@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 });
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}
return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);
var LmChatMistralCloud_node_exports = {};
__export(LmChatMistralCloud_node_exports, {
LmChatMistralCloud: () => LmChatMistralCloud
});
module.exports = __toCommonJS(LmChatMistralCloud_node_exports);
var import_mistralai = require("@langchain/mistralai");
var import_n8n_workflow = require("n8n-workflow");
var import_sharedFields = require("../../../utils/sharedFields");
var import_n8nLlmFailedAttemptHandler = require("../n8nLlmFailedAttemptHandler");
var import_N8nLlmTracing = require("../N8nLlmTracing");
const deprecatedMagistralModelsWithTextOutput = ["magistral-small-2506", "magistral-medium-2506"];
class LmChatMistralCloud {
constructor() {
this.description = {
displayName: "Mistral Cloud Chat Model",
name: "lmChatMistralCloud",
icon: "file:mistral.svg",
group: ["transform"],
version: 1,
description: "For advanced usage with an AI chain",
defaults: {
name: "Mistral Cloud 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.lmchatmistralcloud/"
}
]
}
},
inputs: [],
outputs: [import_n8n_workflow.NodeConnectionTypes.AiLanguageModel],
outputNames: ["Model"],
credentials: [
{
name: "mistralCloudApi",
required: true
}
],
requestDefaults: {
ignoreHttpStatusErrors: true,
baseURL: "https://api.mistral.ai/v1"
},
properties: [
(0, import_sharedFields.getConnectionHintNoticeField)([import_n8n_workflow.NodeConnectionTypes.AiChain, import_n8n_workflow.NodeConnectionTypes.AiAgent]),
{
displayName: "Model",
name: "model",
type: "options",
description: 'The model which will generate the completion. <a href="https://docs.mistral.ai/platform/endpoints/">Learn more</a>.',
typeOptions: {
loadOptions: {
routing: {
request: {
method: "GET",
url: "/models"
},
output: {
postReceive: [
{
type: "rootProperty",
properties: {
property: "data"
}
},
{
type: "filter",
properties: {
pass: "={{ !$responseItem.id.includes('embed') }}"
}
},
{
type: "setKeyValue",
properties: {
name: "={{ $responseItem.id }}",
value: "={{ $responseItem.id }}"
}
},
{
type: "sort",
properties: {
key: "name"
}
}
]
}
}
}
},
routing: {
send: {
type: "body",
property: "model"
}
},
default: "mistral-small"
},
{
displayName: "Options",
name: "options",
placeholder: "Add Option",
description: "Additional options to add",
type: "collection",
default: {},
options: [
{
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: "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: "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"
},
{
displayName: "Enable Safe Mode",
name: "safeMode",
default: false,
type: "boolean",
description: "Whether to inject a safety prompt before all conversations"
},
{
displayName: "Random Seed",
name: "randomSeed",
default: void 0,
type: "number",
description: "The seed to use for random sampling. If set, different calls will generate deterministic results."
}
]
}
]
};
}
async supplyData(itemIndex) {
const credentials = await this.getCredentials("mistralCloudApi");
const modelName = this.getNodeParameter("model", itemIndex);
const options = this.getNodeParameter("options", itemIndex, {
maxRetries: 2,
topP: 1,
temperature: 0.7,
maxTokens: -1,
safeMode: false,
randomSeed: void 0
});
const model = new import_mistralai.ChatMistralAI({
apiKey: credentials.apiKey,
model: modelName,
...options,
callbacks: [new import_N8nLlmTracing.N8nLlmTracing(this)],
onFailedAttempt: (0, import_n8nLlmFailedAttemptHandler.makeN8nLlmFailedAttemptHandler)(this),
metadata: {
output_format: isModelWithJSONOutput(modelName) ? "json" : void 0
}
});
return {
response: model
};
}
}
function isModelWithJSONOutput(modelName) {
if (!modelName.includes("magistral")) {
return false;
}
if (deprecatedMagistralModelsWithTextOutput.includes(modelName)) {
return false;
}
return true;
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
LmChatMistralCloud
});
//# sourceMappingURL=LmChatMistralCloud.node.js.map