altair823
bcbe2b8531
First real Embedder implementation. Wraps fastembed-rs (ONNX runtime)
with the e5 prefix convention, batching, and {data_dir}/${XDG_DATA_HOME}
template expansion so model files land under config.storage.model_dir/
fastembed/ without polluting kb-config's public API.
Public surface:
- pub struct FastembedEmbedder
- pub fn new(config: &Config) -> Result<Self>
- impl kb_core::Embedder (via kb-embed re-export)
Behavior:
- Default model multilingual-e5-small (384 dims). model_id and
model_version come from config.models.embedding.{model,version}.
- Pre-load dim check via TextEmbedding::get_model_info: dim mismatch
bails before paying the ~470MB ONNX init cost.
- e5 prefix applied BEFORE tokenization: "passage: " for
EmbeddingKind::Document, "query: " for EmbeddingKind::Query. Pinned
by prefix_input unit tests.
- Batches inputs into chunks of config.models.embedding.batch_size,
concatenates results in input order.
- L2 normalization is performed by fastembed 4.9's default transformer
pipeline (verified at fastembed/src/text_embedding/output.rs:43);
we skip re-normalization. Integration test pins ‖v‖ ≈ 1.0 ± 1e-3 so
a future fastembed bump that drops this invariant fails loudly.
- Synchronous (no async runtime). Mutex serializes calls into the
underlying ONNX session — conservative; ORT Session is Send+Sync but
callers (kb-app indexer) batch sequentially anyway. Revisit if
profiling shows contention.
- First-run model download surfaces via tracing::info before/after
TextEmbedding::try_new — users no longer stare at a silent 30-60s
pause during the 470MB pull.
Tests:
- 11 default-lane tests covering: check_dim match/mismatch (no model
load), prefix_input Document/Query/empty, resolve_model
known/unknown, expand_path substitution + no-op + XDG_DATA_HOME set
+ XDG_DATA_HOME unset (falls back to ~/.local/share with recursive
~ expansion). XDG tests serialize on a Mutex + RAII guard since
edition 2024 makes set_var/remove_var unsafe.
- 7 #[ignore] integration tests covering: full construction with
default config, dim-mismatch belt-and-braces, Document vs Query
cosine differential, L2 unit norm, byte-equal determinism, batch-64
performance under 5s, snapshot-hash stability over a 5-sentence
multilingual fixture.
- Snapshot test fails LOUDLY when SNAPSHOT_HASH_BASELINE is 0 — prints
the captured hash and panics with paste-back instructions, so first
--ignored run forces the maintainer to pin the baseline rather than
silently passing.
- Workspace: 222 tests pass (default lane); clippy clean.
Allowed deps respected: kb-config, kb-embed (re-exports kb-core
trait surface), fastembed = "4.9", tracing, anyhow. tokenizers and
ort enter transitively through fastembed; reqwest/hyper/hf-hub also
transitive (model download is fastembed's responsibility per spec
carve-out). No direct kb-core dep needed — re-exports cover it.
Pinned to fastembed 4.x rather than the recent 5.x to limit blast
radius; consider bump when p3-3 (lancedb-store) consumes the embedder
output shape.
Out of scope: reranker (P+), Ollama embedding endpoint, candle
adapter, image embeddings (P6).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
46 lines
1.4 KiB
TOML
46 lines
1.4 KiB
TOML
[workspace]
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resolver = "3"
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members = [
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"crates/kb-core",
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"crates/kb-parse-types",
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"crates/kb-config",
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"crates/kb-source-fs",
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"crates/kb-parse-md",
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"crates/kb-normalize",
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"crates/kb-chunk",
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"crates/kb-store-sqlite",
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"crates/kb-search",
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"crates/kb-embed",
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"crates/kb-embed-local",
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"crates/kb-app",
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"crates/kb-cli",
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]
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[workspace.package]
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edition = "2024"
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rust-version = "1.85"
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license = "MIT OR Apache-2.0"
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repository = "https://github.com/altair823/kb"
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version = "0.1.0"
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[workspace.dependencies]
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anyhow = "1"
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thiserror = "2"
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serde = { version = "1", features = ["derive"] }
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serde_json = "1"
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time = { version = "0.3", features = ["serde", "macros", "formatting", "parsing"] }
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uuid = { version = "1", features = ["v7", "serde"] }
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blake3 = "1"
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tracing = "0.1"
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# `bundled` ships SQLite source so the workspace doesn't depend on a
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# system libsqlite3 (matches the kb-store-sqlite feature set).
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rusqlite = { version = "0.32", features = ["bundled"] }
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globset = "0.4"
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tempfile = "3"
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proptest = "1"
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# fastembed-rs ships ONNX runtime via the `ort-download-binaries` feature
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# in its default set (which also pulls `hf-hub` for first-run model
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# downloads). Pinned to the 4.x line per task p3-2 (current 5.x release
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# remains untested for this workspace).
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fastembed = "4.9"
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