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Tao ChenandEvan Mattson b7bb2832aa Python: Input & output attributes in invoke_agent span (#12834 )

### Motivation and Context

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  1. Why is this change required?
  2. What problem does it solve?
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The OTel workgroup has been thinking about enhancing tracing for agents.
This is a proposal from our tracing team:
https://github.com/open-telemetry/semantic-conventions/pull/2528. This
PR implements part of the proposal so that when the proposal gets
merged, we can quickly follow.

### Description

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->
Two new attributes are added to the `invoke_agent` span, namely the
`gen_ai.agent.invocation_input` and `gen_ai.agent.invocation_output`.

<img width="747" height="583" alt="image"
src="https://github.com/user-attachments/assets/d8b81f68-915b-48ee-8f86-66a0d4f686cc"
/>


### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [x] The code builds clean without any errors or warnings
- [x] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>

2025-08-04 21:54:45 +00:00

models

Python: Introduce feature decorator to allow for experimental and release candidate decorator usage (#10691 )

2025-02-27 00:17:54 +00:00

__init__.py

Python: Bedrock agent (#10307 )

2025-01-31 19:44:39 +00:00

action_group_utils.py

Python: Bedrock agent (#10307 )

2025-01-31 19:44:39 +00:00

bedrock_agent_base.py

Python: Update Agent invoke abstraction parameters (#11192 )

2025-03-25 23:16:34 +00:00

bedrock_agent_settings.py

Python: Move to a thinner wrap for Bedrock Agent in Python (#10740 )

2025-03-03 22:07:41 +00:00

bedrock_agent.py

Python: Input & output attributes in invoke_agent span (#12834 )

2025-08-04 21:54:45 +00:00

README.md

Python: Bedrock agent (#10307 )

2025-01-31 19:44:39 +00:00

README.md

Amazon Bedrock AI Agents in Semantic Kernel

Overview

AWS Bedrock Agents is a managed service that allows users to stand up and run AI agents in the AWS cloud quickly.

Tools/Functions

Bedrock Agents allow the use of tools via action groups.

The integration of Bedrock Agents with Semantic Kernel allows users to register kernel functions as tools in Bedrock Agents.

Enable code interpretation

Bedrock Agents can write and execute code via a feature known as code interpretation similar to what OpenAI also offers.

Enable user input

Bedrock Agents can request user input in case of missing information to invoke a tool. When this is enabled, the agent will prompt the user for the missing information. When this is disabled, the agent will guess the missing information.

Knowledge base

Bedrock Agents can leverage data saved on AWS to perform RAG tasks, this is referred to as the knowledge base in AWS.

Multi-agent

Bedrock Agents support multi-agent workflows for more complex tasks. However, it employs a different pattern than what we have in Semantic Kernel, thus this is not supported in the current integration.