@n8n/n8n-nodes-langchain
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181 lines • 6.26 kB
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 LmChatCohere_node_exports = {};
__export(LmChatCohere_node_exports, {
LmChatCohere: () => LmChatCohere,
tokensUsageParser: () => tokensUsageParser
});
module.exports = __toCommonJS(LmChatCohere_node_exports);
var import_cohere = require("@langchain/cohere");
var import_sharedFields = require("../../../utils/sharedFields");
var import_n8nLlmFailedAttemptHandler = require("../n8nLlmFailedAttemptHandler");
var import_N8nLlmTracing = require("../N8nLlmTracing");
function tokensUsageParser(result) {
let totalInputTokens = 0;
let totalOutputTokens = 0;
result.generations?.forEach((generationArray) => {
generationArray.forEach((gen) => {
const inputTokens = gen.generationInfo?.meta?.tokens?.inputTokens ?? 0;
const outputTokens = gen.generationInfo?.meta?.tokens?.outputTokens ?? 0;
totalInputTokens += inputTokens;
totalOutputTokens += outputTokens;
});
});
return {
completionTokens: totalOutputTokens,
promptTokens: totalInputTokens,
totalTokens: totalInputTokens + totalOutputTokens
};
}
class LmChatCohere {
constructor() {
this.description = {
displayName: "Cohere Chat Model",
name: "lmChatCohere",
icon: { light: "file:cohere.svg", dark: "file:cohere.dark.svg" },
group: ["transform"],
version: [1],
description: "For advanced usage with an AI chain",
defaults: {
name: "Cohere 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.lmchatcohere/"
}
]
}
},
inputs: [],
outputs: ["ai_languageModel"],
outputNames: ["Model"],
credentials: [
{
name: "cohereApi",
required: true
}
],
requestDefaults: {
baseURL: "={{$credentials?.url}}",
headers: {
accept: "application/json",
authorization: "=Bearer {{$credentials?.apiKey}}"
}
},
properties: [
(0, import_sharedFields.getConnectionHintNoticeField)(["ai_chain", "ai_agent"]),
{
displayName: "Model",
name: "model",
type: "options",
description: 'The model which will generate the completion. <a href="https://docs.cohere.com/docs/models">Learn more</a>.',
typeOptions: {
loadOptions: {
routing: {
request: {
method: "GET",
url: "/v1/models?page_size=100&endpoint=chat"
},
output: {
postReceive: [
{
type: "rootProperty",
properties: {
property: "models"
}
},
{
type: "setKeyValue",
properties: {
name: "={{$responseItem.name}}",
value: "={{$responseItem.name}}",
description: "={{$responseItem.description}}"
}
},
{
type: "sort",
properties: {
key: "name"
}
}
]
}
}
}
},
default: "command-a-03-2025"
},
{
displayName: "Options",
name: "options",
placeholder: "Add Option",
description: "Additional options to add",
type: "collection",
default: {},
options: [
{
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: "Max Retries",
name: "maxRetries",
default: 2,
description: "Maximum number of retries to attempt",
type: "number"
}
]
}
]
};
}
async supplyData(itemIndex) {
const credentials = await this.getCredentials("cohereApi");
const modelName = this.getNodeParameter("model", itemIndex);
const options = this.getNodeParameter("options", itemIndex, {});
const model = new import_cohere.ChatCohere({
apiKey: credentials.apiKey,
model: modelName,
temperature: options.temperature,
maxRetries: options.maxRetries ?? 2,
callbacks: [new import_N8nLlmTracing.N8nLlmTracing(this, { tokensUsageParser })],
onFailedAttempt: (0, import_n8nLlmFailedAttemptHandler.makeN8nLlmFailedAttemptHandler)(this)
});
return {
response: model
};
}
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
LmChatCohere,
tokensUsageParser
});
//# sourceMappingURL=LmChatCohere.node.js.map