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Merge branch 'main' into feature/ZepVS

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# Conflicts:
#	packages/components/package.json
This commit is contained in:
Henry
2023-08-17 10:23:41 +01:00
parent 913b343956 5a8db9a534
commit a7b1c8c8b3
11 changed files with 474 additions and 232 deletions
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packages/components/nodes/vectorstores/Vectara_Existing/Vectara_Existing.ts
+26 -1
View File
@@ -1,6 +1,6 @@
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { VectaraStore, VectaraLibArgs, VectaraFilter } from 'langchain/vectorstores/vectara'
import { VectaraStore, VectaraLibArgs, VectaraFilter, VectaraContextConfig } from 'langchain/vectorstores/vectara'
class VectaraExisting_VectorStores implements INode {
label: string
@@ -40,9 +40,27 @@ class VectaraExisting_VectorStores implements INode {
additionalParams: true,
optional: true
},
{
label: 'Sentences Before',
name: 'sentencesBefore',
description: 'Number of sentences to fetch before the matched sentence. Defaults to 2.',
type: 'number',
additionalParams: true,
optional: true
},
{
label: 'Sentences After',
name: 'sentencesAfter',
description: 'Number of sentences to fetch after the matched sentence. Defaults to 2.',
type: 'number',
additionalParams: true,
optional: true
},
{
label: 'Lambda',
name: 'lambda',
description:
'Improves retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.',
type: 'number',
additionalParams: true,
optional: true
@@ -77,6 +95,8 @@ class VectaraExisting_VectorStores implements INode {
const corpusId = getCredentialParam('corpusID', credentialData, nodeData)
const vectaraMetadataFilter = nodeData.inputs?.filter as string
const sentencesBefore = nodeData.inputs?.sentencesBefore as number
const sentencesAfter = nodeData.inputs?.sentencesAfter as number
const lambda = nodeData.inputs?.lambda as number
const output = nodeData.outputs?.output as string
const topK = nodeData.inputs?.topK as string
@@ -92,6 +112,11 @@ class VectaraExisting_VectorStores implements INode {
if (vectaraMetadataFilter) vectaraFilter.filter = vectaraMetadataFilter
if (lambda) vectaraFilter.lambda = lambda
const vectaraContextConfig: VectaraContextConfig = {}
if (sentencesBefore) vectaraContextConfig.sentencesBefore = sentencesBefore
if (sentencesAfter) vectaraContextConfig.sentencesAfter = sentencesAfter
vectaraFilter.contextConfig = vectaraContextConfig
const vectorStore = new VectaraStore(vectaraArgs)
if (output === 'retriever') {
packages/components/nodes/vectorstores/Vectara_Upsert/Vectara_Upsert.ts
+26 -1
View File
@@ -1,7 +1,7 @@
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
import { Embeddings } from 'langchain/embeddings/base'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { VectaraStore, VectaraLibArgs, VectaraFilter } from 'langchain/vectorstores/vectara'
import { VectaraStore, VectaraLibArgs, VectaraFilter, VectaraContextConfig } from 'langchain/vectorstores/vectara'
import { Document } from 'langchain/document'
import { flatten } from 'lodash'
@@ -49,9 +49,27 @@ class VectaraUpsert_VectorStores implements INode {
additionalParams: true,
optional: true
},
{
label: 'Sentences Before',
name: 'sentencesBefore',
description: 'Number of sentences to fetch before the matched sentence. Defaults to 2.',
type: 'number',
additionalParams: true,
optional: true
},
{
label: 'Sentences After',
name: 'sentencesAfter',
description: 'Number of sentences to fetch after the matched sentence. Defaults to 2.',
type: 'number',
additionalParams: true,
optional: true
},
{
label: 'Lambda',
name: 'lambda',
description:
'Improves retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.',
type: 'number',
additionalParams: true,
optional: true
@@ -88,6 +106,8 @@ class VectaraUpsert_VectorStores implements INode {
const docs = nodeData.inputs?.document as Document[]
const embeddings = {} as Embeddings
const vectaraMetadataFilter = nodeData.inputs?.filter as string
const sentencesBefore = nodeData.inputs?.sentencesBefore as number
const sentencesAfter = nodeData.inputs?.sentencesAfter as number
const lambda = nodeData.inputs?.lambda as number
const output = nodeData.outputs?.output as string
const topK = nodeData.inputs?.topK as string
@@ -103,6 +123,11 @@ class VectaraUpsert_VectorStores implements INode {
if (vectaraMetadataFilter) vectaraFilter.filter = vectaraMetadataFilter
if (lambda) vectaraFilter.lambda = lambda
const vectaraContextConfig: VectaraContextConfig = {}
if (sentencesBefore) vectaraContextConfig.sentencesBefore = sentencesBefore
if (sentencesAfter) vectaraContextConfig.sentencesAfter = sentencesAfter
vectaraFilter.contextConfig = vectaraContextConfig
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {