@n8n/n8n-nodes-langchain
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JavaScript
;
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
for (var name in all)
__defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
if (from && typeof from === "object" || typeof from === "function") {
for (let key of __getOwnPropNames(from))
if (!__hasOwnProp.call(to, key) && key !== except)
__defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
}
return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);
var ChainRetrievalQa_node_exports = {};
__export(ChainRetrievalQa_node_exports, {
ChainRetrievalQa: () => ChainRetrievalQa
});
module.exports = __toCommonJS(ChainRetrievalQa_node_exports);
var import_n8n_workflow = require("n8n-workflow");
var import_descriptions = require("../../../utils/descriptions");
var import_sharedFields = require("../../../utils/sharedFields");
var import_constants = require("./constants");
var import_processItem = require("./processItem");
class ChainRetrievalQa {
constructor() {
this.description = {
displayName: "Question and Answer Chain",
name: "chainRetrievalQa",
icon: "fa:link",
iconColor: "black",
group: ["transform"],
version: [1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7],
description: "Answer questions about retrieved documents",
defaults: {
name: "Question and Answer Chain",
color: "#909298"
},
codex: {
alias: ["LangChain"],
categories: ["AI"],
subcategories: {
AI: ["Chains", "Root Nodes"]
},
resources: {
primaryDocumentation: [
{
url: "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainretrievalqa/"
}
]
}
},
inputs: [
import_n8n_workflow.NodeConnectionTypes.Main,
{
displayName: "Model",
maxConnections: 1,
type: import_n8n_workflow.NodeConnectionTypes.AiLanguageModel,
required: true
},
{
displayName: "Retriever",
maxConnections: 1,
type: import_n8n_workflow.NodeConnectionTypes.AiRetriever,
required: true
}
],
outputs: [import_n8n_workflow.NodeConnectionTypes.Main],
credentials: [],
properties: [
(0, import_sharedFields.getTemplateNoticeField)(1960),
{
displayName: "Query",
name: "query",
type: "string",
required: true,
default: "={{ $json.input }}",
displayOptions: {
show: {
"@version": [1]
}
}
},
{
displayName: "Query",
name: "query",
type: "string",
required: true,
default: "={{ $json.chat_input }}",
displayOptions: {
show: {
"@version": [1.1]
}
}
},
{
displayName: "Query",
name: "query",
type: "string",
required: true,
default: "={{ $json.chatInput }}",
displayOptions: {
show: {
"@version": [1.2]
}
}
},
{
...import_descriptions.promptTypeOptionsDeprecated,
displayOptions: {
hide: {
"@version": [{ _cnd: { lte: 1.2 } }, { _cnd: { gte: 1.7 } }]
}
}
},
{
...import_descriptions.promptTypeOptions,
displayOptions: {
show: {
"@version": [{ _cnd: { gte: 1.7 } }]
}
}
},
{
...import_descriptions.textFromGuardrailsNode,
displayOptions: {
show: { promptType: ["guardrails"], "@version": [{ _cnd: { gte: 1.4 } }] }
}
},
{
...import_descriptions.textFromPreviousNode,
displayOptions: { show: { promptType: ["auto"], "@version": [{ _cnd: { gte: 1.4 } }] } }
},
{
displayName: "Prompt (User Message)",
name: "text",
type: "string",
required: true,
default: "",
placeholder: "e.g. Hello, how can you help me?",
typeOptions: {
rows: 2
},
displayOptions: {
show: {
promptType: ["define"]
}
}
},
{
displayName: "Options",
name: "options",
type: "collection",
default: {},
placeholder: "Add Option",
options: [
{
...import_constants.systemPromptOption,
description: `Template string used for the system prompt. This should include the variable \`{context}\` for the provided context. For text completion models, you should also include the variable \`{${import_constants.LEGACY_INPUT_TEMPLATE_KEY}}\` for the user\u2019s query.`,
displayOptions: {
show: {
"@version": [{ _cnd: { lt: 1.5 } }]
}
}
},
{
...import_constants.systemPromptOption,
description: `Template string used for the system prompt. This should include the variable \`{context}\` for the provided context. For text completion models, you should also include the variable \`{${import_constants.INPUT_TEMPLATE_KEY}}\` for the user\u2019s query.`,
displayOptions: {
show: {
"@version": [{ _cnd: { gte: 1.5 } }]
}
}
},
(0, import_sharedFields.getBatchingOptionFields)({
show: {
"@version": [{ _cnd: { gte: 1.6 } }]
}
})
]
}
]
};
}
async execute() {
this.logger.debug("Executing Retrieval QA Chain");
const items = this.getInputData();
const returnData = [];
const batchSize = this.getNodeParameter("options.batching.batchSize", 0, 5);
const delayBetweenBatches = this.getNodeParameter(
"options.batching.delayBetweenBatches",
0,
0
);
if (this.getNode().typeVersion >= 1.6 && batchSize >= 1) {
for (let i = 0; i < items.length; i += batchSize) {
const batch = items.slice(i, i + batchSize);
const batchPromises = batch.map(async (_item, batchItemIndex) => {
return await (0, import_processItem.processItem)(this, i + batchItemIndex);
});
const batchResults = await Promise.allSettled(batchPromises);
batchResults.forEach((response, index) => {
if (response.status === "rejected") {
const error = response.reason;
if (this.continueOnFail()) {
const metadata = (0, import_n8n_workflow.parseErrorMetadata)(error);
returnData.push({
json: { error: error.message },
pairedItem: { item: index },
metadata
});
return;
} else {
throw error;
}
}
const output = response.value;
const answer = output.answer;
if (this.getNode().typeVersion >= 1.5) {
returnData.push({ json: { response: answer } });
} else {
returnData.push({ json: { response: { text: answer } } });
}
});
if (i + batchSize < items.length && delayBetweenBatches > 0) {
await (0, import_n8n_workflow.sleep)(delayBetweenBatches);
}
}
} else {
for (let itemIndex = 0; itemIndex < items.length; itemIndex++) {
try {
const response = await (0, import_processItem.processItem)(this, itemIndex);
const answer = response.answer;
if (this.getNode().typeVersion >= 1.5) {
returnData.push({ json: { response: answer } });
} else {
returnData.push({ json: { response: { text: answer } } });
}
} catch (error) {
if (this.continueOnFail()) {
const metadata = (0, import_n8n_workflow.parseErrorMetadata)(error);
returnData.push({
json: { error: error.message },
pairedItem: { item: itemIndex },
metadata
});
continue;
}
throw error;
}
}
}
return [returnData];
}
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
ChainRetrievalQa
});
//# sourceMappingURL=ChainRetrievalQa.node.js.map