From 31bc2cc202879d39f4fbdaf1c2f1d0834e9312f5 Mon Sep 17 00:00:00 2001
From: scotthuang <scotthuang@tencent.com>
Date: Tue, 3 Mar 2026 01:59:06 +0800
Subject: [PATCH] fix(memory-lancedb): pass dimensions to embedding API call

- Add dimensions parameter to Embeddings constructor
- Pass dimensions to OpenAI embeddings.create() API call
- Fixes dimension mismatch when using custom embedding models like DashScope text-embedding-v4
---
 extensions/memory-lancedb/index.ts | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/extensions/memory-lancedb/index.ts b/extensions/memory-lancedb/index.ts
index e45f00fbb57..f02115b1bf6 100644
--- a/extensions/memory-lancedb/index.ts
+++ b/extensions/memory-lancedb/index.ts
@@ -167,15 +167,20 @@ class Embeddings {
     apiKey: string,
     private model: string,
     baseUrl?: string,
+    private dimensions?: number,
   ) {
     this.client = new OpenAI({ apiKey, baseURL: baseUrl });
   }
 
   async embed(text: string): Promise<number[]> {
-    const response = await this.client.embeddings.create({
+    const params: { model: string; input: string; dimensions?: number } = {
       model: this.model,
       input: text,
-    });
+    };
+    if (this.dimensions) {
+      params.dimensions = this.dimensions;
+    }
+    const response = await this.client.embeddings.create(params);
     return response.data[0].embedding;
   }
 }
@@ -298,7 +303,7 @@ const memoryPlugin = {
 
     const vectorDim = dimensions ?? vectorDimsForModel(model);
     const db = new MemoryDB(resolvedDbPath, vectorDim);
-    const embeddings = new Embeddings(apiKey, model, baseUrl);
+    const embeddings = new Embeddings(apiKey, model, baseUrl, dimensions);
 
     api.logger.info(`memory-lancedb: plugin registered (db: ${resolvedDbPath}, lazy init)`);