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Python: Feature/azure ai search agentic rag (search as separate package) (#2328)
* Python: Fix pyright errors and move search provider to core (#1546) * address pablo coments * update azure ai search pypi version to latest prev * init update * Fix MyPy type annotation errors in search provider - Add type annotation to DEFAULT_CONTEXT_PROMPT - Add type annotation to vectorizable_fields - Add union type annotation to vector_queries * Fix DEFAULT_CONTEXT_PROMPT MyPy error and update test - Rename DEFAULT_CONTEXT_PROMPT to _DEFAULT_SEARCH_CONTEXT_PROMPT to avoid conflict with base class Final variable - Update test to use new constant name - All core package tests passing (1123 passed) * Python: Move Azure AI Search to separate package per PR feedback Addresses reviewer feedback from PR #1546 by isolating the beta dependency (azure-search-documents==11.7.0b2) into a new agent-framework-aisearch package. Changes: - Created new agent-framework-aisearch package with complete structure - Moved AzureAISearchContextProvider from core to aisearch package - Added AzureAISearchSettings class for environment variable auto-loading - Added support for direct API key string (auto-converts to AzureKeyCredential) - Added azure_openai_api_key parameter for Knowledge Base authentication - Updated embedding_function type to Callable[[str], Awaitable[list[float]]] - Moved Role import to top-level imports - Maintained lazy loading through agent_framework.azure module - Removed beta dependency from core package - Updated all tests to use new package location - All quality checks pass: ruff format/lint, pyright, mypy (0 errors) - All 21 unit tests pass with 59% coverage Semantic search mode verified working with both API key and managed identity authentication. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Python: Clarify top_k parameter only applies to semantic mode Updated documentation to clarify that the top_k parameter only affects semantic search mode. In agentic mode, the server-side Knowledge Base determines retrieval based on query complexity and reasoning effort. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Python: Add Knowledge Base output mode and retrieval reasoning effort parameters Added support for configurable Knowledge Base behavior in agentic mode: - knowledge_base_output_mode: "extractive_data" (default) or "answer_synthesis" Some knowledge sources require answer_synthesis mode for proper functionality. - retrieval_reasoning_effort: "minimal" (default), "medium", or "low" Controls query planning complexity and multi-hop reasoning depth. These parameters give users fine-grained control over Knowledge Base behavior and enable support for knowledge sources that require answer synthesis. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * effort and outputmode query params * Address PR review feedback for Azure AI Search context provider * comments eduward * ed latest comments --------- Co-authored-by: Farzad Sunavala <farzad.sunavala.enovate.ai> Co-authored-by: farzad528 <farzad528@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com>
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‎python/.env.example‎

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@@ -3,6 +3,14 @@ AZURE_AI_PROJECT_ENDPOINT=""
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AZURE_AI_MODEL_DEPLOYMENT_NAME=""
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# Bing connection for web search (optional, used by samples with web search)
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BING_CONNECTION_ID=""
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# Azure AI Search (optional, used by AzureAISearchContextProvider samples)
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AZURE_SEARCH_ENDPOINT=""
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AZURE_SEARCH_API_KEY=""
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AZURE_SEARCH_INDEX_NAME=""
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AZURE_SEARCH_SEMANTIC_CONFIG=""
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AZURE_SEARCH_KNOWLEDGE_BASE_NAME=""
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# Note: For agentic mode Knowledge Bases, also set AZURE_OPENAI_ENDPOINT below
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# (different from AZURE_AI_PROJECT_ENDPOINT - Knowledge Base needs OpenAI endpoint for model calls)
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# OpenAI
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OPENAI_API_KEY=""
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OPENAI_CHAT_MODEL_ID=""

‎python/packages/aisearch/LICENSE‎

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MIT License
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Copyright (c) Microsoft Corporation.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE

‎python/packages/aisearch/README.md‎

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# Get Started with Microsoft Agent Framework Azure AI Search
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Please install this package via pip:
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```bash
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pip install agent-framework-aisearch --pre
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```
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## Azure AI Search Integration
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The Azure AI Search integration provides context providers for RAG (Retrieval Augmented Generation) capabilities with two modes:
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- **Semantic Mode**: Fast hybrid search (vector + keyword) with semantic ranking
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- **Agentic Mode**: Multi-hop reasoning using Knowledge Bases for complex queries
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### Basic Usage Example
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See the [Azure AI Search context provider examples](https://github.com/microsoft/agent-framework/tree/main/python/samples/getting_started/agents/azure_ai/) which demonstrate:
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- Semantic search with hybrid (vector + keyword) queries
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- Agentic mode with Knowledge Bases for complex multi-hop reasoning
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- Environment variable configuration with Settings class
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- API key and managed identity authentication

‎python/packages/aisearch/agent_framework_aisearch/__init__.py‎

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# Copyright (c) Microsoft. All rights reserved.
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import importlib.metadata
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from ._search_provider import AzureAISearchContextProvider, AzureAISearchSettings
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try:
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__version__ = importlib.metadata.version(__name__)
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except importlib.metadata.PackageNotFoundError:
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__version__ = "0.0.0" # Fallback for development mode
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__all__ = [
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"AzureAISearchContextProvider",
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"AzureAISearchSettings",
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"__version__",
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]

‎python/packages/aisearch/agent_framework_aisearch/_search_provider.py‎

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‎python/packages/aisearch/pyproject.toml‎

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[project]
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name = "agent-framework-aisearch"
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description = "Azure AI Search integration for Microsoft Agent Framework."
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authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
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readme = "README.md"
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requires-python = ">=3.10"
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version = "1.0.0b251118"
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license-files = ["LICENSE"]
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urls.homepage = "https://aka.ms/agent-framework"
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urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
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urls.release_notes = "https://github.com/microsoft/agent-framework/releases?q=tag%3Apython-1&expanded=true"
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urls.issues = "https://github.com/microsoft/agent-framework/issues"
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classifiers = [
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"License :: OSI Approved :: MIT License",
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"Development Status :: 4 - Beta",
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"Intended Audience :: Developers",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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"Programming Language :: Python :: 3.14",
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"Typing :: Typed",
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]
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dependencies = [
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"agent-framework-core",
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"azure-search-documents==11.7.0b2",
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]
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[tool.uv]
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prerelease = "if-necessary-or-explicit"
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environments = [
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"sys_platform == 'darwin'",
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"sys_platform == 'linux'",
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"sys_platform == 'win32'"
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]
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[tool.uv-dynamic-versioning]
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fallback-version = "0.0.0"
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[tool.pytest.ini_options]
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testpaths = 'tests'
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addopts = "-ra -q -r fEX"
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asyncio_mode = "auto"
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asyncio_default_fixture_loop_scope = "function"
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filterwarnings = [
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"ignore:Support for class-based `config` is deprecated:DeprecationWarning:pydantic.*"
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]
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timeout = 120
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[tool.ruff]
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extend = "../../pyproject.toml"
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exclude = ["examples"]
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[tool.coverage.run]
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omit = [
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"**/__init__.py"
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]
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[tool.pyright]
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extends = "../../pyproject.toml"
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exclude = ['tests']
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[tool.mypy]
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plugins = ['pydantic.mypy']
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strict = true
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python_version = "3.10"
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ignore_missing_imports = true
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disallow_untyped_defs = true
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no_implicit_optional = true
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check_untyped_defs = true
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warn_return_any = true
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show_error_codes = true
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warn_unused_ignores = false
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disallow_incomplete_defs = true
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disallow_untyped_decorators = true
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[tool.bandit]
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targets = ["agent_framework_aisearch"]
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exclude_dirs = ["tests"]
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[tool.poe]
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executor.type = "uv"
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include = "../../shared_tasks.toml"
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[tool.poe.tasks]
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mypy = "mypy --config-file $POE_ROOT/pyproject.toml agent_framework_aisearch"
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test = "pytest --cov=agent_framework_aisearch --cov-report=term-missing:skip-covered tests"
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[build-system]
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requires = ["flit-core >= 3.11,<4.0"]
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build-backend = "flit_core.buildapi"

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