281 lines
12 KiB
TypeScript
281 lines
12 KiB
TypeScript
import { HarmBlockThreshold, HarmCategory } from '@google/generative-ai'
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import type { SafetySetting } from '@google/generative-ai'
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import { BaseCache } from '@langchain/core/caches'
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import { ICommonObject, IMultiModalOption, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { getModels, MODEL_TYPE } from '../../../src/modelLoader'
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import { ChatGoogleGenerativeAI, GoogleGenerativeAIChatInput } from './FlowiseChatGoogleGenerativeAI'
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class GoogleGenerativeAI_ChatModels implements INode {
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label: string
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name: string
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version: number
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type: string
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icon: string
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category: string
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description: string
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baseClasses: string[]
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credential: INodeParams
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inputs: INodeParams[]
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constructor() {
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this.label = 'ChatGoogleGenerativeAI'
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this.name = 'chatGoogleGenerativeAI'
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this.version = 3.1
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this.type = 'ChatGoogleGenerativeAI'
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this.icon = 'GoogleGemini.svg'
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this.category = 'Chat Models'
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this.description = 'Wrapper around Google Gemini large language models that use the Chat endpoint'
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this.baseClasses = [this.type, ...getBaseClasses(ChatGoogleGenerativeAI)]
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this.credential = {
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label: 'Connect Credential',
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name: 'credential',
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type: 'credential',
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credentialNames: ['googleGenerativeAI'],
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optional: false,
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description: 'Google Generative AI credential.'
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}
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this.inputs = [
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{
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label: 'Cache',
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name: 'cache',
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type: 'BaseCache',
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optional: true
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},
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{
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label: 'Model Name',
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name: 'modelName',
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type: 'asyncOptions',
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loadMethod: 'listModels',
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default: 'gemini-1.5-flash-latest'
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},
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{
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label: 'Custom Model Name',
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name: 'customModelName',
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type: 'string',
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placeholder: 'gemini-1.5-pro-exp-0801',
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description: 'Custom model name to use. If provided, it will override the model selected',
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additionalParams: true,
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optional: true
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},
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{
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label: 'Temperature',
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name: 'temperature',
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type: 'number',
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step: 0.1,
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default: 0.9,
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optional: true
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},
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{
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label: 'Streaming',
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name: 'streaming',
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type: 'boolean',
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default: true,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Max Output Tokens',
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name: 'maxOutputTokens',
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type: 'number',
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step: 1,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top Probability',
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name: 'topP',
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type: 'number',
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step: 0.1,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top Next Highest Probability Tokens',
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name: 'topK',
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type: 'number',
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description: `Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive`,
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step: 1,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Safety Settings',
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name: 'safetySettings',
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type: 'array',
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description:
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'Safety settings for the model. Refer to the <a href="https://ai.google.dev/gemini-api/docs/safety-settings">official guide</a> on how to use Safety Settings',
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array: [
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{
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label: 'Harm Category',
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name: 'harmCategory',
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type: 'options',
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options: [
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{
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label: 'Dangerous',
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name: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
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description: 'Promotes, facilitates, or encourages harmful acts.'
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},
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{
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label: 'Harassment',
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name: HarmCategory.HARM_CATEGORY_HARASSMENT,
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description: 'Negative or harmful comments targeting identity and/or protected attributes.'
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},
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{
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label: 'Hate Speech',
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name: HarmCategory.HARM_CATEGORY_HATE_SPEECH,
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description: 'Content that is rude, disrespectful, or profane.'
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},
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{
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label: 'Sexually Explicit',
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name: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT,
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description: 'Contains references to sexual acts or other lewd content.'
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},
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{
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label: 'Civic Integrity',
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name: HarmCategory.HARM_CATEGORY_CIVIC_INTEGRITY,
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description: 'Election-related queries.'
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}
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]
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},
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{
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label: 'Harm Block Threshold',
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name: 'harmBlockThreshold',
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type: 'options',
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options: [
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{
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label: 'None',
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name: HarmBlockThreshold.BLOCK_NONE,
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description: 'Always show regardless of probability of unsafe content'
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},
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{
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label: 'Only High',
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name: HarmBlockThreshold.BLOCK_ONLY_HIGH,
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description: 'Block when high probability of unsafe content'
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},
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{
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label: 'Medium and Above',
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name: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
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description: 'Block when medium or high probability of unsafe content'
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},
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{
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label: 'Low and Above',
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name: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
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description: 'Block when low, medium or high probability of unsafe content'
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},
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{
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label: 'Threshold Unspecified (Default Threshold)',
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name: HarmBlockThreshold.HARM_BLOCK_THRESHOLD_UNSPECIFIED,
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description: 'Threshold is unspecified, block using default threshold'
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}
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]
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}
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],
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optional: true,
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additionalParams: true
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},
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{
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label: 'Base URL',
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name: 'baseUrl',
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type: 'string',
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description: 'Base URL for the API. Leave empty to use the default.',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Allow Image Uploads',
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name: 'allowImageUploads',
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type: 'boolean',
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description:
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'Allow image input. Refer to the <a href="https://docs.flowiseai.com/using-flowise/uploads#image" target="_blank">docs</a> for more details.',
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default: false,
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optional: true
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}
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]
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}
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//@ts-ignore
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loadMethods = {
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async listModels(): Promise<INodeOptionsValue[]> {
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return await getModels(MODEL_TYPE.CHAT, 'chatGoogleGenerativeAI')
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}
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}
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async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const apiKey = getCredentialParam('googleGenerativeAPIKey', credentialData, nodeData)
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const temperature = nodeData.inputs?.temperature as string
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const modelName = nodeData.inputs?.modelName as string
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const customModelName = nodeData.inputs?.customModelName as string
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const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
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const topP = nodeData.inputs?.topP as string
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const topK = nodeData.inputs?.topK as string
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const _safetySettings = nodeData.inputs?.safetySettings as string
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const cache = nodeData.inputs?.cache as BaseCache
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const streaming = nodeData.inputs?.streaming as boolean
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const baseUrl = nodeData.inputs?.baseUrl as string | undefined
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const allowImageUploads = nodeData.inputs?.allowImageUploads as boolean
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const obj: GoogleGenerativeAIChatInput = {
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apiKey: apiKey,
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model: customModelName || modelName,
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streaming: streaming ?? true
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}
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// this extra metadata is needed, as langchain does not show the model name in the callbacks.
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obj.metadata = {
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fw_model_name: customModelName || modelName
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}
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if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
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if (topP) obj.topP = parseFloat(topP)
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if (topK) obj.topK = parseFloat(topK)
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if (cache) obj.cache = cache
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if (temperature) obj.temperature = parseFloat(temperature)
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if (baseUrl) obj.baseUrl = baseUrl
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let safetySettings: SafetySetting[] = []
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if (_safetySettings) {
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try {
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const parsedSafetySettings = typeof _safetySettings === 'string' ? JSON.parse(_safetySettings) : _safetySettings
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if (Array.isArray(parsedSafetySettings)) {
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const validSettings = parsedSafetySettings
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.filter((setting: any) => setting.harmCategory && setting.harmBlockThreshold)
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.map((setting: any) => ({
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category: setting.harmCategory as HarmCategory,
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threshold: setting.harmBlockThreshold as HarmBlockThreshold
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}))
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// Remove duplicates by keeping only the first occurrence of each harm category
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const seenCategories = new Set<HarmCategory>()
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safetySettings = validSettings.filter((setting) => {
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if (seenCategories.has(setting.category)) {
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return false
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}
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seenCategories.add(setting.category)
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return true
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})
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}
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} catch (error) {
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console.warn('Failed to parse safety settings:', error)
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}
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}
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if (safetySettings.length > 0) obj.safetySettings = safetySettings
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const multiModalOption: IMultiModalOption = {
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image: {
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allowImageUploads: allowImageUploads ?? false
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}
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}
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const model = new ChatGoogleGenerativeAI(nodeData.id, obj)
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model.setMultiModalOption(multiModalOption)
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return model
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}
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}
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module.exports = { nodeClass: GoogleGenerativeAI_ChatModels }
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