MMR Search for Pinecone, Weaviate, Zep and Supabase

This commit is contained in:
vinodkiran
2023-12-22 12:08:48 +05:30
parent 579f66e57e
commit 56b043264a
5 changed files with 98 additions and 109 deletions
@@ -5,6 +5,7 @@ import { Document } from 'langchain/document'
import { Embeddings } from 'langchain/embeddings/base'
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { addMMRInputParams, resolveVectorStoreOrRetriever } from '../VectorStoreUtils'
class Weaviate_VectorStores implements INode {
label: string
@@ -23,12 +24,12 @@ class Weaviate_VectorStores implements INode {
constructor() {
this.label = 'Weaviate'
this.name = 'weaviate'
this.version = 1.0
this.version = 2.0
this.type = 'Weaviate'
this.icon = 'weaviate.png'
this.category = 'Vector Stores'
this.description =
'Upsert embedded data and perform similarity search upon query using Weaviate, a scalable open-source vector database'
'Upsert embedded data and perform similarity or mmr search using Weaviate, a scalable open-source vector database'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
@@ -107,6 +108,7 @@ class Weaviate_VectorStores implements INode {
optional: true
}
]
addMMRInputParams(this.inputs)
this.outputs = [
{
label: 'Weaviate Retriever',
@@ -174,9 +176,6 @@ class Weaviate_VectorStores implements INode {
const weaviateTextKey = nodeData.inputs?.weaviateTextKey as string
const weaviateMetadataKeys = nodeData.inputs?.weaviateMetadataKeys as string
const embeddings = nodeData.inputs?.embeddings as Embeddings
const output = nodeData.outputs?.output as string
const topK = nodeData.inputs?.topK as string
const k = topK ? parseFloat(topK) : 4
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const weaviateApiKey = getCredentialParam('weaviateApiKey', credentialData, nodeData)
@@ -199,14 +198,7 @@ class Weaviate_VectorStores implements INode {
const vectorStore = await WeaviateStore.fromExistingIndex(embeddings, obj)
if (output === 'retriever') {
const retriever = vectorStore.asRetriever(k)
return retriever
} else if (output === 'vectorStore') {
;(vectorStore as any).k = k
return vectorStore
}
return vectorStore
return resolveVectorStoreOrRetriever(nodeData, vectorStore)
}
}