Addition of Google Gemini Chat Model, Credential and Associated Embeddings

This commit is contained in:
vinodkiran 2023-12-15 20:58:08 +05:30
parent 6a17cdc315
commit e7f13c87d8
6 changed files with 239 additions and 0 deletions

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import { INodeParams, INodeCredential } from '../src/Interface'
class GoogleGenerativeAICredential implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Google Generative AI'
this.name = 'googleGenerativeAI'
this.version = 1.0
this.description = 'Get your <a target="_blank" href="https://ai.google.dev/tutorials/setup">API Key</a> here.'
this.inputs = [
{
label: 'Google AI API Key',
name: 'googleGenerativeAPIKey',
type: 'password'
}
]
}
}
module.exports = { credClass: GoogleGenerativeAICredential }

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import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { BaseCache } from 'langchain/schema'
import { ChatGoogleGenerativeAI } from '@langchain/google-genai'
class GoogleGenerativeAI_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 = 'ChatGoogleGenerativeAI'
this.name = 'chatGoogleGenerativeAI'
this.version = 2.0
this.type = 'ChatGoogleGenerativeAI'
this.icon = 'gemini.png'
this.category = 'Chat Models'
this.description = 'Wrapper around Google Gemini large language models that use the Chat endpoint'
this.baseClasses = [this.type, ...getBaseClasses(ChatGoogleGenerativeAI)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['googleGenerativeAI'],
optional: true,
description: 'Google Generative AI credential.'
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'gemini-pro',
name: 'gemini-pro'
}
],
default: 'gemini-pro',
optional: true
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
default: 0.9,
optional: true
},
{
label: 'Max Output Tokens',
name: 'maxOutputTokens',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const apiKey = getCredentialParam('googleGenerativeAPIKey', credentialData, nodeData)
const temperature = nodeData.inputs?.temperature as string
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 = {
apiKey: apiKey,
modelName: modelName,
maxOutputTokens: 2048
}
if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
const model = new ChatGoogleGenerativeAI(obj)
if (topP) model.topP = parseFloat(topP)
if (cache) model.cache = cache
if (temperature) model.temperature = parseInt(temperature)
return model
}
}
module.exports = { nodeClass: GoogleGenerativeAI_ChatModels }

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import { GoogleVertexAIEmbeddings } from 'langchain/embeddings/googlevertexai'
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { GoogleGenerativeAIEmbeddings, GoogleGenerativeAIEmbeddingsParams } from '@langchain/google-genai'
import { TaskType } from '@google/generative-ai'
class GoogleGenerativeAIEmbedding_Embeddings implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
inputs: INodeParams[]
credential: INodeParams
constructor() {
this.label = 'GoogleGenerativeAI Embeddings'
this.name = 'googleGenerativeAiEmbeddings'
this.version = 1.0
this.type = 'GoogleGenerativeAiEmbeddings'
this.icon = 'gemini.png'
this.category = 'Embeddings'
this.description = 'Google Generative API to generate embeddings for a given text'
this.baseClasses = [this.type, ...getBaseClasses(GoogleVertexAIEmbeddings)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['googleGenerativeAI'],
optional: true,
description: 'Google Generative AI credential.'
}
this.inputs = [
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'embedding-001',
name: 'embedding-001'
}
],
default: 'embedding-001'
},
{
label: 'Task Type',
name: 'tasktype',
type: 'options',
description: 'Type of task for which the embedding will be used',
options: [
{ label: 'TASK_TYPE_UNSPECIFIED', name: 'TASK_TYPE_UNSPECIFIED' },
{ label: 'RETRIEVAL_QUERY', name: 'RETRIEVAL_QUERY' },
{ label: 'RETRIEVAL_DOCUMENT', name: 'RETRIEVAL_DOCUMENT' },
{ label: 'SEMANTIC_SIMILARITY', name: 'SEMANTIC_SIMILARITY' },
{ label: 'CLASSIFICATION', name: 'CLASSIFICATION' },
{ label: 'CLUSTERING', name: 'CLUSTERING' }
],
default: 'TASK_TYPE_UNSPECIFIED'
}
]
}
// eslint-disable-next-line unused-imports/no-unused-vars
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const modelName = nodeData.inputs?.modelName as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const apiKey = getCredentialParam('googleGenerativeAPIKey', credentialData, nodeData)
let taskType: TaskType
switch (nodeData.inputs?.tasktype as string) {
case 'RETRIEVAL_QUERY':
taskType = TaskType.RETRIEVAL_QUERY
break
case 'RETRIEVAL_DOCUMENT':
taskType = TaskType.RETRIEVAL_DOCUMENT
break
case 'SEMANTIC_SIMILARITY':
taskType = TaskType.SEMANTIC_SIMILARITY
break
case 'CLASSIFICATION':
taskType = TaskType.CLASSIFICATION
break
case 'CLUSTERING':
taskType = TaskType.CLUSTERING
break
default:
taskType = TaskType.TASK_TYPE_UNSPECIFIED
break
}
const obj: GoogleGenerativeAIEmbeddingsParams = {
apiKey: apiKey,
modelName: modelName,
taskType: taskType
}
const model = new GoogleGenerativeAIEmbeddings(obj)
return model
}
}
module.exports = { nodeClass: GoogleGenerativeAIEmbedding_Embeddings }

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"@gomomento/sdk-core": "^1.51.1",
"@google-ai/generativelanguage": "^0.2.1",
"@huggingface/inference": "^2.6.1",
"@langchain/google-genai": "^0.0.3",
"@notionhq/client": "^2.2.8",
"@opensearch-project/opensearch": "^1.2.0",
"@pinecone-database/pinecone": "^1.1.1",