mirror of https://github.com/microsoft/agent-framework.git synced 2026-06-16 21:04:09 +08:00

Files

T

Eduard van Valkenburg 4530504a3d Python: Azure AI Search provider improvements - EmbeddingGenerator, async context manager, KB message handling (#4212 )

* small updates and improvements in the azure AISearch provider

* Fix mypy errors and embedding function test

- Use separate variable for embeddings result to avoid mypy type reassignment error
- Fix test_vectorized_query_with_embedding_function: use real async function
  instead of AsyncMock which falsely matches SupportsGetEmbeddings protocol

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* fixes from feedback

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

4530504a3d · 2026-02-25 06:47:26 +00:00

History

agent_framework_azure_ai_search

Python: Azure AI Search provider improvements - EmbeddingGenerator, async context manager, KB message handling (#4212 )

2026-02-25 06:47:26 +00:00

tests

Python: Azure AI Search provider improvements - EmbeddingGenerator, async context manager, KB message handling (#4212 )

2026-02-25 06:47:26 +00:00

AGENTS.md

Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747 )

2026-02-10 23:04:32 +00:00

LICENSE

Python: renamed ai search and cleanup of samples and unified import logic (#2369 )

2025-11-24 17:06:22 +00:00

pyproject.toml

Python: Updated package versions for RC release (#4068 )

2026-02-19 16:11:48 +00:00

README.md

Python: restructure: Python samples into progressive 01-05 layout (#3862 )

2026-02-12 17:36:36 +00:00

README.md

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

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