@langchain/community
Version:
Third-party integrations for LangChain.js
338 lines (337 loc) • 12.5 kB
JavaScript
import { test } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import { OpenAIEmbeddings, OpenAI } from "@langchain/openai";
import { SelfQueryRetriever } from "langchain/retrievers/self_query";
import { QdrantClient } from "@qdrant/js-client-rest";
import { QdrantVectorStore } from "../../vectorstores/qdrant.js";
import { QdrantTranslator } from "../qdrant.js";
test("Qdrant Vector Store Self Query Retriever Test", async () => {
const docs = [
new Document({
pageContent: "A bunch of scientists bring back dinosaurs and mayhem breaks loose",
metadata: { year: 1993, rating: 7.7, genre: "science fiction" },
}),
new Document({
pageContent: "Leo DiCaprio gets lost in a dream within a dream within a dream within a ...",
metadata: { year: 2010, director: "Christopher Nolan", rating: 8.2 },
}),
new Document({
pageContent: "A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea",
metadata: { year: 2006, director: "Satoshi Kon", rating: 8.6 },
}),
new Document({
pageContent: "A bunch of normal-sized women are supremely wholesome and some men pine after them",
metadata: { year: 2019, director: "Greta Gerwig", rating: 8.3 },
}),
new Document({
pageContent: "Toys come alive and have a blast doing so",
metadata: { year: 1995, genre: "animated" },
}),
new Document({
pageContent: "Three men walk into the Zone, three men walk out of the Zone",
metadata: {
year: 1979,
director: "Andrei Tarkovsky",
genre: "science fiction",
rating: 9.9,
},
}),
];
const attributeInfo = [
{
name: "genre",
description: "The genre of the movie",
type: "string or array of strings",
},
{
name: "year",
description: "The year the movie was released",
type: "number",
},
{
name: "director",
description: "The director of the movie",
type: "string",
},
{
name: "rating",
description: "The rating of the movie (1-10)",
type: "number",
},
{
name: "length",
description: "The length of the movie in minutes",
type: "number",
},
];
const embeddings = new OpenAIEmbeddings();
const llm = new OpenAI({
modelName: "gpt-3.5-turbo",
temperature: 0,
});
const documentContents = "Brief summary of a movie";
const client = new QdrantClient({ url: "http://127.0.0.1:6333" });
const vectorStore = await QdrantVectorStore.fromDocuments(docs, embeddings, {
client,
collectionName: crypto.randomUUID(),
});
const selfQueryRetriever = SelfQueryRetriever.fromLLM({
llm,
vectorStore,
documentContents,
attributeInfo,
structuredQueryTranslator: new QdrantTranslator(),
});
const query1 = await selfQueryRetriever.getRelevantDocuments("Which movies are less than 90 minutes?");
expect(query1.length).toEqual(0);
const query2 = await selfQueryRetriever.getRelevantDocuments("Which movies are rated higher than 8.5?");
expect(query2.length).toEqual(2);
const query3 = await selfQueryRetriever.getRelevantDocuments("Which cool movies are directed by Greta Gerwig?");
expect(query3.length).toEqual(1);
});
test("Qdrant Vector Store Self Query Retriever Test With Default Filter Or Merge Operator", async () => {
const docs = [
new Document({
pageContent: "A bunch of scientists bring back dinosaurs and mayhem breaks loose",
metadata: {
year: 1993,
rating: 7.7,
genre: "science fiction",
type: "movie",
},
}),
new Document({
pageContent: "Leo DiCaprio gets lost in a dream within a dream within a dream within a ...",
metadata: {
year: 2010,
director: "Christopher Nolan",
rating: 8.2,
type: "movie",
},
}),
new Document({
pageContent: "A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea",
metadata: {
year: 2006,
director: "Satoshi Kon",
rating: 8.6,
type: "movie",
},
}),
new Document({
pageContent: "A bunch of normal-sized women are supremely wholesome and some men pine after them",
metadata: {
year: 2019,
director: "Greta Gerwig",
rating: 8.3,
type: "movie",
},
}),
new Document({
pageContent: "Toys come alive and have a blast doing so",
metadata: { year: 1995, genre: "animated", type: "movie" },
}),
new Document({
pageContent: "Three men walk into the Zone, three men walk out of the Zone",
metadata: {
year: 1979,
director: "Andrei Tarkovsky",
genre: "science fiction",
rating: 9.9,
type: "movie",
},
}),
new Document({
pageContent: "10x the previous gecs",
metadata: {
year: 2023,
title: "10000 gecs",
artist: "100 gecs",
rating: 9.9,
type: "album",
},
}),
];
const attributeInfo = [
{
name: "genre",
description: "The genre of the movie",
type: "string or array of strings",
},
{
name: "year",
description: "The year the movie was released",
type: "number",
},
{
name: "director",
description: "The director of the movie",
type: "string",
},
{
name: "rating",
description: "The rating of the movie (1-10)",
type: "number",
},
{
name: "length",
description: "The length of the movie in minutes",
type: "number",
},
];
const embeddings = new OpenAIEmbeddings();
const llm = new OpenAI({
modelName: "gpt-3.5-turbo",
});
const documentContents = "Brief summary of a movie";
const client = new QdrantClient({ url: "http://127.0.0.1:6333" });
const vectorStore = await QdrantVectorStore.fromDocuments(docs, embeddings, {
client,
collectionName: crypto.randomUUID(),
});
const selfQueryRetriever = SelfQueryRetriever.fromLLM({
llm,
vectorStore,
documentContents,
attributeInfo,
structuredQueryTranslator: new QdrantTranslator(),
searchParams: {
filter: {
must: [{ key: "metadata.type", match: { value: "movie" } }],
},
mergeFiltersOperator: "or",
k: docs.length,
},
});
const query1 = await selfQueryRetriever.getRelevantDocuments("Which movies are less than 90 minutes?");
expect(query1.length).toEqual(6);
const query2 = await selfQueryRetriever.getRelevantDocuments("Which movies are rated higher than 8.5?");
expect(query2.length).toEqual(7);
const query3 = await selfQueryRetriever.getRelevantDocuments("Which movies are directed by Greta Gerwig?");
expect(query3.length).toEqual(6);
const query4 = await selfQueryRetriever.getRelevantDocuments("Awawawa au au au wawawawa hello?");
expect(query4.length).toEqual(6); // this one should return documents since default filter takes over
});
test("Qdrant Vector Store Self Query Retriever Test With Default Filter And Merge Operator", async () => {
const docs = [
new Document({
pageContent: "A bunch of scientists bring back dinosaurs and mayhem breaks loose",
metadata: {
year: 1993,
rating: 7.7,
genre: "science fiction",
type: "movie",
},
}),
new Document({
pageContent: "Leo DiCaprio gets lost in a dream within a dream within a dream within a ...",
metadata: {
year: 2010,
director: "Christopher Nolan",
rating: 8.2,
type: "movie",
},
}),
new Document({
pageContent: "A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea",
metadata: {
year: 2006,
director: "Satoshi Kon",
rating: 8.6,
type: "movie",
},
}),
new Document({
pageContent: "A bunch of normal-sized women are supremely wholesome and some men pine after them",
metadata: {
year: 2019,
director: "Greta Gerwig",
rating: 8.3,
type: "movie",
},
}),
new Document({
pageContent: "Toys come alive and have a blast doing so",
metadata: { year: 1995, genre: "animated", type: "movie" },
}),
new Document({
pageContent: "Three men walk into the Zone, three men walk out of the Zone",
metadata: {
year: 1979,
director: "Andrei Tarkovsky",
genre: "science fiction",
rating: 9.9,
type: "movie",
},
}),
new Document({
pageContent: "10x the previous gecs",
metadata: {
year: 2023,
title: "10000 gecs",
artist: "100 gecs",
rating: 9.9,
type: "album",
},
}),
];
const attributeInfo = [
{
name: "genre",
description: "The genre of the movie",
type: "string or array of strings",
},
{
name: "year",
description: "The year the movie was released",
type: "number",
},
{
name: "director",
description: "The director of the movie",
type: "string",
},
{
name: "rating",
description: "The rating of the movie (1-10)",
type: "number",
},
{
name: "length",
description: "The length of the movie in minutes",
type: "number",
},
];
const embeddings = new OpenAIEmbeddings();
const llm = new OpenAI({
modelName: "gpt-3.5-turbo",
});
const documentContents = "Brief summary of a movie";
const client = new QdrantClient({ url: "http://127.0.0.1:6333" });
const vectorStore = await QdrantVectorStore.fromDocuments(docs, embeddings, {
client,
collectionName: crypto.randomUUID(),
});
const selfQueryRetriever = SelfQueryRetriever.fromLLM({
llm,
vectorStore,
documentContents,
attributeInfo,
structuredQueryTranslator: new QdrantTranslator(),
searchParams: {
filter: {
must: [{ key: "metadata.type", match: { value: "movie" } }],
},
mergeFiltersOperator: "and",
k: docs.length,
},
});
const query1 = await selfQueryRetriever.getRelevantDocuments("Which movies are less than 90 minutes?");
expect(query1.length).toEqual(0);
const query2 = await selfQueryRetriever.getRelevantDocuments("Which movies are rated higher than 8.5?");
expect(query2.length).toEqual(2);
const query3 = await selfQueryRetriever.getRelevantDocuments("Which cool movies are directed by Greta Gerwig?");
expect(query3.length).toEqual(1);
const query4 = await selfQueryRetriever.getRelevantDocuments("Awawawa au au au wawawawa hello?");
expect(query4.length).toBeGreaterThan(0); // this one should return documents since default filter takes over
});