Skip to main content

Zep Open Source Retriever

Zep is a long-term memory service for AI Assistant apps. With Zep, you can provide AI assistants with the ability to recall past conversations, no matter how distant, while also reducing hallucinations, latency, and cost.

Interested in Zep Cloud? See Zep Cloud Installation Guide

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

Installation​

Follow the Zep Open Source Quickstart Guide to install and get started with Zep.

Setup​

tip

See this section for general instructions on installing integration packages.

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

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.invoke(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.invoke(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.invoke(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.invoke(query);
  console.log("Filtered search");
  console.log(JSON.stringify(filteredDocs, null, 2));
};

API Reference:

Was this page helpful?


You can also leave detailed feedback on GitHub.