langchain[patch]: Issue #2756 Add Qdrant custom payload on documents to query them by filter

langchain/src/document.ts

@@ -5,6 +5,7 @@ export interface DocumentInput<
   pageContent: string;
 
   metadata?: Metadata;
+  customPayload?: object;
 }
 
 /**
@@ -19,6 +20,8 @@ export class Document<
 
   metadata: Metadata;
 
+  customPayload?: object | undefined;
+
   constructor(fields: DocumentInput<Metadata>) {
     this.pageContent = fields.pageContent
       ? fields.pageContent.toString()

langchain/src/vectorstores/qdrant.ts

@@ -84,13 +84,18 @@ export class QdrantVectorStore extends VectorStore {
    * from the documents using the `Embeddings` instance and then adds the
    * vectors to the database.
    * @param documents Array of `Document` instances to be added to the Qdrant database.
+   * @param customPayload Optional 'object' in JSON format used to query database on more criteria
    * @returns Promise that resolves when the documents have been added to the database.
    */
-  async addDocuments(documents: Document[]): Promise<void> {
+  async addDocuments(
+    documents: Document[],
+    customPayload?: object
+  ): Promise<void> {
     const texts = documents.map(({ pageContent }) => pageContent);
     await this.addVectors(
       await this.embeddings.embedDocuments(texts),
-      documents
+      documents,
+      customPayload
     );
   }
 
@@ -100,9 +105,14 @@ export class QdrantVectorStore extends VectorStore {
    * database.
    * @param vectors Array of vectors to be added to the Qdrant database.
    * @param documents Array of `Document` instances associated with the vectors.
+   * @param customPayload Optional 'object' in JSON format used to query database on more criteria
    * @returns Promise that resolves when the vectors have been added to the database.
    */
-  async addVectors(vectors: number[][], documents: Document[]): Promise<void> {
+  async addVectors(
+    vectors: number[][],
+    documents: Document[],
+    customPayload?: object
+  ): Promise<void> {
     if (vectors.length === 0) {
       return;
     }
@@ -115,6 +125,8 @@ export class QdrantVectorStore extends VectorStore {
       payload: {
         content: documents[idx].pageContent,
         metadata: documents[idx].metadata,
+        ...(documents[idx].customPayload ? documents[idx].customPayload != customPayload ? 
+          documents[idx].customPayload : customPayload : customPayload),
       },
     }));
 
@@ -204,20 +216,23 @@ export class QdrantVectorStore extends VectorStore {
    * @param metadatas Array or single object of metadata to be associated with the texts.
    * @param embeddings `Embeddings` instance used to generate vectors from the texts.
    * @param dbConfig `QdrantLibArgs` instance specifying the configuration for the Qdrant database.
+   * @param customPayload Optional 'object' in JSON format used to query database on more criteria
    * @returns Promise that resolves with a new `QdrantVectorStore` instance.
    */
   static async fromTexts(
     texts: string[],
     metadatas: object[] | object,
     embeddings: Embeddings,
-    dbConfig: QdrantLibArgs
+    dbConfig: QdrantLibArgs,
+    customPayload? : object
   ): Promise<QdrantVectorStore> {
     const docs = [];
     for (let i = 0; i < texts.length; i += 1) {
       const metadata = Array.isArray(metadatas) ? metadatas[i] : metadatas;
       const newDoc = new Document({
         pageContent: texts[i],
         metadata,
+        customPayload: customPayload,
       });
       docs.push(newDoc);
     }
@@ -230,15 +245,17 @@ export class QdrantVectorStore extends VectorStore {
    * @param docs Array of `Document` instances to be added to the Qdrant database.
    * @param embeddings `Embeddings` instance used to generate vectors from the documents.
    * @param dbConfig `QdrantLibArgs` instance specifying the configuration for the Qdrant database.
+   * @param customPayload Optional 'object' in JSON format used to query database on more criteria
    * @returns Promise that resolves with a new `QdrantVectorStore` instance.
    */
   static async fromDocuments(
     docs: Document[],
     embeddings: Embeddings,
-    dbConfig: QdrantLibArgs
+    dbConfig: QdrantLibArgs,
+    customPayload?: object
   ): Promise<QdrantVectorStore> {
     const instance = new this(embeddings, dbConfig);
-    await instance.addDocuments(docs);
+    await instance.addDocuments(docs, customPayload);
     return instance;
   }
 

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

@@ -31,3 +31,103 @@ test("QdrantVectorStore works", async () => {
 
   expect(results).toHaveLength(0);
 });
+
+test("QdrantVectorStore adds vectors with custom payload", async () => {
+  // Mock Qdrant client
+  const client = {
+    upsert: jest.fn(),
+    search: jest.fn<any>().mockResolvedValue([]),
+    getCollections: jest.fn<any>().mockResolvedValue({ collections: [] }),
+    createCollection: jest.fn(),
+  };
+
+  // Mock embeddings
+  const embeddings = new FakeEmbeddings();
+
+  // Create QdrantVectorStore instance with the mock client
+  const qdrantVectorStore = new QdrantVectorStore(embeddings, {
+    client: client as any,
+  });
+
+  // Define a custom payload
+  const customPayload = {
+    customField1: "value1",
+    customField2: "value2",
+  };
+
+  // Add documents with custom payload
+  await qdrantVectorStore.addDocuments(
+    [
+      {
+        pageContent: "hello",
+        metadata: {},
+      },
+    ],
+    customPayload
+  );
+
+  // Verify that the Qdrant client's upsert method was called with the correct arguments
+  expect(client.upsert).toHaveBeenCalledTimes(1);
+  expect(client.upsert).toHaveBeenCalledWith("documents", {
+    wait: true,
+    points: [
+      expect.objectContaining({
+        payload: expect.objectContaining({
+          content: "hello",
+          metadata: {},
+          ...customPayload,
+        }),
+      }),
+    ],
+  });
+});
+
+test("QdrantVectorStore adds vectors with custom payload in Document", async () => {
+  // Mock Qdrant client
+  const client = {
+    upsert: jest.fn(),
+    search: jest.fn<any>().mockResolvedValue([]),
+    getCollections: jest.fn<any>().mockResolvedValue({ collections: [] }),
+    createCollection: jest.fn(),
+  };
+
+  // Mock embeddings
+  const embeddings = new FakeEmbeddings();
+
+  // Create QdrantVectorStore instance with the mock client
+  const qdrantVectorStore = new QdrantVectorStore(embeddings, {
+    client: client as any,
+  });
+
+  // Define a custom payload
+  const customPayload = {
+    customField1: "value1",
+    customField2: "value2",
+  };
+
+  // Add documents with custom payload
+  await qdrantVectorStore.addDocuments(
+    [
+      {
+        pageContent: "hello",
+        metadata: {},
+        customPayload: customPayload
+      },
+    ],
+  );
+
+  // Verify that the Qdrant client's upsert method was called with the correct arguments
+  expect(client.upsert).toHaveBeenCalledTimes(1);
+  expect(client.upsert).toHaveBeenCalledWith("documents", {
+    wait: true,
+    points: [
+      expect.objectContaining({
+        payload: expect.objectContaining({
+          content: "hello",
+          metadata: {},
+          ...customPayload,
+        }),
+      }),
+    ],
+  });
+});