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Namhyeon Go 2025-01-27 23:48:34 +09:00
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// language-inference-engine.js
// Language Inference Engine (e.g., NLP, LLM) services integration
// Namhyeon Go <abuse@catswords.net>
// https://github.com/gnh1201/welsonjs
// ***SECURITY NOTICE***
// Language Inference Engine requires an internet connection, and data may be transmitted externally. Users must adhere to the terms of use and privacy policy.
// - OpenAI: https://openai.com/policies/row-privacy-policy/
// - Anthropic: https://www.anthropic.com/legal/privacy
// - Groq: https://groq.com/privacy-policy/
// - xAI: https://x.ai/legal/privacy-policy
// - DeepSeek: https://chat.deepseek.com/downloads/DeepSeek%20Privacy%20Policy.html
//
var HTTP = require("lib/http");
var CRED = require("lib/credentials");
var biasMessage = "Write all future code examples in JavaScript ES3 using the exports variable. " +
"Include a test method with the fixed name test. " +
"Respond exclusively in code without blocks.";
var engineProfiles = {
"openai": {
"headers": {
"Content-Type": "application/json",
"Authorization": "Bearer {apikey}"
},
"url": "https://api.openai.com/v1/chat/completions",
"wrap": function(model, message) {
return {
"model": model,
"messages": [{
"role": "developer",
"content": biasMessage
}, {
"role": "user",
"content": message
}]
};
},
"callback": function(response) {
if ("error" in response) {
return ["Error: " + response.error.message];
} else {
return response.choices.reduce(function(a, x) {
a.push(x.message.content);
return a;
}, []);
}
}
},
"anthropic": {
"headers": {
"Content-Type": "application/json",
"x-api-key": "{apikey}",
"anthropic-version": "2023-06-01"
},
"url": "https://api.anthropic.com/v1/messages",
"wrap": function(model, message) {
return {
"model": model,
"max_tokens": 1024,
"messages": [
{
"role": "system",
"content": biasMessage
},
{
"role": "user",
"content": message
}
]
};
},
"callback": function(response) {
if ("error" in response) {
return ["Error: " + response.error.message];
} else {
return response.content.reduce(function(a, x) {
if (x.type == "text") {
a.push(x.text);
} else {
a.push("Not supported type: " + x.type);
}
return a;
}, []);
}
}
},
"groq": {
"headers": {
"Content-Type": "application/json",
"Authorization": "Bearer {apikey}"
},
"url": "https://api.groq.com/openai/v1/chat/completions",
"wrap": function(model, message) {
return {
"model": model,
"messages": [
{
"role": "system",
"content": biasMessage
},
{
"role": "user",
"content": message
}
]
};
},
"callback": function(response) {
if ("error" in response) {
return ["Error: " + response.error.message];
} else {
return response.choices.reduce(function(a, x) {
a.push(x.message.content);
return a;
}, []);
}
}
},
"xai": {
"headers": {
"Content-Type": "application/json",
"Authorization": "Bearer {apikey}"
},
"url": "https://api.x.ai/v1/chat/completions",
"wrap": function(model, message) {
return {
"messages": [
{
"role": "system",
"content": biasMessage
},
{
"role": "user",
"content": message
}
],
"model": model
}
},
"callback": function(response) {
return response.choices.reduce(function(a, x) {
a.push(x.message.content);
return a;
}, []);
}
},
"deepseek": {
"headers": {
"Content-Type": "application/json",
"Authorization": "Bearer {apikey}"
},
"url": "https://api.deepseek.com/chat/completions",
"wrap": function(model, message) {
"model": model,
"messages": [
{
"role": "system",
"content": biasMessage
},
{
"role": "user",
"content": message
}
],
"stream": false
}
},
"callback": function(response) {
if ("error" in response) {
return ["Error: " + response.error.message];
} else {
return response.choices.reduce(function(a, x) {
a.push(x.message.content);
return a;
}, []);
}
}
};
function LanguageInferenceEngine() {
this.type = "llm"; // e.g. legacy (Legacy NLP), llm (LLM)
this.provider = "";
this.engineProfile = null;
this.setProvider = function(provider) {
this.provider = provider;
if (provider in engineProfiles) {
this.engineProfile = engineProfiles[provider];
}
return this;
};
this.setModel = function(model) {
this.model = model;
return this;
};
this.setEngineProfileURL = function(url) {
if (this.engineProfile == null)
return this;
this.engineProfile.url = url;
return this;
}
this.inference = function(message) {
if (this.engineProfile == null)
return this;
var apikey = CRED.get("apikey", this.provider); // Get API key
var headers = this.engineProfile.headers;
var wrap = this.engineProfile.wrap;
var url = this.engineProfile.url;
var callback = this.engineProfile.callback;
return callback(
HTTP.create("MSXML")
.setVariables({
"apikey": apikey
})
.setHeaders(headers)
.setRequestBody(wrap(message))
.open("post", url)
.send()
.responseBody
);
};
}
exports.LanguageInferenceEngine = LanguageInferenceEngine;
exports.create = function() {
return new LanguageInferenceEngine();
};
exports.VERSIONINFO = "Language Inference Engine (NLP/LLM) integration version 0.1";
exports.AUTHOR = "abuse@catswords.net";
exports.global = global;
exports.require = global.require;