feat(controls): enrich semantic retrieval query with finding intent + C5 live test (#222)
This commit was merged in pull request #222.
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@@ -234,13 +234,22 @@ pub async fn semantic_stamp_findings(
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let Some(region) = fetch_region(repo_path, &file, line) else {
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continue;
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};
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let region_emb = match llm.embed(vec![region.content.clone()]).await {
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// Retrieve on the finding's intent + the code, not the region alone: two
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// findings in one file share overlapping windows and otherwise embed alike,
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// collapsing onto the same controls. The finding's title/description carry
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// the discriminating signal (e.g. "brute-force protection" vs "weak hash").
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// The raw `region` still goes to the judge for snippet grounding.
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let query = format!(
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"{}\n{}\n\n{}",
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finding.title, finding.description, region.content
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);
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let query_emb = match llm.embed(vec![query]).await {
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Ok(mut embs) => match embs.pop() {
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Some(v) => v,
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None => continue,
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},
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Err(e) => {
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tracing::warn!(error = %e, "region embed failed; skipping finding");
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tracing::warn!(error = %e, "query embed failed; skipping finding");
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continue;
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}
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};
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@@ -248,7 +257,7 @@ pub async fn semantic_stamp_findings(
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.check(
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&index,
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®ion,
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®ion_emb,
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&query_emb,
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SEMANTIC_TOP_K,
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&finding.repo_id,
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)
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@@ -22,18 +22,20 @@ impl<J: ControlJudge> SemanticControlChecker<J> {
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Self { judge }
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}
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/// Map a code region to the controls it violates. `region_embedding` is the
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/// region's embedding (the caller computes it via the LLM); the top-`k`
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/// nearest controls in `index` are judged and grounded.
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/// Map a code region to the controls it violates. `query_embedding` is the
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/// caller-supplied retrieval embedding — typically the finding's intent
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/// (title/description) plus the region, so retrieval keys on what the finding
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/// is *about*, not just the ambient code. The top-`k` nearest controls in
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/// `index` are then judged against the raw `region` and grounded.
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pub async fn check(
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&self,
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index: &ControlIndex,
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region: &CandidateRegion,
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region_embedding: &[f64],
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query_embedding: &[f64],
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k: usize,
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repo_id: &str,
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) -> Vec<Finding> {
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let candidates = index.nearest(region_embedding, k);
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let candidates = index.nearest(query_embedding, k);
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let mut findings = Vec::new();
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for spec in &candidates {
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let verdict = self.judge.judge(spec, region).await;
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