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Giles Odigwe
7135ed13eb
* Python: Add file_ids and data_sources support to AzureAIAgentClient.get_code_interpreter_tool() Update the factory method to accept file_ids and data_sources keyword arguments, matching the underlying azure.ai.agents SDK CodeInterpreterTool constructor. This enables users to attach uploaded files for code interpreter analysis. Fixes #4050 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * addressed comments * addressed comments * Add per-message file attachment support for AzureAIAgentClient Add hosted_file handling in _prepare_messages() to convert Content.from_hosted_file() into MessageAttachment on ThreadMessageOptions. This enables per-message file scoping for code interpreter, matching the underlying Azure AI Agents SDK MessageAttachment pattern. - Add hosted_file case in _prepare_messages() match statement - Import MessageAttachment from azure.ai.agents.models - Add sample for per-message CSV file attachment with code interpreter - Add employees.csv test data file - Add 3 unit tests for hosted_file attachment conversion Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: validation, fix assertions, remove MessageAttachment - Add empty string validation in resolve_file_ids() - Add test for Content with file_id=None - Add test for empty string file_ids - Revert MessageAttachment/hosted_file handling from _prepare_messages() (moved to separate issue #4352 for proper design) - Remove per-message file upload sample and employees.csv - Keep data_sources assertion as-is (dict keyed by asset_identifier) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
7135ed13eb
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2026-03-03 23:01:17 +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.