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* Bump Python package versions for 1.13.0 release Bump all 37 Python package projects because the CHANGELOG-driven release includes cross-package feature-usage telemetry, with core and root advancing to 1.13.0, OpenAI to 1.12.0, patch bumps for other stable packages, and 260730 stamps for alpha and beta packages. No optional beta cohort bump was applied; every prerelease package changed. Raise core floors conservatively across co-released packages. Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541 * Align co-released Python package dependencies Update the four hosting adapter pins to the co-released agent-framework-hosting alpha and raise the Azure Functions Durable Task floor to the co-released beta. Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541 * Minimize Python release lockfile updates Regenerate uv.lock with the pre-commit hook pinned uv version so the release changes only workspace package versions while preserving platform markers and agentlightning 0.3.0. Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541 --------- Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541
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})