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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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