From ffb195ea7a3afa4c9865da2817bbbdd486c086d7 Mon Sep 17 00:00:00 2001
From: shodevacc <69896964+shodevacc@users.noreply.github.com>
Date: Mon, 18 Mar 2024 00:53:51 -0400
Subject: [PATCH] Fix: Metadata filters doesn't seem to work for Qdrant (#623)
---
examples/qdrantdb/README.md | 11 +++
examples/qdrantdb/preFilters.ts | 82 +++++++++++++++++++
.../storage/vectorStore/QdrantVectorStore.ts | 2 +-
3 files changed, 94 insertions(+), 1 deletion(-)
create mode 100644 examples/qdrantdb/README.md
create mode 100644 examples/qdrantdb/preFilters.ts
diff --git a/examples/qdrantdb/README.md b/examples/qdrantdb/README.md
new file mode 100644
index 000000000..7ea0de26c
--- /dev/null
+++ b/examples/qdrantdb/README.md
@@ -0,0 +1,11 @@
+# Qdrant Vector Store Example
+
+How to run `examples/qdrantdb/preFilters.ts`:
+
+Add your OpenAI API Key into a file called `.env` in the parent folder of this directory. It should look like this:
+
+```
+OPEN_API_KEY=sk-you-key
+```
+
+Now, open a new terminal window and inside `examples`, run `npx ts-node qdrantdb/preFilters.ts`.
diff --git a/examples/qdrantdb/preFilters.ts b/examples/qdrantdb/preFilters.ts
new file mode 100644
index 000000000..54a394ab7
--- /dev/null
+++ b/examples/qdrantdb/preFilters.ts
@@ -0,0 +1,82 @@
+import * as dotenv from "dotenv";
+import {
+ CallbackManager,
+ Document,
+ MetadataMode,
+ QdrantVectorStore,
+ VectorStoreIndex,
+ serviceContextFromDefaults,
+ storageContextFromDefaults,
+} from "llamaindex";
+
+// Load environment variables from local .env file
+dotenv.config();
+
+const collectionName = "dog_colors";
+const qdrantUrl = "http://127.0.0.1:6333";
+
+async function main() {
+ try {
+ const docs = [
+ new Document({
+ text: "The dog is brown",
+ metadata: {
+ dogId: "1",
+ },
+ }),
+ new Document({
+ text: "The dog is red",
+ metadata: {
+ dogId: "2",
+ },
+ }),
+ ];
+ console.log("Creating QdrantDB vector store");
+ const qdrantVs = new QdrantVectorStore({ url: qdrantUrl, collectionName });
+ const ctx = await storageContextFromDefaults({ vectorStore: qdrantVs });
+
+ console.log("Embedding documents and adding to index");
+ const index = await VectorStoreIndex.fromDocuments(docs, {
+ storageContext: ctx,
+ serviceContext: serviceContextFromDefaults({
+ callbackManager: new CallbackManager({
+ onRetrieve: (data) => {
+ console.log(
+ "The retrieved nodes are:",
+ data.nodes.map((node) => node.node.getContent(MetadataMode.NONE)),
+ );
+ },
+ }),
+ }),
+ });
+
+ console.log(
+ "Querying index with no filters: Expected output: Brown probably",
+ );
+ const queryEngineNoFilters = index.asQueryEngine();
+ const noFilterResponse = await queryEngineNoFilters.query({
+ query: "What is the color of the dog?",
+ });
+ console.log("No filter response:", noFilterResponse.toString());
+ console.log("Querying index with dogId 2: Expected output: Red");
+ const queryEngineDogId2 = index.asQueryEngine({
+ preFilters: {
+ filters: [
+ {
+ key: "dogId",
+ value: "2",
+ filterType: "ExactMatch",
+ },
+ ],
+ },
+ });
+ const response = await queryEngineDogId2.query({
+ query: "What is the color of the dog?",
+ });
+ console.log("Filter with dogId 2 response:", response.toString());
+ } catch (e) {
+ console.error(e);
+ }
+}
+
+main();
diff --git a/packages/core/src/storage/vectorStore/QdrantVectorStore.ts b/packages/core/src/storage/vectorStore/QdrantVectorStore.ts
index 44448c71a..61eecf7a9 100644
--- a/packages/core/src/storage/vectorStore/QdrantVectorStore.ts
+++ b/packages/core/src/storage/vectorStore/QdrantVectorStore.ts
@@ -289,7 +289,7 @@ export class QdrantVectorStore implements VectorStore {
* @param query The VectorStoreQuery to be used
*/
private async buildQueryFilter(query: VectorStoreQuery) {
- if (!query.docIds && !query.queryStr) {
+ if (!query.docIds && !query.queryStr && !query.filters) {
return null;
}
--
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