Merge 11c02404e4edd818c1d3b181b3f55412279342c4 into 8a05c05596ca9ba0735dafd8e359885de4c2c969

src/memory/manager-search.ts

@@ -5,6 +5,72 @@ import { cosineSimilarity, parseEmbedding } from "./internal.js";
 const vectorToBlob = (embedding: number[]): Buffer =>
   Buffer.from(new Float32Array(embedding).buffer);
 
+/**
+ * Extract a relevant snippet window around the query match in the text.
+ * If the query is found, returns a window centered on the match.
+ * Otherwise falls back to the beginning of the text.
+ */
+function extractRelevantSnippet(
+  text: string,
+  query: string,
+  maxChars: number,
+): { snippet: string; offsetLines: number } {
+  if (text.length <= maxChars) {
+    return { snippet: text, offsetLines: 0 };
+  }
+
+  // Try to find the query (case-insensitive) in the text
+  const lowerText = text.toLowerCase();
+  const queryTerms = query
+    .toLowerCase()
+    .split(/\s+/)
+    .filter((term) => term.length > 2);
+
+  let matchIndex = -1;
+
+  // Find the first matching term
+  for (const term of queryTerms) {
+    const idx = lowerText.indexOf(term);
+    if (idx !== -1) {
+      matchIndex = idx;
+      break;
+    }
+  }
+
+  // If no match found, fall back to beginning
+  if (matchIndex === -1) {
+    return { snippet: truncateUtf16Safe(text, maxChars), offsetLines: 0 };
+  }
+
+  // Calculate window start, trying to center the match
+  const halfWindow = Math.floor(maxChars / 2);
+  let windowStart = Math.max(0, matchIndex - halfWindow);
+  let windowEnd = Math.min(text.length, windowStart + maxChars);
+
+  // Adjust if we're near the end
+  if (windowEnd === text.length && windowEnd - windowStart < maxChars) {
+    windowStart = Math.max(0, windowEnd - maxChars);
+  }
+
+  // Try to start at a line boundary for cleaner output
+  if (windowStart > 0) {
+    const lineStart = text.lastIndexOf("\n", windowStart);
+    if (lineStart !== -1 && windowStart - lineStart < 100) {
+      windowStart = lineStart + 1;
+      // Recalculate windowEnd to maintain maxChars length after snap
+      windowEnd = Math.min(text.length, windowStart + maxChars);
+    }
+  }
+
+  // Count lines before the window to adjust startLine/endLine display
+  const textBeforeWindow = text.substring(0, windowStart);
+  const offsetLines = (textBeforeWindow.match(/\n/g) || []).length;
+
+  const snippet = text.substring(windowStart, windowEnd);
+  return { snippet: truncateUtf16Safe(snippet, maxChars), offsetLines };
+}
+
+
 export type SearchSource = string;
 
 export type SearchRowResult = {
@@ -22,6 +88,7 @@ export async function searchVector(params: {
   vectorTable: string;
   providerModel: string;
   queryVec: number[];
+  queryText: string;
   limit: number;
   snippetMaxChars: number;
   ensureVectorReady: (dimensions: number) => Promise<boolean>;
@@ -57,15 +124,18 @@ export async function searchVector(params: {
       source: SearchSource;
       dist: number;
     }>;
-    return rows.map((row) => ({
-      id: row.id,
-      path: row.path,
-      startLine: row.start_line,
-      endLine: row.end_line,
-      score: 1 - row.dist,
-      snippet: truncateUtf16Safe(row.text, params.snippetMaxChars),
-      source: row.source,
-    }));
+    return rows.map((row) => {
+      const { snippet, offsetLines } = extractRelevantSnippet(row.text, params.queryText, params.snippetMaxChars);
+      return {
+        id: row.id,
+        path: row.path,
+        startLine: row.start_line + offsetLines,
+        endLine: row.end_line,
+        score: 1 - row.dist,
+        snippet,
+        source: row.source,
+      };
+    });
   }
 
   const candidates = listChunks({
@@ -82,15 +152,22 @@ export async function searchVector(params: {
   return scored
     .toSorted((a, b) => b.score - a.score)
     .slice(0, params.limit)
-    .map((entry) => ({
-      id: entry.chunk.id,
-      path: entry.chunk.path,
-      startLine: entry.chunk.startLine,
-      endLine: entry.chunk.endLine,
-      score: entry.score,
-      snippet: truncateUtf16Safe(entry.chunk.text, params.snippetMaxChars),
-      source: entry.chunk.source,
-    }));
+    .map((entry) => {
+      const { snippet, offsetLines } = extractRelevantSnippet(
+        entry.chunk.text,
+        params.queryText,
+        params.snippetMaxChars,
+      );
+      return {
+        id: entry.chunk.id,
+        path: entry.chunk.path,
+        startLine: entry.chunk.startLine + offsetLines,
+        endLine: entry.chunk.endLine,
+        score: entry.score,
+        snippet,
+        source: entry.chunk.source,
+      };
+    });
 }
 
 export function listChunks(params: {
@@ -177,14 +254,15 @@ export async function searchKeyword(params: {
 
   return rows.map((row) => {
     const textScore = params.bm25RankToScore(row.rank);
+    const { snippet, offsetLines } = extractRelevantSnippet(row.text, params.query, params.snippetMaxChars);
     return {
       id: row.id,
       path: row.path,
-      startLine: row.start_line,
+      startLine: row.start_line + offsetLines,
       endLine: row.end_line,
       score: textScore,
       textScore,
-      snippet: truncateUtf16Safe(row.text, params.snippetMaxChars),
+      snippet,
       source: row.source,
     };
   });

src/memory/manager.ts

@@ -345,7 +345,7 @@ export class MemoryIndexManager extends MemoryManagerEmbeddingOps implements Mem
     const queryVec = await this.embedQueryWithTimeout(cleaned);
     const hasVector = queryVec.some((v) => v !== 0);
     const vectorResults = hasVector
-      ? await this.searchVector(queryVec, candidates).catch(() => [])
+      ? await this.searchVector(queryVec, cleaned, candidates).catch(() => [])
       : [];
 
     if (!hybrid.enabled || !this.fts.enabled || !this.fts.available) {
@@ -386,6 +386,7 @@ export class MemoryIndexManager extends MemoryManagerEmbeddingOps implements Mem
 
   private async searchVector(
     queryVec: number[],
+    queryText: string,
     limit: number,
   ): Promise<Array<MemorySearchResult & { id: string }>> {
     // This method should never be called without a provider
@@ -397,6 +398,7 @@ export class MemoryIndexManager extends MemoryManagerEmbeddingOps implements Mem
       vectorTable: VECTOR_TABLE,
       providerModel: this.provider.model,
       queryVec,
+      queryText,
       limit,
       snippetMaxChars: SNIPPET_MAX_CHARS,
       ensureVectorReady: async (dimensions) => await this.ensureVectorReady(dimensions),