Merge branch 'main' into feature/UnstructuredLoader

This commit is contained in:
Henry 2023-10-12 19:23:41 +01:00
commit 7a13cda9a3
16 changed files with 356 additions and 38 deletions

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@ -1,6 +1,6 @@
{ {
"name": "flowise", "name": "flowise",
"version": "1.3.7", "version": "1.3.8",
"private": true, "private": true,
"homepage": "https://flowiseai.com", "homepage": "https://flowiseai.com",
"workspaces": [ "workspaces": [

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@ -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 }

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@ -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 }

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@ -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
}
}

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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 }

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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 }

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@ -1,5 +1,5 @@
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' 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 { PineconeLibArgs, PineconeStore } from 'langchain/vectorstores/pinecone'
import { Embeddings } from 'langchain/embeddings/base' import { Embeddings } from 'langchain/embeddings/base'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
@ -95,8 +95,7 @@ class Pinecone_Existing_VectorStores implements INode {
const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData) const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData) const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData)
const client = new PineconeClient() const client = new Pinecone({
await client.init({
apiKey: pineconeApiKey, apiKey: pineconeApiKey,
environment: pineconeEnv environment: pineconeEnv
}) })

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@ -1,5 +1,5 @@
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' 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 { PineconeLibArgs, PineconeStore } from 'langchain/vectorstores/pinecone'
import { Embeddings } from 'langchain/embeddings/base' import { Embeddings } from 'langchain/embeddings/base'
import { Document } from 'langchain/document' import { Document } from 'langchain/document'
@ -96,8 +96,7 @@ class PineconeUpsert_VectorStores implements INode {
const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData) const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData) const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData)
const client = new PineconeClient() const client = new Pinecone({
await client.init({
apiKey: pineconeApiKey, apiKey: pineconeApiKey,
environment: pineconeEnv environment: pineconeEnv
}) })

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@ -1,6 +1,6 @@
{ {
"name": "flowise-components", "name": "flowise-components",
"version": "1.3.8", "version": "1.3.10",
"description": "Flowiseai Components", "description": "Flowiseai Components",
"main": "dist/src/index", "main": "dist/src/index",
"types": "dist/src/index.d.ts", "types": "dist/src/index.d.ts",
@ -20,13 +20,14 @@
"@aws-sdk/client-dynamodb": "^3.360.0", "@aws-sdk/client-dynamodb": "^3.360.0",
"@aws-sdk/client-s3": "^3.427.0", "@aws-sdk/client-s3": "^3.427.0",
"@dqbd/tiktoken": "^1.0.7", "@dqbd/tiktoken": "^1.0.7",
"@elastic/elasticsearch": "^8.9.0",
"@getzep/zep-js": "^0.6.3", "@getzep/zep-js": "^0.6.3",
"@gomomento/sdk": "^1.40.2", "@gomomento/sdk": "^1.40.2",
"@google-ai/generativelanguage": "^0.2.1", "@google-ai/generativelanguage": "^0.2.1",
"@huggingface/inference": "^2.6.1", "@huggingface/inference": "^2.6.1",
"@notionhq/client": "^2.2.8", "@notionhq/client": "^2.2.8",
"@opensearch-project/opensearch": "^1.2.0", "@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", "@qdrant/js-client-rest": "^1.2.2",
"@supabase/supabase-js": "^2.29.0", "@supabase/supabase-js": "^2.29.0",
"@types/js-yaml": "^4.0.5", "@types/js-yaml": "^4.0.5",

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@ -238,9 +238,6 @@ export const additionalCallbacks = async (nodeData: INodeData, options: ICommonO
}) })
callbacks.push(tracer) callbacks.push(tracer)
} else if (provider === 'langFuse') { } 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 release = analytic[provider].release as string
const langFuseSecretKey = getCredentialParam('langFuseSecretKey', credentialData, nodeData) const langFuseSecretKey = getCredentialParam('langFuseSecretKey', credentialData, nodeData)
@ -252,9 +249,6 @@ export const additionalCallbacks = async (nodeData: INodeData, options: ICommonO
publicKey: langFusePublicKey, publicKey: langFusePublicKey,
baseUrl: langFuseEndpoint ?? 'https://cloud.langfuse.com' 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 if (release) langFuseOptions.release = release
const handler = new CallbackHandler(langFuseOptions) const handler = new CallbackHandler(langFuseOptions)

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@ -1,6 +1,6 @@
{ {
"name": "flowise", "name": "flowise",
"version": "1.3.7", "version": "1.3.8",
"description": "Flowiseai Server", "description": "Flowiseai Server",
"main": "dist/index", "main": "dist/index",
"types": "dist/index.d.ts", "types": "dist/index.d.ts",

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@ -1,6 +1,6 @@
{ {
"name": "flowise-ui", "name": "flowise-ui",
"version": "1.3.5", "version": "1.3.6",
"license": "SEE LICENSE IN LICENSE.md", "license": "SEE LICENSE IN LICENSE.md",
"homepage": "https://flowiseai.com", "homepage": "https://flowiseai.com",
"author": { "author": {

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@ -81,27 +81,6 @@ const analyticProviders = [
type: 'credential', type: 'credential',
credentialNames: ['langfuseApi'] 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', label: 'Release',
name: 'release', name: 'release',