Giles Odigwe
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* Bump Python package versions for 1.15.0 release Prepare the CHANGELOG-selected Python packages for the 1.15.0 release. Root and core move to 1.15.0; changed stable extensions receive package-specific minor or patch bumps; changed beta packages receive the 260821 stamp; no beta cohort bump is applied. Core dependency floors use the conservative policy for co-released packages. Release validation also adds the six dependency required by the supported Azure Cosmos SDK floor and retains cross-platform-compatible development-tool pins. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 98e979bd-1d07-41fd-946d-00db8a93e248 * Remove hook-only formatting changes Keep the Python 1.15.0 release commit scoped to package metadata, release notes, dependency floors, and the lockfile. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 98e979bd-1d07-41fd-946d-00db8a93e248 * Minimize release lockfile changes Restore the upstream PyPI-backed lockfile and retain only package versions and dependency metadata changed by the Python 1.15.0 release. Also preserve the development-tool upgrades already present on main. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 98e979bd-1d07-41fd-946d-00db8a93e248 * Retain OpenAI core compatibility floor Keep agent-framework-openai 1.13.1 compatible with core 1.13 because its streaming tool-call index fix uses the existing additional_properties API and does not require core 1.15. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 98e979bd-1d07-41fd-946d-00db8a93e248 * Raise OpenAI version and core floor Bump agent-framework-openai to 1.14.0 and require core 1.15.0 so the new dependency requirement is signaled as a minor release. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 98e979bd-1d07-41fd-946d-00db8a93e248 --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 98e979bd-1d07-41fd-946d-00db8a93e248
Get Started with Microsoft Agent Framework Anthropic
Please install this package via pip:
pip install agent-framework-anthropic --pre
Anthropic Integration
The Anthropic integration enables communication with the Anthropic API, allowing your Agent Framework applications to leverage Anthropic's capabilities.
The package also includes Anthropic-hosted transport wrappers for:
- Microsoft Foundry via
AnthropicFoundryClient - Amazon Bedrock via
AnthropicBedrockClient - Google Vertex AI via
AnthropicVertexClient
Basic Usage Example
See the Anthropic agent examples which demonstrate:
- Connecting to a Anthropic endpoint with an agent
- Streaming and non-streaming responses
Structured system blocks for prompt caching
Use instructions with Anthropic-native system blocks when you need structured system prompt content, such as
prompt-cache cache_control metadata. Do not combine structured instructions blocks with a leading system message.
from anthropic.types.beta import BetaTextBlockParam
from agent_framework_anthropic import AnthropicClient
client = AnthropicClient()
system_blocks: list[BetaTextBlockParam] = [
{"type": "text", "text": "Stable instructions", "cache_control": {"type": "ephemeral", "ttl": "1h"}},
]
response = await client.get_response("Hello", options={"instructions": system_blocks})
Instructions contributed later in a run — by a context provider such as SkillsProvider, or by per-run
options — are appended as an additional text block after the configured blocks. The blocks you supply keep
their structure and their position, so a cache_control breakpoint stays valid.