Merge branch 'main' into feature/UnstructuredLoader
This commit is contained in:
Henry
commit
7a13cda9a3
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|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "flowise",
|
||||
"version": "1.3.7",
|
||||
"version": "1.3.8",
|
||||
"private": true,
|
||||
"homepage": "https://flowiseai.com",
|
||||
"workspaces": [
|
||||
|
|
|
|||
|
|
@ -0,0 +1,31 @@
|
|||
import { INodeParams, INodeCredential } from '../src/Interface'
|
||||
|
||||
class ElectricsearchAPI implements INodeCredential {
|
||||
label: string
|
||||
name: string
|
||||
version: number
|
||||
description: string
|
||||
inputs: INodeParams[]
|
||||
|
||||
constructor() {
|
||||
this.label = 'Elasticsearch API'
|
||||
this.name = 'elasticsearchApi'
|
||||
this.version = 1.0
|
||||
this.description =
|
||||
'Refer to <a target="_blank" href="https://www.elastic.co/guide/en/kibana/current/api-keys.html">official guide</a> on how to get an API Key from ElasticSearch'
|
||||
this.inputs = [
|
||||
{
|
||||
label: 'Elasticsearch Endpoint',
|
||||
name: 'endpoint',
|
||||
type: 'string'
|
||||
},
|
||||
{
|
||||
label: 'Elasticsearch API Key',
|
||||
name: 'apiKey',
|
||||
type: 'password'
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = { credClass: ElectricsearchAPI }
|
||||
|
|
@ -0,0 +1,36 @@
|
|||
import { INodeParams, INodeCredential } from '../src/Interface'
|
||||
|
||||
class ElasticSearchUserPassword implements INodeCredential {
|
||||
label: string
|
||||
name: string
|
||||
version: number
|
||||
description: string
|
||||
inputs: INodeParams[]
|
||||
|
||||
constructor() {
|
||||
this.label = 'ElasticSearch User Password'
|
||||
this.name = 'elasticSearchUserPassword'
|
||||
this.version = 1.0
|
||||
this.description =
|
||||
'Refer to <a target="_blank" href="https://www.elastic.co/guide/en/kibana/current/tutorial-secure-access-to-kibana.html">official guide</a> on how to get User Password from ElasticSearch'
|
||||
this.inputs = [
|
||||
{
|
||||
label: 'Cloud ID',
|
||||
name: 'cloudId',
|
||||
type: 'string'
|
||||
},
|
||||
{
|
||||
label: 'ElasticSearch User',
|
||||
name: 'username',
|
||||
type: 'string'
|
||||
},
|
||||
{
|
||||
label: 'ElasticSearch Password',
|
||||
name: 'password',
|
||||
type: 'password'
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = { credClass: ElasticSearchUserPassword }
|
||||
|
|
@ -0,0 +1,193 @@
|
|||
import {
|
||||
getBaseClasses,
|
||||
getCredentialData,
|
||||
getCredentialParam,
|
||||
ICommonObject,
|
||||
INodeData,
|
||||
INodeOutputsValue,
|
||||
INodeParams
|
||||
} from '../../../src'
|
||||
import { Client, ClientOptions } from '@elastic/elasticsearch'
|
||||
import { ElasticClientArgs, ElasticVectorSearch } from 'langchain/vectorstores/elasticsearch'
|
||||
import { Embeddings } from 'langchain/embeddings/base'
|
||||
import { VectorStore } from 'langchain/vectorstores/base'
|
||||
import { Document } from 'langchain/document'
|
||||
|
||||
export abstract class ElasticSearchBase {
|
||||
label: string
|
||||
name: string
|
||||
version: number
|
||||
description: string
|
||||
type: string
|
||||
icon: string
|
||||
category: string
|
||||
baseClasses: string[]
|
||||
inputs: INodeParams[]
|
||||
credential: INodeParams
|
||||
outputs: INodeOutputsValue[]
|
||||
|
||||
protected constructor() {
|
||||
this.type = 'Elasticsearch'
|
||||
this.icon = 'elasticsearch.png'
|
||||
this.category = 'Vector Stores'
|
||||
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
|
||||
this.credential = {
|
||||
label: 'Connect Credential',
|
||||
name: 'credential',
|
||||
type: 'credential',
|
||||
credentialNames: ['elasticsearchApi', 'elasticSearchUserPassword']
|
||||
}
|
||||
this.inputs = [
|
||||
{
|
||||
label: 'Embeddings',
|
||||
name: 'embeddings',
|
||||
type: 'Embeddings'
|
||||
},
|
||||
{
|
||||
label: 'Index Name',
|
||||
name: 'indexName',
|
||||
placeholder: '<INDEX_NAME>',
|
||||
type: 'string'
|
||||
},
|
||||
{
|
||||
label: 'Top K',
|
||||
name: 'topK',
|
||||
description: 'Number of top results to fetch. Default to 4',
|
||||
placeholder: '4',
|
||||
type: 'number',
|
||||
additionalParams: true,
|
||||
optional: true
|
||||
},
|
||||
{
|
||||
label: 'Similarity',
|
||||
name: 'similarity',
|
||||
description: 'Similarity measure used in Elasticsearch.',
|
||||
type: 'options',
|
||||
default: 'l2_norm',
|
||||
options: [
|
||||
{
|
||||
label: 'l2_norm',
|
||||
name: 'l2_norm'
|
||||
},
|
||||
{
|
||||
label: 'dot_product',
|
||||
name: 'dot_product'
|
||||
},
|
||||
{
|
||||
label: 'cosine',
|
||||
name: 'cosine'
|
||||
}
|
||||
],
|
||||
additionalParams: true,
|
||||
optional: true
|
||||
}
|
||||
]
|
||||
this.outputs = [
|
||||
{
|
||||
label: 'Elasticsearch Retriever',
|
||||
name: 'retriever',
|
||||
baseClasses: this.baseClasses
|
||||
},
|
||||
{
|
||||
label: 'Elasticsearch Vector Store',
|
||||
name: 'vectorStore',
|
||||
baseClasses: [this.type, ...getBaseClasses(ElasticVectorSearch)]
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
abstract constructVectorStore(
|
||||
embeddings: Embeddings,
|
||||
elasticSearchClientArgs: ElasticClientArgs,
|
||||
docs: Document<Record<string, any>>[] | undefined
|
||||
): Promise<VectorStore>
|
||||
|
||||
async init(nodeData: INodeData, _: string, options: ICommonObject, docs: Document<Record<string, any>>[] | undefined): Promise<any> {
|
||||
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
|
||||
const endPoint = getCredentialParam('endpoint', credentialData, nodeData)
|
||||
const cloudId = getCredentialParam('cloudId', credentialData, nodeData)
|
||||
const indexName = nodeData.inputs?.indexName as string
|
||||
const embeddings = nodeData.inputs?.embeddings as Embeddings
|
||||
const topK = nodeData.inputs?.topK as string
|
||||
const similarityMeasure = nodeData.inputs?.similarityMeasure as string
|
||||
const k = topK ? parseFloat(topK) : 4
|
||||
const output = nodeData.outputs?.output as string
|
||||
|
||||
const elasticSearchClientArgs = this.prepareClientArgs(endPoint, cloudId, credentialData, nodeData, similarityMeasure, indexName)
|
||||
|
||||
const vectorStore = await this.constructVectorStore(embeddings, elasticSearchClientArgs, docs)
|
||||
|
||||
if (output === 'retriever') {
|
||||
return vectorStore.asRetriever(k)
|
||||
} else if (output === 'vectorStore') {
|
||||
;(vectorStore as any).k = k
|
||||
return vectorStore
|
||||
}
|
||||
return vectorStore
|
||||
}
|
||||
|
||||
protected prepareConnectionOptions(
|
||||
endPoint: string | undefined,
|
||||
cloudId: string | undefined,
|
||||
credentialData: ICommonObject,
|
||||
nodeData: INodeData
|
||||
) {
|
||||
let elasticSearchClientOptions: ClientOptions = {}
|
||||
if (endPoint) {
|
||||
let apiKey = getCredentialParam('apiKey', credentialData, nodeData)
|
||||
elasticSearchClientOptions = {
|
||||
node: endPoint,
|
||||
auth: {
|
||||
apiKey: apiKey
|
||||
}
|
||||
}
|
||||
} else if (cloudId) {
|
||||
let username = getCredentialParam('username', credentialData, nodeData)
|
||||
let password = getCredentialParam('password', credentialData, nodeData)
|
||||
elasticSearchClientOptions = {
|
||||
cloud: {
|
||||
id: cloudId
|
||||
},
|
||||
auth: {
|
||||
username: username,
|
||||
password: password
|
||||
}
|
||||
}
|
||||
}
|
||||
return elasticSearchClientOptions
|
||||
}
|
||||
|
||||
protected prepareClientArgs(
|
||||
endPoint: string | undefined,
|
||||
cloudId: string | undefined,
|
||||
credentialData: ICommonObject,
|
||||
nodeData: INodeData,
|
||||
similarityMeasure: string,
|
||||
indexName: string
|
||||
) {
|
||||
let elasticSearchClientOptions = this.prepareConnectionOptions(endPoint, cloudId, credentialData, nodeData)
|
||||
let vectorSearchOptions = {}
|
||||
switch (similarityMeasure) {
|
||||
case 'dot_product':
|
||||
vectorSearchOptions = {
|
||||
similarity: 'dot_product'
|
||||
}
|
||||
break
|
||||
case 'cosine':
|
||||
vectorSearchOptions = {
|
||||
similarity: 'cosine'
|
||||
}
|
||||
break
|
||||
default:
|
||||
vectorSearchOptions = {
|
||||
similarity: 'l2_norm'
|
||||
}
|
||||
}
|
||||
const elasticSearchClientArgs: ElasticClientArgs = {
|
||||
client: new Client(elasticSearchClientOptions),
|
||||
indexName: indexName,
|
||||
vectorSearchOptions: vectorSearchOptions
|
||||
}
|
||||
return elasticSearchClientArgs
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,31 @@
|
|||
import { ICommonObject, INode, INodeData } from '../../../src/Interface'
|
||||
import { Embeddings } from 'langchain/embeddings/base'
|
||||
|
||||
import { ElasticClientArgs, ElasticVectorSearch } from 'langchain/vectorstores/elasticsearch'
|
||||
import { ElasticSearchBase } from './ElasticSearchBase'
|
||||
import { VectorStore } from 'langchain/vectorstores/base'
|
||||
import { Document } from 'langchain/document'
|
||||
|
||||
class ElasicsearchExisting_VectorStores extends ElasticSearchBase implements INode {
|
||||
constructor() {
|
||||
super()
|
||||
this.label = 'Elasticsearch Load Existing Index'
|
||||
this.name = 'ElasticsearchIndex'
|
||||
this.version = 1.0
|
||||
this.description = 'Load existing index from Elasticsearch (i.e: Document has been upserted)'
|
||||
}
|
||||
|
||||
async constructVectorStore(
|
||||
embeddings: Embeddings,
|
||||
elasticSearchClientArgs: ElasticClientArgs,
|
||||
docs: Document<Record<string, any>>[] | undefined
|
||||
): Promise<VectorStore> {
|
||||
return await ElasticVectorSearch.fromExistingIndex(embeddings, elasticSearchClientArgs)
|
||||
}
|
||||
|
||||
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
|
||||
return super.init(nodeData, _, options, undefined)
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = { nodeClass: ElasicsearchExisting_VectorStores }
|
||||
|
|
@ -0,0 +1,55 @@
|
|||
import { ICommonObject, INode, INodeData } from '../../../src/Interface'
|
||||
import { Embeddings } from 'langchain/embeddings/base'
|
||||
import { Document } from 'langchain/document'
|
||||
|
||||
import { ElasticClientArgs, ElasticVectorSearch } from 'langchain/vectorstores/elasticsearch'
|
||||
import { flatten } from 'lodash'
|
||||
import { ElasticSearchBase } from './ElasticSearchBase'
|
||||
import { VectorStore } from 'langchain/vectorstores/base'
|
||||
|
||||
class ElasicsearchUpsert_VectorStores extends ElasticSearchBase implements INode {
|
||||
constructor() {
|
||||
super()
|
||||
this.label = 'Elasticsearch Upsert Document'
|
||||
this.name = 'ElasticsearchUpsert'
|
||||
this.version = 1.0
|
||||
this.description = 'Upsert documents to Elasticsearch'
|
||||
this.inputs.unshift({
|
||||
label: 'Document',
|
||||
name: 'document',
|
||||
type: 'Document',
|
||||
list: true
|
||||
})
|
||||
}
|
||||
|
||||
async constructVectorStore(
|
||||
embeddings: Embeddings,
|
||||
elasticSearchClientArgs: ElasticClientArgs,
|
||||
docs: Document<Record<string, any>>[]
|
||||
): Promise<VectorStore> {
|
||||
const vectorStore = new ElasticVectorSearch(embeddings, elasticSearchClientArgs)
|
||||
await vectorStore.addDocuments(docs)
|
||||
return vectorStore
|
||||
}
|
||||
|
||||
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
|
||||
const docs = nodeData.inputs?.document as Document[]
|
||||
|
||||
const flattenDocs = docs && docs.length ? flatten(docs) : []
|
||||
const finalDocs = []
|
||||
for (let i = 0; i < flattenDocs.length; i += 1) {
|
||||
finalDocs.push(new Document(flattenDocs[i]))
|
||||
}
|
||||
|
||||
// The following code is a workaround for a bug (Langchain Issue #1589) in the underlying library.
|
||||
// Store does not support object in metadata and fail silently
|
||||
finalDocs.forEach((d) => {
|
||||
delete d.metadata.pdf
|
||||
delete d.metadata.loc
|
||||
})
|
||||
// end of workaround
|
||||
return super.init(nodeData, _, options, flattenDocs)
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = { nodeClass: ElasicsearchUpsert_VectorStores }
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 3.6 KiB |
|
|
@ -1,5 +1,5 @@
|
|||
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
|
||||
import { PineconeClient } from '@pinecone-database/pinecone'
|
||||
import { Pinecone } from '@pinecone-database/pinecone'
|
||||
import { PineconeLibArgs, PineconeStore } from 'langchain/vectorstores/pinecone'
|
||||
import { Embeddings } from 'langchain/embeddings/base'
|
||||
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
|
||||
|
|
@ -95,8 +95,7 @@ class Pinecone_Existing_VectorStores implements INode {
|
|||
const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
|
||||
const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData)
|
||||
|
||||
const client = new PineconeClient()
|
||||
await client.init({
|
||||
const client = new Pinecone({
|
||||
apiKey: pineconeApiKey,
|
||||
environment: pineconeEnv
|
||||
})
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
|
||||
import { PineconeClient } from '@pinecone-database/pinecone'
|
||||
import { Pinecone } from '@pinecone-database/pinecone'
|
||||
import { PineconeLibArgs, PineconeStore } from 'langchain/vectorstores/pinecone'
|
||||
import { Embeddings } from 'langchain/embeddings/base'
|
||||
import { Document } from 'langchain/document'
|
||||
|
|
@ -96,8 +96,7 @@ class PineconeUpsert_VectorStores implements INode {
|
|||
const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
|
||||
const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData)
|
||||
|
||||
const client = new PineconeClient()
|
||||
await client.init({
|
||||
const client = new Pinecone({
|
||||
apiKey: pineconeApiKey,
|
||||
environment: pineconeEnv
|
||||
})
|
||||
|
Before Width: | Height: | Size: 2.4 KiB After Width: | Height: | Size: 2.4 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 2.4 KiB |
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "flowise-components",
|
||||
"version": "1.3.8",
|
||||
"version": "1.3.10",
|
||||
"description": "Flowiseai Components",
|
||||
"main": "dist/src/index",
|
||||
"types": "dist/src/index.d.ts",
|
||||
|
|
@ -20,13 +20,14 @@
|
|||
"@aws-sdk/client-dynamodb": "^3.360.0",
|
||||
"@aws-sdk/client-s3": "^3.427.0",
|
||||
"@dqbd/tiktoken": "^1.0.7",
|
||||
"@elastic/elasticsearch": "^8.9.0",
|
||||
"@getzep/zep-js": "^0.6.3",
|
||||
"@gomomento/sdk": "^1.40.2",
|
||||
"@google-ai/generativelanguage": "^0.2.1",
|
||||
"@huggingface/inference": "^2.6.1",
|
||||
"@notionhq/client": "^2.2.8",
|
||||
"@opensearch-project/opensearch": "^1.2.0",
|
||||
"@pinecone-database/pinecone": "^0.0.14",
|
||||
"@pinecone-database/pinecone": "^1.1.1",
|
||||
"@qdrant/js-client-rest": "^1.2.2",
|
||||
"@supabase/supabase-js": "^2.29.0",
|
||||
"@types/js-yaml": "^4.0.5",
|
||||
|
|
|
|||
|
|
@ -238,9 +238,6 @@ export const additionalCallbacks = async (nodeData: INodeData, options: ICommonO
|
|||
})
|
||||
callbacks.push(tracer)
|
||||
} else if (provider === 'langFuse') {
|
||||
const flushAt = analytic[provider].flushAt as string
|
||||
const flushInterval = analytic[provider].flushInterval as string
|
||||
const requestTimeout = analytic[provider].requestTimeout as string
|
||||
const release = analytic[provider].release as string
|
||||
|
||||
const langFuseSecretKey = getCredentialParam('langFuseSecretKey', credentialData, nodeData)
|
||||
|
|
@ -252,9 +249,6 @@ export const additionalCallbacks = async (nodeData: INodeData, options: ICommonO
|
|||
publicKey: langFusePublicKey,
|
||||
baseUrl: langFuseEndpoint ?? 'https://cloud.langfuse.com'
|
||||
}
|
||||
if (flushAt) langFuseOptions.flushAt = parseInt(flushAt, 10)
|
||||
if (flushInterval) langFuseOptions.flushInterval = parseInt(flushInterval, 10)
|
||||
if (requestTimeout) langFuseOptions.requestTimeout = parseInt(requestTimeout, 10)
|
||||
if (release) langFuseOptions.release = release
|
||||
|
||||
const handler = new CallbackHandler(langFuseOptions)
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "flowise",
|
||||
"version": "1.3.7",
|
||||
"version": "1.3.8",
|
||||
"description": "Flowiseai Server",
|
||||
"main": "dist/index",
|
||||
"types": "dist/index.d.ts",
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "flowise-ui",
|
||||
"version": "1.3.5",
|
||||
"version": "1.3.6",
|
||||
"license": "SEE LICENSE IN LICENSE.md",
|
||||
"homepage": "https://flowiseai.com",
|
||||
"author": {
|
||||
|
|
|
|||
|
|
@ -81,27 +81,6 @@ const analyticProviders = [
|
|||
type: 'credential',
|
||||
credentialNames: ['langfuseApi']
|
||||
},
|
||||
{
|
||||
label: 'Flush At',
|
||||
name: 'flushAt',
|
||||
type: 'number',
|
||||
optional: true,
|
||||
description: 'Number of queued requests'
|
||||
},
|
||||
{
|
||||
label: 'Flush Interval',
|
||||
name: 'flushInterval',
|
||||
type: 'number',
|
||||
optional: true,
|
||||
description: 'Interval in ms to flush requests'
|
||||
},
|
||||
{
|
||||
label: 'Request Timeout',
|
||||
name: 'requestTimeout',
|
||||
type: 'number',
|
||||
optional: true,
|
||||
description: 'Timeout in ms for requests'
|
||||
},
|
||||
{
|
||||
label: 'Release',
|
||||
name: 'release',
|
||||
|
|
|
|||
Loading…
Reference in New Issue