Class ZepVectorStore

ZepVectorStore is a VectorStore implementation that uses the Zep long-term memory store as a backend.

If the collection does not exist, it will be created automatically.

Requires zep-js to be installed:

npm install @getzep/zep-js

Hierarchy

VectorStore
- ZepVectorStore

Constructors

constructor

new ZepVectorStore(embeddings, args): ZepVectorStore
Parameters
- embeddings: Embeddings
- args: IZepConfig
Returns ZepVectorStore
Overrides VectorStore.constructor
- Defined in langchain/src/vectorstores/zep.ts:67

Properties

FilterType

FilterType: string | object

client

client: default

The ZepClient instance used to interact with Zep's API.

collection

collection: default

The Zep document collection.

embeddings

embeddings: Embeddings

lc_kwargs

lc_kwargs: SerializedFields

lc_namespace

lc_namespace: string[] = ...

A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.

lc_serializable

lc_serializable: boolean = false

Accessors

lc_aliases

get lc_aliases(): undefined | {
[key: string]: string;
}
A map of aliases for constructor args. Keys are the attribute names, e.g. "foo". Values are the alias that will replace the key in serialization. This is used to eg. make argument names match Python.

Returns undefined | {
[key: string]: string;
}
Inherited from VectorStore.lc_aliases
- Defined in langchain/src/load/serializable.ts:132

lc_attributes

get lc_attributes(): undefined | SerializedFields
A map of additional attributes to merge with constructor args. Keys are the attribute names, e.g. "foo". Values are the attribute values, which will be serialized. These attributes need to be accepted by the constructor as arguments.

Returns undefined | SerializedFields
Inherited from VectorStore.lc_attributes
- Defined in langchain/src/load/serializable.ts:122

lc_id

get lc_id(): string[]
The final serialized identifier for the module.

Returns string[]
Inherited from VectorStore.lc_id
- Defined in langchain/src/load/serializable.ts:100

lc_secrets

get lc_secrets(): undefined | {
[key: string]: string;
}
A map of secrets, which will be omitted from serialization. Keys are paths to the secret in constructor args, e.g. "foo.bar.baz". Values are the secret ids, which will be used when deserializing.

Returns undefined | {
[key: string]: string;
}
Inherited from VectorStore.lc_secrets
- Defined in langchain/src/load/serializable.ts:112

Methods

_similaritySearchWithScore

_similaritySearchWithScore(query, k, filter?): Promise<[Document<Record<string, any>>, number][]>
Parameters
- query: string
- k: number
- Optional filter: Record<string, unknown>
Returns Promise<[Document<Record<string, any>>, number][]>
- Defined in langchain/src/vectorstores/zep.ts:226

_vectorstoreType

_vectorstoreType(): string
Returns string
Overrides VectorStore._vectorstoreType
- Defined in langchain/src/vectorstores/zep.ts:184

addDocuments

addDocuments(documents): Promise<string[]>
Adds documents to the collection. The documents are first embedded into vectors using the provided embedding model.
Parameters
- documents: Document<Record<string, any>>[]
  
  The documents to add.
Returns Promise<string[]>
- A promise that resolves with the UUIDs of the added documents.
Overrides VectorStore.addDocuments
- Defined in langchain/src/vectorstores/zep.ts:175

addVectors

addVectors(vectors, documents): Promise<string[]>
Adds vectors and corresponding documents to the collection.
Parameters
- vectors: number[][]
  
  The vectors to add.
- documents: Document<Record<string, any>>[]
  
  The corresponding documents to add.
Returns Promise<string[]>
- A promise that resolves with the UUIDs of the added documents.
Overrides VectorStore.addVectors
- Defined in langchain/src/vectorstores/zep.ts:143

asRetriever

asRetriever(kOrFields?, filter?, callbacks?, tags?, metadata?, verbose?): VectorStoreRetriever<ZepVectorStore>
Parameters
- Optional kOrFields: number | Partial<VectorStoreRetrieverInput<ZepVectorStore>>
- Optional filter: string | object
- Optional callbacks: Callbacks
- Optional tags: string[]
- Optional metadata: Record<string, unknown>
- Optional verbose: boolean
Returns VectorStoreRetriever<ZepVectorStore>
Inherited from VectorStore.asRetriever
- Defined in langchain/src/vectorstores/base.ts:246

delete

delete(params): Promise<void>
Deletes documents from the collection.
Parameters
- params: IZepDeleteParams
  
  The list of Zep document UUIDs to delete.
Returns Promise<void>
Overrides VectorStore.delete
- Defined in langchain/src/vectorstores/zep.ts:194

maxMarginalRelevanceSearch

maxMarginalRelevanceSearch(query, options): Promise<Document<Record<string, any>>[]>
Return documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.
Parameters
- query: string
  
  Text to look up documents similar to.
- options: MaxMarginalRelevanceSearchOptions<string | object>
Returns Promise<Document<Record<string, any>>[]>
- List of documents selected by maximal marginal relevance.
Overrides VectorStore.maxMarginalRelevanceSearch
- Defined in langchain/src/vectorstores/zep.ts:311

similaritySearch

similaritySearch(query, k?, filter?, _callbacks?): Promise<Document<Record<string, any>>[]>
Performs a similarity search on the Zep collection.
Parameters
- query: string
  
  The query string to search for.
- Optional k: number = 4
  
  The number of results to return. Defaults to 4.
- Optional filter: string | object = undefined
  
  An optional set of JSONPath filters to apply to the search.
- Optional _callbacks: Callbacks = undefined
  
  Optional callbacks. Currently not implemented.
Returns Promise<Document<Record<string, any>>[]>
- A promise that resolves to an array of Documents that are similar to the query.
Async
Overrides VectorStore.similaritySearch
- Defined in langchain/src/vectorstores/zep.ts:270

similaritySearchVectorWithScore

similaritySearchVectorWithScore(query, k, filter?): Promise<[Document<Record<string, any>>, number][]>
Performs a similarity search in the collection and returns the results with their scores.
Parameters
- query: number[]
  
  The query vector.
- k: number
  
  The number of results to return.
- Optional filter: Record<string, unknown>
  
  The filter to apply to the search. Zep only supports Record<string, unknown> as filter.
Returns Promise<[Document<Record<string, any>>, number][]>
- A promise that resolves with the search results and their scores.
Overrides VectorStore.similaritySearchVectorWithScore
- Defined in langchain/src/vectorstores/zep.ts:210

similaritySearchWithScore

similaritySearchWithScore(query, k?, filter?, _callbacks?): Promise<[Document<Record<string, any>>, number][]>
Parameters
- query: string
- k: number = 4
- filter: undefined | Record<string, unknown> = undefined
- _callbacks: undefined = undefined
Returns Promise<[Document<Record<string, any>>, number][]>
Overrides VectorStore.similaritySearchWithScore
- Defined in langchain/src/vectorstores/zep.ts:242

toJSON

toJSON(): Serialized
Returns Serialized
Inherited from VectorStore.toJSON
- Defined in langchain/src/load/serializable.ts:140

toJSONNotImplemented

toJSONNotImplemented(): SerializedNotImplemented
Returns SerializedNotImplemented
Inherited from VectorStore.toJSONNotImplemented
- Defined in langchain/src/load/serializable.ts:214

`Static` fromDocuments

fromDocuments(docs, embeddings, zepConfig): Promise<ZepVectorStore>
Creates a new ZepVectorStore instance from an array of Documents. Each Document is added to a Zep collection.
Parameters
- docs: Document<Record<string, any>>[]
  
  The Documents to add.
- embeddings: Embeddings
  
  The embeddings to use for vectorizing the Document contents.
- zepConfig: IZepConfig
  
  The configuration object for the Zep API.
Returns Promise<ZepVectorStore>
- A promise that resolves with the new ZepVectorStore instance.
Overrides VectorStore.fromDocuments
- Defined in langchain/src/vectorstores/zep.ts:389

`Static` fromTexts

fromTexts(texts, metadatas, embeddings, zepConfig): Promise<ZepVectorStore>
Creates a new ZepVectorStore instance from an array of texts. Each text is converted into a Document and added to the collection.
Parameters
- texts: string[]
  
  The texts to convert into Documents.
- metadatas: object | object[]
  
  The metadata to associate with each Document. If an array is provided, each element is associated with the corresponding Document. If an object is provided, it is associated with all Documents.
- embeddings: Embeddings
  
  The embeddings to use for vectorizing the texts.
- zepConfig: IZepConfig
  
  The configuration object for the Zep API.
Returns Promise<ZepVectorStore>
- A promise that resolves with the new ZepVectorStore instance.
Overrides VectorStore.fromTexts
- Defined in langchain/src/vectorstores/zep.ts:363

`Static` lc_name

lc_name(): string
The name of the serializable. Override to provide an alias or to preserve the serialized module name in minified environments.

Implemented as a static method to support loading logic.

Returns string
Inherited from VectorStore.lc_name
- Defined in langchain/src/load/serializable.ts:93

Class ZepVectorStore

Hierarchy

Index

Constructors

Properties

Accessors

Methods

Constructors

constructor

Parameters

embeddings: Embeddings

args: IZepConfig

Returns ZepVectorStore

Properties

FilterType

client

collection

embeddings

lc_kwargs

lc_namespace

lc_serializable

Accessors

lc_aliases

Returns undefined | { [key: string]: string; }

lc_attributes

Returns undefined | SerializedFields

lc_id

Returns string[]

lc_secrets

Returns undefined | { [key: string]: string; }

Methods

_similaritySearchWithScore

Parameters

query: string

k: number

Optional filter: Record<string, unknown>

Returns Promise<[Document<Record<string, any>>, number][]>

_vectorstoreType

Returns string

addDocuments

Parameters

documents: Document<Record<string, any>>[]

Returns Promise<string[]>

addVectors

Parameters

vectors: number[][]

documents: Document<Record<string, any>>[]

Returns Promise<string[]>

asRetriever

Parameters

Optional kOrFields: number | Partial<VectorStoreRetrieverInput<ZepVectorStore>>

Optional filter: string | object

Optional callbacks: Callbacks

Optional tags: string[]

Optional metadata: Record<string, unknown>

Optional verbose: boolean

Returns VectorStoreRetriever<ZepVectorStore>

delete

Parameters

params: IZepDeleteParams

Returns Promise<void>

maxMarginalRelevanceSearch

Parameters

query: string

options: MaxMarginalRelevanceSearchOptions<string | object>

Returns Promise<Document<Record<string, any>>[]>

similaritySearch

Parameters

query: string

Optional k: number = 4

Optional filter: string | object = undefined

Optional _callbacks: Callbacks = undefined

Returns Promise<Document<Record<string, any>>[]>

Async

similaritySearchVectorWithScore

Parameters

query: number[]

k: number

Optional filter: Record<string, unknown>

Returns Promise<[Document<Record<string, any>>, number][]>

Returns undefined | {
[key: string]: string;
}

Returns undefined | {
[key: string]: string;
}

`Optional` filter: Record<string, unknown>

`Optional` kOrFields: number | Partial<VectorStoreRetrieverInput<ZepVectorStore>>

`Optional` filter: string | object

`Optional` callbacks: Callbacks

`Optional` tags: string[]

`Optional` metadata: Record<string, unknown>

`Optional` verbose: boolean

`Optional` k: number = 4

`Optional` filter: string | object = undefined

`Optional` _callbacks: Callbacks = undefined

`Optional` filter: Record<string, unknown>

`Static` fromDocuments

`Static` fromTexts

`Static` lc_name