Support storing and retrieving Document id field in MemoryVectorStore

langchain/src/vectorstores/memory.ts

@@ -17,6 +17,7 @@ interface MemoryVector {
   embedding: number[];
   // eslint-disable-next-line @typescript-eslint/no-explicit-any
   metadata: Record<string, any>;
+  id?: string;
 }
 
 /**
@@ -165,7 +166,7 @@ export class MemoryVectorStore extends VectorStore {
    * @param documents Array of `Document` instances to be added to the store.
    * @returns Promise that resolves when all documents have been added.
    */
-  async addDocuments(documents: Document[]): Promise<void> {
+  async addDocuments(documents: Document[]): Promise<vo > {
     const texts = documents.map(({ pageContent }) => pageContent);
     return this.addVectors(
       await this.embeddings.embedDocuments(texts),
@@ -186,6 +187,7 @@ export class MemoryVectorStore extends VectorStore {
       content: documents[idx].pageContent,
       embedding,
       metadata: documents[idx].metadata,
+      id: documents[idx].id
     }));
 
     this.memoryVectors = this.memoryVectors.concat(memoryVectors);

langchain/src/vectorstores/tests/memory.test.ts

@@ -30,6 +30,44 @@ test("MemoryVectorStore with external ids", async () => {
   ]);
 });
 
+test("MemoryVectorStore stores and retrieves document IDs", async () => {
+  const embeddings = new SyntheticEmbeddings({
+    vectorSize: 1536,
+  });
+  const store = new MemoryVectorStore(embeddings);
+
+  const filterFunc = (doc: DocumentInterface): boolean => {
+    const { metadata } = doc;
+    if (metadata.namespace <= 2) {
+      return true;
+    }
+    return false;
+  };
+
+  const retriever = store.asRetriever({
+    k: 2,
+    filter: filterFunc,
+  });
+
+  expect(retriever).toBeDefined();
+
+  await retriever.addDocuments([
+    { pageContent: "hello", metadata: { namespace: 1 }, id: 1 },
+    { pageContent: "hello", metadata: { namespace: 2 }, id: 2 },
+    { pageContent: "hello", metadata: { namespace: 3 }, id: 3 },
+    { pageContent: "hello", metadata: { namespace: 4 }, id: 4 },
+  ]);
+
+  const results = await retriever.getRelevantDocuments("hello");
+
+  expect(results).toHaveLength(2);
+
+  expect(results).toEqual([
+    new Document({ metadata: { namespace: 1 }, pageContent: "hello", id: 1 }),
+    new Document({ metadata: { namespace: 2 }, pageContent: "hello", id: 2 }),
+  ]);
+});
+
 test("MemoryVectorStore as retriever can filter metadata", async () => {
   const embeddings = new SyntheticEmbeddings({
     vectorSize: 1536,