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Giles Odigwe
ce7b5b17c1
* Fix as_agent() not defaulting name/description from client properties AzureAIClient.as_agent() and AzureAIAgentClient.as_agent() now fall back to self.agent_name and self.agent_description when name/description are not explicitly passed. This ensures Agent.name is populated for telemetry spans without requiring callers to repeat the name. Fixes #4471 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review: use is None checks instead of truthiness Switch from name or self.agent_name to explicit is None checks so that callers can intentionally pass empty strings without them being replaced by client defaults. Added edge-case tests for empty strings. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update docstrings to document name/description defaulting behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
ce7b5b17c1
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2026-03-05 20:12:11 +00:00
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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.