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Merge branch 'main' into FEATURE/elasticsearch-vectorstore

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Henry Heng 2023-10-11 14:22:48 +01:00 committed by GitHub
parent 57760dc633 96de11f710
commit 0be1823a0e
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92 changed files with 1960 additions and 238 deletions
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2
package.json
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@ -1,6 +1,6 @@
{
"name": "flowise",
"version": "1.3.6",
"version": "1.3.7",
"private": true,
"homepage": "https://flowiseai.com",
"workspaces": [

47
packages/components/credentials/AWSCredential.credential.ts Normal file
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@ -0,0 +1,47 @@
import { INodeParams, INodeCredential } from '../src/Interface'
class AWSApi implements INodeCredential {
label: string
name: string
version: number
description: string
optional: boolean
inputs: INodeParams[]
constructor() {
this.label = 'AWS security credentials'
this.name = 'awsApi'
this.version = 1.0
this.description =
'Your <a target="_blank" href="https://docs.aws.amazon.com/IAM/latest/UserGuide/security-creds.html">AWS security credentials</a>. When unspecified, credentials will be sourced from the runtime environment according to the default AWS SDK behavior.'
this.optional = true
this.inputs = [
{
label: 'AWS Access Key',
name: 'awsKey',
type: 'string',
placeholder: '<AWS_ACCESS_KEY_ID>',
description: 'The access key for your AWS account.',
optional: true
},
{
label: 'AWS Secret Access Key',
name: 'awsSecret',
type: 'password',
placeholder: '<AWS_SECRET_ACCESS_KEY>',
description: 'The secret key for your AWS account.',
optional: true
},
{
label: 'AWS Session Key',
name: 'awsSession',
type: 'password',
placeholder: '<AWS_SESSION_TOKEN>',
description: 'The session key for your AWS account. This is only needed when you are using temporary credentials.',
optional: true
}
]
}
}
module.exports = { credClass: AWSApi }

36
packages/components/credentials/MomentoCacheApi.credential.ts Normal file
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@ -0,0 +1,36 @@
import { INodeParams, INodeCredential } from '../src/Interface'
class MomentoCacheApi implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Momento Cache API'
this.name = 'momentoCacheApi'
this.version = 1.0
this.description =
'Refer to <a target="_blank" href="https://docs.momentohq.com/cache/develop/authentication/api-keys">official guide</a> on how to get API key on Momento'
this.inputs = [
{
label: 'Cache',
name: 'momentoCache',
type: 'string'
},
{
label: 'API Key',
name: 'momentoApiKey',
type: 'password'
},
{
label: 'Endpoint',
name: 'momentoEndpoint',
type: 'string'
}
]
}
}
module.exports = { credClass: MomentoCacheApi }

43
packages/components/credentials/RedisCacheApi.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
class RedisCacheApi implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Redis Cache API'
this.name = 'redisCacheApi'
this.version = 1.0
this.inputs = [
{
label: 'Redis Host',
name: 'redisCacheHost',
type: 'string',
default: '127.0.0.1'
},
{
label: 'Port',
name: 'redisCachePort',
type: 'number',
default: '6789'
},
{
label: 'User',
name: 'redisCacheUser',
type: 'string',
placeholder: '<REDIS_USERNAME>'
},
{
label: 'Password',
name: 'redisCachePwd',
type: 'password',
placeholder: '<REDIS_PASSWORD>'
}
]
}
}
module.exports = { credClass: RedisCacheApi }

28
packages/components/credentials/UpstashRedisApi.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
class UpstashRedisApi implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
constructor() {
this.label = 'Upstash Redis API'
this.name = 'upstashRedisApi'
this.version = 1.0
this.inputs = [
{
label: 'Upstash Redis REST URL',
name: 'upstashConnectionUrl',
type: 'string'
},
{
label: 'Token',
name: 'upstashConnectionToken',
type: 'password'
}
]
}
}
module.exports = { credClass: UpstashRedisApi }

26
packages/components/credentials/UpstashRedisMemoryApi.credential.ts Normal file
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@ -0,0 +1,26 @@
import { INodeParams, INodeCredential } from '../src/Interface'
class UpstashRedisMemoryApi implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Upstash Redis Memory API'
this.name = 'upstashRedisMemoryApi'
this.version = 1.0
this.description =
'Refer to <a target="_blank" href="https://upstash.com/docs/redis/overall/getstarted">official guide</a> on how to create redis instance and get redis REST Token'
this.inputs = [
{
label: 'Upstash Redis REST Token',
name: 'upstashRestToken',
type: 'password'
}
]
}
}
module.exports = { credClass: UpstashRedisMemoryApi }

8
packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts
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@ -95,8 +95,12 @@ class ConversationalAgent_Agents implements INode {
const callbacks = await additionalCallbacks(nodeData, options)
if (options && options.chatHistory) {
memory.chatHistory = mapChatHistory(options)
executor.memory = memory
const chatHistoryClassName = memory.chatHistory.constructor.name
// Only replace when its In-Memory
if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') {
memory.chatHistory = mapChatHistory(options)
executor.memory = memory
}
}
const result = await executor.call({ input }, [...callbacks])

6
packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts
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@ -82,7 +82,11 @@ class ConversationalRetrievalAgent_Agents implements INode {
if (executor.memory) {
;(executor.memory as any).memoryKey = 'chat_history'
;(executor.memory as any).outputKey = 'output'
;(executor.memory as any).chatHistory = mapChatHistory(options)
const chatHistoryClassName = (executor.memory as any).chatHistory.constructor.name
// Only replace when its In-Memory
if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') {
;(executor.memory as any).chatHistory = mapChatHistory(options)
}
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)

8
packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts
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@ -81,8 +81,12 @@ class OpenAIFunctionAgent_Agents implements INode {
const memory = nodeData.inputs?.memory as BaseChatMemory
if (options && options.chatHistory) {
memory.chatHistory = mapChatHistory(options)
executor.memory = memory
const chatHistoryClassName = memory.chatHistory.constructor.name
// Only replace when its In-Memory
if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') {
memory.chatHistory = mapChatHistory(options)
executor.memory = memory
}
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)

57
packages/components/nodes/cache/MomentoCache/MomentoCache.ts vendored Normal file
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@ -0,0 +1,57 @@
import { getBaseClasses, getCredentialData, getCredentialParam, ICommonObject, INode, INodeData, INodeParams } from '../../../src'
import { MomentoCache as LangchainMomentoCache } from 'langchain/cache/momento'
import { CacheClient, Configurations, CredentialProvider } from '@gomomento/sdk'
class MomentoCache implements INode {
label: string
name: string
version: number
description: string
type: string
icon: string
category: string
baseClasses: string[]
inputs: INodeParams[]
credential: INodeParams
constructor() {
this.label = 'Momento Cache'
this.name = 'momentoCache'
this.version = 1.0
this.type = 'MomentoCache'
this.icon = 'momento.png'
this.category = 'Cache'
this.baseClasses = [this.type, ...getBaseClasses(LangchainMomentoCache)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
optional: true,
credentialNames: ['momentoCacheApi']
}
this.inputs = []
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const apiKey = getCredentialParam('momentoApiKey', credentialData, nodeData)
const cacheName = getCredentialParam('momentoCache', credentialData, nodeData)
// See https://github.com/momentohq/client-sdk-javascript for connection options
const client = new CacheClient({
configuration: Configurations.Laptop.v1(),
credentialProvider: CredentialProvider.fromString({
apiKey: apiKey
}),
defaultTtlSeconds: 60 * 60 * 24
})
let momentoCache = await LangchainMomentoCache.fromProps({
client,
cacheName: cacheName
})
return momentoCache
}
}
module.exports = { nodeClass: MomentoCache }

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52
packages/components/nodes/cache/RedisCache/RedisCache.ts vendored Normal file
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import { getBaseClasses, getCredentialData, getCredentialParam, ICommonObject, INode, INodeData, INodeParams } from '../../../src'
import { RedisCache as LangchainRedisCache } from 'langchain/cache/ioredis'
import { Redis } from 'ioredis'
class RedisCache implements INode {
label: string
name: string
version: number
description: string
type: string
icon: string
category: string
baseClasses: string[]
inputs: INodeParams[]
credential: INodeParams
constructor() {
this.label = 'Redis Cache'
this.name = 'redisCache'
this.version = 1.0
this.type = 'RedisCache'
this.icon = 'redis.svg'
this.category = 'Cache'
this.baseClasses = [this.type, ...getBaseClasses(LangchainRedisCache)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
optional: true,
credentialNames: ['redisCacheApi']
}
this.inputs = []
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const username = getCredentialParam('redisCacheUser', credentialData, nodeData)
const password = getCredentialParam('redisCachePwd', credentialData, nodeData)
const portStr = getCredentialParam('redisCachePort', credentialData, nodeData)
const host = getCredentialParam('redisCacheHost', credentialData, nodeData)
const client = new Redis({
port: portStr ? parseInt(portStr) : 6379,
host,
username,
password
})
return new LangchainRedisCache(client)
}
}
module.exports = { nodeClass: RedisCache }

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packages/components/nodes/cache/RedisCache/redis.svg vendored Normal file
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@ -0,0 +1 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 128 128" id="redis"><path fill="#A41E11" d="M121.8 93.1c-6.7 3.5-41.4 17.7-48.8 21.6-7.4 3.9-11.5 3.8-17.3 1s-42.7-17.6-49.4-20.8c-3.3-1.6-5-2.9-5-4.2v-12.7s48-10.5 55.8-13.2c7.8-2.8 10.4-2.9 17-.5s46.1 9.5 52.6 11.9v12.5c0 1.3-1.5 2.7-4.9 4.4z"></path><path fill="#D82C20" d="M121.8 80.5c-6.7 3.5-41.4 17.7-48.8 21.6-7.4 3.9-11.5 3.8-17.3 1-5.8-2.8-42.7-17.7-49.4-20.9-6.6-3.2-6.8-5.4-.3-7.9 6.5-2.6 43.2-17 51-19.7 7.8-2.8 10.4-2.9 17-.5s41.1 16.1 47.6 18.5c6.7 2.4 6.9 4.4.2 7.9z"></path><path fill="#A41E11" d="M121.8 72.5c-6.7 3.5-41.4 17.7-48.8 21.6-7.4 3.8-11.5 3.8-17.3 1-5.8-2.8-42.7-17.7-49.4-20.9-3.3-1.6-5-2.9-5-4.2v-12.7s48-10.5 55.8-13.2c7.8-2.8 10.4-2.9 17-.5s46.1 9.5 52.6 11.9v12.5c0 1.3-1.5 2.7-4.9 4.5z"></path><path fill="#D82C20" d="M121.8 59.8c-6.7 3.5-41.4 17.7-48.8 21.6-7.4 3.8-11.5 3.8-17.3 1-5.8-2.8-42.7-17.7-49.4-20.9s-6.8-5.4-.3-7.9c6.5-2.6 43.2-17 51-19.7 7.8-2.8 10.4-2.9 17-.5s41.1 16.1 47.6 18.5c6.7 2.4 6.9 4.4.2 7.9z"></path><path fill="#A41E11" d="M121.8 51c-6.7 3.5-41.4 17.7-48.8 21.6-7.4 3.8-11.5 3.8-17.3 1-5.8-2.7-42.7-17.6-49.4-20.8-3.3-1.6-5.1-2.9-5.1-4.2v-12.7s48-10.5 55.8-13.2c7.8-2.8 10.4-2.9 17-.5s46.1 9.5 52.6 11.9v12.5c.1 1.3-1.4 2.6-4.8 4.4z"></path><path fill="#D82C20" d="M121.8 38.3c-6.7 3.5-41.4 17.7-48.8 21.6-7.4 3.8-11.5 3.8-17.3 1s-42.7-17.6-49.4-20.8-6.8-5.4-.3-7.9c6.5-2.6 43.2-17 51-19.7 7.8-2.8 10.4-2.9 17-.5s41.1 16.1 47.6 18.5c6.7 2.4 6.9 4.4.2 7.8z"></path><path fill="#fff" d="M80.4 26.1l-10.8 1.2-2.5 5.8-3.9-6.5-12.5-1.1 9.3-3.4-2.8-5.2 8.8 3.4 8.2-2.7-2.2 5.4zM66.5 54.5l-20.3-8.4 29.1-4.4z"></path><ellipse cx="38.4" cy="35.4" fill="#fff" rx="15.5" ry="6"></ellipse><path fill="#7A0C00" d="M93.3 27.7l17.2 6.8-17.2 6.8z"></path><path fill="#AD2115" d="M74.3 35.3l19-7.6v13.6l-1.9.8z"></path></svg>
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49
packages/components/nodes/cache/UpstashRedisCache/UpstashRedisCache.ts vendored Normal file
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@ -0,0 +1,49 @@
import { getBaseClasses, getCredentialData, getCredentialParam, ICommonObject, INode, INodeData, INodeParams } from '../../../src'
import { UpstashRedisCache as LangchainUpstashRedisCache } from 'langchain/cache/upstash_redis'
class UpstashRedisCache implements INode {
label: string
name: string
version: number
description: string
type: string
icon: string
category: string
baseClasses: string[]
inputs: INodeParams[]
credential: INodeParams
constructor() {
this.label = 'Upstash Redis Cache'
this.name = 'upstashRedisCache'
this.version = 1.0
this.type = 'UpstashRedisCache'
this.icon = 'upstash.png'
this.category = 'Cache'
this.baseClasses = [this.type, ...getBaseClasses(LangchainUpstashRedisCache)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
optional: true,
credentialNames: ['upstashRedisApi']
}
this.inputs = []
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const upstashConnectionUrl = getCredentialParam('upstashConnectionUrl', credentialData, nodeData)
const upstashToken = getCredentialParam('upstashConnectionToken', credentialData, nodeData)
const cache = new LangchainUpstashRedisCache({
config: {
url: upstashConnectionUrl,
token: upstashToken
}
})
return cache
}
}
module.exports = { nodeClass: UpstashRedisCache }

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8
packages/components/nodes/chains/ConversationChain/ConversationChain.ts
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@ -106,8 +106,12 @@ class ConversationChain_Chains implements INode {
const memory = nodeData.inputs?.memory as BufferMemory
if (options && options.chatHistory) {
memory.chatHistory = mapChatHistory(options)
chain.memory = memory
const chatHistoryClassName = memory.chatHistory.constructor.name
// Only replace when its In-Memory
if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') {
memory.chatHistory = mapChatHistory(options)
chain.memory = memory
}
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)

6
packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts
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@ -179,7 +179,11 @@ class ConversationalRetrievalQAChain_Chains implements INode {
const obj = { question: input }
if (options && options.chatHistory && chain.memory) {
;(chain.memory as any).chatHistory = mapChatHistory(options)
const chatHistoryClassName = (chain.memory as any).chatHistory.constructor.name
// Only replace when its In-Memory
if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') {
;(chain.memory as any).chatHistory = mapChatHistory(options)
}
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)

31
packages/components/nodes/chains/SqlDatabaseChain/SqlDatabaseChain.ts
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@ -1,5 +1,5 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { SqlDatabaseChain, SqlDatabaseChainInput } from 'langchain/chains/sql_db'
import { SqlDatabaseChain, SqlDatabaseChainInput, DEFAULT_SQL_DATABASE_PROMPT } from 'langchain/chains/sql_db'
import { getBaseClasses, getInputVariables } from '../../../src/utils'
import { DataSource } from 'typeorm'
import { SqlDatabase } from 'langchain/sql_db'
@ -10,25 +10,6 @@ import { DataSourceOptions } from 'typeorm/data-source'
type DatabaseType = 'sqlite' | 'postgres' | 'mssql' | 'mysql'
const defaultPrompt = `Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. Unless the user specifies in his question a specific number of examples he wishes to obtain, always limit your query to at most {top_k} results. You can order the results by a relevant column to return the most interesting examples in the database.
Never query for all the columns from a specific table, only ask for a the few relevant columns given the question.
Pay attention to use only the column names that you can see in the schema description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
Use the following format:
Question: "Question here"
SQLQuery: "SQL Query to run"
SQLResult: "Result of the SQLQuery"
Answer: "Final answer here"
Only use the tables listed below.
{table_info}
Question: {input}`
class SqlDatabaseChain_Chains implements INode {
label: string
name: string
@ -43,7 +24,7 @@ class SqlDatabaseChain_Chains implements INode {
constructor() {
this.label = 'Sql Database Chain'
this.name = 'sqlDatabaseChain'
this.version = 3.0
this.version = 4.0
this.type = 'SqlDatabaseChain'
this.icon = 'sqlchain.svg'
this.category = 'Chains'
@ -89,7 +70,8 @@ class SqlDatabaseChain_Chains implements INode {
label: 'Include Tables',
name: 'includesTables',
type: 'string',
description: 'Tables to include for queries.',
description: 'Tables to include for queries, seperated by comma. Can only use Include Tables or Ignore Tables',
placeholder: 'table1, table2',
additionalParams: true,
optional: true
},
@ -97,7 +79,8 @@ class SqlDatabaseChain_Chains implements INode {
label: 'Ignore Tables',
name: 'ignoreTables',
type: 'string',
description: 'Tables to ignore for queries.',
description: 'Tables to ignore for queries, seperated by comma. Can only use Ignore Tables or Include Tables',
placeholder: 'table1, table2',
additionalParams: true,
optional: true
},
@ -129,7 +112,7 @@ class SqlDatabaseChain_Chains implements INode {
warning:
'Prompt must include 3 input variables: {input}, {dialect}, {table_info}. You can refer to official guide from description above',
rows: 4,
placeholder: defaultPrompt,
placeholder: DEFAULT_SQL_DATABASE_PROMPT.template + DEFAULT_SQL_DATABASE_PROMPT.templateFormat,
additionalParams: true,
optional: true
}

176
packages/components/nodes/chatmodels/AWSBedrock/AWSChatBedrock.ts Normal file
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import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ChatBedrock } from 'langchain/chat_models/bedrock'
import { BaseBedrockInput } from 'langchain/dist/util/bedrock'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
/**
* I had to run the following to build the component
* and get the icon copied over to the dist directory
* Flowise/packages/components > yarn build
*
* @author Michael Connor <mlconnor@yahoo.com>
*/
class AWSChatBedrock_ChatModels implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
credential: INodeParams
inputs: INodeParams[]
constructor() {
this.label = 'AWS Bedrock'
this.name = 'awsChatBedrock'
this.version = 2.0
this.type = 'AWSChatBedrock'
this.icon = 'awsBedrock.png'
this.category = 'Chat Models'
this.description = 'Wrapper around AWS Bedrock large language models'
this.baseClasses = [this.type, ...getBaseClasses(ChatBedrock)]
this.credential = {
label: 'AWS Credential',
name: 'credential',
type: 'credential',
credentialNames: ['awsApi'],
optional: true
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Region',
name: 'region',
type: 'options',
options: [
{ label: 'af-south-1', name: 'af-south-1' },
{ label: 'ap-east-1', name: 'ap-east-1' },
{ label: 'ap-northeast-1', name: 'ap-northeast-1' },
{ label: 'ap-northeast-2', name: 'ap-northeast-2' },
{ label: 'ap-northeast-3', name: 'ap-northeast-3' },
{ label: 'ap-south-1', name: 'ap-south-1' },
{ label: 'ap-south-2', name: 'ap-south-2' },
{ label: 'ap-southeast-1', name: 'ap-southeast-1' },
{ label: 'ap-southeast-2', name: 'ap-southeast-2' },
{ label: 'ap-southeast-3', name: 'ap-southeast-3' },
{ label: 'ap-southeast-4', name: 'ap-southeast-4' },
{ label: 'ap-southeast-5', name: 'ap-southeast-5' },
{ label: 'ap-southeast-6', name: 'ap-southeast-6' },
{ label: 'ca-central-1', name: 'ca-central-1' },
{ label: 'ca-west-1', name: 'ca-west-1' },
{ label: 'cn-north-1', name: 'cn-north-1' },
{ label: 'cn-northwest-1', name: 'cn-northwest-1' },
{ label: 'eu-central-1', name: 'eu-central-1' },
{ label: 'eu-central-2', name: 'eu-central-2' },
{ label: 'eu-north-1', name: 'eu-north-1' },
{ label: 'eu-south-1', name: 'eu-south-1' },
{ label: 'eu-south-2', name: 'eu-south-2' },
{ label: 'eu-west-1', name: 'eu-west-1' },
{ label: 'eu-west-2', name: 'eu-west-2' },
{ label: 'eu-west-3', name: 'eu-west-3' },
{ label: 'il-central-1', name: 'il-central-1' },
{ label: 'me-central-1', name: 'me-central-1' },
{ label: 'me-south-1', name: 'me-south-1' },
{ label: 'sa-east-1', name: 'sa-east-1' },
{ label: 'us-east-1', name: 'us-east-1' },
{ label: 'us-east-2', name: 'us-east-2' },
{ label: 'us-gov-east-1', name: 'us-gov-east-1' },
{ label: 'us-gov-west-1', name: 'us-gov-west-1' },
{ label: 'us-west-1', name: 'us-west-1' },
{ label: 'us-west-2', name: 'us-west-2' }
],
default: 'us-east-1',
optional: false
},
{
label: 'Model Name',
name: 'model',
type: 'options',
options: [
{ label: 'amazon.titan-tg1-large', name: 'amazon.titan-tg1-large' },
{ label: 'amazon.titan-e1t-medium', name: 'amazon.titan-e1t-medium' },
{ label: 'stability.stable-diffusion-xl', name: 'stability.stable-diffusion-xl' },
{ label: 'ai21.j2-grande-instruct', name: 'ai21.j2-grande-instruct' },
{ label: 'ai21.j2-jumbo-instruct', name: 'ai21.j2-jumbo-instruct' },
{ label: 'ai21.j2-mid', name: 'ai21.j2-mid' },
{ label: 'ai21.j2-ultra', name: 'ai21.j2-ultra' },
{ label: 'anthropic.claude-instant-v1', name: 'anthropic.claude-instant-v1' },
{ label: 'anthropic.claude-v1', name: 'anthropic.claude-v1' },
{ label: 'anthropic.claude-v2', name: 'anthropic.claude-v2' }
],
default: 'anthropic.claude-v2',
optional: false
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
description: 'Temperature parameter may not apply to certain model. Please check available model parameters',
optional: true,
default: 0.7,
additionalParams: false
},
{
label: 'Max Tokens to Sample',
name: 'max_tokens_to_sample',
type: 'number',
step: 10,
description: 'Max Tokens parameter may not apply to certain model. Please check available model parameters',
optional: false,
default: 200,
additionalParams: false
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const iRegion = nodeData.inputs?.region as string
const iModel = nodeData.inputs?.model as string
const iTemperature = nodeData.inputs?.temperature as string
const iMax_tokens_to_sample = nodeData.inputs?.max_tokens_to_sample as string
const cache = nodeData.inputs?.cache as BaseCache
const obj: BaseBedrockInput & BaseLLMParams = {
region: iRegion,
model: iModel,
maxTokens: parseInt(iMax_tokens_to_sample, 10),
temperature: parseFloat(iTemperature)
}
/**
* Long-term credentials specified in LLM configuration are optional.
* Bedrock's credential provider falls back to the AWS SDK to fetch
* credentials from the running environment.
* When specified, we override the default provider with configured values.
* @see https://github.com/aws/aws-sdk-js-v3/blob/main/packages/credential-provider-node/README.md
*/
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
if (credentialData && Object.keys(credentialData).length !== 0) {
const credentialApiKey = getCredentialParam('awsKey', credentialData, nodeData)
const credentialApiSecret = getCredentialParam('awsSecret', credentialData, nodeData)
const credentialApiSession = getCredentialParam('awsSession', credentialData, nodeData)
obj.credentials = {
accessKeyId: credentialApiKey,
secretAccessKey: credentialApiSecret,
sessionToken: credentialApiSession
}
}
if (cache) obj.cache = cache
const amazonBedrock = new ChatBedrock(obj)
return amazonBedrock
}
}
module.exports = { nodeClass: AWSChatBedrock_ChatModels }

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14
packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI.ts
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@ -2,6 +2,8 @@ import { OpenAIBaseInput } from 'langchain/dist/types/openai-types'
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { AzureOpenAIInput, ChatOpenAI } from 'langchain/chat_models/openai'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class AzureChatOpenAI_ChatModels implements INode {
label: string
@ -18,7 +20,7 @@ class AzureChatOpenAI_ChatModels implements INode {
constructor() {
this.label = 'Azure ChatOpenAI'
this.name = 'azureChatOpenAI'
this.version = 1.0
this.version = 2.0
this.type = 'AzureChatOpenAI'
this.icon = 'Azure.svg'
this.category = 'Chat Models'
@ -31,6 +33,12 @@ class AzureChatOpenAI_ChatModels implements INode {
credentialNames: ['azureOpenAIApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -107,6 +115,7 @@ class AzureChatOpenAI_ChatModels implements INode {
const presencePenalty = nodeData.inputs?.presencePenalty as string
const timeout = nodeData.inputs?.timeout as string
const streaming = nodeData.inputs?.streaming as boolean
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
@ -114,7 +123,7 @@ class AzureChatOpenAI_ChatModels implements INode {
const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
const obj: Partial<AzureOpenAIInput> & Partial<OpenAIBaseInput> = {
const obj: Partial<AzureOpenAIInput> & BaseLLMParams & Partial<OpenAIBaseInput> = {
temperature: parseFloat(temperature),
modelName,
azureOpenAIApiKey,
@ -128,6 +137,7 @@ class AzureChatOpenAI_ChatModels implements INode {
if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (cache) obj.cache = cache
const model = new ChatOpenAI(obj)
return model

57
packages/components/nodes/chatmodels/Bittensor/Bittensor.ts Normal file
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@ -0,0 +1,57 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { NIBittensorChatModel, BittensorInput } from 'langchain/experimental/chat_models/bittensor'
import { BaseCache } from 'langchain/schema'
class Bittensor_ChatModels implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
inputs: INodeParams[]
constructor() {
this.label = 'NIBittensorChat'
this.name = 'NIBittensorChatModel'
this.version = 2.0
this.type = 'BittensorChat'
this.icon = 'logo.png'
this.category = 'Chat Models'
this.description = 'Wrapper around Bittensor subnet 1 large language models'
this.baseClasses = [this.type, ...getBaseClasses(NIBittensorChatModel)]
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'System prompt',
name: 'system_prompt',
type: 'string',
additionalParams: true,
optional: true
}
]
}
async init(nodeData: INodeData, _: string): Promise<any> {
const system_prompt = nodeData.inputs?.system_prompt as string
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<BittensorInput> = {
systemPrompt: system_prompt
}
if (cache) obj.cache = cache
const model = new NIBittensorChatModel(obj)
return model
}
}
module.exports = { nodeClass: Bittensor_ChatModels }

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14
packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts
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@ -1,6 +1,8 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { AnthropicInput, ChatAnthropic } from 'langchain/chat_models/anthropic'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class ChatAnthropic_ChatModels implements INode {
label: string
@ -17,7 +19,7 @@ class ChatAnthropic_ChatModels implements INode {
constructor() {
this.label = 'ChatAnthropic'
this.name = 'chatAnthropic'
this.version = 1.0
this.version = 2.0
this.type = 'ChatAnthropic'
this.icon = 'chatAnthropic.png'
this.category = 'Chat Models'
@ -30,6 +32,12 @@ class ChatAnthropic_ChatModels implements INode {
credentialNames: ['anthropicApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -135,11 +143,12 @@ class ChatAnthropic_ChatModels implements INode {
const topP = nodeData.inputs?.topP as string
const topK = nodeData.inputs?.topK as string
const streaming = nodeData.inputs?.streaming as boolean
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const anthropicApiKey = getCredentialParam('anthropicApiKey', credentialData, nodeData)
const obj: Partial<AnthropicInput> & { anthropicApiKey?: string } = {
const obj: Partial<AnthropicInput> & BaseLLMParams & { anthropicApiKey?: string } = {
temperature: parseFloat(temperature),
modelName,
anthropicApiKey,
@ -149,6 +158,7 @@ class ChatAnthropic_ChatModels implements INode {
if (maxTokensToSample) obj.maxTokensToSample = parseInt(maxTokensToSample, 10)
if (topP) obj.topP = parseFloat(topP)
if (topK) obj.topK = parseFloat(topK)
if (cache) obj.cache = cache
const model = new ChatAnthropic(obj)
return model

11
packages/components/nodes/chatmodels/ChatGooglePaLM/ChatGooglePaLM.ts
View File

@ -1,6 +1,7 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ChatGooglePaLM, GooglePaLMChatInput } from 'langchain/chat_models/googlepalm'
import { BaseCache } from 'langchain/schema'
class ChatGooglePaLM_ChatModels implements INode {
label: string
@ -17,7 +18,7 @@ class ChatGooglePaLM_ChatModels implements INode {
constructor() {
this.label = 'ChatGooglePaLM'
this.name = 'chatGooglePaLM'
this.version = 1.0
this.version = 2.0
this.type = 'ChatGooglePaLM'
this.icon = 'Google_PaLM_Logo.svg'
this.category = 'Chat Models'
@ -30,6 +31,12 @@ class ChatGooglePaLM_ChatModels implements INode {
credentialNames: ['googleMakerSuite']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -96,6 +103,7 @@ class ChatGooglePaLM_ChatModels implements INode {
const temperature = nodeData.inputs?.temperature as string
const topP = nodeData.inputs?.topP as string
const topK = nodeData.inputs?.topK as string
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
@ -108,6 +116,7 @@ class ChatGooglePaLM_ChatModels implements INode {
if (topP) obj.topP = parseFloat(topP)
if (topK) obj.topK = parseFloat(topK)
if (cache) obj.cache = cache
const model = new ChatGooglePaLM(obj)
return model

11
packages/components/nodes/chatmodels/ChatGoogleVertexAI/ChatGoogleVertexAI.ts
View File

@ -2,6 +2,7 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Inter
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ChatGoogleVertexAI, GoogleVertexAIChatInput } from 'langchain/chat_models/googlevertexai'
import { GoogleAuthOptions } from 'google-auth-library'
import { BaseCache } from 'langchain/schema'
class GoogleVertexAI_ChatModels implements INode {
label: string
@ -18,7 +19,7 @@ class GoogleVertexAI_ChatModels implements INode {
constructor() {
this.label = 'ChatGoogleVertexAI'
this.name = 'chatGoogleVertexAI'
this.version = 1.0
this.version = 2.0
this.type = 'ChatGoogleVertexAI'
this.icon = 'vertexai.svg'
this.category = 'Chat Models'
@ -34,6 +35,12 @@ class GoogleVertexAI_ChatModels implements INode {
'Google Vertex AI credential. If you are using a GCP service like Cloud Run, or if you have installed default credentials on your local machine, you do not need to set this credential.'
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -113,6 +120,7 @@ class GoogleVertexAI_ChatModels implements INode {
const modelName = nodeData.inputs?.modelName as string
const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
const topP = nodeData.inputs?.topP as string
const cache = nodeData.inputs?.cache as BaseCache
const obj: GoogleVertexAIChatInput<GoogleAuthOptions> = {
temperature: parseFloat(temperature),
@ -122,6 +130,7 @@ class GoogleVertexAI_ChatModels implements INode {
if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
if (topP) obj.topP = parseFloat(topP)
if (cache) obj.cache = cache
const model = new ChatGoogleVertexAI(obj)
return model

11
packages/components/nodes/chatmodels/ChatHuggingFace/ChatHuggingFace.ts
View File

@ -1,6 +1,7 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { HFInput, HuggingFaceInference } from './core'
import { BaseCache } from 'langchain/schema'
class ChatHuggingFace_ChatModels implements INode {
label: string
@ -17,7 +18,7 @@ class ChatHuggingFace_ChatModels implements INode {
constructor() {
this.label = 'ChatHuggingFace'
this.name = 'chatHuggingFace'
this.version = 1.0
this.version = 2.0
this.type = 'ChatHuggingFace'
this.icon = 'huggingface.png'
this.category = 'Chat Models'
@ -30,6 +31,12 @@ class ChatHuggingFace_ChatModels implements INode {
credentialNames: ['huggingFaceApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model',
name: 'model',
@ -102,6 +109,7 @@ class ChatHuggingFace_ChatModels implements INode {
const hfTopK = nodeData.inputs?.hfTopK as string
const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
const endpoint = nodeData.inputs?.endpoint as string
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
@ -119,6 +127,7 @@ class ChatHuggingFace_ChatModels implements INode {
if (endpoint) obj.endpoint = endpoint
const huggingFace = new HuggingFaceInference(obj)
if (cache) huggingFace.cache = cache
return huggingFace
}
}

14
packages/components/nodes/chatmodels/ChatLocalAI/ChatLocalAI.ts
View File

@ -2,6 +2,8 @@ import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { OpenAIChat } from 'langchain/llms/openai'
import { OpenAIChatInput } from 'langchain/chat_models/openai'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class ChatLocalAI_ChatModels implements INode {
label: string
@ -17,13 +19,19 @@ class ChatLocalAI_ChatModels implements INode {
constructor() {
this.label = 'ChatLocalAI'
this.name = 'chatLocalAI'
this.version = 1.0
this.version = 2.0
this.type = 'ChatLocalAI'
this.icon = 'localai.png'
this.category = 'Chat Models'
this.description = 'Use local LLMs like llama.cpp, gpt4all using LocalAI'
this.baseClasses = [this.type, 'BaseChatModel', ...getBaseClasses(OpenAIChat)]
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Base Path',
name: 'basePath',
@ -78,8 +86,9 @@ class ChatLocalAI_ChatModels implements INode {
const topP = nodeData.inputs?.topP as string
const timeout = nodeData.inputs?.timeout as string
const basePath = nodeData.inputs?.basePath as string
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<OpenAIChatInput> & { openAIApiKey?: string } = {
const obj: Partial<OpenAIChatInput> & BaseLLMParams & { openAIApiKey?: string } = {
temperature: parseFloat(temperature),
modelName,
openAIApiKey: 'sk-'
@ -88,6 +97,7 @@ class ChatLocalAI_ChatModels implements INode {
if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
if (topP) obj.topP = parseFloat(topP)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (cache) obj.cache = cache
const model = new OpenAIChat(obj, { basePath })

15
packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts
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@ -1,6 +1,8 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ChatOpenAI, OpenAIChatInput } from 'langchain/chat_models/openai'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class ChatOpenAI_ChatModels implements INode {
label: string
@ -17,7 +19,7 @@ class ChatOpenAI_ChatModels implements INode {
constructor() {
this.label = 'ChatOpenAI'
this.name = 'chatOpenAI'
this.version = 1.0
this.version = 2.0
this.type = 'ChatOpenAI'
this.icon = 'openai.png'
this.category = 'Chat Models'
@ -30,6 +32,12 @@ class ChatOpenAI_ChatModels implements INode {
credentialNames: ['openAIApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -151,7 +159,9 @@ class ChatOpenAI_ChatModels implements INode {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
const obj: Partial<OpenAIChatInput> & { openAIApiKey?: string } = {
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<OpenAIChatInput> & BaseLLMParams & { openAIApiKey?: string } = {
temperature: parseFloat(temperature),
modelName,
openAIApiKey,
@ -163,6 +173,7 @@ class ChatOpenAI_ChatModels implements INode {
if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (cache) obj.cache = cache
let parsedBaseOptions: any | undefined = undefined

14
packages/components/nodes/chatmodels/ChatOpenAICustom/ChatOpenAICustom.ts
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@ -1,6 +1,8 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ChatOpenAI, OpenAIChatInput } from 'langchain/chat_models/openai'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class ChatOpenAICustom_ChatModels implements INode {
label: string
@ -17,7 +19,7 @@ class ChatOpenAICustom_ChatModels implements INode {
constructor() {
this.label = 'ChatOpenAI Custom'
this.name = 'chatOpenAICustom'
this.version = 1.0
this.version = 2.0
this.type = 'ChatOpenAI-Custom'
this.icon = 'openai.png'
this.category = 'Chat Models'
@ -31,6 +33,12 @@ class ChatOpenAICustom_ChatModels implements INode {
optional: true
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -113,11 +121,12 @@ class ChatOpenAICustom_ChatModels implements INode {
const streaming = nodeData.inputs?.streaming as boolean
const basePath = nodeData.inputs?.basepath as string
const baseOptions = nodeData.inputs?.baseOptions
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
const obj: Partial<OpenAIChatInput> & { openAIApiKey?: string } = {
const obj: Partial<OpenAIChatInput> & BaseLLMParams & { openAIApiKey?: string } = {
temperature: parseFloat(temperature),
modelName,
openAIApiKey,
@ -129,6 +138,7 @@ class ChatOpenAICustom_ChatModels implements INode {
if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (cache) obj.cache = cache
let parsedBaseOptions: any | undefined = undefined

112
packages/components/nodes/documentloaders/PlainText/PlainText.ts Normal file
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@ -0,0 +1,112 @@
import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
import { TextSplitter } from 'langchain/text_splitter'
import { Document } from 'langchain/document'
import { handleEscapeCharacters } from '../../../src'
class PlainText_DocumentLoaders implements INode {
label: string
name: string
version: number
description: string
type: string
icon: string
category: string
baseClasses: string[]
inputs: INodeParams[]
outputs: INodeOutputsValue[]
constructor() {
this.label = 'Plain Text'
this.name = 'plainText'
this.version = 2.0
this.type = 'Document'
this.icon = 'plaintext.svg'
this.category = 'Document Loaders'
this.description = `Load data from plain text`
this.baseClasses = [this.type]
this.inputs = [
{
label: 'Text',
name: 'text',
type: 'string',
rows: 4,
placeholder:
'Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua...'
},
{
label: 'Text Splitter',
name: 'textSplitter',
type: 'TextSplitter',
optional: true
},
{
label: 'Metadata',
name: 'metadata',
type: 'json',
optional: true,
additionalParams: true
}
]
this.outputs = [
{
label: 'Document',
name: 'document',
baseClasses: this.baseClasses
},
{
label: 'Text',
name: 'text',
baseClasses: ['string', 'json']
}
]
}
async init(nodeData: INodeData): Promise<any> {
const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
const text = nodeData.inputs?.text as string
const metadata = nodeData.inputs?.metadata
const output = nodeData.outputs?.output as string
let alldocs: Document<Record<string, any>>[] = []
if (textSplitter) {
const docs = await textSplitter.createDocuments([text])
alldocs.push(...docs)
} else {
alldocs.push(
new Document({
pageContent: text
})
)
}
let finaldocs: Document<Record<string, any>>[] = []
if (metadata) {
const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
for (const doc of alldocs) {
const newdoc = {
...doc,
metadata: {
...doc.metadata,
...parsedMetadata
}
}
finaldocs.push(newdoc)
}
} else {
finaldocs = alldocs
}
if (output === 'document') {
return finaldocs
} else {
let finaltext = ''
for (const doc of finaldocs) {
finaltext += `${doc.pageContent}\n`
}
return handleEscapeCharacters(finaltext, false)
}
}
}
module.exports = { nodeClass: PlainText_DocumentLoaders }

7
packages/components/nodes/documentloaders/PlainText/plaintext.svg Normal file
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@ -0,0 +1,7 @@
<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-highlight" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
<path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
<path d="M3 19h4l10.5 -10.5a2.828 2.828 0 1 0 -4 -4l-10.5 10.5v4"></path>
<path d="M12.5 5.5l4 4"></path>
<path d="M4.5 13.5l4 4"></path>
<path d="M21 15v4h-8l4 -4z"></path>
</svg>
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36
packages/components/nodes/documentloaders/Text/Text.ts
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@ -1,6 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
import { TextSplitter } from 'langchain/text_splitter'
import { TextLoader } from 'langchain/document_loaders/fs/text'
import { Document } from 'langchain/document'
import { handleEscapeCharacters } from '../../../src'
class Text_DocumentLoaders implements INode {
label: string
@ -12,11 +14,12 @@ class Text_DocumentLoaders implements INode {
category: string
baseClasses: string[]
inputs: INodeParams[]
outputs: INodeOutputsValue[]
constructor() {
this.label = 'Text File'
this.name = 'textFile'
this.version = 1.0
this.version = 2.0
this.type = 'Document'
this.icon = 'textFile.svg'
this.category = 'Document Loaders'
@ -43,12 +46,25 @@ class Text_DocumentLoaders implements INode {
additionalParams: true
}
]
this.outputs = [
{
label: 'Document',
name: 'document',
baseClasses: this.baseClasses
},
{
label: 'Text',
name: 'text',
baseClasses: ['string', 'json']
}
]
}
async init(nodeData: INodeData): Promise<any> {
const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
const txtFileBase64 = nodeData.inputs?.txtFile as string
const metadata = nodeData.inputs?.metadata
const output = nodeData.outputs?.output as string
let alldocs = []
let files: string[] = []
@ -75,9 +91,9 @@ class Text_DocumentLoaders implements INode {
}
}
let finaldocs: Document<Record<string, any>>[] = []
if (metadata) {
const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
let finaldocs = []
for (const doc of alldocs) {
const newdoc = {
...doc,
@ -88,9 +104,19 @@ class Text_DocumentLoaders implements INode {
}
finaldocs.push(newdoc)
}
return finaldocs
} else {
finaldocs = alldocs
}
if (output === 'document') {
return finaldocs
} else {
let finaltext = ''
for (const doc of finaldocs) {
finaltext += `${doc.pageContent}\n`
}
return handleEscapeCharacters(finaltext, false)
}
return alldocs
}
}

175
packages/components/nodes/llms/AWSBedrock/AWSBedrock.ts Normal file
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@ -0,0 +1,175 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { Bedrock } from 'langchain/llms/bedrock'
import { BaseBedrockInput } from 'langchain/dist/util/bedrock'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
/**
* I had to run the following to build the component
* and get the icon copied over to the dist directory
* Flowise/packages/components > yarn build
*
* @author Michael Connor <mlconnor@yahoo.com>
*/
class AWSBedrock_LLMs implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
credential: INodeParams
inputs: INodeParams[]
constructor() {
this.label = 'AWS Bedrock'
this.name = 'awsBedrock'
this.version = 1.2
this.type = 'AWSBedrock'
this.icon = 'awsBedrock.png'
this.category = 'LLMs'
this.description = 'Wrapper around AWS Bedrock large language models'
this.baseClasses = [this.type, ...getBaseClasses(Bedrock)]
this.credential = {
label: 'AWS Credential',
name: 'credential',
type: 'credential',
credentialNames: ['awsApi'],
optional: true
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Region',
name: 'region',
type: 'options',
options: [
{ label: 'af-south-1', name: 'af-south-1' },
{ label: 'ap-east-1', name: 'ap-east-1' },
{ label: 'ap-northeast-1', name: 'ap-northeast-1' },
{ label: 'ap-northeast-2', name: 'ap-northeast-2' },
{ label: 'ap-northeast-3', name: 'ap-northeast-3' },
{ label: 'ap-south-1', name: 'ap-south-1' },
{ label: 'ap-south-2', name: 'ap-south-2' },
{ label: 'ap-southeast-1', name: 'ap-southeast-1' },
{ label: 'ap-southeast-2', name: 'ap-southeast-2' },
{ label: 'ap-southeast-3', name: 'ap-southeast-3' },
{ label: 'ap-southeast-4', name: 'ap-southeast-4' },
{ label: 'ap-southeast-5', name: 'ap-southeast-5' },
{ label: 'ap-southeast-6', name: 'ap-southeast-6' },
{ label: 'ca-central-1', name: 'ca-central-1' },
{ label: 'ca-west-1', name: 'ca-west-1' },
{ label: 'cn-north-1', name: 'cn-north-1' },
{ label: 'cn-northwest-1', name: 'cn-northwest-1' },
{ label: 'eu-central-1', name: 'eu-central-1' },
{ label: 'eu-central-2', name: 'eu-central-2' },
{ label: 'eu-north-1', name: 'eu-north-1' },
{ label: 'eu-south-1', name: 'eu-south-1' },
{ label: 'eu-south-2', name: 'eu-south-2' },
{ label: 'eu-west-1', name: 'eu-west-1' },
{ label: 'eu-west-2', name: 'eu-west-2' },
{ label: 'eu-west-3', name: 'eu-west-3' },
{ label: 'il-central-1', name: 'il-central-1' },
{ label: 'me-central-1', name: 'me-central-1' },
{ label: 'me-south-1', name: 'me-south-1' },
{ label: 'sa-east-1', name: 'sa-east-1' },
{ label: 'us-east-1', name: 'us-east-1' },
{ label: 'us-east-2', name: 'us-east-2' },
{ label: 'us-gov-east-1', name: 'us-gov-east-1' },
{ label: 'us-gov-west-1', name: 'us-gov-west-1' },
{ label: 'us-west-1', name: 'us-west-1' },
{ label: 'us-west-2', name: 'us-west-2' }
],
default: 'us-east-1',
optional: false
},
{
label: 'Model Name',
name: 'model',
type: 'options',
options: [
{ label: 'amazon.titan-tg1-large', name: 'amazon.titan-tg1-large' },
{ label: 'amazon.titan-e1t-medium', name: 'amazon.titan-e1t-medium' },
{ label: 'stability.stable-diffusion-xl', name: 'stability.stable-diffusion-xl' },
{ label: 'ai21.j2-grande-instruct', name: 'ai21.j2-grande-instruct' },
{ label: 'ai21.j2-jumbo-instruct', name: 'ai21.j2-jumbo-instruct' },
{ label: 'ai21.j2-mid', name: 'ai21.j2-mid' },
{ label: 'ai21.j2-ultra', name: 'ai21.j2-ultra' },
{ label: 'anthropic.claude-instant-v1', name: 'anthropic.claude-instant-v1' },
{ label: 'anthropic.claude-v1', name: 'anthropic.claude-v1' },
{ label: 'anthropic.claude-v2', name: 'anthropic.claude-v2' }
],
default: 'anthropic.claude-v2',
optional: false
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
description: 'Temperature parameter may not apply to certain model. Please check available model parameters',
optional: true,
default: 0.7,
additionalParams: false
},
{
label: 'Max Tokens to Sample',
name: 'max_tokens_to_sample',
type: 'number',
step: 10,
description: 'Max Tokens parameter may not apply to certain model. Please check available model parameters',
optional: false,
default: 200,
additionalParams: false
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const iRegion = nodeData.inputs?.region as string
const iModel = nodeData.inputs?.model as string
const iTemperature = nodeData.inputs?.temperature as string
const iMax_tokens_to_sample = nodeData.inputs?.max_tokens_to_sample as string
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<BaseBedrockInput> & BaseLLMParams = {
model: iModel,
region: iRegion,
temperature: parseFloat(iTemperature),
maxTokens: parseInt(iMax_tokens_to_sample, 10)
}
/**
* Long-term credentials specified in LLM configuration are optional.
* Bedrock's credential provider falls back to the AWS SDK to fetch
* credentials from the running environment.
* When specified, we override the default provider with configured values.
* @see https://github.com/aws/aws-sdk-js-v3/blob/main/packages/credential-provider-node/README.md
*/
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
if (credentialData && Object.keys(credentialData).length !== 0) {
const credentialApiKey = getCredentialParam('awsKey', credentialData, nodeData)
const credentialApiSecret = getCredentialParam('awsSecret', credentialData, nodeData)
const credentialApiSession = getCredentialParam('awsSession', credentialData, nodeData)
obj.credentials = {
accessKeyId: credentialApiKey,
secretAccessKey: credentialApiSecret,
sessionToken: credentialApiSession
}
}
if (cache) obj.cache = cache
const amazonBedrock = new Bedrock(obj)
return amazonBedrock
}
}
module.exports = { nodeClass: AWSBedrock_LLMs }

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16
packages/components/nodes/llms/Azure OpenAI/AzureOpenAI.ts
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@ -1,7 +1,8 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { AzureOpenAIInput, OpenAI, OpenAIInput } from 'langchain/llms/openai'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class AzureOpenAI_LLMs implements INode {
label: string
name: string
@ -17,7 +18,7 @@ class AzureOpenAI_LLMs implements INode {
constructor() {
this.label = 'Azure OpenAI'
this.name = 'azureOpenAI'
this.version = 1.0
this.version = 2.0
this.type = 'AzureOpenAI'
this.icon = 'Azure.svg'
this.category = 'LLMs'
@ -30,6 +31,12 @@ class AzureOpenAI_LLMs implements INode {
credentialNames: ['azureOpenAIApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -163,7 +170,9 @@ class AzureOpenAI_LLMs implements INode {
const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
const obj: Partial<AzureOpenAIInput> & Partial<OpenAIInput> = {
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<AzureOpenAIInput> & BaseLLMParams & Partial<OpenAIInput> = {
temperature: parseFloat(temperature),
modelName,
azureOpenAIApiKey,
@ -179,6 +188,7 @@ class AzureOpenAI_LLMs implements INode {
if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (bestOf) obj.bestOf = parseInt(bestOf, 10)
if (cache) obj.cache = cache
const model = new OpenAI(obj)
return model

68
packages/components/nodes/llms/Bittensor/Bittensor.ts Normal file
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@ -0,0 +1,68 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { NIBittensorLLM, BittensorInput } from 'langchain/experimental/llms/bittensor'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class Bittensor_LLMs implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
inputs: INodeParams[]
constructor() {
this.label = 'NIBittensorLLM'
this.name = 'NIBittensorLLM'
this.version = 2.0
this.type = 'Bittensor'
this.icon = 'logo.png'
this.category = 'LLMs'
this.description = 'Wrapper around Bittensor subnet 1 large language models'
this.baseClasses = [this.type, ...getBaseClasses(NIBittensorLLM)]
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'System prompt',
name: 'system_prompt',
type: 'string',
additionalParams: true,
optional: true
},
{
label: 'Top Responses',
name: 'topResponses',
type: 'number',
step: 1,
optional: true,
additionalParams: true
}
]
}
async init(nodeData: INodeData, _: string): Promise<any> {
const system_prompt = nodeData.inputs?.system_prompt as string
const topResponses = Number(nodeData.inputs?.topResponses as number)
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<BittensorInput> & BaseLLMParams = {
systemPrompt: system_prompt,
topResponses: topResponses
}
if (cache) obj.cache = cache
const model = new NIBittensorLLM(obj)
return model
}
}
module.exports = { nodeClass: Bittensor_LLMs }

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13
packages/components/nodes/llms/Cohere/Cohere.ts
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@ -1,6 +1,7 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { Cohere, CohereInput } from './core'
import { BaseCache } from 'langchain/schema'
class Cohere_LLMs implements INode {
label: string
@ -17,7 +18,7 @@ class Cohere_LLMs implements INode {
constructor() {
this.label = 'Cohere'
this.name = 'cohere'
this.version = 1.0
this.version = 2.0
this.type = 'Cohere'
this.icon = 'cohere.png'
this.category = 'LLMs'
@ -30,6 +31,12 @@ class Cohere_LLMs implements INode {
credentialNames: ['cohereApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -85,7 +92,7 @@ class Cohere_LLMs implements INode {
const temperature = nodeData.inputs?.temperature as string
const modelName = nodeData.inputs?.modelName as string
const maxTokens = nodeData.inputs?.maxTokens as string
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const cohereApiKey = getCredentialParam('cohereApiKey', credentialData, nodeData)
@ -96,7 +103,7 @@ class Cohere_LLMs implements INode {
if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
if (modelName) obj.model = modelName
if (temperature) obj.temperature = parseFloat(temperature)
if (cache) obj.cache = cache
const model = new Cohere(obj)
return model
}

12
packages/components/nodes/llms/GooglePaLM/GooglePaLM.ts
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@ -1,7 +1,7 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { GooglePaLM, GooglePaLMTextInput } from 'langchain/llms/googlepalm'
import { BaseCache } from 'langchain/schema'
class GooglePaLM_LLMs implements INode {
label: string
name: string
@ -17,7 +17,7 @@ class GooglePaLM_LLMs implements INode {
constructor() {
this.label = 'GooglePaLM'
this.name = 'GooglePaLM'
this.version = 1.0
this.version = 2.0
this.type = 'GooglePaLM'
this.icon = 'Google_PaLM_Logo.svg'
this.category = 'LLMs'
@ -30,6 +30,12 @@ class GooglePaLM_LLMs implements INode {
credentialNames: ['googleMakerSuite']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -126,6 +132,7 @@ class GooglePaLM_LLMs implements INode {
const topP = nodeData.inputs?.topP as string
const topK = nodeData.inputs?.topK as string
const stopSequencesObj = nodeData.inputs?.stopSequencesObj
const cache = nodeData.inputs?.cache as BaseCache
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
@ -139,6 +146,7 @@ class GooglePaLM_LLMs implements INode {
if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
if (topP) obj.topP = parseFloat(topP)
if (topK) obj.topK = parseFloat(topK)
if (cache) obj.cache = cache
let parsedStopSequences: any | undefined = undefined
if (stopSequencesObj) {

11
packages/components/nodes/llms/GoogleVertexAI/GoogleVertexAI.ts
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@ -2,6 +2,7 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Inter
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { GoogleVertexAI, GoogleVertexAITextInput } from 'langchain/llms/googlevertexai'
import { GoogleAuthOptions } from 'google-auth-library'
import { BaseCache } from 'langchain/schema'
class GoogleVertexAI_LLMs implements INode {
label: string
@ -18,7 +19,7 @@ class GoogleVertexAI_LLMs implements INode {
constructor() {
this.label = 'GoogleVertexAI'
this.name = 'googlevertexai'
this.version = 1.0
this.version = 2.0
this.type = 'GoogleVertexAI'
this.icon = 'vertexai.svg'
this.category = 'LLMs'
@ -34,6 +35,12 @@ class GoogleVertexAI_LLMs implements INode {
'Google Vertex AI credential. If you are using a GCP service like Cloud Run, or if you have installed default credentials on your local machine, you do not need to set this credential.'
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -120,6 +127,7 @@ class GoogleVertexAI_LLMs implements INode {
const modelName = nodeData.inputs?.modelName as string
const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
const topP = nodeData.inputs?.topP as string
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<GoogleVertexAITextInput> = {
temperature: parseFloat(temperature),
@ -129,6 +137,7 @@ class GoogleVertexAI_LLMs implements INode {
if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
if (topP) obj.topP = parseFloat(topP)
if (cache) obj.cache = cache
const model = new GoogleVertexAI(obj)
return model

13
packages/components/nodes/llms/HuggingFaceInference/HuggingFaceInference.ts
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@ -1,6 +1,7 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { HFInput, HuggingFaceInference } from './core'
import { BaseCache } from 'langchain/schema'
class HuggingFaceInference_LLMs implements INode {
label: string
@ -17,7 +18,7 @@ class HuggingFaceInference_LLMs implements INode {
constructor() {
this.label = 'HuggingFace Inference'
this.name = 'huggingFaceInference_LLMs'
this.version = 1.0
this.version = 2.0
this.type = 'HuggingFaceInference'
this.icon = 'huggingface.png'
this.category = 'LLMs'
@ -30,6 +31,12 @@ class HuggingFaceInference_LLMs implements INode {
credentialNames: ['huggingFaceApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model',
name: 'model',
@ -106,6 +113,8 @@ class HuggingFaceInference_LLMs implements INode {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<HFInput> = {
model,
apiKey: huggingFaceApiKey
@ -119,6 +128,8 @@ class HuggingFaceInference_LLMs implements INode {
if (endpoint) obj.endpoint = endpoint
const huggingFace = new HuggingFaceInference(obj)
if (cache) huggingFace.cache = cache
return huggingFace
}
}

17
packages/components/nodes/llms/OpenAI/OpenAI.ts
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@ -1,6 +1,8 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { OpenAI, OpenAIInput } from 'langchain/llms/openai'
import { BaseLLMParams } from 'langchain/llms/base'
import { BaseCache } from 'langchain/schema'
class OpenAI_LLMs implements INode {
label: string
@ -17,7 +19,7 @@ class OpenAI_LLMs implements INode {
constructor() {
this.label = 'OpenAI'
this.name = 'openAI'
this.version = 2.0
this.version = 3.0
this.type = 'OpenAI'
this.icon = 'openai.png'
this.category = 'LLMs'
@ -30,6 +32,12 @@ class OpenAI_LLMs implements INode {
credentialNames: ['openAIApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
@ -149,7 +157,9 @@ class OpenAI_LLMs implements INode {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
const obj: Partial<OpenAIInput> & { openAIApiKey?: string } = {
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<OpenAIInput> & BaseLLMParams & { openAIApiKey?: string } = {
temperature: parseFloat(temperature),
modelName,
openAIApiKey,
@ -164,8 +174,9 @@ class OpenAI_LLMs implements INode {
if (batchSize) obj.batchSize = parseInt(batchSize, 10)
if (bestOf) obj.bestOf = parseInt(bestOf, 10)
let parsedBaseOptions: any | undefined = undefined
if (cache) obj.cache = cache
let parsedBaseOptions: any | undefined = undefined
if (baseOptions) {
try {
parsedBaseOptions = typeof baseOptions === 'object' ? baseOptions : JSON.parse(baseOptions)

16
packages/components/nodes/llms/Replicate/Replicate.ts
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@ -1,6 +1,8 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { Replicate, ReplicateInput } from 'langchain/llms/replicate'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class Replicate_LLMs implements INode {
label: string
@ -17,7 +19,7 @@ class Replicate_LLMs implements INode {
constructor() {
this.label = 'Replicate'
this.name = 'replicate'
this.version = 1.0
this.version = 2.0
this.type = 'Replicate'
this.icon = 'replicate.svg'
this.category = 'LLMs'
@ -30,6 +32,12 @@ class Replicate_LLMs implements INode {
credentialNames: ['replicateApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model',
name: 'model',
@ -103,7 +111,9 @@ class Replicate_LLMs implements INode {
const name = modelName.split(':')[0].split('/').pop()
const org = modelName.split(':')[0].split('/')[0]
const obj: ReplicateInput = {
const cache = nodeData.inputs?.cache as BaseCache
const obj: ReplicateInput & BaseLLMParams = {
model: `${org}/${name}:${version}`,
apiKey
}
@ -120,6 +130,8 @@ class Replicate_LLMs implements INode {
}
if (Object.keys(inputs).length) obj.input = inputs
if (cache) obj.cache = cache
const model = new Replicate(obj)
return model
}

118
packages/components/nodes/memory/UpstashRedisBackedChatMemory/UpstashRedisBackedChatMemory.ts Normal file
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@ -0,0 +1,118 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ICommonObject } from '../../../src'
import { BufferMemory, BufferMemoryInput } from 'langchain/memory'
import { UpstashRedisChatMessageHistory } from 'langchain/stores/message/upstash_redis'
class UpstashRedisBackedChatMemory_Memory implements INode {
label: string
name: string
version: number
description: string
type: string
icon: string
category: string
baseClasses: string[]
credential: INodeParams
inputs: INodeParams[]
constructor() {
this.label = 'Upstash Redis-Backed Chat Memory'
this.name = 'upstashRedisBackedChatMemory'
this.version = 1.0
this.type = 'UpstashRedisBackedChatMemory'
this.icon = 'upstash.svg'
this.category = 'Memory'
this.description = 'Summarizes the conversation and stores the memory in Upstash Redis server'
this.baseClasses = [this.type, ...getBaseClasses(BufferMemory)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
description: 'Configure password authentication on your upstash redis instance',
credentialNames: ['upstashRedisMemoryApi']
}
this.inputs = [
{
label: 'Upstash Redis REST URL',
name: 'baseURL',
type: 'string',
placeholder: 'https://<your-url>.upstash.io'
},
{
label: 'Session Id',
name: 'sessionId',
type: 'string',
description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId',
default: '',
additionalParams: true,
optional: true
},
{
label: 'Session Timeouts',
name: 'sessionTTL',
type: 'number',
description: 'Omit this parameter to make sessions never expire',
additionalParams: true,
optional: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
return initalizeUpstashRedis(nodeData, options)
}
async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise<void> {
const redis = await initalizeUpstashRedis(nodeData, options)
const sessionId = nodeData.inputs?.sessionId as string
const chatId = options?.chatId as string
options.logger.info(`Clearing Upstash Redis memory session ${sessionId ? sessionId : chatId}`)
await redis.clear()
options.logger.info(`Successfully cleared Upstash Redis memory session ${sessionId ? sessionId : chatId}`)
}
}
const initalizeUpstashRedis = async (nodeData: INodeData, options: ICommonObject): Promise<BufferMemory> => {
const baseURL = nodeData.inputs?.baseURL as string
const sessionId = nodeData.inputs?.sessionId as string
const sessionTTL = nodeData.inputs?.sessionTTL as string
const chatId = options?.chatId as string
let isSessionIdUsingChatMessageId = false
if (!sessionId && chatId) isSessionIdUsingChatMessageId = true
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const upstashRestToken = getCredentialParam('upstashRestToken', credentialData, nodeData)
const redisChatMessageHistory = new UpstashRedisChatMessageHistory({
sessionId: sessionId ? sessionId : chatId,
sessionTTL: sessionTTL ? parseInt(sessionTTL, 10) : undefined,
config: {
url: baseURL,
token: upstashRestToken
}
})
const memory = new BufferMemoryExtended({
chatHistory: redisChatMessageHistory,
isSessionIdUsingChatMessageId
})
return memory
}
interface BufferMemoryExtendedInput {
isSessionIdUsingChatMessageId: boolean
}
class BufferMemoryExtended extends BufferMemory {
isSessionIdUsingChatMessageId? = false
constructor(fields: BufferMemoryInput & Partial<BufferMemoryExtendedInput>) {
super(fields)
this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId
}
}
module.exports = { nodeClass: UpstashRedisBackedChatMemory_Memory }

12
packages/components/nodes/memory/UpstashRedisBackedChatMemory/upstash.svg Normal file
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@ -0,0 +1,12 @@
<?xml version="1.0" encoding="UTF-8"?>
<svg width="256px" height="341px" viewBox="0 0 256 341" version="1.1" xmlns="http://www.w3.org/2000/svg" preserveAspectRatio="xMidYMid">
<title>upstash</title>
<g>
<path d="M0,298.416784 C56.5542815,354.970323 148.246768,354.970323 204.801032,298.416784 C261.354571,241.86252 261.354571,150.170106 204.801032,93.6158424 L179.200462,119.215688 C221.61634,161.631567 221.61634,230.401059 179.200462,272.816213 C136.785307,315.232092 68.0157428,315.232092 25.5998642,272.816213 L0,298.416784 Z" fill="#00C98D"></path>
<path d="M51.200362,247.216367 C79.4772765,275.493137 125.323122,275.493137 153.600615,247.216367 C181.877385,218.939598 181.877385,173.093028 153.600615,144.816259 L128.000769,170.416105 C142.139154,184.55449 142.139154,207.477412 128.000769,221.616521 C113.86166,235.754906 90.9387378,235.754906 76.800353,221.616521 L51.200362,247.216367 Z" fill="#00C98D"></path>
<path d="M256,42.415426 C199.445737,-14.1384753 107.753322,-14.1384753 51.1994207,42.415426 C-5.35485714,98.9696894 -5.35485714,190.662104 51.1994207,247.216367 L76.7989048,221.616521 C34.3841124,179.200643 34.3841124,110.431151 76.7989048,68.0159962 C119.214783,25.6001177 187.984275,25.6001177 230.39943,68.0159962 L256,42.415426 Z" fill="#00C98D"></path>
<path d="M204.800308,93.6158424 C176.523538,65.3390727 130.676245,65.3390727 102.399475,93.6158424 C74.1219813,121.893336 74.1219813,167.739181 102.399475,196.015951 L127.999321,170.416105 C113.860936,156.27772 113.860936,133.354797 127.999321,119.215688 C142.137706,105.077304 165.060629,105.077304 179.199738,119.215688 L204.800308,93.6158424 Z" fill="#00C98D"></path>
<path d="M256,42.415426 C199.445737,-14.1384753 107.753322,-14.1384753 51.1994207,42.415426 C-5.35485714,98.9696894 -5.35485714,190.662104 51.1994207,247.216367 L76.7989048,221.616521 C34.3841124,179.200643 34.3841124,110.431151 76.7989048,68.0159962 C119.214783,25.6001177 187.984275,25.6001177 230.39943,68.0159962 L256,42.415426 Z" fill-opacity="0.4" fill="#FFFFFF"></path>
<path d="M204.800308,93.6158424 C176.523538,65.3390727 130.676245,65.3390727 102.399475,93.6158424 C74.1219813,121.893336 74.1219813,167.739181 102.399475,196.015951 L127.999321,170.416105 C113.860936,156.27772 113.860936,133.354797 127.999321,119.215688 C142.137706,105.077304 165.060629,105.077304 179.199738,119.215688 L204.800308,93.6158424 Z" fill-opacity="0.4" fill="#FFFFFF"></path>
</g>
</svg>
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107
packages/components/nodes/retrievers/SimilarityThresholdRetriever/SimilarityThresholdRetriever.ts Normal file
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@ -0,0 +1,107 @@
import { VectorStore } from 'langchain/vectorstores/base'
import { INode, INodeData, INodeParams, INodeOutputsValue } from '../../../src/Interface'
import { handleEscapeCharacters } from '../../../src'
import { ScoreThresholdRetriever } from 'langchain/retrievers/score_threshold'
class SimilarityThresholdRetriever_Retrievers implements INode {
label: string
name: string
version: number
description: string
type: string
icon: string
category: string
baseClasses: string[]
inputs: INodeParams[]
outputs: INodeOutputsValue[]
constructor() {
this.label = 'Similarity Score Threshold Retriever'
this.name = 'similarityThresholdRetriever'
this.version = 1.0
this.type = 'SimilarityThresholdRetriever'
this.icon = 'similaritythreshold.svg'
this.category = 'Retrievers'
this.description = 'Return results based on the minimum similarity percentage'
this.baseClasses = [this.type, 'BaseRetriever']
this.inputs = [
{
label: 'Vector Store',
name: 'vectorStore',
type: 'VectorStore'
},
{
label: 'Minimum Similarity Score (%)',
name: 'minSimilarityScore',
description: 'Finds results with at least this similarity score',
type: 'number',
default: 80,
step: 1
},
{
label: 'Max K',
name: 'maxK',
description: `The maximum number of results to fetch`,
type: 'number',
default: 20,
step: 1
},
{
label: 'K Increment',
name: 'kIncrement',
description: `How much to increase K by each time. It'll fetch N results, then N + kIncrement, then N + kIncrement * 2, etc.`,
type: 'number',
default: 2,
step: 1
}
]
this.outputs = [
{
label: 'Similarity Threshold Retriever',
name: 'retriever',
baseClasses: this.baseClasses
},
{
label: 'Document',
name: 'document',
baseClasses: ['Document']
},
{
label: 'Text',
name: 'text',
baseClasses: ['string', 'json']
}
]
}
async init(nodeData: INodeData, input: string): Promise<any> {
const vectorStore = nodeData.inputs?.vectorStore as VectorStore
const minSimilarityScore = nodeData.inputs?.minSimilarityScore as number
const maxK = nodeData.inputs?.maxK as string
const kIncrement = nodeData.inputs?.kIncrement as string
const output = nodeData.outputs?.output as string
const retriever = ScoreThresholdRetriever.fromVectorStore(vectorStore, {
minSimilarityScore: minSimilarityScore ? minSimilarityScore / 100 : 0.9,
maxK: maxK ? parseInt(maxK, 10) : 100,
kIncrement: kIncrement ? parseInt(kIncrement, 10) : 2
})
if (output === 'retriever') return retriever
else if (output === 'document') return await retriever.getRelevantDocuments(input)
else if (output === 'text') {
let finaltext = ''
const docs = await retriever.getRelevantDocuments(input)
for (const doc of docs) finaltext += `${doc.pageContent}\n`
return handleEscapeCharacters(finaltext, false)
}
return retriever
}
}
module.exports = { nodeClass: SimilarityThresholdRetriever_Retrievers }

5
packages/components/nodes/retrievers/SimilarityThresholdRetriever/similaritythreshold.svg Normal file
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@ -0,0 +1,5 @@
<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-chart-line" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
<path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
<path d="M4 19l16 0"></path>
<path d="M4 15l4 -6l4 2l4 -5l4 4"></path>
</svg>
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2
packages/components/nodes/vectorstores/Chroma/core.ts
View File

@ -30,7 +30,7 @@ export class ChromaExtended extends Chroma {
if (this.chromaApiKey) {
obj.fetchOptions = {
headers: {
'X-Api-Key': this.chromaApiKey
Authorization: `Bearer ${this.chromaApiKey}`
}
}
}

9
packages/components/package.json
View File

@ -1,6 +1,6 @@
{
"name": "flowise-components",
"version": "1.3.7",
"version": "1.3.8",
"description": "Flowiseai Components",
"main": "dist/src/index",
"types": "dist/src/index.d.ts",
@ -18,8 +18,9 @@
"dependencies": {
"@aws-sdk/client-dynamodb": "^3.360.0",
"@dqbd/tiktoken": "^1.0.7",
"@getzep/zep-js": "^0.6.3",
"@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",
@ -29,6 +30,7 @@
"@supabase/supabase-js": "^2.29.0",
"@types/js-yaml": "^4.0.5",
"@types/jsdom": "^21.1.1",
"@upstash/redis": "^1.22.1",
"@zilliz/milvus2-sdk-node": "^2.2.24",
"apify-client": "^2.7.1",
"axios": "^0.27.2",
@ -43,7 +45,8 @@
"google-auth-library": "^9.0.0",
"graphql": "^16.6.0",
"html-to-text": "^9.0.5",
"langchain": "^0.0.152",
"ioredis": "^5.3.2",
"langchain": "^0.0.157",
"langfuse-langchain": "^1.0.14-alpha.0",
"langsmith": "^0.0.32",
"linkifyjs": "^4.1.1",

29
packages/components/src/handler.ts
View File

@ -151,6 +151,7 @@ export class CustomChainHandler extends BaseCallbackHandler {
socketIOClientId = ''
skipK = 0 // Skip streaming for first K numbers of handleLLMStart
returnSourceDocuments = false
cachedResponse = true
constructor(socketIO: Server, socketIOClientId: string, skipK?: number, returnSourceDocuments?: boolean) {
super()
@ -161,6 +162,7 @@ export class CustomChainHandler extends BaseCallbackHandler {
}
handleLLMStart() {
this.cachedResponse = false
if (this.skipK > 0) this.skipK -= 1
}
@ -178,9 +180,30 @@ export class CustomChainHandler extends BaseCallbackHandler {
this.socketIO.to(this.socketIOClientId).emit('end')
}
handleChainEnd(outputs: ChainValues): void | Promise<void> {
if (this.returnSourceDocuments) {
this.socketIO.to(this.socketIOClientId).emit('sourceDocuments', outputs?.sourceDocuments)
handleChainEnd(outputs: ChainValues, _: string, parentRunId?: string): void | Promise<void> {
/*
Langchain does not call handleLLMStart, handleLLMEnd, handleLLMNewToken when the chain is cached.
Callback Order is "Chain Start -> LLM Start --> LLM Token --> LLM End -> Chain End" for normal responses.
Callback Order is "Chain Start -> Chain End" for cached responses.
*/
if (this.cachedResponse && parentRunId === undefined) {
const cachedValue = outputs.text ?? outputs.response ?? outputs.output ?? outputs.output_text
//split at whitespace, and keep the whitespace. This is to preserve the original formatting.
const result = cachedValue.split(/(\s+)/)
result.forEach((token: string, index: number) => {
if (index === 0) {
this.socketIO.to(this.socketIOClientId).emit('start', token)
}
this.socketIO.to(this.socketIOClientId).emit('token', token)
})
if (this.returnSourceDocuments) {
this.socketIO.to(this.socketIOClientId).emit('sourceDocuments', outputs?.sourceDocuments)
}
this.socketIO.to(this.socketIOClientId).emit('end')
} else {
if (this.returnSourceDocuments) {
this.socketIO.to(this.socketIOClientId).emit('sourceDocuments', outputs?.sourceDocuments)
}
}
}
}

24
packages/server/marketplaces/chatflows/API Agent OpenAI.json
View File

@ -89,7 +89,7 @@
"id": "chatOpenAI_1",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -201,7 +201,15 @@
"id": "chatOpenAI_1-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_1-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -392,7 +400,7 @@
"id": "chatOpenAI_2",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -504,7 +512,15 @@
"id": "chatOpenAI_2-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_2-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,

36
packages/server/marketplaces/chatflows/API Agent.json
View File

@ -397,7 +397,7 @@
"id": "chatOpenAI_2",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -509,7 +509,15 @@
"id": "chatOpenAI_2-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_2-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -551,7 +559,7 @@
"id": "chatOpenAI_1",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -663,7 +671,15 @@
"id": "chatOpenAI_1-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_1-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -705,7 +721,7 @@
"id": "chatOpenAI_3",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -817,7 +833,15 @@
"id": "chatOpenAI_3-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_3-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,

16
packages/server/marketplaces/chatflows/Antonym.json
View File

@ -169,14 +169,14 @@
"id": "chatOpenAI_0",
"position": {
"x": 1226.7977900193628,
"y": 48.01100655894436
"y": -22.01100655894436
},
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -288,7 +288,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -313,7 +321,7 @@
"selected": false,
"positionAbsolute": {
"x": 1226.7977900193628,
"y": 48.01100655894436
"y": -22.01100655894436
},
"dragging": false
},

12
packages/server/marketplaces/chatflows/AutoGPT.json
View File

@ -252,7 +252,7 @@
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -364,7 +364,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,

12
packages/server/marketplaces/chatflows/BabyAGI.json
View File

@ -78,7 +78,7 @@
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -190,7 +190,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,

12
packages/server/marketplaces/chatflows/CSV Agent.json
View File

@ -70,7 +70,7 @@
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -182,7 +182,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,

12
packages/server/marketplaces/chatflows/ChatGPTPlugin.json
View File

@ -215,7 +215,7 @@
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -327,7 +327,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,

16
packages/server/marketplaces/chatflows/Claude LLM.json
View File

@ -141,14 +141,14 @@
"id": "chatAnthropic_0",
"position": {
"x": 800.5525382783799,
"y": -76.7988221837009
"y": -130.7988221837009
},
"type": "customNode",
"data": {
"id": "chatAnthropic_0",
"label": "ChatAnthropic",
"name": "chatAnthropic",
"version": 1,
"version": 2,
"type": "ChatAnthropic",
"baseClasses": ["ChatAnthropic", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -258,7 +258,15 @@
"id": "chatAnthropic_0-input-topK-number"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatAnthropic_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "claude-2",
"temperature": 0.9,
@ -280,7 +288,7 @@
"selected": false,
"positionAbsolute": {
"x": 800.5525382783799,
"y": -76.7988221837009
"y": -130.7988221837009
},
"dragging": false
},

12
packages/server/marketplaces/chatflows/Conversational Agent.json
View File

@ -157,7 +157,7 @@
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@ -269,7 +269,15 @@
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12
packages/server/marketplaces/chatflows/Conversational Retrieval Agent.json
View File

@ -13,7 +13,7 @@
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@ -126,7 +126,15 @@
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16
packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json
View File

@ -7,14 +7,14 @@
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@ -126,7 +126,15 @@
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@ -150,7 +158,7 @@
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12
packages/server/marketplaces/chatflows/Flowise Docs QnA.json
View File

@ -386,7 +386,7 @@
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@ -498,7 +498,15 @@
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16
packages/server/marketplaces/chatflows/HuggingFace LLM Chain.json
View File

@ -148,14 +148,14 @@
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@ -232,7 +232,15 @@
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@ -256,7 +264,7 @@
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16
packages/server/marketplaces/chatflows/Local QnA.json
View File

@ -265,14 +265,14 @@
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@ -325,7 +325,15 @@
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@ -348,7 +356,7 @@
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16
packages/server/marketplaces/chatflows/Long Term Memory.json
View File

@ -115,14 +115,14 @@
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@ -234,7 +234,15 @@
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@ -259,7 +267,7 @@
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12
packages/server/marketplaces/chatflows/MRKLAgent.json
View File

@ -156,7 +156,7 @@
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@ -268,7 +268,15 @@
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16
packages/server/marketplaces/chatflows/Metadata Filter Load.json
View File

@ -113,14 +113,14 @@
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@ -232,7 +232,15 @@
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12
packages/server/marketplaces/chatflows/Metadata Filter Upsert.json
View File

@ -436,7 +436,7 @@
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@ -548,7 +548,15 @@
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12
packages/server/marketplaces/chatflows/Multi Prompt Chain.json
View File

@ -278,7 +278,7 @@
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@ -390,7 +390,15 @@
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12
packages/server/marketplaces/chatflows/Multi Retrieval QA Chain.json
View File

@ -679,7 +679,7 @@
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@ -791,7 +791,15 @@
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52
packages/server/marketplaces/chatflows/Multiple VectorDB.json
View File

@ -321,14 +321,14 @@
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@ -436,7 +436,15 @@
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@ -557,7 +565,7 @@
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@ -732,14 +740,14 @@
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@ -847,7 +855,15 @@
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@ -993,14 +1009,14 @@
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@ -1108,7 +1124,15 @@
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@ -1135,7 +1159,7 @@
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12
packages/server/marketplaces/chatflows/OpenAI Agent.json
View File

@ -281,7 +281,7 @@
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@ -393,7 +393,15 @@
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32
packages/server/marketplaces/chatflows/Prompt Chaining with VectorStore.json
View File

@ -260,13 +260,13 @@
"id": "chatOpenAI_0",
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@ -385,7 +385,15 @@
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@ -411,7 +419,7 @@
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@ -420,13 +428,13 @@
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@ -545,7 +553,15 @@
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32
packages/server/marketplaces/chatflows/Prompt Chaining.json
View File

@ -289,14 +289,14 @@
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@ -404,7 +404,15 @@
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16
packages/server/marketplaces/chatflows/Replicate LLM.json
View File

@ -148,13 +148,13 @@
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@ -226,7 +226,15 @@
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54
packages/server/marketplaces/chatflows/SQL DB Chain.json
View File

@ -13,7 +13,7 @@
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@ -126,7 +126,15 @@
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"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": "0",
@ -167,7 +175,7 @@
"data": {
"id": "sqlDatabaseChain_0",
"label": "Sql Database Chain",
"version": 2,
"version": 4,
"name": "sqlDatabaseChain",
"type": "SqlDatabaseChain",
"baseClasses": ["SqlDatabaseChain", "BaseChain", "Runnable"],
@ -206,6 +214,46 @@
"placeholder": "1270.0.0.1:5432/chinook",
"id": "sqlDatabaseChain_0-input-url-string"
},
{
"label": "Include Tables",
"name": "includesTables",
"type": "string",
"description": "Tables to include for queries, seperated by comma. Can only use Include Tables or Ignore Tables",
"placeholder": "table1, table2",
"additionalParams": true,
"optional": true,
"id": "sqlDatabaseChain_0-input-includesTables-string"
},
{
"label": "Ignore Tables",
"name": "ignoreTables",
"type": "string",
"description": "Tables to ignore for queries, seperated by comma. Can only use Ignore Tables or Include Tables",
"placeholder": "table1, table2",
"additionalParams": true,
"optional": true,
"id": "sqlDatabaseChain_0-input-ignoreTables-string"
},
{
"label": "Sample table's rows info",
"name": "sampleRowsInTableInfo",
"type": "number",
"description": "Number of sample row for tables to load for info.",
"placeholder": "3",
"additionalParams": true,
"optional": true,
"id": "sqlDatabaseChain_0-input-sampleRowsInTableInfo-number"
},
{
"label": "Top Keys",
"name": "topK",
"type": "number",
"description": "If you are querying for several rows of a table you can select the maximum number of results you want to get by using the top_k parameter (default is 10). This is useful for avoiding query results that exceed the prompt max length or consume tokens unnecessarily.",
"placeholder": "10",
"additionalParams": true,
"optional": true,
"id": "sqlDatabaseChain_0-input-topK-number"
},
{
"label": "Custom Prompt",
"name": "customPrompt",

16
packages/server/marketplaces/chatflows/Simple Conversation Chain.json
View File

@ -64,14 +64,14 @@
"id": "chatOpenAI_0",
"position": {
"x": 754.8942497823595,
"y": -70.76607584232393
"y": -140
},
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -183,7 +183,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -208,7 +216,7 @@
"selected": false,
"positionAbsolute": {
"x": 754.8942497823595,
"y": -70.76607584232393
"y": -140
},
"dragging": false
},

16
packages/server/marketplaces/chatflows/Simple LLM Chain.json
View File

@ -148,14 +148,14 @@
"id": "openAI_0",
"position": {
"x": 513.3297923232442,
"y": -42.67554802812833
"y": -112.67554802812833
},
"type": "customNode",
"data": {
"id": "openAI_0",
"label": "OpenAI",
"name": "openAI",
"version": 2,
"version": 3,
"type": "OpenAI",
"baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
"category": "LLMs",
@ -263,7 +263,15 @@
"id": "openAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "openAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo-instruct",
"temperature": 0.7,
@ -290,7 +298,7 @@
"selected": false,
"positionAbsolute": {
"x": 513.3297923232442,
"y": -42.67554802812833
"y": -112.67554802812833
},
"dragging": false
}

16
packages/server/marketplaces/chatflows/Translator.json
View File

@ -157,14 +157,14 @@
"id": "chatOpenAI_0",
"position": {
"x": 436.97058562345904,
"y": 99.96180150605153
"y": 29.96180150605153
},
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -276,7 +276,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": "0",
@ -301,7 +309,7 @@
"selected": false,
"positionAbsolute": {
"x": 436.97058562345904,
"y": 99.96180150605153
"y": 29.96180150605153
},
"dragging": false
}

12
packages/server/marketplaces/chatflows/Vectara LLM Chain Upload.json
View File

@ -124,7 +124,7 @@
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"version": 1,
"version": 2,
"name": "chatOpenAI",
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "Runnable"],
@ -230,7 +230,15 @@
"id": "chatOpenAI_0-input-baseOptions-json"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": "0.5",

32
packages/server/marketplaces/chatflows/WebBrowser.json
View File

@ -194,14 +194,14 @@
"id": "chatOpenAI_0",
"position": {
"x": 734.7477982032904,
"y": -400.9979556765114
"y": -470.9979556765114
},
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -313,7 +313,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -338,7 +346,7 @@
"selected": false,
"positionAbsolute": {
"x": 734.7477982032904,
"y": -400.9979556765114
"y": -470.9979556765114
},
"dragging": false
},
@ -432,14 +440,14 @@
"id": "chatOpenAI_1",
"position": {
"x": 68.312124033115,
"y": -169.65476709991256
"y": -239.65476709991256
},
"type": "customNode",
"data": {
"id": "chatOpenAI_1",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"version": 1,
"version": 2,
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"category": "Chat Models",
@ -551,7 +559,15 @@
"id": "chatOpenAI_1-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_1-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo",
"temperature": 0.9,
@ -576,7 +592,7 @@
"selected": false,
"positionAbsolute": {
"x": 68.312124033115,
"y": -169.65476709991256
"y": -239.65476709991256
},
"dragging": false
}

12
packages/server/marketplaces/chatflows/WebPage QnA.json
View File

@ -13,7 +13,7 @@
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"version": 1,
"version": 2,
"name": "chatOpenAI",
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
@ -126,7 +126,15 @@
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo-16k",
"temperature": "0.9",

12
packages/server/marketplaces/chatflows/Zapier NLA.json
View File

@ -115,7 +115,7 @@
"id": "openAI_0",
"label": "OpenAI",
"name": "openAI",
"version": 2,
"version": 3,
"type": "OpenAI",
"baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
"category": "LLMs",
@ -223,7 +223,15 @@
"id": "openAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "openAI_0-input-cache-BaseCache"
}
],
"inputs": {
"modelName": "gpt-3.5-turbo-instruct",
"temperature": 0.7,

2
packages/server/package.json
View File

@ -1,6 +1,6 @@
{
"name": "flowise",
"version": "1.3.6",
"version": "1.3.7",
"description": "Flowiseai Server",
"main": "dist/index",
"types": "dist/index.d.ts",

2
packages/server/src/commands/start.ts
View File

@ -27,6 +27,7 @@ export default class Start extends Command {
LOG_LEVEL: Flags.string(),
TOOL_FUNCTION_BUILTIN_DEP: Flags.string(),
TOOL_FUNCTION_EXTERNAL_DEP: Flags.string(),
NUMBER_OF_PROXIES: Flags.string(),
DATABASE_TYPE: Flags.string(),
DATABASE_PATH: Flags.string(),
DATABASE_PORT: Flags.string(),
@ -72,6 +73,7 @@ export default class Start extends Command {
if (flags.PORT) process.env.PORT = flags.PORT
if (flags.DEBUG) process.env.DEBUG = flags.DEBUG
if (flags.NUMBER_OF_PROXIES) process.env.NUMBER_OF_PROXIES = flags.NUMBER_OF_PROXIES
// Authorization
if (flags.FLOWISE_USERNAME) process.env.FLOWISE_USERNAME = flags.FLOWISE_USERNAME

1
packages/server/src/utils/index.ts
View File

@ -477,6 +477,7 @@ export const replaceInputsWithConfig = (flowNodeData: INodeData, overrideConfig:
*/
export const isStartNodeDependOnInput = (startingNodes: IReactFlowNode[], nodes: IReactFlowNode[]): boolean => {
for (const node of startingNodes) {
if (node.data.category === 'Cache') return true
for (const inputName in node.data.inputs) {
const inputVariables = getInputVariables(node.data.inputs[inputName])
if (inputVariables.length > 0) return true

14
packages/server/src/utils/rateLimit.ts
View File

@ -12,7 +12,7 @@ async function addRateLimiter(id: string, duration: number, limit: number, messa
rateLimiters[id] = rateLimit({
windowMs: duration * 1000,
max: limit,
handler: (req, res) => {
handler: (_, res) => {
res.status(429).send(message)
}
})
@ -33,15 +33,19 @@ export function getRateLimiter(req: Request, res: Response, next: NextFunction)
export async function createRateLimiter(chatFlow: IChatFlow) {
if (!chatFlow.apiConfig) return
const apiConfig: any = JSON.parse(chatFlow.apiConfig)
const apiConfig = JSON.parse(chatFlow.apiConfig)
const rateLimit: { limitDuration: number; limitMax: number; limitMsg: string } = apiConfig.rateLimit
if (!rateLimit) return
const { limitDuration, limitMax, limitMsg } = rateLimit
if (limitMax && limitDuration && limitMsg) await addRateLimiter(chatFlow.id, limitDuration, limitMax, limitMsg)
}
export async function initializeRateLimiter(chatFlowPool: IChatFlow[]) {
await chatFlowPool.map(async (chatFlow) => {
await createRateLimiter(chatFlow)
})
await Promise.all(
chatFlowPool.map(async (chatFlow) => {
await createRateLimiter(chatFlow)
})
)
}

2
packages/ui/package.json
View File

@ -1,6 +1,6 @@
{
"name": "flowise-ui",
"version": "1.3.4",
"version": "1.3.5",
"license": "SEE LICENSE IN LICENSE.md",
"homepage": "https://flowiseai.com",
"author": {

2
packages/ui/src/views/chatflows/Configuration.js
View File

@ -136,7 +136,7 @@ const Configuration = () => {
<TooltipWithParser
style={{ mb: 1, mt: 2, marginLeft: 10 }}
title={
'Visit <a target="_blank" href="https://docs.flowiseai.com/deployment#rate-limit-setup-guide">Rate Limit Setup Guide</a> to set up Rate Limit correctly in your hosting environment.'
'Visit <a target="_blank" href="https://docs.flowiseai.com/rate-limit">Rate Limit Setup Guide</a> to set up Rate Limit correctly in your hosting environment.'
}
/>
</Typography>

19
packages/ui/src/views/chatmessage/ChatMessage.js
View File

@ -64,27 +64,10 @@ export const ChatMessage = ({ open, chatflowid, isDialog }) => {
window.open(data, '_blank')
}
const handleVectaraMetadata = (message) => {
if (message.sourceDocuments && message.sourceDocuments[0].metadata.length)
message.sourceDocuments = message.sourceDocuments.map((docs) => {
const newMetadata = docs.metadata.reduce((newMetadata, metadata) => {
newMetadata[metadata.name] = metadata.value
return newMetadata
}, {})
return {
pageContent: docs.pageContent,
metadata: newMetadata
}
})
return message
}
const removeDuplicateURL = (message) => {
const visitedURLs = []
const newSourceDocuments = []
message = handleVectaraMetadata(message)
message.sourceDocuments.forEach((source) => {
if (isValidURL(source.metadata.source) && !visitedURLs.includes(source.metadata.source)) {
visitedURLs.push(source.metadata.source)
@ -174,8 +157,6 @@ export const ChatMessage = ({ open, chatflowid, isDialog }) => {
if (response.data) {
let data = response.data
data = handleVectaraMetadata(data)
if (typeof data === 'object' && data.text && data.sourceDocuments) {
if (!isChatFlowAvailableToStream) {
setMessages((prevMessages) => [

15
packages/ui/src/views/marketplaces/index.js
View File

@ -175,19 +175,8 @@ const Marketplace = () => {
)}
</TabPanel>
))}
{!isChatflowsLoading && (!getAllChatflowsMarketplacesApi.data || getAllChatflowsMarketplacesApi.data.length === 0) && (
<Stack sx={{ alignItems: 'center', justifyContent: 'center' }} flexDirection='column'>
<Box sx={{ p: 2, height: 'auto' }}>
<img
style={{ objectFit: 'cover', height: '30vh', width: 'auto' }}
src={WorkflowEmptySVG}
alt='WorkflowEmptySVG'
/>
</Box>
<div>No Marketplace Yet</div>
</Stack>
)}
{!isToolsLoading && (!getAllToolsMarketplacesApi.data || getAllToolsMarketplacesApi.data.length === 0) && (
{((!isChatflowsLoading && (!getAllChatflowsMarketplacesApi.data || getAllChatflowsMarketplacesApi.data.length === 0)) ||
(!isToolsLoading && (!getAllToolsMarketplacesApi.data || getAllToolsMarketplacesApi.data.length === 0))) && (
<Stack sx={{ alignItems: 'center', justifyContent: 'center' }} flexDirection='column'>
<Box sx={{ p: 2, height: 'auto' }}>
<img