/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
import {
NodeConnectionType,
type INodeProperties,
type IExecuteFunctions,
type INodeType,
type INodeTypeDescription,
type SupplyData,
} from 'n8n-workflow';
import { ChatAnthropic } from '@langchain/anthropic';
import type { LLMResult } from '@langchain/core/outputs';
import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
import { N8nLlmTracing } from '../N8nLlmTracing';
const modelField: INodeProperties = {
displayName: 'Model',
name: 'model',
type: 'options',
// eslint-disable-next-line n8n-nodes-base/node-param-options-type-unsorted-items
options: [
{
name: 'Claude 3 Opus(20240229)',
value: 'claude-3-opus-20240229',
},
{
name: 'Claude 3 Sonnet(20240229)',
value: 'claude-3-sonnet-20240229',
},
{
name: 'Claude 3 Haiku(20240307)',
value: 'claude-3-haiku-20240307',
},
{
name: 'LEGACY: Claude 2',
value: 'claude-2',
},
{
name: 'LEGACY: Claude 2.1',
value: 'claude-2.1',
},
{
name: 'LEGACY: Claude Instant 1.2',
value: 'claude-instant-1.2',
},
{
name: 'LEGACY: Claude Instant 1',
value: 'claude-instant-1',
},
],
description:
'The model which will generate the completion. Learn more.',
default: 'claude-2',
};
export class LmChatAnthropic implements INodeType {
description: INodeTypeDescription = {
displayName: 'Anthropic Chat Model',
// eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased
name: 'lmChatAnthropic',
icon: 'file:anthropic.svg',
group: ['transform'],
version: [1, 1.1],
description: 'Language Model Anthropic',
defaults: {
name: 'Anthropic Chat Model',
},
codex: {
categories: ['AI'],
subcategories: {
AI: ['Language Models'],
},
resources: {
primaryDocumentation: [
{
url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatanthropic/',
},
],
},
alias: ['claude', 'sonnet', 'opus'],
},
// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
inputs: [],
// eslint-disable-next-line n8n-nodes-base/node-class-description-outputs-wrong
outputs: [NodeConnectionType.AiLanguageModel],
outputNames: ['Model'],
credentials: [
{
name: 'anthropicApi',
required: true,
},
],
properties: [
getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiChain]),
{
...modelField,
displayOptions: {
show: {
'@version': [1],
},
},
},
{
...modelField,
default: 'claude-3-sonnet-20240229',
displayOptions: {
hide: {
'@version': [1],
},
},
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Maximum Number of Tokens',
name: 'maxTokensToSample',
default: 4096,
description: 'The maximum number of tokens to generate in the completion',
type: 'number',
},
{
displayName: 'Sampling Temperature',
name: 'temperature',
default: 0.7,
typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
description:
'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.',
type: 'number',
},
{
displayName: 'Top K',
name: 'topK',
default: -1,
typeOptions: { maxValue: 1, minValue: -1, numberPrecision: 1 },
description:
'Used to remove "long tail" low probability responses. Defaults to -1, which disables it.',
type: 'number',
},
{
displayName: 'Top P',
name: 'topP',
default: 1,
typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
description:
'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.',
type: 'number',
},
],
},
],
};
async supplyData(this: IExecuteFunctions, itemIndex: number): Promise {
const credentials = await this.getCredentials('anthropicApi');
const modelName = this.getNodeParameter('model', itemIndex) as string;
const options = this.getNodeParameter('options', itemIndex, {}) as {
maxTokensToSample?: number;
temperature: number;
topK: number;
topP: number;
};
const tokensUsageParser = (llmOutput: LLMResult['llmOutput']) => {
const usage = (llmOutput?.usage as { input_tokens: number; output_tokens: number }) ?? {
input_tokens: 0,
output_tokens: 0,
};
return {
completionTokens: usage.output_tokens,
promptTokens: usage.input_tokens,
totalTokens: usage.input_tokens + usage.output_tokens,
};
};
const model = new ChatAnthropic({
anthropicApiKey: credentials.apiKey as string,
modelName,
maxTokens: options.maxTokensToSample,
temperature: options.temperature,
topK: options.topK,
topP: options.topP,
callbacks: [new N8nLlmTracing(this, { tokensUsageParser })],
});
return {
response: model,
};
}
}