[ybai08]

What

The documentary half of #1996, which the issue says is worth a PR on its own once the answer is "a re-embed is needed".

• docs/architecture/embedding.md says what is bundled: model_optimized.onnx from Qdrant/bge-small-en-v1.5-onnx-Q, FLOAT16 weights, 66,465,124 bytes, with the throughput I measured and the machine it was measured on. It also records why an int8 export does not replace it: half the size and 1.6 times as fast on chunk-sized text, but not the same vector space (over the eval's 66 queries a mean cosine of 0.997 and a minimum of 0.978, and one of them moves a rank), and the bundled file is pinned by hash.
• docs/architecture/search.md: the Known gaps line is deleted, as the issue asks. What it said is now stated where the embedder is described, not listed as a gap.
• docs/adr/0007-bundled-embeddings.md: the Status line now ends with the fact that the bundled file is FP16, not the int8 the Decision names, and points at where it was measured. Nothing else in the ADR changes.
• docs/adr/0036-the-index-records-its-embedder.md: its link to the deleted Known gaps line now goes to embedding.md#choosing.

Why

Refs #1996. The measurements, the method and the full table are in this comment on the issue.

The ADR edits are a Status line and a link, the two edits docs/adr/README.md lets an accepted ADR take. An earlier revision of this PR added a dated correction section to ADR 0007; it was removed in review.

Not in this PR: the other finding from the issue comment, that the same pinned weights widened to fp32 embed 2.3 to 2.7 times as fast on this machine with identical ranks. That needs a decision under ADR 0036 and would be a proposal, not a doc fix. The issue stays open for it and for the re-embed path.

How to test

python scripts/check_docs.py   # from the repo root

Docs only; that check passes (118 files, 0 problems). The numbers were measured once, on one Apple M6, with onnxruntime 1.29.0's CPU provider; nothing was measured on x86, Windows or Linux.

High-level PR Summary

This PR updates documentation to accurately reflect that the bundled embedding model uses FLOAT16 weights (not int8 as originally documented), includes measured performance metrics (72 short passages/sec, 14.5 chunk-sized passages/sec on Apple M6), explains why an int8 alternative was not adopted despite being faster (different vector space with cosine similarity of 0.998 mean), and corrects the historical inaccuracy in ADR 0007 while maintaining the original decision's validity.

⏱️ Estimated Review Time: 5-15 minutes

💡 Review Order Suggestion

Order	File Path
1	docs/adr/0007-bundled-embeddings.md
2	docs/architecture/embedding.md
3	docs/architecture/search.md

Summary by CodeRabbit

• Documentation
  • Clarified that the bundled bge-small embedding model uses FLOAT16 weights and documented its measured file size.
  • Added CPU throughput comparisons with an int8 export, including model size, speed, similarity, and retrieval-evaluation results.
  • Documented that using a different model build requires re-embedding, and updated where the bundled-model constraint is described.
  • Removed the outdated precision discrepancy from the listed search gaps.

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📝 Walkthrough

Walkthrough

The documentation identifies the bundled ONNX model as FLOAT16, records its size and performance comparisons, and describes the requirement to re-embed when using another model build.

Changes

Bundled Embedding Documentation

Layer / File(s)	Summary
Bundled model precision and details docs/adr/0007-bundled-embeddings.md, docs/architecture/embedding.md, docs/architecture/search.md	The ADR corrects the int8 description. The embedding documentation adds model size, throughput, and int8 comparison details. The search documentation removes the prior known-gap item.

Priority: ⬇️ Low

Estimated code review effort: 1 (Trivial) | ~5 minutes

Change: Other

Merge Risk: ⚪ Minimal · up to 21545

The documentation correctly explains that replacing the bundled model build requires re-embedding. No actionable issue remains before merge.

Architecture Summary

Architecture risk: 🔵 Low · up to a3ab7

The change affects 1 system.

Changed systems: docs

Architecture concerns
No architecture-level concerns identified.

Review details

Systems and components

• observed — docs (service) was modified; 3 changed files map to changed impact.

Before / after behavior

• observed — Modified behavior in docs/adr/0007-bundled-embeddings.md: The status now flags the Decision’s int8 description as inconsistent with the bundled FP16 file.
• observed — Modified behavior in docs/adr/0007-bundled-embeddings.md: Adds a correction identifying the bundled ONNX file’s FLOAT16 weights and confirming its 384 dimensions and 66,465,124-byte size; it retains the decision to bundle and run the file in process on the CPU and links to further explanation.
• observed — Modified behavior in docs/architecture/embedding.md: Adds details about the bundled bge-small file’s FLOAT16 weights, size, and measured throughput, then compares an int8 export’s size, speed, vector similarity, and retrieval results. It states that the bundled file is hash-pinned and replacing it requires re-embedding.
• observed — Modified behavior in docs/architecture/search.md: Removed the Known gaps item describing the bundled model’s FP16 weights, its difference from ADR 0007’s int8 specification, and the stated constraints and re-embedding requirement for replacing the hash-pinned model.

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check. Docstring coverage is scoped to functions touched by this diff. Analyzed 0 functions across 0…
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly describes the main documentation change: correcting the bundled embedder’s format and reporting its measured size and speed.

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Actionable comments posted: 1

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Inline comments:
Review comments at @docs/architecture/embedding.md:
- Line 24: Update the hash-pinning and re-embedding statement in the
embedding-model comparison to apply only to libraries using the bundled model.
Preserve the existing claim for those libraries without implying that libraries
selecting curated or Hugging Face embedders use the bundled file.

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[MODSetter]

Reviewed this. Every number checks out against the pins: the manifest's F16, 66,465,124 bytes and sha256 match bundled.py, and the throughput and int8 figures match your measurements on #1996. Three doc fixes before it can merge.

1. ADR 0036 now links to nothing

docs/adr/0036-the-index-records-its-embedder.md:30 points at "(search, Known gaps)", and this PR deletes that Known gaps line. Change the link to ([embedding](../architecture/embedding.md#choosing)); a link fix is an edit an accepted ADR may take.

2. The cosine isn't over the queries

embedding.md:24 says the 0.998 mean and 0.978 minimum cosine are "over the retrieval eval's 66 queries", but your comment on #1996 measured them over the eval corpus's passages (119 short and 21 chunk-sized). Say so, or post a per-query cosine on #1996.

3. An accepted ADR takes no new sections

docs/adr/README.md says the only edits an accepted ADR takes are its Status line and fixes to its links, so the new "Correction, 2026-10-02" section in ADR 0007 can't stay. Drop it and end the Status line with the fact, for example: "…; the bundled file is FP16, not the int8 the Decision names (66,465,124 bytes, measured in embedding, #1996)". ADR 0036 already records FP16 as decided.

Push the fixes to this branch and it will be reviewed again.

[ybai08]

All three are pushed in 87b8ce4.

1. ADR 0036 now links to embedding.md#choosing.
2. The sentence was wrong, and going back to the run's output showed the table on The bundled embedding model is FP16, not the int8 ADR 0007 specifies #1996 was too: its cosine column paired the mean over the 119 short passages (0.998) with the minimum over the 66 queries (0.978). Over the 66 queries it is a mean of 0.997 and a minimum of 0.978; over the 119 short passages, 0.998 and 0.992. The doc now gives the per-query pair with the passages' beside it, and the per-set figures are on the issue: The bundled embedding model is FP16, not the int8 ADR 0007 specifies #1996 (comment)
3. The Correction section is gone, and ADR 0007's Status line ends with your wording, with The bundled embedding model is FP16, not the int8 ADR 0007 specifies #1996 as a link.

python scripts/check_docs.py passes (118 files, 0 problems). I updated the PR description to match.