This release is a pre-release and may not be stable for production use.
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.
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