5 Commits

Author SHA1 Message Date
Eric Zhu
615882ccc8 Use SecretStr type for api key (#5939)
To prevent accidental export of API keys
2025-03-13 21:48:09 -07:00
Eitan Yarmush
817f728d04
add LLMStreamStartEvent and LLMStreamEndEvent (#5890)
These changes are needed because there is currently no way to get
logging information about Streaming LLM requests/responses.

I decided to put the StreamStart event AFTER the first chunk so there
aren't false positives about connections/auth.

Closes #5730
---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-03-11 15:02:46 -07:00
Eric Zhu
740afe5b61
Add ToolCallEvent and log it from all builtin tools (#5859)
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>
2025-03-07 16:04:45 -08:00
Leonardo Pinheiro
906b09e451
fix: Update SKChatCompletionAdapter message conversion (#5749)
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## 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>
2025-03-03 23:05:54 +00:00
Victor Dibia
05fc763b8a
add anthropic native support (#5695)
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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)
```

 

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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 #5205 
Closes #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
2025-02-26 07:27:41 +00:00