Improve MemFuse recall via hybrid ranking and candidate generation.

Add RRF fusion with English word-level lexical scoring, tiered keyword fetch, and vector margin expansion (0.15/200) to fix pre-rank truncation; wire DashScope embedding bench path and update baseline to 28.8% recall@20.

Co-authored-by: Cursor <cursoragent@cursor.com>

scripts/embed-memory-v2-dashscope.mjs

@@ -0,0 +1,21 @@
+import { loadMemindEnvFiles } from './memind-runtime-profile.mjs';
+
+loadMemindEnvFiles(process.cwd());
+
+process.env.MEMIND_EMBEDDING_PROVIDER =
+  process.env.MEMIND_EMBEDDING_PROVIDER ?? 'dashscope';
+process.env.MEMIND_EMBEDDING_FROM_LLM_KEYS =
+  process.env.MEMIND_EMBEDDING_FROM_LLM_KEYS ?? '1';
+process.env.MEMIND_EMBEDDING_MODEL =
+  process.env.MEMIND_EMBEDDING_MODEL ?? 'text-embedding-v3';
+
+export {
+  embedText,
+  embedQuery,
+  prefetchEmbedTexts,
+  probeEmbeddingAvailability,
+  flushEmbeddingCache,
+  __resetEmbeddingCacheForTests,
+} from './embed-memory-v2-openai-compat.mjs';
+
+export { default } from './embed-memory-v2-openai-compat.mjs';