* Refactor Gemini to use OpenAI interface API * add TODO * handle errors better (gemini) * remove unused code
155 lines
4.6 KiB
JavaScript
155 lines
4.6 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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const {
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NO_SYSTEM_PROMPT_MODELS,
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} = require("../../../AiProviders/gemini/index.js");
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const { APIError } = require("../error.js");
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/**
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* The agent provider for the Gemini provider.
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* We wrap Gemini in UnTooled because its tool-calling is not supported via the dedicated OpenAI API.
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*/
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class GeminiProvider extends InheritMultiple([Provider, UnTooled]) {
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model;
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constructor(config = {}) {
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const { model = "gemini-2.0-flash-lite" } = config;
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super();
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const client = new OpenAI({
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baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/",
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apiKey: process.env.GEMINI_API_KEY,
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maxRetries: 0,
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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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/**
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* Format the messages to the format required by the Gemini API since some models do not support system prompts.
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* @see {NO_SYSTEM_PROMPT_MODELS}
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* @param {import("openai").OpenAI.ChatCompletionMessage[]} messages
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* @returns {import("openai").OpenAI.ChatCompletionMessage[]}
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*/
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formatMessages(messages) {
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if (!NO_SYSTEM_PROMPT_MODELS.includes(this.model)) return messages;
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// Replace the system message with a user/assistant message pair
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const formattedMessages = [];
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for (const message of messages) {
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if (message.role === "system") {
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formattedMessages.push({
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role: "user",
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content: message.content,
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});
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formattedMessages.push({
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role: "assistant",
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content: "Okay, I'll follow your instructions.",
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});
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continue;
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}
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formattedMessages.push(message);
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}
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return formattedMessages;
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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: this.cleanMsgs(this.formatMessages(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("Gemini chat: No results!");
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if (result.choices.length === 0)
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throw new Error("Gemini 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 = []) {
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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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this.cleanMsgs(this.formatMessages(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(this.formatMessages(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 {
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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 new APIError(
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error?.message
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? `${this.constructor.name} encountered an error while executing the request: ${error.message}`
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: "There was an error with the Gemini provider executing the request"
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);
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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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return 0;
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}
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}
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module.exports = GeminiProvider;
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