Optional
filter?: TFilterModelA path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.
Optional
filterStatic
ContentStatic
IdProtected
PrismaProtected
dbProtected
selectProtected
tableProtected
vectorA 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.
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.
The final serialized identifier for the module.
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.
Adds the specified documents to the store.
The documents to add.
A promise that resolves when the documents have been added.
Adds the specified vectors to the store.
The vectors to add.
The documents associated with the vectors.
A promise that resolves when the vectors have been added.
Optional
kOrFields: number | Partial<VectorStoreRetrieverInput<PrismaVectorStore<TModel, TModelName, TSelectModel, TFilterModel>>>Optional
filter: string | objectOptional
callbacks: CallbacksOptional
tags: string[]Optional
metadata: Record<string, unknown>Optional
verbose: booleanPerforms a similarity search with the specified query.
The query to use for the similarity search.
The number of results to return.
The filter to apply to the results.
The callbacks to use during the search.
A promise that resolves with the search results.
Performs a similarity search with the specified vector and returns the results along with their scores.
The vector to use for the similarity search.
The number of results to return.
Optional
filter: TFilterModelThe filter to apply to the results.
A promise that resolves with the search results and their scores.
Performs a similarity search with the specified query and returns the results along with their scores.
The query to use for the similarity search.
Optional
k: numberThe number of results to return.
Optional
filter: TFilterModelThe filter to apply to the results.
The callbacks to use during the search.
A promise that resolves with the search results and their scores.
Optional
maxReturn documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.
Text to look up documents similar to.
Static
fromCreates a new PrismaVectorStore from the specified documents.
The documents to use to create the store.
The embeddings to use.
The database configuration.
A promise that resolves with the new PrismaVectorStore.
Static
fromCreates a new PrismaVectorStore from the specified texts.
The texts to use to create the store.
The metadata for the texts.
The embeddings to use.
The database configuration.
A promise that resolves with the new PrismaVectorStore.
Static
lc_Static
withCreates a new PrismaVectorStore with the specified model.
The PrismaClient instance.
An object with create, fromTexts, and fromDocuments methods.
Optional
filter?: TFiltersGenerated using TypeDoc
A specific implementation of the VectorStore class that is designed to work with Prisma. It provides methods for adding models, documents, and vectors, as well as for performing similarity searches.