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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
152 lines
3.7 KiB
JavaScript
152 lines
3.7 KiB
JavaScript
const OpenAI = require("openai");
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const Provider = require("./ai-provider.js");
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const { RetryError } = require("../error.js");
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/**
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* The agent provider for the OpenAI API.
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* By default, the model is set to 'gpt-3.5-turbo'.
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*/
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class OpenAIProvider extends Provider {
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model;
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static COST_PER_TOKEN = {
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"gpt-4": {
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input: 0.03,
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output: 0.06,
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},
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"gpt-4o": {
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input: 0.005,
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output: 0.015,
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},
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"gpt-4-32k": {
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input: 0.06,
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output: 0.12,
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},
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"gpt-3.5-turbo": {
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input: 0.0015,
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output: 0.002,
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},
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"gpt-3.5-turbo-16k": {
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input: 0.003,
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output: 0.004,
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},
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};
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constructor(config = {}) {
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const {
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options = {
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apiKey: process.env.OPEN_AI_KEY,
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maxRetries: 3,
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},
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model = "gpt-4o",
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} = config;
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const client = new OpenAI(options);
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super(client);
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this.model = model;
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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 OpenAI 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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const response = await this.client.chat.completions.create({
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model: this.model,
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// stream: true,
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messages,
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...(Array.isArray(functions) && functions?.length > 0
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? { functions }
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: {}),
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});
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// Right now, we only support one completion,
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// so we just take the first one in the list
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const completion = response.choices[0].message;
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const cost = this.getCost(response.usage);
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// treat function calls
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if (completion.function_call) {
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let functionArgs = {};
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try {
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functionArgs = JSON.parse(completion.function_call.arguments);
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} catch (error) {
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// call the complete function again in case it gets a json error
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return this.complete(
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[
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...messages,
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{
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role: "function",
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name: completion.function_call.name,
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function_call: completion.function_call,
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content: error?.message,
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},
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],
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functions
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);
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}
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// console.log(completion, { functionArgs })
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return {
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result: null,
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functionCall: {
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name: completion.function_call.name,
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arguments: functionArgs,
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},
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cost,
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};
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}
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return {
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result: completion.content,
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cost,
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};
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} catch (error) {
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// If invalid Auth error we need to abort because no amount of waiting
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// will make auth better.
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if (error instanceof OpenAI.AuthenticationError) throw error;
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if (
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error instanceof OpenAI.RateLimitError ||
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error instanceof OpenAI.InternalServerError ||
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error instanceof OpenAI.APIError // Also will catch AuthenticationError!!!
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) {
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throw new RetryError(error.message);
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}
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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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*/
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getCost(usage) {
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if (!usage) {
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return Number.NaN;
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}
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// regex to remove the version number from the model
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const modelBase = this.model.replace(/-(\d{4})$/, "");
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if (!(modelBase in OpenAIProvider.COST_PER_TOKEN)) {
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return Number.NaN;
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}
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const costPerToken = OpenAIProvider.COST_PER_TOKEN?.[modelBase];
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const inputCost = (usage.prompt_tokens / 1000) * costPerToken.input;
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const outputCost = (usage.completion_tokens / 1000) * costPerToken.output;
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return inputCost + outputCost;
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}
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}
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module.exports = OpenAIProvider;
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