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https://github.com/Mintplex-Labs/anything-llm.git
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15cf921616
* Support SQL Agent skill * add MSSQL agent connector * Add frontend to agent skills remove FAKE_DB mock reset skills to pickup child-skill dynamically * add prompt examples for tools on untooled * add better logging on SQL agents * Wipe toolruns on each chat relay so tools can be used within the same session * update comments
119 lines
3.1 KiB
JavaScript
119 lines
3.1 KiB
JavaScript
const OpenAI = require("openai");
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const Provider = require("./ai-provider.js");
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const InheritMultiple = require("./helpers/classes.js");
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const UnTooled = require("./helpers/untooled.js");
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/**
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* The agent provider for the LocalAI provider.
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*/
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class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
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model;
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constructor(config = {}) {
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const { model = null } = config;
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super();
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const client = new OpenAI({
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baseURL: process.env.LOCAL_AI_BASE_PATH,
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apiKey: process.env.LOCAL_AI_API_KEY ?? null,
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maxRetries: 3,
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});
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this._client = client;
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this.model = model;
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this.verbose = true;
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}
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get client() {
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return this._client;
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}
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async #handleFunctionCallChat({ messages = [] }) {
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return await this.client.chat.completions
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.create({
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model: this.model,
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temperature: 0,
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messages,
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})
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.then((result) => {
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if (!result.hasOwnProperty("choices"))
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throw new Error("LocalAI chat: No results!");
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if (result.choices.length === 0)
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throw new Error("LocalAI chat: No results length!");
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return result.choices[0].message.content;
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})
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.catch((_) => {
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return null;
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});
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}
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/**
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* Create a completion based on the received messages.
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*
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* @param messages A list of messages to send to the API.
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* @param functions
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* @returns The completion.
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*/
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async complete(messages, functions = null) {
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try {
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let completion;
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if (functions.length > 0) {
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const { toolCall, text } = await this.functionCall(
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messages,
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functions,
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this.#handleFunctionCallChat.bind(this)
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);
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if (toolCall !== null) {
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this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
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this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
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return {
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result: null,
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functionCall: {
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name: toolCall.name,
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arguments: toolCall.arguments,
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},
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cost: 0,
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};
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}
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completion = { content: text };
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}
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if (!completion?.content) {
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this.providerLog(
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"Will assume chat completion without tool call inputs."
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);
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const response = await this.client.chat.completions.create({
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model: this.model,
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messages: this.cleanMsgs(messages),
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});
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completion = response.choices[0].message;
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}
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// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
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// from calling the exact same function over and over in a loop within a single chat exchange
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// _but_ we should enable it to call previously used tools in a new chat interaction.
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this.deduplicator.reset("runs");
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return { result: completion.content, cost: 0 };
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} catch (error) {
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throw error;
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}
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}
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/**
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* Get the cost of the completion.
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*
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* @param _usage The completion to get the cost for.
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* @returns The cost of the completion.
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* Stubbed since LocalAI has no cost basis.
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*/
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getCost(_usage) {
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return 0;
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}
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}
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module.exports = LocalAiProvider;
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