mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Eduard van Valkenburg
0cd40f8354
* [BREAKING] Refactor middleware layering and raw clients Reorder chat client layers so function invocation wraps chat middleware, and chat middleware stays outside telemetry while still running for each inner model call. Add middleware pipeline caching, refresh docs and samples, and split Anthropic into raw and public clients to match the standard layering model. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Tighten typing ignores in ancillary modules Add targeted typing ignores in workflow visualization and lab modules so pyright stays clean alongside the middleware refactor work. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix categorize_middleware to unpack tuple/Sequence and use relative MRO assertions - Broaden isinstance check in categorize_middleware from list to Sequence so tuples and other Sequence types are properly unpacked instead of being appended as a single item. - Replace fragile hardcoded MRO index assertions in anthropic test with relative ordering via mro.index(). - Add regression tests for categorize_middleware with tuple, list, and None inputs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix middleware string decomposition, add middleware param to FunctionInvocationLayer, and add tests (#4710) - Guard categorize_middleware Sequence check against str/bytes to prevent character-by-character decomposition of accidentally passed strings - Add explicit middleware parameter to FunctionInvocationLayer.get_response and merge it into client_kwargs before categorization, fixing the inconsistency where only OpenAIChatClient supported this parameter - Add assertions that RawAnthropicClient does not inherit convenience layers - Add chat middleware cache test with non-empty base middleware - Add tests for single unwrapped middleware item and string input Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Apply pre-commit auto-fixes * Address review feedback for #4710: review comment fixes --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <copilot@github.com>
0cd40f8354
ยท
2026-03-20 00:43:37 +00:00
History
Get Started with Microsoft Agent Framework Bedrock
Install the provider package:
pip install agent-framework-bedrock --pre
Bedrock Integration
The Bedrock integration enables Microsoft Agent Framework applications to call Amazon Bedrock models with familiar chat abstractions, including tool/function calling when you attach tools through ChatOptions.
Basic Usage Example
See the Bedrock sample for a runnable end-to-end script that:
- Loads credentials from the
BEDROCK_*environment variables - Instantiates
BedrockChatClient - Sends a simple conversation turn and prints the response