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Zep Retriever

This example shows how to use the Zep Retriever in a retrieval chain to retrieve documents from Zep memory store.

Setup

npm i @getzep/zep-js @langchain/community

Usage

import { ZepRetriever } from "@langchain/community/retrievers/zep";
import { ZepMemory } from "@langchain/community/memory/zep";
import { Memory as MemoryModel, Message } from "@getzep/zep-js";
import { randomUUID } from "crypto";

function sleep(ms: number) {
// eslint-disable-next-line no-promise-executor-return
return new Promise((resolve) => setTimeout(resolve, ms));
}

export const run = async () => {
const zepConfig = {
url: process.env.ZEP_URL || "http://localhost:8000",
sessionId: `session_${randomUUID()}`,
};

console.log(`Zep Config: ${JSON.stringify(zepConfig)}`);

const memory = new ZepMemory({
baseURL: zepConfig.url,
sessionId: zepConfig.sessionId,
});

// Generate chat messages about traveling to France
const chatMessages = [
{
role: "AI",
message: "Bonjour! How can I assist you with your travel plans today?",
},
{ role: "User", message: "I'm planning a trip to France." },
{
role: "AI",
message: "That sounds exciting! What cities are you planning to visit?",
},
{ role: "User", message: "I'm thinking of visiting Paris and Nice." },
{
role: "AI",
message: "Great choices! Are you interested in any specific activities?",
},
{ role: "User", message: "I would love to visit some vineyards." },
{
role: "AI",
message:
"France has some of the best vineyards in the world. I can help you find some.",
},
{ role: "User", message: "That would be great!" },
{ role: "AI", message: "Do you prefer red or white wine?" },
{ role: "User", message: "I prefer red wine." },
{
role: "AI",
message:
"Perfect! I'll find some vineyards that are known for their red wines.",
},
{ role: "User", message: "Thank you, that would be very helpful." },
{
role: "AI",
message:
"You're welcome! I'll also look up some French wine etiquette for you.",
},
{
role: "User",
message: "That sounds great. I can't wait to start my trip!",
},
{
role: "AI",
message:
"I'm sure you'll have a fantastic time. Do you have any other questions about your trip?",
},
{ role: "User", message: "Not at the moment, thank you for your help!" },
];

const zepClient = await memory.zepClientPromise;
if (!zepClient) {
throw new Error("ZepClient is not initialized");
}

// Add chat messages to memory
for (const chatMessage of chatMessages) {
let m: MemoryModel;
if (chatMessage.role === "AI") {
m = new MemoryModel({
messages: [new Message({ role: "ai", content: chatMessage.message })],
});
} else {
m = new MemoryModel({
messages: [
new Message({ role: "human", content: chatMessage.message }),
],
});
}

await zepClient.memory.addMemory(zepConfig.sessionId, m);
}

// Wait for messages to be summarized, enriched, embedded and indexed.
await sleep(10000);

// Simple similarity search
const query = "Can I drive red cars in France?";
const retriever = new ZepRetriever({ ...zepConfig, topK: 3 });
const docs = await retriever.getRelevantDocuments(query);
console.log("Simple similarity search");
console.log(JSON.stringify(docs, null, 2));

// mmr reranking search
const mmrRetriever = new ZepRetriever({
...zepConfig,
topK: 3,
searchType: "mmr",
mmrLambda: 0.5,
});
const mmrDocs = await mmrRetriever.getRelevantDocuments(query);
console.log("MMR reranking search");
console.log(JSON.stringify(mmrDocs, null, 2));

// summary search with mmr reranking
const mmrSummaryRetriever = new ZepRetriever({
...zepConfig,
topK: 3,
searchScope: "summary",
searchType: "mmr",
mmrLambda: 0.5,
});
const mmrSummaryDocs = await mmrSummaryRetriever.getRelevantDocuments(query);
console.log("Summary search with MMR reranking");
console.log(JSON.stringify(mmrSummaryDocs, null, 2));

// Filtered search
const filteredRetriever = new ZepRetriever({
...zepConfig,
topK: 3,
filter: {
where: { jsonpath: '$.system.entities[*] ? (@.Label == "GPE")' },
},
});
const filteredDocs = await filteredRetriever.getRelevantDocuments(query);
console.log("Filtered search");
console.log(JSON.stringify(filteredDocs, null, 2));
};

API Reference: