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Merge branch 'FlowiseAI:main' into vectara-upload-files

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Seif
2023-09-12 14:56:19 -07:00
committed by GitHub
parent 0a59483eeb 26499bc555
commit cb21c11373
64 changed files with 1661 additions and 103 deletions
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packages/components/nodes/chains/SqlDatabaseChain/SqlDatabaseChain.ts
+86 -8
View File
@@ -43,7 +43,7 @@ class SqlDatabaseChain_Chains implements INode {
constructor() {
this.label = 'Sql Database Chain'
this.name = 'sqlDatabaseChain'
this.version = 2.0
this.version = 3.0
this.type = 'SqlDatabaseChain'
this.icon = 'sqlchain.svg'
this.category = 'Chains'
@@ -85,6 +85,41 @@ class SqlDatabaseChain_Chains implements INode {
type: 'string',
placeholder: '1270.0.0.1:5432/chinook'
},
{
label: 'Include Tables',
name: 'includesTables',
type: 'string',
description: 'Tables to include for queries.',
additionalParams: true,
optional: true
},
{
label: 'Ignore Tables',
name: 'ignoreTables',
type: 'string',
description: 'Tables to ignore for queries.',
additionalParams: true,
optional: true
},
{
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
},
{
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
},
{
label: 'Custom Prompt',
name: 'customPrompt',
@@ -104,20 +139,50 @@ class SqlDatabaseChain_Chains implements INode {
async init(nodeData: INodeData): Promise<any> {
const databaseType = nodeData.inputs?.database as DatabaseType
const model = nodeData.inputs?.model as BaseLanguageModel
const url = nodeData.inputs?.url
const url = nodeData.inputs?.url as string
const includesTables = nodeData.inputs?.includesTables
const splittedIncludesTables = includesTables == '' ? undefined : includesTables?.split(',')
const ignoreTables = nodeData.inputs?.ignoreTables
const splittedIgnoreTables = ignoreTables == '' ? undefined : ignoreTables?.split(',')
const sampleRowsInTableInfo = nodeData.inputs?.sampleRowsInTableInfo as number
const topK = nodeData.inputs?.topK as number
const customPrompt = nodeData.inputs?.customPrompt as string
const chain = await getSQLDBChain(databaseType, url, model, customPrompt)
const chain = await getSQLDBChain(
databaseType,
url,
model,
splittedIncludesTables,
splittedIgnoreTables,
sampleRowsInTableInfo,
topK,
customPrompt
)
return chain
}
async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
const databaseType = nodeData.inputs?.database as DatabaseType
const model = nodeData.inputs?.model as BaseLanguageModel
const url = nodeData.inputs?.url
const url = nodeData.inputs?.url as string
const includesTables = nodeData.inputs?.includesTables
const splittedIncludesTables = includesTables == '' ? undefined : includesTables?.split(',')
const ignoreTables = nodeData.inputs?.ignoreTables
const splittedIgnoreTables = ignoreTables == '' ? undefined : ignoreTables?.split(',')
const sampleRowsInTableInfo = nodeData.inputs?.sampleRowsInTableInfo as number
const topK = nodeData.inputs?.topK as number
const customPrompt = nodeData.inputs?.customPrompt as string
const chain = await getSQLDBChain(databaseType, url, model, customPrompt)
const chain = await getSQLDBChain(
databaseType,
url,
model,
splittedIncludesTables,
splittedIgnoreTables,
sampleRowsInTableInfo,
topK,
customPrompt
)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
if (options.socketIO && options.socketIOClientId) {
@@ -131,7 +196,16 @@ class SqlDatabaseChain_Chains implements INode {
}
}
const getSQLDBChain = async (databaseType: DatabaseType, url: string, llm: BaseLanguageModel, customPrompt?: string) => {
const getSQLDBChain = async (
databaseType: DatabaseType,
url: string,
llm: BaseLanguageModel,
includesTables?: string[],
ignoreTables?: string[],
sampleRowsInTableInfo?: number,
topK?: number,
customPrompt?: string
) => {
const datasource = new DataSource(
databaseType === 'sqlite'
? {
@@ -145,13 +219,17 @@ const getSQLDBChain = async (databaseType: DatabaseType, url: string, llm: BaseL
)
const db = await SqlDatabase.fromDataSourceParams({
appDataSource: datasource
appDataSource: datasource,
includesTables: includesTables,
ignoreTables: ignoreTables,
sampleRowsInTableInfo: sampleRowsInTableInfo
})
const obj: SqlDatabaseChainInput = {
llm,
database: db,
verbose: process.env.DEBUG === 'true' ? true : false
verbose: process.env.DEBUG === 'true' ? true : false,
topK: topK
}
if (customPrompt) {
packages/components/nodes/chatmodels/ChatGooglePaLM/ChatGooglePaLM.ts
+117
View File
@@ -0,0 +1,117 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { ChatGooglePaLM, GooglePaLMChatInput } from 'langchain/chat_models/googlepalm'
class ChatGooglePaLM_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 = 'ChatGooglePaLM'
this.name = 'chatGooglePaLM'
this.version = 1.0
this.type = 'ChatGooglePaLM'
this.icon = 'Google_PaLM_Logo.svg'
this.category = 'Chat Models'
this.description = 'Wrapper around Google MakerSuite PaLM large language models using the Chat endpoint'
this.baseClasses = [this.type, ...getBaseClasses(ChatGooglePaLM)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['googleMakerSuite']
}
this.inputs = [
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'models/chat-bison-001',
name: 'models/chat-bison-001'
}
],
default: 'models/chat-bison-001',
optional: true
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
default: 0.7,
optional: true,
description:
'Controls the randomness of the output.\n' +
'Values can range from [0.0,1.0], inclusive. A value closer to 1.0 ' +
'will produce responses that are more varied and creative, while ' +
'a value closer to 0.0 will typically result in more straightforward ' +
'responses from the model.'
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true,
description:
'Top-p changes how the model selects tokens for output.\n' +
'Tokens are selected from most probable to least until ' +
'the sum of their probabilities equals the top-p value.\n' +
'For example, if tokens A, B, and C have a probability of .3, .2, and .1 ' +
'and the top-p value is .5, then the model will select either A or B ' +
'as the next token (using temperature).'
},
{
label: 'Top-k',
name: 'topK',
type: 'number',
step: 1,
optional: true,
additionalParams: true,
description:
'Top-k changes how the model selects tokens for output.\n' +
'A top-k of 1 means the selected token is the most probable among ' +
'all tokens in the model vocabulary (also called greedy decoding), ' +
'while a top-k of 3 means that the next token is selected from ' +
'among the 3 most probable tokens (using temperature).'
}
// 'The "examples" field should contain a list of pairs of strings to use as prior turns for this conversation.'
// NB: While 'examples:[]' exists in langchain.ts backend, it is unlikely to be actually used there, since ChatOpenAI doesn't support it
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const modelName = nodeData.inputs?.modelName as string
const temperature = nodeData.inputs?.temperature as string
const topP = nodeData.inputs?.topP as string
const topK = nodeData.inputs?.topK as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
const obj: Partial<GooglePaLMChatInput> = {
modelName: modelName,
temperature: parseFloat(temperature),
apiKey: googleMakerSuiteKey
}
if (topP) obj.topP = parseFloat(topP)
if (topK) obj.topK = parseFloat(topK)
const model = new ChatGooglePaLM(obj)
return model
}
}
module.exports = { nodeClass: ChatGooglePaLM_ChatModels }
packages/components/nodes/chatmodels/ChatGooglePaLM/Google_PaLM_Logo.svg
+67
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@@ -0,0 +1,67 @@
<?xml version="1.0" encoding="utf-8"?>
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xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" width="192px" height="192px"
viewBox="0 0 192 192" enable-background="new 0 0 192 192" xml:space="preserve">
<symbol id="material_x5F_product_x5F_standard_x5F_icon_x5F_keylines_00000077318920148093339210000006245950728745084294_" viewBox="-96 -96 192 192">
<g opacity="0.4">
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<use xlink:href="#SVGID_1_" overflow="visible"/>
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packages/components/nodes/chatmodels/ChatGoogleVertexAI/ChatGoogleVertexAI.ts
+8
View File
@@ -46,6 +46,14 @@ class GoogleVertexAI_ChatModels implements INode {
{
label: 'codechat-bison',
name: 'codechat-bison'
},
{
label: 'chat-bison-32k',
name: 'chat-bison-32k'
},
{
label: 'codechat-bison-32k',
name: 'codechat-bison-32k'
}
],
default: 'chat-bison',
packages/components/nodes/documentloaders/ApifyWebsiteContentCrawler/ApifyWebsiteContentCrawler.ts
+44 -9
View File
@@ -21,11 +21,17 @@ class ApifyWebsiteContentCrawler_DocumentLoaders implements INode {
this.name = 'apifyWebsiteContentCrawler'
this.type = 'Document'
this.icon = 'apify-symbol-transparent.svg'
this.version = 1.0
this.version = 2.0
this.category = 'Document Loaders'
this.description = 'Load data from Apify Website Content Crawler'
this.baseClasses = [this.type]
this.inputs = [
{
label: 'Text Splitter',
name: 'textSplitter',
type: 'TextSplitter',
optional: true
},
{
label: 'Start URLs',
name: 'urls',
@@ -64,14 +70,16 @@ class ApifyWebsiteContentCrawler_DocumentLoaders implements INode {
name: 'maxCrawlDepth',
type: 'number',
optional: true,
default: 1
default: 1,
additionalParams: true
},
{
label: 'Max crawl pages',
name: 'maxCrawlPages',
type: 'number',
optional: true,
default: 3
default: 3,
additionalParams: true
},
{
label: 'Additional input',
@@ -80,13 +88,15 @@ class ApifyWebsiteContentCrawler_DocumentLoaders implements INode {
default: JSON.stringify({}),
description:
'For additional input options for the crawler see <a target="_blank" href="https://apify.com/apify/website-content-crawler/input-schema">documentation</a>.',
optional: true
optional: true,
additionalParams: true
},
{
label: 'Text Splitter',
name: 'textSplitter',
type: 'TextSplitter',
optional: true
label: 'Metadata',
name: 'metadata',
type: 'json',
optional: true,
additionalParams: true
}
]
this.credential = {
@@ -99,6 +109,7 @@ class ApifyWebsiteContentCrawler_DocumentLoaders implements INode {
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
const metadata = nodeData.inputs?.metadata
// Get input options and merge with additional input
const urls = nodeData.inputs?.urls as string
@@ -132,7 +143,31 @@ class ApifyWebsiteContentCrawler_DocumentLoaders implements INode {
}
})
return textSplitter ? loader.loadAndSplit(textSplitter) : loader.load()
let docs = []
if (textSplitter) {
docs = await loader.loadAndSplit(textSplitter)
} else {
docs = await loader.load()
}
if (metadata) {
const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
let finaldocs = []
for (const doc of docs) {
const newdoc = {
...doc,
metadata: {
...doc.metadata,
...parsedMetadata
}
}
finaldocs.push(newdoc)
}
return finaldocs
}
return docs
}
}
packages/components/nodes/embeddings/GooglePaLMEmbedding/GooglePaLMEmbedding.ts
+65
View File
@@ -0,0 +1,65 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { GooglePaLMEmbeddings, GooglePaLMEmbeddingsParams } from 'langchain/embeddings/googlepalm'
class GooglePaLMEmbedding_Embeddings 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 = 'Google PaLM Embeddings'
this.name = 'googlePaLMEmbeddings'
this.version = 1.0
this.type = 'GooglePaLMEmbeddings'
this.icon = 'Google_PaLM_Logo.svg'
this.category = 'Embeddings'
this.description = 'Google MakerSuite PaLM API to generate embeddings for a given text'
this.baseClasses = [this.type, ...getBaseClasses(GooglePaLMEmbeddings)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['googleMakerSuite']
}
this.inputs = [
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'models/embedding-gecko-001',
name: 'models/embedding-gecko-001'
}
],
default: 'models/embedding-gecko-001',
optional: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const modelName = nodeData.inputs?.modelName as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
const obj: Partial<GooglePaLMEmbeddingsParams> = {
modelName: modelName,
apiKey: googleMakerSuiteKey
}
const model = new GooglePaLMEmbeddings(obj)
return model
}
}
module.exports = { nodeClass: GooglePaLMEmbedding_Embeddings }
packages/components/nodes/embeddings/GooglePaLMEmbedding/Google_PaLM_Logo.svg
+67
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packages/components/nodes/embeddings/GoogleVertexAIEmbedding/GoogleVertexAIEmbedding.ts
+25 -1
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@@ -33,11 +33,34 @@ class GoogleVertexAIEmbedding_Embeddings implements INode {
description:
'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 = []
this.inputs = [
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'textembedding-gecko@001',
name: 'textembedding-gecko@001'
},
{
label: 'textembedding-gecko@latest',
name: 'textembedding-gecko@latest'
},
{
label: 'textembedding-gecko-multilingual@latest',
name: 'textembedding-gecko-multilingual@latest'
}
],
default: 'textembedding-gecko@001',
optional: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const modelName = nodeData.inputs?.modelName as string
const googleApplicationCredentialFilePath = getCredentialParam('googleApplicationCredentialFilePath', credentialData, nodeData)
const googleApplicationCredential = getCredentialParam('googleApplicationCredential', credentialData, nodeData)
const projectID = getCredentialParam('projectID', credentialData, nodeData)
@@ -59,6 +82,7 @@ class GoogleVertexAIEmbedding_Embeddings implements INode {
if (projectID) authOptions.projectId = projectID
}
const obj: GoogleVertexAIEmbeddingsParams = {}
if (modelName) obj.model = modelName
if (Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
const model = new GoogleVertexAIEmbeddings(obj)
packages/components/nodes/llms/GooglePaLM/GooglePaLM.ts
+158
View File
@@ -0,0 +1,158 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { GooglePaLM, GooglePaLMTextInput } from 'langchain/llms/googlepalm'
class GooglePaLM_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 = 'GooglePaLM'
this.name = 'GooglePaLM'
this.version = 1.0
this.type = 'GooglePaLM'
this.icon = 'Google_PaLM_Logo.svg'
this.category = 'LLMs'
this.description = 'Wrapper around Google MakerSuite PaLM large language models'
this.baseClasses = [this.type, ...getBaseClasses(GooglePaLM)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['googleMakerSuite']
}
this.inputs = [
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'models/text-bison-001',
name: 'models/text-bison-001'
}
],
default: 'models/text-bison-001',
optional: true
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
default: 0.7,
optional: true,
description:
'Controls the randomness of the output.\n' +
'Values can range from [0.0,1.0], inclusive. A value closer to 1.0 ' +
'will produce responses that are more varied and creative, while ' +
'a value closer to 0.0 will typically result in more straightforward ' +
'responses from the model.'
},
{
label: 'Max Output Tokens',
name: 'maxOutputTokens',
type: 'number',
step: 1,
optional: true,
additionalParams: true,
description: 'Maximum number of tokens to generate in the completion.'
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true,
description:
'Top-p changes how the model selects tokens for output.\n' +
'Tokens are selected from most probable to least until ' +
'the sum of their probabilities equals the top-p value.\n' +
'For example, if tokens A, B, and C have a probability of .3, .2, and .1 ' +
'and the top-p value is .5, then the model will select either A or B ' +
'as the next token (using temperature).'
},
{
label: 'Top-k',
name: 'topK',
type: 'number',
step: 1,
optional: true,
additionalParams: true,
description:
'Top-k changes how the model selects tokens for output.\n' +
'A top-k of 1 means the selected token is the most probable among ' +
'all tokens in the model vocabulary (also called greedy decoding), ' +
'while a top-k of 3 means that the next token is selected from ' +
'among the 3 most probable tokens (using temperature).'
},
{
label: 'Stop Sequences',
name: 'stopSequencesObj',
type: 'json',
optional: true,
additionalParams: true
//default: { list:[] },
//description:
// 'The "list" field should contain a list of character strings (up to 5) that will stop output generation.\n' +
// ' * If specified, the API will stop at the first appearance of a stop sequence.\n' +
// 'Note: The stop sequence will not be included as part of the response.'
}
/*
{
label: 'Safety Settings',
name: 'safetySettings',
type: 'json',
optional: true,
additionalParams: true
}
*/
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const modelName = nodeData.inputs?.modelName as string
const temperature = nodeData.inputs?.temperature as string
const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
const topP = nodeData.inputs?.topP as string
const topK = nodeData.inputs?.topK as string
const stopSequencesObj = nodeData.inputs?.stopSequencesObj
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
const obj: Partial<GooglePaLMTextInput> = {
modelName: modelName,
temperature: parseFloat(temperature),
apiKey: googleMakerSuiteKey
}
if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
if (topP) obj.topP = parseFloat(topP)
if (topK) obj.topK = parseFloat(topK)
let parsedStopSequences: any | undefined = undefined
if (stopSequencesObj) {
try {
parsedStopSequences = typeof stopSequencesObj === 'object' ? stopSequencesObj : JSON.parse(stopSequencesObj)
obj.stopSequences = parsedStopSequences.list || []
} catch (exception) {
throw new Error("Invalid JSON in the GooglePaLM's stopSequences: " + exception)
}
}
const model = new GooglePaLM(obj)
return model
}
}
module.exports = { nodeClass: GooglePaLM_LLMs }
packages/components/nodes/llms/GooglePaLM/Google_PaLM_Logo.svg
+67
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packages/components/nodes/llms/GoogleVertexAI/GoogleVertexAI.ts
+12
View File
@@ -50,6 +50,18 @@ class GoogleVertexAI_LLMs implements INode {
{
label: 'code-gecko',
name: 'code-gecko'
},
{
label: 'text-bison-32k',
name: 'text-bison-32k'
},
{
label: 'code-bison-32k',
name: 'code-bison-32k'
},
{
label: 'code-gecko-32k',
name: 'code-gecko-32k'
}
],
default: 'text-bison'
packages/components/nodes/vectorstores/Chroma/Chroma_Existing.ts
+14
View File
@@ -51,6 +51,13 @@ class Chroma_Existing_VectorStores implements INode {
type: 'string',
optional: true
},
{
label: 'Chroma Metadata Filter',
name: 'chromaMetadataFilter',
type: 'json',
optional: true,
additionalParams: true
},
{
label: 'Top K',
name: 'topK',
@@ -86,13 +93,20 @@ class Chroma_Existing_VectorStores implements INode {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const chromaApiKey = getCredentialParam('chromaApiKey', credentialData, nodeData)
const chromaMetadataFilter = nodeData.inputs?.chromaMetadataFilter
const obj: {
collectionName: string
url?: string
chromaApiKey?: string
filter?: object | undefined
} = { collectionName }
if (chromaURL) obj.url = chromaURL
if (chromaApiKey) obj.chromaApiKey = chromaApiKey
if (chromaMetadataFilter) {
const metadatafilter = typeof chromaMetadataFilter === 'object' ? chromaMetadataFilter : JSON.parse(chromaMetadataFilter)
obj.filter = metadatafilter
}
const vectorStore = await ChromaExtended.fromExistingCollection(embeddings, obj)