Development build. This page describes main, not a released package. The latest published Lodestar.Extensions.AI is 0.1.0 — read its documentation.

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One type, OnnxEmbeddingGenerator: it presents the ONNX embedding path as Microsoft.Extensions.AI's IEmbeddingGenerator<string, Embedding<float>>, so a consumer written against that abstraction — a Semantic Kernel pipeline, a Microsoft.Extensions.AI chain, anything that takes the interface — can hold Lodestar embeddings without knowing Lodestar.

This package adds no arithmetic. Every vector it returns comes from OnnxTextEmbedder.EmbedBatch, unchanged, so what it owes is the interface contract and not a numerical one. That is why it carries no oracle corpus of its own: its suite asserts that its output is identical to the embedder's, and the embedder's own frozen corpora say what those numbers are.

Weights are never committed to this repository. A running example would need a model of tens of megabytes, and decisions/0002 rules that out; tools/fetch_*.py pulls vocabularies against a pinned SHA-256 when they are needed, and weights are not among them.

So the fences on these pages compile against the packed package and are marked docs-run: skip, which is what that marker is for — the same arrangement Lodestar.Onnx makes, and for the same reason.

Lodestar.Extensions.AI belongs to the interop tier, Lodestar.Extensions.*, which may take a dependency a core package refused because converting to a foreign type is not computing with it — decisions/0003. It exists because a core package carries no external dependency — decisions/0003. A caller who wants embeddings and not the Microsoft.Extensions.AI abstractions takes Lodestar.Onnx alone and restores nothing extra.

Type	What it is
OnnxEmbeddingGenerator	Presents an OnnxTextEmbedder as an IEmbeddingGenerator<string, Embedding<float>>.

• ONNX inference — the package this one adapts.
• Semantic search with embeddings — the chain it sits in.
• Python → C# equivalence.