feat(CF-1315): Hybrid search with tsvector + RRF

Add PostgreSQL full-text search alongside pgvector for exact matches
on Jira keys, error messages, file paths. Merge results with
Reciprocal Rank Fusion. Default mode: hybrid, with graceful
degradation to keyword-only when embeddings unavailable.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/embeddings.ts

@@ -67,3 +67,29 @@ export async function getEmbedding(text: string): Promise<number[] | null> {
 export function formatEmbedding(embedding: number[]): string {
   return `[${embedding.join(',')}]`;
 }
+
+/**
+ * Reciprocal Rank Fusion — merge two ranked result lists (CF-1315)
+ * @param vectorResults IDs ranked by vector similarity (best first)
+ * @param keywordResults IDs ranked by ts_rank (best first)
+ * @param k RRF parameter (default 60, standard)
+ * @returns Merged IDs sorted by RRF score descending
+ */
+export function rrfMerge(
+  vectorResults: (number | string)[],
+  keywordResults: (number | string)[],
+  k: number = 60
+): { id: number | string; score: number }[] {
+  const scores = new Map<number | string, number>();
+
+  vectorResults.forEach((id, rank) => {
+    scores.set(id, (scores.get(id) || 0) + 1 / (k + rank + 1));
+  });
+  keywordResults.forEach((id, rank) => {
+    scores.set(id, (scores.get(id) || 0) + 1 / (k + rank + 1));
+  });
+
+  return Array.from(scores.entries())
+    .map(([id, score]) => ({ id, score }))
+    .sort((a, b) => b.score - a.score);
+}