mirror of
https://github.com/gnh1201/welsonjs.git
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288 lines
8.7 KiB
JavaScript
288 lines
8.7 KiB
JavaScript
// language-inference-engine.js
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// Language Inference Engine (e.g., NLP, LLM) services integration
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// Namhyeon Go <abuse@catswords.net>
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// https://github.com/gnh1201/welsonjs
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// ***SECURITY NOTICE***
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// Language Inference Engine requires an internet connection, and data may be transmitted externally. Users must adhere to the terms of use and privacy policy.
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// - OpenAI: https://openai.com/policies/row-privacy-policy/
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// - Anthropic: https://www.anthropic.com/legal/privacy
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// - Groq: https://groq.com/privacy-policy/
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// - xAI: https://x.ai/legal/privacy-policy
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// - Google Gemini: https://developers.google.com/idx/support/privacy
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// - DeepSeek: https://chat.deepseek.com/downloads/DeepSeek%20Privacy%20Policy.html
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//
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var HTTP = require("lib/http");
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var CRED = require("lib/credentials");
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var biasMessage = "Write all future code examples in JavaScript ES3 using the exports variable. " +
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"Include a test method with the fixed name test. " +
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"Respond exclusively in code without blocks.";
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var engineProfiles = {
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"openai": {
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"headers": {
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"Content-Type": "application/json",
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"Authorization": "Bearer {apikey}"
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},
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"url": "https://api.openai.com/v1/chat/completions",
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"wrap": function(model, message) {
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return {
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"model": model,
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"messages": [{
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"role": "developer",
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"content": biasMessage
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}, {
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"role": "user",
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"content": message
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}]
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};
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},
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"callback": function(response) {
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if ("error" in response) {
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return ["Error: " + response.error.message];
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} else {
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return response.choices.reduce(function(a, x) {
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a.push(x.message.content);
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return a;
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}, []);
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}
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}
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},
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"anthropic": {
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"headers": {
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"Content-Type": "application/json",
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"x-api-key": "{apikey}",
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"anthropic-version": "2023-06-01"
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},
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"url": "https://api.anthropic.com/v1/messages",
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"wrap": function(model, message) {
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return {
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"model": model,
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"max_tokens": 1024,
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"messages": [
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{
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"role": "system",
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"content": biasMessage
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},
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{
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"role": "user",
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"content": message
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}
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]
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};
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},
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"callback": function(response) {
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if ("error" in response) {
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return ["Error: " + response.error.message];
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} else {
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return response.content.reduce(function(a, x) {
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if (x.type == "text") {
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a.push(x.text);
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} else {
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a.push("Not supported type: " + x.type);
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}
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return a;
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}, []);
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}
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}
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},
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"groq": {
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"headers": {
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"Content-Type": "application/json",
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"Authorization": "Bearer {apikey}"
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},
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"url": "https://api.groq.com/openai/v1/chat/completions",
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"wrap": function(model, message) {
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return {
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"model": model,
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"messages": [
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{
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"role": "system",
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"content": biasMessage
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},
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{
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"role": "user",
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"content": message
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}
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]
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};
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},
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"callback": function(response) {
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if ("error" in response) {
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return ["Error: " + response.error.message];
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} else {
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return response.choices.reduce(function(a, x) {
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a.push(x.message.content);
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return a;
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}, []);
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}
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}
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},
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"xai": {
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"headers": {
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"Content-Type": "application/json",
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"Authorization": "Bearer {apikey}"
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},
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"url": "https://api.x.ai/v1/chat/completions",
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"wrap": function(model, message) {
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return {
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"messages": [
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{
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"role": "system",
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"content": biasMessage
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},
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{
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"role": "user",
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"content": message
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}
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],
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"model": model
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}
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},
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"callback": function(response) {
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return response.choices.reduce(function(a, x) {
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a.push(x.message.content);
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return a;
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}, []);
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}
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},
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"google": {
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"headers": {
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"Content-Type": "application/json",
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"Authorization": "Bearer {apikey}"
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},
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"url": "https://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent?key={apikey}",
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"warp": function(model, message) {
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return {
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"contents": [
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{
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"parts": [
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{
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"text": message
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}
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]
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}
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]
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}
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},
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"callback": function(response) {
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if ("error" in response) {
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return ["Error: " + response.error.message];
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} else {
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return response.candidates.reduce(function(a, x) {
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x.content.parts.forEach(function(part) {
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if ("text" in part) {
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a.push(part.text);
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} else {
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a.push("Not supported type");
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}
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});
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return a;
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}, []);
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}
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}
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},
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"deepseek": {
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"headers": {
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"Content-Type": "application/json",
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"Authorization": "Bearer {apikey}"
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},
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"url": "https://api.deepseek.com/chat/completions",
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"wrap": function(model, message) {
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"model": model,
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"messages": [
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{
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"role": "system",
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"content": biasMessage
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},
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{
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"role": "user",
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"content": message
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}
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],
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"stream": false
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}
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},
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"callback": function(response) {
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if ("error" in response) {
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return ["Error: " + response.error.message];
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} else {
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return response.choices.reduce(function(a, x) {
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a.push(x.message.content);
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return a;
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}, []);
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}
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}
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};
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function LanguageInferenceEngine() {
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this.type = "llm"; // e.g. legacy (Legacy NLP), llm (LLM)
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this.provider = "";
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this.engineProfile = null;
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this.setProvider = function(provider) {
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this.provider = provider;
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if (provider in engineProfiles) {
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this.engineProfile = engineProfiles[provider];
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}
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return this;
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};
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this.setModel = function(model) {
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this.model = model;
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return this;
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};
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this.setEngineProfileURL = function(url) {
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if (this.engineProfile == null)
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return this;
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this.engineProfile.url = url;
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return this;
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}
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this.inference = function(message) {
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if (this.engineProfile == null)
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return this;
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var apikey = CRED.get("apikey", this.provider); // Get API key
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var headers = this.engineProfile.headers;
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var wrap = this.engineProfile.wrap;
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var url = this.engineProfile.url;
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var callback = this.engineProfile.callback;
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var response = HTTP.create("MSXML")
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.setVariables({
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"apikey": apikey
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})
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.setHeaders(headers)
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.setRequestBody(wrap(message))
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.open("post", url)
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.send()
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.responseBody;
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return callback(response);
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};
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}
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exports.LanguageInferenceEngine = LanguageInferenceEngine;
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exports.create = function() {
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return new LanguageInferenceEngine();
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};
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exports.VERSIONINFO = "Language Inference Engine (NLP/LLM) integration version 0.1.1";
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exports.AUTHOR = "abuse@catswords.net";
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exports.global = global;
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exports.require = global.require;
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