feat: Add select-algorithm samples for DocumentDB vector index selection (5 languages)#74
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Add DocumentDB vector index algorithm selection samples demonstrating HNSW, IVF, and DiskANN index types across TypeScript, Python, Go, Java, and .NET. Each sample creates indexes with documented defaults, performs vector searches, and compares results. CI updated to validate all new samples in the existing workflow matrix. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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- Rename MONGO_CLUSTER_NAME to DOCUMENTDB_CLUSTER_NAME in all 5 language samples - Add DOCUMENTDB_CLUSTER_NAME dual-output in Bicep (preserves backward compat) - Replace Data Explorer cleanup guidance with VS Code extension - Strengthen algorithm guidance: DiskANN recommended for enterprise (16K dims, disk-based) - Remove python-dotenv from pip install (repo rule Azure-Samples#10) - Fix Python filename refs (select_algorithm.py -> compare_all.py) - Revert out-of-scope vector-search-* changes to origin/main Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Summary
Adds select-algorithm samples demonstrating how to choose the optimal vector index algorithm (HNSW, IVF, DiskANN) for Azure Cosmos DB for MongoDB (vCore) / DocumentDB, in 5 languages: TypeScript, Python, Go, Java, and .NET.
What's included
ai/select-algorithm-typescript/ai/select-algorithm-python/ai/select-algorithm-go/ai/select-algorithm-java/ai/select-algorithm-dotnet/Each sample includes:
CI
validate-samples.yml— Builds all 5 language samples on PR and pushKey parameters (from docs)
Documentation references