Notes:
- We can also only add it to BaseChatMessage, that would be fine
- I don't care what the extra field is called as long as there is an
extra field somewhere
- I don't have preference for the type, a str could work, but a dict
would be more useful.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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## Why are these changes needed?
convenience - allows to just run "agenthost"
```
dotnet pack --no-build --configuration Release --output './output/release' -bl\n
dotnet tool install --add-source ./output/release Microsoft.AutoGen.AgentHost
agenthost
```
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solves. -->
## Related issue number
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closes#5646
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introduced in this PR.
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Replace the undefined `tools` variable with `tool_schema` parameter
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## Why are these changes needed?
This change keeps the documentation up to date :
https://microsoft.github.io/autogen/stable//user-guide/core-user-guide/components/tools.html
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solves. -->
## Related issue number
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introduced in this PR.
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## Why are these changes needed?
Fix minor issues in docs:
- probably editing left over
- typo
- code formatting inconsistency
## Related issue number
N/A
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Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
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## Why are these changes needed?
The HttpTool in AutoGen accepts a headers parameter, but it is not being
used in the actual request. This fix ensures that the headers provided
by users are correctly included in HTTP requests. This resolves issues
where authentication or other custom headers are required but currently
ignored.
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solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5638
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Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
## Why are these changes needed?
See issue for a bug description.
The problem was that a lot of openrouter models return `""` as
`tool_call.arguments`, which caused `json.loads` to fail
## Related issue number
https://github.com/microsoft/autogen/issues/5666
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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This PR makes makes ChatCompletionCache support component config
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## Why are these changes needed?
Ensures we have a path to serializing ChatCompletionCache , similar to
the ChatCompletion client that it wraps.
This PR does the following
- Makes CacheStore serializable first (part of this includes converting
from Protocol to base class). Makes it's derivatives serializable as
well (diskcache, redis)
- Makes ChatCompletionCache serializable
- Adds some tests
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solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5141
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cc @nour-bouzid
Resolves#5192
Test
```python
import asyncio
import os
from random import randint
from typing import List
from autogen_core.tools import BaseTool, FunctionTool
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
async def get_current_time(city: str) -> str:
return f"The current time in {city} is {randint(0, 23)}:{randint(0, 59)}."
tools: List[BaseTool] = [
FunctionTool(
get_current_time,
name="get_current_time",
description="Get current time for a city.",
),
]
model_client = OpenAIChatCompletionClient(
model="anthropic/claude-3.5-haiku-20241022",
base_url="https://openrouter.ai/api/v1",
api_key=os.environ["OPENROUTER_API_KEY"],
model_info={
"family": "claude-3.5-haiku",
"function_calling": True,
"vision": False,
"json_output": False,
}
)
agent = AssistantAgent(
name="Agent",
model_client=model_client,
tools=tools,
system_message= "You are an assistant with some tools that can be used to answer some questions",
)
async def main() -> None:
await Console(agent.run_stream(task="What is current time of Paris and Toronto?"))
asyncio.run(main())
```
```
---------- user ----------
What is current time of Paris and Toronto?
---------- Agent ----------
I'll help you find the current time for Paris and Toronto by using the get_current_time function for each city.
---------- Agent ----------
[FunctionCall(id='toolu_01NwP3fNAwcYKn1x656Dq9xW', arguments='{"city": "Paris"}', name='get_current_time'), FunctionCall(id='toolu_018d4cWSy3TxXhjgmLYFrfRt', arguments='{"city": "Toronto"}', name='get_current_time')]
---------- Agent ----------
[FunctionExecutionResult(content='The current time in Paris is 1:10.', call_id='toolu_01NwP3fNAwcYKn1x656Dq9xW', is_error=False), FunctionExecutionResult(content='The current time in Toronto is 7:28.', call_id='toolu_018d4cWSy3TxXhjgmLYFrfRt', is_error=False)]
---------- Agent ----------
The current time in Paris is 1:10.
The current time in Toronto is 7:28.
```
---------
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
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Update AGS, Remove Numpy Dep
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## Why are these changes needed?
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## Related issue number
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Closes#5639
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## Why are these changes needed?
Fixes the problem where Gallery items could only be modified via JSON
This PR does the following
- Refactor TeamBuilder to have modular component editor UI primarily
focused on editing each component type.
- Refactor the Gallery UX
- improve layout to use tabs for each component type
- enable editing of each component item by reusing the component editor
- Enable switching between form editing and UI editing for coponent
editor view
This way, gallery items can be readily modified and then reused in the
component library in team builder.
It also implements an upate to the Gallery data structure to make it
more intuitive - it has a components field that has teams, agents,
models ...
<img width="1598" alt="image"
src="https://github.com/user-attachments/assets/3c3a228a-0bd2-4fc1-85ec-c9685c80bf72"
/>
<img width="1614" alt="image"
src="https://github.com/user-attachments/assets/5b6ed840-9c48-47bc-8c17-2aa50c7dcb99"
/>
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solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5465Closes#5047
cc @nour-bouzid @balakreshnan @EItanya @joslat @IustinT @leonG7
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Fix typo in doc
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Fixing grammar issues
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