@n8n/n8n-nodes-langchain
Version:
259 lines • 12.1 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.LmChatDatabricks = void 0;
const openai_1 = require("@langchain/openai");
const ai_utilities_1 = require("@n8n/ai-utilities");
const n8n_workflow_1 = require("n8n-workflow");
const token_provider_1 = require("./token-provider");
const error_handling_1 = require("../../vendors/OpenAi/helpers/error-handling");
function assertHttpsHost(ctx, host) {
if (!URL.canParse(host) || new URL(host).protocol !== 'https:') {
throw new n8n_workflow_1.NodeOperationError(ctx.getNode(), 'Databricks host must use https');
}
}
async function searchModels(filter) {
const credentials = await this.getCredentials('databricksOAuth2Api');
assertHttpsHost(this, credentials.host);
const host = credentials.host.replace(/\/$/, '');
const response = await this.helpers.httpRequestWithAuthentication.call(this, 'databricksOAuth2Api', {
method: 'GET',
url: `${host}/api/2.0/serving-endpoints`,
headers: { Accept: 'application/json', 'User-Agent': token_provider_1.CHAT_MODEL_USER_AGENT },
json: true,
});
const endpoints = response.endpoints ?? [];
const allResults = endpoints
.filter((endpoint) => endpoint.task?.includes('chat'))
.map((endpoint) => {
const modelNames = (endpoint.config?.served_entities ?? [])
.map((entity) => entity.external_model?.name ?? entity.foundation_model?.name)
.filter(Boolean)
.join(', ');
return {
name: endpoint.name,
value: endpoint.name,
url: `${host}/ml/endpoints/${endpoint.name}`,
description: modelNames || 'Model serving endpoint',
};
});
if (filter) {
const filterLower = filter.toLowerCase();
return {
results: allResults.filter((r) => r.name.toLowerCase().includes(filterLower) ||
r.description.toLowerCase().includes(filterLower)),
};
}
return { results: allResults };
}
class LmChatDatabricks {
constructor() {
this.methods = {
listSearch: {
searchModels,
},
};
this.description = {
displayName: 'Databricks Chat Model',
name: 'lmChatDatabricks',
hidden: true,
icon: { light: 'file:databricks.svg', dark: 'file:databricks.dark.svg' },
group: ['transform'],
version: [1],
description: 'For advanced usage with an AI chain',
defaults: {
name: 'Databricks Chat Model',
},
codex: {
categories: ['AI'],
subcategories: {
AI: ['Language Models', 'Root Nodes'],
'Language Models': ['Chat Models (Recommended)'],
},
resources: {
primaryDocumentation: [
{
url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatdatabricks/',
},
],
},
},
inputs: [],
outputs: [n8n_workflow_1.NodeConnectionTypes.AiLanguageModel],
outputNames: ['Model'],
credentials: [
{
name: 'databricksOAuth2Api',
required: true,
},
],
properties: [
(0, ai_utilities_1.getConnectionHintNoticeField)([n8n_workflow_1.NodeConnectionTypes.AiChain, n8n_workflow_1.NodeConnectionTypes.AiAgent]),
{
displayName: 'If using JSON response format, you must include word "json" in the prompt in your chain or agent. Also, make sure the selected endpoint supports JSON mode.',
name: 'notice',
type: 'notice',
default: '',
displayOptions: {
show: {
'/options.responseFormat': ['json_object'],
},
},
},
{
displayName: 'Model',
name: 'model',
type: 'resourceLocator',
default: { mode: 'list', value: '' },
required: true,
modes: [
{
displayName: 'From List',
name: 'list',
type: 'list',
placeholder: 'Select a model...',
typeOptions: {
searchListMethod: 'searchModels',
searchable: true,
},
},
{
displayName: 'ID',
name: 'id',
type: 'string',
placeholder: 'my-serving-endpoint',
},
],
description: 'The serving endpoint. Choose from the list, or specify an ID.',
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Frequency Penalty',
name: 'frequencyPenalty',
default: 0,
typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
description: "Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim",
type: 'number',
},
{
displayName: 'Maximum Number of Tokens',
name: 'maxTokens',
default: -1,
description: '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).',
type: 'number',
typeOptions: {
maxValue: 32768,
},
},
{
displayName: 'Response Format',
name: 'responseFormat',
default: 'text',
type: 'options',
options: [
{
name: 'Text',
value: 'text',
description: 'Regular text response',
},
{
name: 'JSON',
value: 'json_object',
description: 'Enables JSON mode, which should guarantee the message the model generates is valid JSON',
},
],
},
{
displayName: 'Presence Penalty',
name: 'presencePenalty',
default: 0,
typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
description: "Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics",
type: 'number',
},
{
displayName: 'Sampling Temperature',
name: 'temperature',
default: 0.7,
typeOptions: { maxValue: 2, 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: 'Timeout',
name: 'timeout',
default: 360000,
description: 'Maximum amount of time a request is allowed to take in milliseconds',
type: 'number',
},
{
displayName: 'Max Retries',
name: 'maxRetries',
default: 2,
description: 'Maximum number of retries to attempt',
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(itemIndex) {
const credential = await this.getCredentials('databricksOAuth2Api');
if (credential.grantType === 'authorizationCode') {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), 'User (Authorization Code) login is not supported by this node yet - use a Client Credentials (Service Principal) credential');
}
assertHttpsHost(this, credential.host);
const baseURL = `${credential.host.replace(/\/$/, '')}/serving-endpoints`;
const modelName = this.getNodeParameter('model', itemIndex, '', {
extractValue: true,
});
const options = this.getNodeParameter('options', itemIndex, {});
const egressFilter = this.helpers.getSecureEgressFilter();
const timeout = options.timeout;
const configuration = {
baseURL,
fetch: (0, token_provider_1.createDatabricksFetch)((0, token_provider_1.getDatabricksTokenProvider)(this.getNode(), credential, egressFilter), egressFilter),
fetchOptions: {
dispatcher: (0, ai_utilities_1.getProxyAgent)(baseURL, {
headersTimeout: timeout,
bodyTimeout: timeout,
}, egressFilter?.createSecureLookup()),
},
};
const modelKwargs = {};
if (options.responseFormat) {
modelKwargs.response_format = { type: options.responseFormat };
}
const model = new openai_1.ChatOpenAI({
apiKey: 'databricks-oauth',
model: modelName,
...options,
timeout,
maxRetries: options.maxRetries ?? 2,
configuration,
callbacks: [new ai_utilities_1.N8nLlmTracing(this)],
modelKwargs: Object.keys(modelKwargs).length > 0 ? modelKwargs : undefined,
onFailedAttempt: (0, ai_utilities_1.makeN8nLlmFailedAttemptHandler)(this, error_handling_1.openAiFailedAttemptHandler),
});
return {
response: model,
};
}
}
exports.LmChatDatabricks = LmChatDatabricks;
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