dtamind-components
Version:
DTAmindai Components
324 lines • 11.7 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const openai_1 = require("@langchain/openai");
const utils_1 = require("../../../src/utils");
const FlowiseChatOpenAI_1 = require("./FlowiseChatOpenAI");
const modelLoader_1 = require("../../../src/modelLoader");
const https_proxy_agent_1 = require("https-proxy-agent");
class ChatOpenAI_ChatModels {
constructor() {
//@ts-ignore
this.loadMethods = {
async listModels() {
return await (0, modelLoader_1.getModels)(modelLoader_1.MODEL_TYPE.CHAT, 'chatOpenAI');
}
};
this.label = 'ChatOpenAI';
this.name = 'chatOpenAI';
this.version = 8.3;
this.type = 'ChatOpenAI';
this.icon = 'openai.svg';
this.category = 'Chat Models';
this.description = 'Wrapper around OpenAI large language models that use the Chat endpoint';
this.baseClasses = [this.type, ...(0, utils_1.getBaseClasses)(openai_1.ChatOpenAI)];
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['openAIApi']
};
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
type: 'asyncOptions',
loadMethod: 'listModels',
default: 'gpt-4o-mini'
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
default: 0.9,
optional: true
},
{
label: 'Streaming',
name: 'streaming',
type: 'boolean',
default: true,
optional: true,
additionalParams: true
},
{
label: 'Max Tokens',
name: 'maxTokens',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Frequency Penalty',
name: 'frequencyPenalty',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Presence Penalty',
name: 'presencePenalty',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Timeout',
name: 'timeout',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Strict Tool Calling',
name: 'strictToolCalling',
type: 'boolean',
description: 'Whether the model supports the `strict` argument when passing in tools. If not specified, the `strict` argument will not be passed to OpenAI.',
optional: true,
additionalParams: true
},
{
label: 'Stop Sequence',
name: 'stopSequence',
type: 'string',
rows: 4,
optional: true,
description: 'List of stop words to use when generating. Use comma to separate multiple stop words.',
additionalParams: true
},
{
label: 'BasePath',
name: 'basepath',
type: 'string',
optional: true,
additionalParams: true
},
{
label: 'Proxy Url',
name: 'proxyUrl',
type: 'string',
optional: true,
additionalParams: true
},
{
label: 'BaseOptions',
name: 'baseOptions',
type: 'json',
optional: true,
additionalParams: true
},
{
label: 'Allow Image Uploads',
name: 'allowImageUploads',
type: 'boolean',
description: 'Allow image input. Refer to the <a href="https://docs.flowiseai.com/using-flowise/uploads#image" target="_blank">docs</a> for more details.',
default: false,
optional: true
},
{
label: 'Image Resolution',
description: 'This parameter controls the resolution in which the model views the image.',
name: 'imageResolution',
type: 'options',
options: [
{
label: 'Low',
name: 'low'
},
{
label: 'High',
name: 'high'
},
{
label: 'Auto',
name: 'auto'
}
],
default: 'low',
optional: false,
show: {
allowImageUploads: true
}
},
{
label: 'Reasoning',
description: 'Whether the model supports reasoning. Only applicable for reasoning models.',
name: 'reasoning',
type: 'boolean',
default: false,
optional: true,
additionalParams: true
},
{
label: 'Reasoning Effort',
description: 'Constrains effort on reasoning for reasoning models',
name: 'reasoningEffort',
type: 'options',
options: [
{
label: 'Low',
name: 'low'
},
{
label: 'Medium',
name: 'medium'
},
{
label: 'High',
name: 'high'
}
],
additionalParams: true,
show: {
reasoning: true
}
},
{
label: 'Reasoning Summary',
description: `A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process`,
name: 'reasoningSummary',
type: 'options',
options: [
{
label: 'Auto',
name: 'auto'
},
{
label: 'Concise',
name: 'concise'
},
{
label: 'Detailed',
name: 'detailed'
}
],
additionalParams: true,
show: {
reasoning: true
}
}
];
}
async init(nodeData, _, options) {
const temperature = nodeData.inputs?.temperature;
const modelName = nodeData.inputs?.modelName;
const maxTokens = nodeData.inputs?.maxTokens;
const topP = nodeData.inputs?.topP;
const frequencyPenalty = nodeData.inputs?.frequencyPenalty;
const presencePenalty = nodeData.inputs?.presencePenalty;
const timeout = nodeData.inputs?.timeout;
const stopSequence = nodeData.inputs?.stopSequence;
const streaming = nodeData.inputs?.streaming;
const strictToolCalling = nodeData.inputs?.strictToolCalling;
const basePath = nodeData.inputs?.basepath;
const proxyUrl = nodeData.inputs?.proxyUrl;
const baseOptions = nodeData.inputs?.baseOptions;
const reasoningEffort = nodeData.inputs?.reasoningEffort;
const reasoningSummary = nodeData.inputs?.reasoningSummary;
const allowImageUploads = nodeData.inputs?.allowImageUploads;
const imageResolution = nodeData.inputs?.imageResolution;
if (nodeData.inputs?.credentialId) {
nodeData.credential = nodeData.inputs?.credentialId;
}
const credentialData = await (0, utils_1.getCredentialData)(nodeData.credential ?? '', options);
const openAIApiKey = (0, utils_1.getCredentialParam)('openAIApiKey', credentialData, nodeData);
const cache = nodeData.inputs?.cache;
const obj = {
temperature: parseFloat(temperature),
modelName,
openAIApiKey,
apiKey: openAIApiKey,
streaming: streaming ?? true
};
if (maxTokens)
obj.maxTokens = parseInt(maxTokens, 10);
if (topP)
obj.topP = parseFloat(topP);
if (frequencyPenalty)
obj.frequencyPenalty = parseFloat(frequencyPenalty);
if (presencePenalty)
obj.presencePenalty = parseFloat(presencePenalty);
if (timeout)
obj.timeout = parseInt(timeout, 10);
if (cache)
obj.cache = cache;
if (stopSequence) {
const stopSequenceArray = stopSequence.split(',').map((item) => item.trim());
obj.stop = stopSequenceArray;
}
if (strictToolCalling)
obj.supportsStrictToolCalling = strictToolCalling;
if (modelName.includes('o1') || modelName.includes('o3') || modelName.includes('gpt-5')) {
delete obj.temperature;
delete obj.stop;
const reasoning = {};
if (reasoningEffort) {
reasoning.effort = reasoningEffort;
}
if (reasoningSummary) {
reasoning.summary = reasoningSummary;
}
obj.reasoning = reasoning;
}
let parsedBaseOptions = undefined;
if (baseOptions) {
try {
parsedBaseOptions = typeof baseOptions === 'object' ? baseOptions : JSON.parse(baseOptions);
}
catch (exception) {
throw new Error("Invalid JSON in the ChatOpenAI's BaseOptions: " + exception);
}
}
if (basePath || parsedBaseOptions) {
obj.configuration = {
baseURL: basePath,
defaultHeaders: parsedBaseOptions
};
}
if (proxyUrl) {
obj.configuration = {
...obj?.configuration,
httpAgent: new https_proxy_agent_1.HttpsProxyAgent(proxyUrl)
};
}
const multiModalOption = {
image: {
allowImageUploads: allowImageUploads ?? false,
imageResolution
}
};
const model = new FlowiseChatOpenAI_1.ChatOpenAI(nodeData.id, obj);
model.setMultiModalOption(multiModalOption);
return model;
}
}
module.exports = { nodeClass: ChatOpenAI_ChatModels };
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