[pull] main from microsoft:main#132
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pull[bot] merged 2 commits intographrag:mainfrom Feb 21, 2026
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* addd streaming * fixes
#2236) * feat(graphrag-vectors): add filtering, timestamps, and CRUD operations Implement the vector store enhancements from the graphrag-vectors-design spec: New modules: - filtering.py: Pydantic-based filter expression system with F builder, operator overloads, JSON serialization, client-side evaluate(), and per-backend compilation (SQL for LanceDB/CosmosDB, OData for Azure AI Search) - timestamp.py: ISO 8601 timestamp explosion into filterable component fields Enhanced VectorStoreDocument: - data: dict for user-defined metadata fields - create_date / update_date: automatic ISO 8601 timestamps Enhanced VectorStore base class: - fields config for typed metadata columns - insert / count / remove / update CRUD methods - select, filters, include_vectors params on search methods - Automatic timestamp explosion on insert/update - User-defined date field explosion Backend implementations (LanceDB, Azure AI Search, CosmosDB): - Full filter compilation to native query languages - Typed schema creation with user-defined fields - All new CRUD operations Breaking changes: - search_by_id raises IndexError when document not found - Updated indexer_adapters.py caller to handle the new exception Tests: - 54 unit tests for filtering and timestamp modules - 28 LanceDB integration tests covering CRUD, filters, timestamps, select, include_vectors, and user-defined date field explosion * fix: resolve CI build failures (formatting, lint, pyright, test mocks) - Fix ruff formatting and lint errors across all changed files - Refactor filtering.py: move operator overloads from monkey-patching to direct class methods for pyright visibility - Use validation_alias/serialization_alias with populate_by_name for Pydantic AND/OR/NOT models (pyright + runtime compatible) - Use Operator enum members instead of string literals in FieldRef - Add missing abstract methods (insert, count, remove, update) to test mock VectorStore classes - Update mock method signatures to match base class (select, filters, include_vectors params) - Add docstrings to FieldRef magic methods (ruff D105) - Fix noqa:S608 placement in cosmosdb.py * feat: add top-level vector_size to VectorStoreConfig Add a vector_size field (default 3072) to VectorStoreConfig so users can set it once instead of on every individual index schema. The value is propagated to new IndexSchema entries during validation. * chore: add semversioner patch entry * chore: add ismatch and ftype to spellcheck dictionary * Add example notebooks for LanceDB, Azure AI Search, and CosmosDB vector stores - Three notebooks demonstrating: document loading, similarity search, metadata filtering with F builder, timestamp filtering, document update/removal - Sample data files (text_units.parquet, embeddings.text_unit_text.parquet) - Add CPY001, SLF001, DTZ005 to notebook lint ignores in pyproject.toml * refactor: extract model/tokenizer creation from generate_text_embeddings into callers
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