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release notes
release notes
Published 3/4/2025
Contains new featuresTo use the new Ollama Client:
pip install -U "autogen-ext[ollama]"
from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_core.models import UserMessage
ollama_client = OllamaChatCompletionClient(
model="llama3",
)
result = await ollama_client.create([UserMessage(content="What is the capital of France?", source="user")]) # type: ignore
print(result)
To load a client from configuration:
from autogen_core.models import ChatCompletionClient
config = {
"provider": "OllamaChatCompletionClient",
"config": {"model": "llama3"},
}
client = ChatCompletionClient.load_component(config)
It also supports structured output:
from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_core.models import UserMessage
from pydantic import BaseModel
class StructuredOutput(BaseModel):
first_name: str
last_name: str
ollama_client = OllamaChatCompletionClient(
model="llama3",
response_format=StructuredOutput,
)
result = await ollama_client.create([UserMessage(content="Who was the first man on the moon?", source="user")]) # type: ignore
print(result)
name Field in FunctionExecutionResultNow name field is required in FunctionExecutionResult:
exec_result = FunctionExecutionResult(call_id="...", content="...", name="...", is_error=False)
thought Field in CreateResult and ThoughtEventNow CreateResult uses the optional thought field for the extra text content generated as part of a tool call from model. It is currently supported by OpenAIChatCompletionClient.
When available, the thought content will be emitted by AssistantAgent as a ThoughtEvent message.
metadata Field in AgentChat Message TypesAdded a metadata field for custom message content set by applications.
Now, if there is an exception raised within an AgentChat agent such as the AssistantAgent, instead of silently stopping the team, it will raise the exception.
New termination conditions for better control of agents.
See how you use TextMessageTerminationCondition to control a single agent team running in a loop: https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/teams.html#single-agent-team.
FunctionCallTermination is also discussed as an example for custom termination condition: https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/termination.html#custom-termination-condition
The ChainLit sample contains UserProxyAgent in a team, and shows you how to use it to get user input from UI. See: https://github.com/microsoft/autogen/tree/main/python/samples/agentchat_chainlit
Full Changelog: https://github.com/microsoft/autogen/compare/python-v0.4.7...python-v0.4.8
release notes
Published 3/4/2025
Contains new featuresTo use the new Ollama Client:
pip install -U "autogen-ext[ollama]"
from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_core.models import UserMessage
ollama_client = OllamaChatCompletionClient(
model="llama3",
)
result = await ollama_client.create([UserMessage(content="What is the capital of France?", source="user")]) # type: ignore
print(result)
To load a client from configuration:
from autogen_core.models import ChatCompletionClient
config = {
"provider": "OllamaChatCompletionClient",
"config": {"model": "llama3"},
}
client = ChatCompletionClient.load_component(config)
It also supports structured output:
from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_core.models import UserMessage
from pydantic import BaseModel
class StructuredOutput(BaseModel):
first_name: str
last_name: str
ollama_client = OllamaChatCompletionClient(
model="llama3",
response_format=StructuredOutput,
)
result = await ollama_client.create([UserMessage(content="Who was the first man on the moon?", source="user")]) # type: ignore
print(result)
name Field in FunctionExecutionResultNow name field is required in FunctionExecutionResult:
exec_result = FunctionExecutionResult(call_id="...", content="...", name="...", is_error=False)
thought Field in CreateResult and ThoughtEventNow CreateResult uses the optional thought field for the extra text content generated as part of a tool call from model. It is currently supported by OpenAIChatCompletionClient.
When available, the thought content will be emitted by AssistantAgent as a ThoughtEvent message.
metadata Field in AgentChat Message TypesAdded a metadata field for custom message content set by applications.
Now, if there is an exception raised within an AgentChat agent such as the AssistantAgent, instead of silently stopping the team, it will raise the exception.
New termination conditions for better control of agents.
See how you use TextMessageTerminationCondition to control a single agent team running in a loop: https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/teams.html#single-agent-team.
FunctionCallTermination is also discussed as an example for custom termination condition: https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/termination.html#custom-termination-condition
The ChainLit sample contains UserProxyAgent in a team, and shows you how to use it to get user input from UI. See: https://github.com/microsoft/autogen/tree/main/python/samples/agentchat_chainlit
Full Changelog: https://github.com/microsoft/autogen/compare/python-v0.4.7...python-v0.4.8
A programming framework for agentic AI