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 GuideNote: The
ZepVectorStore
works with Documents
and is intended to be used as a Retriever
.
It offers separate functionality to Zep’s ZepMemory
class, which is designed for persisting, enriching
and searching your user’s chat history.
Why Zep’s VectorStore? 🤖🚀
Zep automatically embeds documents added to the Zep Vector Store using low-latency models local to the Zep server. The Zep TS/JS client can be used in non-Node edge environments. These two together with Zep’s chat memory functionality make Zep ideal for building conversational LLM apps where latency and performance are important.Supported Search Types
Zep supports both similarity search and Maximal Marginal Relevance (MMR) search. MMR search is particularly useful for Retrieval Augmented Generation applications as it re-ranks results to ensure diversity in the returned documents.Installation
Follow the Zep Open Source Quickstart Guide to install and get started with Zep.Usage
You’ll need your Zep API URL and optionally an API key to use the Zep VectorStore. See the Zep docs for more information. In the examples below, we’re using Zep’s auto-embedding feature which automatically embed documents on the Zep server using low-latency embedding models. Since LangChain requires passing in aEmbeddings
instance, we pass in FakeEmbeddings
.
Note: If you pass in an Embeddings
instance other than FakeEmbeddings
, this class will be used to embed documents.
You must also set your document collection to isAutoEmbedded === false
. See the OpenAIEmbeddings
example below.
Example: Creating a ZepVectorStore from Documents & Querying
npm
Example: Querying a ZepVectorStore using a metadata filter
Example: Using a LangChain Embedding Class such as OpenAIEmbeddings
Related
- Vector store conceptual guide
- Vector store how-to guides