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feat: Implement MistralCloud Chat & Embeddings nodes (#8239)
Signed-off-by: Oleg Ivaniv <me@olegivaniv.com> Co-authored-by: Michael Kret <michael.k@radency.com>
This commit is contained in:
@@ -0,0 +1,197 @@
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/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
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import {
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NodeConnectionType,
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type IExecuteFunctions,
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type INodeType,
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type INodeTypeDescription,
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type SupplyData,
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} from 'n8n-workflow';
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import type { ChatMistralAIInput } from '@langchain/mistralai';
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import { ChatMistralAI } from '@langchain/mistralai';
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import { logWrapper } from '../../../utils/logWrapper';
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import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
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export class LmChatMistralCloud implements INodeType {
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description: INodeTypeDescription = {
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displayName: 'Mistral Cloud Chat Model',
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// eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased
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name: 'lmChatMistralCloud',
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icon: 'file:mistral.svg',
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group: ['transform'],
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version: 1,
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description: 'For advanced usage with an AI chain',
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defaults: {
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name: 'Mistral Cloud Chat Model',
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},
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codex: {
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categories: ['AI'],
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subcategories: {
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AI: ['Language Models'],
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},
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resources: {
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primaryDocumentation: [
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{
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url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatmistralcloud/',
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},
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],
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},
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},
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// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
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inputs: [],
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// eslint-disable-next-line n8n-nodes-base/node-class-description-outputs-wrong
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outputs: [NodeConnectionType.AiLanguageModel],
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outputNames: ['Model'],
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credentials: [
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{
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name: 'mistralCloudApi',
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required: true,
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},
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],
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requestDefaults: {
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ignoreHttpStatusErrors: true,
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baseURL: 'https://api.mistral.ai/v1',
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},
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properties: [
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getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiAgent]),
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{
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displayName: 'Model',
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name: 'model',
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type: 'options',
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description:
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'The model which will generate the completion. <a href="https://docs.mistral.ai/platform/endpoints/">Learn more</a>.',
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typeOptions: {
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loadOptions: {
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routing: {
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request: {
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method: 'GET',
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url: '/models',
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},
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output: {
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postReceive: [
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{
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type: 'rootProperty',
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properties: {
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property: 'data',
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},
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},
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{
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type: 'filter',
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properties: {
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pass: "={{ !$responseItem.id.includes('embed') }}",
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},
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},
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{
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type: 'setKeyValue',
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properties: {
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name: '={{ $responseItem.id }}',
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value: '={{ $responseItem.id }}',
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},
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},
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{
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type: 'sort',
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properties: {
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key: 'name',
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},
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},
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],
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},
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},
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},
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},
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routing: {
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send: {
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type: 'body',
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property: 'model',
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},
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},
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default: 'mistral-small',
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},
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{
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displayName: 'Options',
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name: 'options',
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placeholder: 'Add Option',
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description: 'Additional options to add',
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type: 'collection',
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default: {},
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options: [
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{
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displayName: 'Maximum Number of Tokens',
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name: 'maxTokens',
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default: -1,
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description:
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'The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).',
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type: 'number',
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typeOptions: {
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maxValue: 32768,
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},
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},
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{
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displayName: 'Sampling Temperature',
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name: 'temperature',
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default: 0.7,
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typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
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description:
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'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.',
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type: 'number',
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},
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{
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displayName: 'Max Retries',
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name: 'maxRetries',
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default: 2,
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description: 'Maximum number of retries to attempt',
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type: 'number',
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},
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{
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displayName: 'Top P',
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name: 'topP',
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default: 1,
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typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
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description:
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'Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.',
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type: 'number',
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},
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{
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displayName: 'Enable Safe Mode',
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name: 'safeMode',
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default: false,
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type: 'boolean',
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description: 'Whether to inject a safety prompt before all conversations',
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},
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{
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displayName: 'Random Seed',
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name: 'randomSeed',
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default: undefined,
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type: 'number',
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description:
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'The seed to use for random sampling. If set, different calls will generate deterministic results.',
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},
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],
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},
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],
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};
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async supplyData(this: IExecuteFunctions, itemIndex: number): Promise<SupplyData> {
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const credentials = await this.getCredentials('mistralCloudApi');
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const modelName = this.getNodeParameter('model', itemIndex) as string;
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const options = this.getNodeParameter('options', itemIndex, {
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maxRetries: 2,
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topP: 1,
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temperature: 0.7,
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maxTokens: -1,
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safeMode: false,
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randomSeed: undefined,
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}) as Partial<ChatMistralAIInput>;
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const model = new ChatMistralAI({
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apiKey: credentials.apiKey as string,
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modelName,
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...options,
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});
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return {
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response: logWrapper(model, this),
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};
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}
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}
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