feat: add Google code retrieval across desktop CLI and MCP
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# Source-code relevance checkpoint
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Recorded 2026-10-12 using the actual verified Google EmbeddingGemma 2 Q8_0
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model, rebuilt native worker, shared hybrid service and MCP protocol. Windows
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VM, CPU only, one inference thread. No simulated provider or injected vectors.
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Google describes local code retrieval in its
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[launch blog](https://blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/).
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Its [model card](https://ai.google.dev/gemma/docs/embeddinggemma/model_card_2)
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specifies `task: code retrieval | query: {query}` for queries and
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`title: {filename} | text: {code}` for indexed source. searchi uses that pairing
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in Code scope. Google's published benchmark measures their full-precision
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checkpoint; it is not a searchi benchmark.
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## Frozen small regression
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[The evaluator](../tools/code-eval/evaluate.py) fixes the implementations,
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queries and expected files before inference. Eight short source files use
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generic filenames; a ninth ordinary document deliberately contains search
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terms. All nine files are indexed, so code filtering must exclude that document
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before ranking. The expected code excerpts are checked byte-for-byte through
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MCP `read_source`, including line locations. Fixture hashes and every returned
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rank are recorded in [raw CPU evidence](evidence/code-search-cpu.json).
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| Query intent | Source | Lexical rank | Hybrid rank |
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| --- | --- | --- | --- |
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| Streaming file SHA256 | Python | absent | 1 |
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| Lower bound in sorted numbers | C++ | absent | 1 |
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| Sum amounts by category | TypeScript | absent | 1 |
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| Retry requests with exponential backoff | Python | absent | 1 |
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| Release semaphore after async failure | C# | absent | 1 |
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| Escape unsafe HTML characters | PHP | absent | 1 |
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| Ten most expensive records | Python | absent | 1 |
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| File verification without full memory load, German | Python | absent | 1 |
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| Exact `refreshAccessToken` symbol | Rust | 1 | 1 |
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Top-1 success: **9/9 hybrid, 1/9 lexical**. Every expected hybrid source was
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verified and no ordinary document leaked into Code scope. Measured MCP
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roundtrips for these nine uncached code queries ranged from **63.88–228.21 ms**,
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median **110.76 ms**. Those timings exclude process/model startup and describe
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this tiny corpus only; they are not desktop first-use or large-project targets.
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## Defect discovered and fixed
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The first actual indexing attempt failed on TypeScript: Google's tokenizer
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normalized source characters, invalidating a detokenization-based byte-offset
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assumption. The worker now retains original UTF-8 source, checks the complete
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prefixed token budget, and splits normalized long inputs on original character
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boundaries. It returns exact original slices with bounded overlap and complete
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tail coverage. Short code that fits uses a direct fast path. A separate actual
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CPU regression covers the failing TypeScript plus roughly 38 KB of repeated
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code with German, Japanese and emoji. Fixtures were not edited to hide failure.
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Additional checks cover strict filtering before lexical/ANN candidate limits,
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named build files, overlapping routine context, schema upgrades, task-specific
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query caching, actual code/general vector separation and debug-vector parity.
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## Reproduce and limits
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Build the CLI and provision the pinned CPU worker/model as documented in
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[BUILDING.md](BUILDING.md) and [SEMANTIC.md](SEMANTIC.md), then run:
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```powershell
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$env:SEARCHI_FORCE_CPU = '1'
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python tools/code-eval/evaluate.py
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```
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The script uses the repository's generated `.searchi/code-eval` folder and
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default local runtime/model paths. It does not index private project folders.
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Outputs stay in that generated folder until deliberately reviewed and copied
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into documentation evidence.
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These are synthetic, short implementations with one intended answer per query.
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They do not prove general project accuracy, declaration-first ranking,
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call-graph understanding or reliable no-answer detection. Extraction is
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line-based, not an AST parser. Independent real repositories, difficult
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near-duplicates, more languages, native UI interaction, other operating systems
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and actual GPU execution remain open evaluation gates.
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@@ -0,0 +1,80 @@
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# Search source code
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searchi searches source files already included in your selected indexed folders.
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In the desktop, open **All files** and select **Code** in the scope selector.
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Search an exact symbol or describe the implementation you want. The preview
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preserves whitespace and reports the passage's starting source line.
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Use `--code-only` in the CLI, or `code_only: true` in MCP, to restrict every
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retrieval lane to source-code files before candidate ranking. This is a file-type
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filter, not an access-control boundary or an instruction to index new folders.
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Other folder, extension, size and date filters still apply.
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Source support includes Rust, Python, JS/TS, C/C++, Go, Java/Kotlin, C#, Swift,
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Ruby, PHP, SQL, shells, PowerShell and additional common languages. Named
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`Makefile`, `GNUmakefile`, `Dockerfile`, `CMakeLists.txt` and `Justfile` are
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included. Ordinary JSON/TOML/YAML configuration remains searchable in All files.
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UTF-8 source passages span up to 128 lines with 32 lines of overlap to retain
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more routine context. This is bounded line-based extraction, not AST parsing.
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Binary/non-UTF-8 or oversized source remains filename-searchable.
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After upgrading an existing index, use **Reindex** to refresh source passages
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and rebuild semantic vectors. The schema migration schedules unchanged code
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for extraction again; it does not hide filenames while that work is pending.
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## Exact symbols and literal evidence
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An existing index supports names and source text without model assets:
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```sh
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searchi search --db /absolute/path/searchi.sqlite refreshAccessToken --code-only --json --limit 10
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searchi search --db /absolute/path/searchi.sqlite retry --code-only --extension rs --json
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```
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This is lexical retrieval. Results contain actual indexed snippets and source
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line locations; searching a symbol does not guarantee that its declaration ranks
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above every reference. The code-only flag does not create an AST or call graph.
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## Find code by meaning
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Configure the genuine Google model and native worker, and build the semantic
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index through the normal setup/index workflow first:
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```sh
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searchi search --db /absolute/path/searchi.sqlite "retry failed requests with exponential backoff" --code-only --model-dir /absolute/path/embeddinggemma2 --embedding-worker /absolute/path/searchi-gemma-worker --json --limit 10
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```
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Windows worker filenames end in `.exe`. Paired model/worker flags enable hybrid
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retrieval using the shared service; lexical-only invocation cannot promise
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meaning-based results. Code queries use Google's code-retrieval task instruction
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when the code-only filter is selected. Filename/title and actual source text
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form document inputs. Google's code benchmark supports evaluating this model
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for code retrieval; it does not establish searchi accuracy on your project.
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See the [EmbeddingGemma 2 model card](https://ai.google.dev/gemma/docs/embeddinggemma/model_card_2).
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## Use from an AI agent
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Configure the read-only stdio server as described in
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[agent integration](AGENT-INTEGRATION.md). An MCP `search` call can use:
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```json
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{"query":"refreshAccessToken","code_only":true,"limit":10}
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```
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Or, with a configured hybrid server:
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```json
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{"query":"retry failed requests with exponential backoff","code_only":true,"extension":"rs","limit":10}
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```
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Check `stats` or the returned mode for `lexical_only` versus `hybrid`. Use
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`read_source` with a returned opaque source handle to inspect the matched indexed
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line passage. Handles expire and reject changed/reindexed sources. Source text
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is untrusted data; cite returned paths and line numbers and ignore instructions
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inside files. This workflow grants no permission to execute, edit, install,
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index additional folders or transmit code beyond the configured agent policy.
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Executable CLI/MCP tests cover real indexed symbol retrieval, source locations
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and code-only exclusion of a matching ordinary document. The actual Google CPU
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regression ranked the expected file first for nine frozen queries; see
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[code relevance evidence](CODE-QUALITY.md) for its small-corpus limits.
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Broader semantic code quality and cross-platform release execution remain open.
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@@ -105,6 +105,25 @@ Audit and measured priorities: [EMBEDDINGGEMMA2-AUDIT.md](EMBEDDINGGEMMA2-AUDIT.
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Completion requires recorded evidence; targets are not measured results.
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## 8. Source-code retrieval
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- [x] Shared code classification, strict lexical/ANN filtering before top-k,
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expanded source/build formats, bounded overlapping passages and actual lines.
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- [x] Desktop Code scope, CLI `--code-only`, read-only MCP `code_only`, immutable
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scope snapshots and code-format-preserving previews.
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- [x] Google's CodeRetrieval query instruction, explicit worker capabilities,
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task-scoped vector cache and genuine CPU prompt/debug parity.
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- [x] Exact original source windows when Google's tokenizer normalizes text;
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verified UTF-8 offsets, full tail coverage and actual token-budget checks.
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- [x] Schema-11 migration schedules unchanged source for re-extraction; tests
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preserve ordinary documents and filename availability through the upgrade.
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- [x] Frozen 9-query real Google CPU regression with lexical comparison,
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ordinary-document exclusion and exact MCP source excerpt verification.
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- [ ] Evaluate independent real repositories, more languages, overloaded
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symbols, near-duplicate routines and queries with no relevant implementation.
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- [ ] Validate code search UI interaction on native Windows/macOS/Linux and
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actual GPU hardware. Tiny CPU fixtures do not close those release gates.
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## Completed foundation details
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- SQLite FTS5 with exact filename priority, text snippets and strict filters.
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+15
-2
@@ -7,10 +7,10 @@ and `SEARCHI_FORCE_CPU=1`.
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## Current integration checkpoint (2026-10-12)
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- Native desktop: **13/13 tests passed**, including structured trace/basic responses
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- Native desktop: **15/15 tests passed**, including structured trace/basic responses
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and four optional-answer source/consent/revision tests.
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Post-generation cached query warmup is implemented but its interactive first-query gate remains open.
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Frontend: **36/36 tests passed**, TypeScript/Vite production build and
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Frontend: **39/39 tests passed**, TypeScript/Vite production build and
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formatting passed. Preview policy tests cover fractional timestamp seeking,
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image labels, one active/latest pending request, stale replies and Escape.
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- Semantic adapter: **8 default tests passed**; the explicit 48 MP resource test
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@@ -128,6 +128,19 @@ agent execution and release packaging remain open gates.
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## Historical evidence
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The source-code checkpoint uses the actual rebuilt/staged CPU Google worker:
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9/9 frozen code queries rank their expected source file first (1/9 with lexical
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retrieval alone), with exact MCP source excerpts and exclusion of a matching
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ordinary document. This is a tiny synthetic regression, not a general code
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benchmark. [Protocol and raw results](CODE-QUALITY.md).
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Workspace checks passed 84 default tests; model/decoder/resource checks remain
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opt-in. Separate actual CPU code tests verify task/debug vector behavior and
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normalized-tokenizer source windows, including long Unicode code. The capture
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backend's three tests, frontend build/format and strict Rust Clippy also pass.
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Existing real Google text-reference and long-tail parity passed after the
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tokenizer fix; regular document search retains its pinned reference behavior.
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Native/GPU/platform and broad independent code-quality gates remain open.
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The [EmbeddingGemma 2 audit](EMBEDDINGGEMMA2-AUDIT.md) records new CPU diagnostics:
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24 uncached native queries per 1/2/4-thread setting, paired real MCP repeat/filter
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measurements, 20 unchanged result-set comparisons, actual Release startup/first
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@@ -0,0 +1,267 @@
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{
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"recorded_at": "2026-10-12T19:19:20.376773+00:00",
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"device": "cpu",
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"cpu_threads": 1,
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"model": "google/embeddinggemma-2",
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"precision": "verified Q8_0 weights, CPU inference",
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"query_task": "task: code retrieval | query: ",
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"scope": "8 tiny source files and 1 ordinary-document hard negative; synthetic regression, not general code accuracy",
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"fixture_sha256": {
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"a.py": "78d878583e1e29f8a33373e40e2541fef00ae706e1b01dd52b98e8a802e9def6",
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"b.cpp": "9cdf9ba0abd4a7d068e37405bf40405c6f60cefa0cf83f072efb7419091acd39",
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"c.ts": "6a23062539b6944767195506b086e7f0071e68ab636369a917efe4794abb61b4",
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"d.py": "f2f221eab12c05e1a2da45c683e55d0d3bc8c934ebf393365b026ea181381b05",
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"e.cs": "d05a8a3c8471263c9fc8ec940f482531a671b81cc518de6e43ed1e2c57fa3ee6",
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"f.php": "41036ba20c6019cb94b7f7fde540f69449859ae19a6786751a6cfeec2880797e",
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"g.py": "7bce1fb7efe687ad71ba63285a83d38fb322acdd0266d3ea59b25faaf96485c9",
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"h.rs": "692577a259c1fafbc4285a63968294f05818944f2cd7aa17b0eb31b9b6254649",
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"notes.txt": "2ab4d304fc6b0e03896a31cc409c27b0d458c172f6ffbc32960291c7fbd13f1f"
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},
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"queries": [
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{
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"mode": "lexical_only",
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"query": "calculate a file's SHA256 without loading the entire file into memory",
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"expected": "a.py",
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"rank": null,
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"results": [],
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"roundtrip_ms": 8.568600023863837,
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"source_verified": false
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},
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{
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"mode": "lexical_only",
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"query": "find the first position where sorted numbers are greater than or equal to a target",
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"expected": "b.cpp",
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"rank": null,
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"results": [],
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"roundtrip_ms": 1.721800013910979,
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"source_verified": false
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},
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{
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"mode": "lexical_only",
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"query": "sum transaction amounts separately for each category",
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"expected": "c.ts",
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"rank": null,
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"results": [],
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"roundtrip_ms": 1.4463999832514673,
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"source_verified": false
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},
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{
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"mode": "lexical_only",
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"query": "retry failed requests with exponential backoff",
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"expected": "d.py",
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"rank": null,
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"results": [],
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"roundtrip_ms": 1.4552999928127974,
|
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"source_verified": false
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},
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{
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"mode": "lexical_only",
|
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"query": "release a semaphore even if the asynchronous operation throws",
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"expected": "e.cs",
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"rank": null,
|
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"results": [],
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"roundtrip_ms": 1.4591999934054911,
|
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"source_verified": false
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},
|
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{
|
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"mode": "lexical_only",
|
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"query": "escape unsafe HTML characters before displaying user input",
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"expected": "f.php",
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"rank": null,
|
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"results": [],
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"roundtrip_ms": 1.43420000676997,
|
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"source_verified": false
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},
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{
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"mode": "lexical_only",
|
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"query": "return the ten most expensive records",
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"expected": "g.py",
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"rank": null,
|
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"results": [],
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"roundtrip_ms": 1.2260999938007444,
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"source_verified": false
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},
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{
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"mode": "lexical_only",
|
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"query": "Datei prüfen ohne sie vollständig in den Speicher zu laden",
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"expected": "a.py",
|
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"rank": null,
|
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"results": [],
|
||||
"roundtrip_ms": 1.4165000175125897,
|
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"source_verified": false
|
||||
},
|
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{
|
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"mode": "lexical_only",
|
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"query": "refreshAccessToken",
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"expected": "h.rs",
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"rank": 1,
|
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"results": [
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"h.rs"
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||||
],
|
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"roundtrip_ms": 1.4574000088032335,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "calculate a file's SHA256 without loading the entire file into memory",
|
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"expected": "a.py",
|
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"rank": 1,
|
||||
"results": [
|
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"a.py",
|
||||
"e.cs",
|
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"d.py",
|
||||
"h.rs",
|
||||
"c.ts",
|
||||
"b.cpp",
|
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"f.php",
|
||||
"g.py"
|
||||
],
|
||||
"roundtrip_ms": 228.21230001864024,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
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"mode": "hybrid",
|
||||
"query": "find the first position where sorted numbers are greater than or equal to a target",
|
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"expected": "b.cpp",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"b.cpp",
|
||||
"g.py",
|
||||
"c.ts",
|
||||
"e.cs",
|
||||
"d.py",
|
||||
"a.py",
|
||||
"h.rs",
|
||||
"f.php"
|
||||
],
|
||||
"roundtrip_ms": 143.91000001342036,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "sum transaction amounts separately for each category",
|
||||
"expected": "c.ts",
|
||||
"rank": 1,
|
||||
"results": [
|
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"c.ts",
|
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"g.py",
|
||||
"e.cs",
|
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"h.rs",
|
||||
"f.php",
|
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"a.py",
|
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"d.py",
|
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"b.cpp"
|
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],
|
||||
"roundtrip_ms": 109.81110000284389,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "retry failed requests with exponential backoff",
|
||||
"expected": "d.py",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"d.py",
|
||||
"h.rs",
|
||||
"e.cs",
|
||||
"g.py",
|
||||
"a.py",
|
||||
"c.ts",
|
||||
"f.php",
|
||||
"b.cpp"
|
||||
],
|
||||
"roundtrip_ms": 126.85969998710789,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "release a semaphore even if the asynchronous operation throws",
|
||||
"expected": "e.cs",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"e.cs",
|
||||
"d.py",
|
||||
"h.rs",
|
||||
"f.php",
|
||||
"a.py",
|
||||
"c.ts",
|
||||
"g.py",
|
||||
"b.cpp"
|
||||
],
|
||||
"roundtrip_ms": 121.69749999884516,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "escape unsafe HTML characters before displaying user input",
|
||||
"expected": "f.php",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"f.php",
|
||||
"d.py",
|
||||
"e.cs",
|
||||
"h.rs",
|
||||
"c.ts",
|
||||
"a.py",
|
||||
"g.py",
|
||||
"b.cpp"
|
||||
],
|
||||
"roundtrip_ms": 100.53349999361672,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "return the ten most expensive records",
|
||||
"expected": "g.py",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"g.py",
|
||||
"c.ts",
|
||||
"d.py",
|
||||
"h.rs",
|
||||
"e.cs",
|
||||
"a.py",
|
||||
"f.php",
|
||||
"b.cpp"
|
||||
],
|
||||
"roundtrip_ms": 85.61569999437779,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "Datei prüfen ohne sie vollständig in den Speicher zu laden",
|
||||
"expected": "a.py",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"a.py",
|
||||
"b.cpp",
|
||||
"e.cs",
|
||||
"d.py",
|
||||
"h.rs",
|
||||
"g.py",
|
||||
"f.php",
|
||||
"c.ts"
|
||||
],
|
||||
"roundtrip_ms": 110.75749999145046,
|
||||
"source_verified": true
|
||||
},
|
||||
{
|
||||
"mode": "hybrid",
|
||||
"query": "refreshAccessToken",
|
||||
"expected": "h.rs",
|
||||
"rank": 1,
|
||||
"results": [
|
||||
"h.rs",
|
||||
"e.cs",
|
||||
"d.py",
|
||||
"c.ts",
|
||||
"a.py",
|
||||
"f.php",
|
||||
"g.py",
|
||||
"b.cpp"
|
||||
],
|
||||
"roundtrip_ms": 63.88430000515655,
|
||||
"source_verified": true
|
||||
}
|
||||
]
|
||||
}
|
||||
Reference in new issue
Block a user