All errors were API mismatches — handler code calling wrong method names, wrong argument types, or missing imports/derives. No logic changes. Build now passes with SQLX_OFFLINE=true. Key fixes: - embed_text -> embed_one, Vector -> Vec<f32> conversion - extract_token: extract auth header from HttpRequest first - AuthError variants aligned to actual enum definition - recursive async fns boxed (dfs_paths in inference + path_finder) - missing derives (Default, Serialize), imports (sqlx::Row, Timelike) - borrow-after-move: compute .len() before struct field move - streaming_body -> streaming with Result<Bytes> for SSE - CI: add SQLX_OFFLINE=true for offline builds without DB 25 files changed, 99 insertions(+), 81 deletions(-) Co-authored-by: rock <[email protected]>
This commit was merged in pull request #26.
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@@ -158,12 +158,12 @@ pub async fn unified_synthesis_handler(
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// Entity Linking
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if body.link_entities {
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let linker = EntityLinker::new(state.pool.clone());
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match linker.link_entities(&body.content) {
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Ok(links) => {
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match linker.link_mentions(&body.content, &body.project).await {
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Ok((links, _unlinked)) => {
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let alias_count = links.iter().filter(|l| l.confidence > 0.85).count();
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entity_linking = Some(EntityLinkingResult {
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mention_links: links.iter().map(|l| MentionLinkResponse {
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mention: l.mention.clone(),
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mention: l.mention_text.clone(),
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entity_id: l.entity_id.clone(),
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confidence: l.confidence,
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}).collect(),
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@@ -179,14 +179,14 @@ pub async fn unified_synthesis_handler(
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// Inference
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if body.infer_facts {
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let engine = InferenceEngine::new(state.pool.clone());
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match engine.infer_facts(&body.content, 5, 0.6, &body.project) {
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let engine = InferenceEngine::new(state.pool.clone(), vec![]);
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match engine.infer_facts(&body.project, &body.content, 5).await {
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Ok(facts) => {
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inference = Some(InferenceResult {
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inferred_facts: facts.iter().map(|f| InferredFactResponse {
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source: f.source.clone(),
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relation: f.relation.clone(),
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target: f.target.clone(),
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source: f.source_id.clone(),
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relation: f.relation_type.clone(),
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target: f.target_id.clone(),
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confidence: f.confidence,
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}).collect(),
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fact_count: facts.len(),
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