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# Fix for Issue #3797 ## Problem Vector store search failed with Pydantic ValidationError when chunk metadata contained list-type values. **Error:** ``` ValidationError: 3 validation errors for VectorStoreSearchResponse attributes.tags.str: Input should be a valid string attributes.tags.float: Input should be a valid number attributes.tags.bool: Input should be a valid boolean ``` **Root Cause:** - `Chunk.metadata` accepts `dict[str, Any]` (any type allowed) - `VectorStoreSearchResponse.attributes` requires `dict[str, str | float | bool]` (primitives only) - Direct assignment at line 641 caused validation failure for non-primitive types ## Solution Added utility function to filter metadata to primitive types before creating search response. ## Impact **Fixed:** - Vector search works with list metadata (e.g., `tags: ["transformers", "gpu"]`) - Lists become searchable as comma-separated strings - No ValidationError on search responses **Preserved:** - Full metadata still available in `VectorStoreContent.metadata` - No API schema changes - Backward compatible with existing primitive metadata **Affected:** All vector store providers using `OpenAIVectorStoreMixin`: FAISS, Chroma, Qdrant, Milvus, Weaviate, PGVector, SQLite-vec ## Testing tests/unit/providers/vector_io/test_vector_utils.py::test_sanitize_metadata_for_attributes --------- Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com> |
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| llama-stack-spec.yaml | ||
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| stainless-llama-stack-spec.yaml | ||
