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https://github.com/Mintplex-Labs/anything-llm.git
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8422f92542
* add LMStudio agent support (generic) support "work" with non-tool callable LLMs, highly dependent on system specs * add comments * enable few-shot prompting per function for OSS models * Add Agent support for Ollama models * azure, groq, koboldcpp agent support complete + WIP togetherai * WIP gemini agent support * WIP gemini blocked and will not fix for now * azure fix * merge fix * add localai agent support * azure untooled agent support * merge fix * refactor implementation of several agent provideers * update bad merge comment --------- Co-authored-by: timothycarambat <rambat1010@gmail.com>
114 lines
2.9 KiB
JavaScript
114 lines
2.9 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 provider for the TogetherAI provider.
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*/
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class TogetherAIProvider extends InheritMultiple([Provider, UnTooled]) {
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model;
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constructor(config = {}) {
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const { model = "mistralai/Mistral-7B-Instruct-v0.1" } = config;
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super();
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const client = new OpenAI({
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baseURL: "https://api.together.xyz/v1",
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apiKey: process.env.TOGETHER_AI_API_KEY,
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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("LMStudio chat: No results!");
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if (result.choices.length === 0)
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throw new Error("LMStudio 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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return {
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result: completion.content,
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cost: 0,
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};
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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 LMStudio 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 = TogetherAIProvider;
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