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45527eed29
Merged and refactored eval module per Eduard's PR review: - Merge _eval.py + _local_eval.py into single _evaluation.py - Convert EvalItem from dataclass to regular class - Rename to_dict() to to_eval_data() - Convert _AgentEvalData to TypedDict - Simplify check system: unified async pattern with isawaitable - Parallelize checks and evaluators with asyncio.gather - Add all/any mode to tool_called_check - Fix bool(passed) truthy bug in _coerce_result - Remove deprecated function_evaluator/async_function_evaluator aliases - Remove _MinimalAgent, tighten evaluate_agent signature - Set self.name in __init__ (LocalEvaluator, FoundryEvals) - Limit FoundryEvals to AsyncOpenAI only - Type project_client as AIProjectClient - Remove NotImplementedError continuous eval code - Add evaluation samples in 02-agents/ and 03-workflows/ - Update all imports and tests (167 passing) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
45527eed29
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Get Started with Microsoft Agent Framework Azure AI
Please install this package via pip:
pip install agent-framework-azure-ai --pre
Foundry Memory Context Provider
The Foundry Memory context provider enables semantic memory capabilities for your agents using Azure AI Foundry Memory Store. It automatically:
- Retrieves static (user profile) memories on first run
- Searches for contextual memories based on conversation
- Updates the memory store with new conversation messages
Basic Usage Example
See the Foundry Memory example which demonstrates:
- Creating a memory store using Azure AI Projects client
- Setting up an agent with FoundryMemoryProvider
- Teaching the agent user preferences
- Retrieving information using remembered context across conversations
- Automatic memory updates with configurable delays
and see the README for more information.