This release is a pre-release and may not be stable for production use.
Get Started with Microsoft Agent Framework Azure AI Search
Please install this package via pip:
pip install agent-framework-azure-ai-search --pre
Azure AI Search Integration
The Azure AI Search integration provides context providers for RAG (Retrieval Augmented Generation) capabilities with two modes:
- Semantic Mode: Fast hybrid search (vector + keyword) with semantic ranking
- Agentic Mode: Multi-hop reasoning using Knowledge Bases for complex queries
API versions: stable vs preview
The integration auto-detects which build of azure-search-documents is installed — there is
nothing to configure in code:
| Channel | Install | Data-plane api-version (chosen by the SDK) |
|---|---|---|
| Stable | pip install azure-search-documents (>=12.0.0) |
2026-04-01 |
| Preview | pip install --pre "azure-search-documents>=12.1.0b1" |
2026-05-01-preview |
The provider never pins an api-version; the installed build selects its own, so newer
releases work without code changes.
Agentic output modes (answer_synthesis) and extended reasoning effort (low/medium)
ship only in the preview build. When a stable build is installed, the provider uses extractive
output with minimal reasoning effort and raises an actionable error if a preview-only option is
explicitly requested. Switching channels is a single change — the install — with no code edits.
Query-time user identity
Agentic retrieval can forward a caller-specific Azure AI Search authorization token when the
index uses permission fields for document-level access control. Pass a sync or async Azure token
credential for the caller via query_source_credential; the provider requests the Azure AI Search
resource scope and forwards the token on each Knowledge Base retrieval request. This capability
requires azure-search-documents>=12.1.0b1, installed with
pip install --pre "azure-search-documents>=12.1.0b1".
context_provider = AzureAISearchContextProvider(
endpoint=search_endpoint,
credential=application_credential,
mode="agentic",
knowledge_base_name=knowledge_base_name,
query_source_credential=user_credential,
)
Basic Usage Example
See the Azure AI Search context provider examples which demonstrate:
- Semantic search with hybrid (vector + keyword) queries
- Agentic mode with Knowledge Bases for complex multi-hop reasoning
- Environment variable configuration with Settings class
- API key and managed identity authentication
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