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Eduard van Valkenburg
3e03a305f6
* Implement annotation-based context compaction Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Handle missing compaction attributes in BaseChatClient Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CI typing and bandit issues Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Optimize incremental compaction annotation pass Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refinement * Python: add ToolResultCompactionStrategy and CompactionProvider Add ToolResultCompactionStrategy that collapses older tool-call groups into short summary messages (e.g. [Tool calls: get_weather]) while keeping the most recent groups verbatim. This mirrors the .NET ToolResultCompactionStrategy from PR #4533. Add CompactionProvider as a context-provider that auto-applies compaction before each agent turn and stores compacted history in session state after each turn. Includes tests and samples for both features. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refinement and alignment with dotnet PR * updated tool result compaction * updated tool result compaction * Python: add ToolResultCompactionStrategy, CompactionProvider, and skip_excluded - ToolResultCompactionStrategy collapses older tool-call groups into [Tool results: func_name: result] summaries with bidirectional tracing (same pattern as SummarizationStrategy). - CompactionProvider as BaseContextProvider with separate before_strategy and after_strategy parameters. before_strategy compacts loaded context; after_strategy compacts stored history via history_source_id. - InMemoryHistoryProvider gains skip_excluded flag to filter out messages marked as excluded by compaction strategies. - Tests, samples, and exports updated. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed checks * fix mypy * Fix: ensure summary messages from both strategies get full compaction annotations SummarizationStrategy was not calling annotate_message_groups after inserting its summary message, so the summary lacked core group annotations (id, kind, index, has_reasoning, _excluded). Added the missing call. ToolResultCompactionStrategy already had it. Added tests verifying both strategies produce fully annotated summaries. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated propagation * fix mypy --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
3e03a305f6
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2026-03-11 19:23:00 +00:00
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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