mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-19 12:40:09 +01:00
Enabled use of @agent
(and skills) via dev API calls (#2161)
* Use `@agent` via dev API * Move EphemeralEventListener to same file as agent
This commit is contained in:
parent
fdc3add53c
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87
server/utils/agents/aibitat/plugins/http-socket.js
Normal file
87
server/utils/agents/aibitat/plugins/http-socket.js
Normal file
@ -0,0 +1,87 @@
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const chalk = require("chalk");
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const { RetryError } = require("../error");
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const { Telemetry } = require("../../../../models/telemetry");
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/**
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* HTTP Interface plugin for Aibitat to emulate a websocket interface in the agent
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* framework so we dont have to modify the interface for passing messages and responses
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* in REST or WSS.
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*/
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const httpSocket = {
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name: "httpSocket",
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startupConfig: {
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params: {
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handler: {
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required: true,
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},
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muteUserReply: {
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required: false,
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default: true,
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},
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introspection: {
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required: false,
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default: true,
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},
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},
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},
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plugin: function ({
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handler,
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muteUserReply = true, // Do not post messages to "USER" back to frontend.
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introspection = false, // when enabled will attach socket to Aibitat object with .introspect method which reports status updates to frontend.
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}) {
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return {
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name: this.name,
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setup(aibitat) {
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aibitat.onError(async (error) => {
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if (!!error?.message) {
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console.error(chalk.red(` error: ${error.message}`), error);
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aibitat.introspect(
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`Error encountered while running: ${error.message}`
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);
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}
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if (error instanceof RetryError) {
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console.error(chalk.red(` retrying in 60 seconds...`));
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setTimeout(() => {
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aibitat.retry();
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}, 60_000);
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return;
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}
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});
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aibitat.introspect = (messageText) => {
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if (!introspection) return; // Dump thoughts when not wanted.
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handler.send(
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JSON.stringify({ type: "statusResponse", content: messageText })
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);
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};
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// expose function for sockets across aibitat
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// type param must be set or else msg will not be shown or handled in UI.
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aibitat.socket = {
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send: (type = "__unhandled", content = "") => {
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handler.send(JSON.stringify({ type, content }));
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},
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};
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// We can only receive one message response with HTTP
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// so we end on first response.
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aibitat.onMessage((message) => {
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if (message.from !== "USER")
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Telemetry.sendTelemetry("agent_chat_sent");
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if (message.from === "USER" && muteUserReply) return;
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handler.send(JSON.stringify(message));
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handler.close();
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});
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aibitat.onTerminate(() => {
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handler.close();
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});
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},
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};
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},
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};
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module.exports = {
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httpSocket,
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};
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@ -22,9 +22,25 @@ const WORKSPACE_AGENT = {
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AgentPlugins.webScraping.name, // Collector web-scraping
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];
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const _setting = (
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await SystemSettings.get({ label: "default_agent_skills" })
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)?.value;
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return {
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role: Provider.systemPrompt(provider),
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functions: [
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...defaultFunctions,
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...(await agentSkillsFromSystemSettings()),
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],
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};
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},
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};
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/**
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* Fetches and preloads the names/identifiers for plugins that will be dynamically
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* loaded later
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* @returns {Promise<string[]>}
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*/
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async function agentSkillsFromSystemSettings() {
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const systemFunctions = [];
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const _setting = (await SystemSettings.get({ label: "default_agent_skills" }))
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?.value;
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safeJsonParse(_setting, []).forEach((skillName) => {
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if (!AgentPlugins.hasOwnProperty(skillName)) return;
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@ -33,7 +49,7 @@ const WORKSPACE_AGENT = {
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// need to be named via `${parent}#${child}` naming convention
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if (Array.isArray(AgentPlugins[skillName].plugin)) {
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for (const subPlugin of AgentPlugins[skillName].plugin) {
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defaultFunctions.push(
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systemFunctions.push(
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`${AgentPlugins[skillName].name}#${subPlugin.name}`
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);
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}
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@ -41,17 +57,13 @@ const WORKSPACE_AGENT = {
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}
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// This is normal single-stage plugin
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defaultFunctions.push(AgentPlugins[skillName].name);
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systemFunctions.push(AgentPlugins[skillName].name);
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});
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return {
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role: Provider.systemPrompt(provider),
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functions: defaultFunctions,
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};
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},
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};
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return systemFunctions;
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}
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module.exports = {
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USER_AGENT,
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WORKSPACE_AGENT,
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agentSkillsFromSystemSettings,
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};
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351
server/utils/agents/ephemeral.js
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351
server/utils/agents/ephemeral.js
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@ -0,0 +1,351 @@
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const AIbitat = require("./aibitat");
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const AgentPlugins = require("./aibitat/plugins");
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const { httpSocket } = require("./aibitat/plugins/http-socket.js");
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const { WorkspaceChats } = require("../../models/workspaceChats");
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const { safeJsonParse } = require("../http");
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const {
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USER_AGENT,
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WORKSPACE_AGENT,
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agentSkillsFromSystemSettings,
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} = require("./defaults");
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const { AgentHandler } = require(".");
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const {
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WorkspaceAgentInvocation,
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} = require("../../models/workspaceAgentInvocation");
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/**
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* This is an instance and functional Agent handler, but it does not utilize
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* sessions or websocket's and is instead a singular one-off agent run that does
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* not persist between invocations
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*/
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class EphemeralAgentHandler extends AgentHandler {
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#invocationUUID = null;
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#workspace = null;
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#userId = null;
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#threadId = null;
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#sessionId = null;
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#prompt = null;
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#funcsToLoad = [];
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aibitat = null;
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channel = null;
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provider = null;
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model = null;
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constructor({
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uuid,
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workspace,
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prompt,
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userId = null,
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threadId = null,
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sessionId = null,
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}) {
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super({ uuid });
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this.#invocationUUID = uuid;
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this.#workspace = workspace;
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this.#prompt = prompt;
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this.#userId = userId;
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this.#threadId = threadId;
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this.#sessionId = sessionId;
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}
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log(text, ...args) {
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console.log(`\x1b[36m[EphemeralAgentHandler]\x1b[0m ${text}`, ...args);
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}
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closeAlert() {
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this.log(`End ${this.#invocationUUID}::${this.provider}:${this.model}`);
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}
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async #chatHistory(limit = 10) {
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try {
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const rawHistory = (
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await WorkspaceChats.where(
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{
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workspaceId: this.#workspace.id,
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user_id: this.#userId || null,
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thread_id: this.#threadId || null,
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api_session_id: this.#sessionId,
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include: true,
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},
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limit,
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{ id: "desc" }
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)
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).reverse();
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const agentHistory = [];
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rawHistory.forEach((chatLog) => {
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agentHistory.push(
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{
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from: USER_AGENT.name,
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to: WORKSPACE_AGENT.name,
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content: chatLog.prompt,
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state: "success",
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},
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{
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from: WORKSPACE_AGENT.name,
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to: USER_AGENT.name,
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content: safeJsonParse(chatLog.response)?.text || "",
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state: "success",
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}
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);
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});
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return agentHistory;
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} catch (e) {
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this.log("Error loading chat history", e.message);
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return [];
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}
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}
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/**
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* Finds or assumes the model preference value to use for API calls.
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* If multi-model loading is supported, we use their agent model selection of the workspace
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* If not supported, we attempt to fallback to the system provider value for the LLM preference
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* and if that fails - we assume a reasonable base model to exist.
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* @returns {string} the model preference value to use in API calls
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*/
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#fetchModel() {
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if (!Object.keys(this.noProviderModelDefault).includes(this.provider))
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return this.#workspace.agentModel || this.providerDefault();
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// Provider has no reliable default (cant load many models) - so we need to look at system
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// for the model param.
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const sysModelKey = this.noProviderModelDefault[this.provider];
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if (!!sysModelKey)
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return process.env[sysModelKey] ?? this.providerDefault();
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// If all else fails - look at the provider default list
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return this.providerDefault();
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}
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#providerSetupAndCheck() {
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this.provider = this.#workspace.agentProvider;
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this.model = this.#fetchModel();
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this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`);
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this.checkSetup();
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}
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#attachPlugins(args) {
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for (const name of this.#funcsToLoad) {
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// Load child plugin
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if (name.includes("#")) {
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const [parent, childPluginName] = name.split("#");
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if (!AgentPlugins.hasOwnProperty(parent)) {
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this.log(
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`${parent} is not a valid plugin. Skipping inclusion to agent cluster.`
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);
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continue;
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}
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const childPlugin = AgentPlugins[parent].plugin.find(
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(child) => child.name === childPluginName
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);
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if (!childPlugin) {
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this.log(
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`${parent} does not have child plugin named ${childPluginName}. Skipping inclusion to agent cluster.`
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);
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continue;
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}
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const callOpts = this.parseCallOptions(
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args,
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childPlugin?.startupConfig?.params,
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name
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);
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this.aibitat.use(childPlugin.plugin(callOpts));
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this.log(
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`Attached ${parent}:${childPluginName} plugin to Agent cluster`
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);
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continue;
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}
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// Load single-stage plugin.
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if (!AgentPlugins.hasOwnProperty(name)) {
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this.log(
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`${name} is not a valid plugin. Skipping inclusion to agent cluster.`
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);
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continue;
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}
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const callOpts = this.parseCallOptions(
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args,
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AgentPlugins[name].startupConfig.params
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);
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const AIbitatPlugin = AgentPlugins[name];
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this.aibitat.use(AIbitatPlugin.plugin(callOpts));
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this.log(`Attached ${name} plugin to Agent cluster`);
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}
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}
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async #loadAgents() {
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// Default User agent and workspace agent
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this.log(`Attaching user and default agent to Agent cluster.`);
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this.aibitat.agent(USER_AGENT.name, await USER_AGENT.getDefinition());
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this.aibitat.agent(
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WORKSPACE_AGENT.name,
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await WORKSPACE_AGENT.getDefinition(this.provider)
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);
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this.#funcsToLoad = [
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AgentPlugins.docSummarizer.name,
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AgentPlugins.webScraping.name,
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...(await agentSkillsFromSystemSettings()),
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];
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}
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async init() {
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this.#providerSetupAndCheck();
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return this;
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}
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async createAIbitat(
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args = {
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handler,
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}
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) {
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this.aibitat = new AIbitat({
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provider: this.provider ?? "openai",
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model: this.model ?? "gpt-4o",
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chats: await this.#chatHistory(20),
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handlerProps: {
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log: this.log,
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},
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});
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// Attach HTTP response object if defined for chunk streaming.
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this.log(`Attached ${httpSocket.name} plugin to Agent cluster`);
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this.aibitat.use(
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httpSocket.plugin({
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handler: args.handler,
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muteUserReply: true,
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introspection: true,
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})
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);
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// Load required agents (Default + custom)
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await this.#loadAgents();
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// Attach all required plugins for functions to operate.
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this.#attachPlugins(args);
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}
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startAgentCluster() {
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return this.aibitat.start({
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from: USER_AGENT.name,
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to: this.channel ?? WORKSPACE_AGENT.name,
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content: this.#prompt,
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});
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}
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/**
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* Determine if the message provided is an agent invocation.
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* @param {{message:string}} parameters
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* @returns {boolean}
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*/
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static isAgentInvocation({ message }) {
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const agentHandles = WorkspaceAgentInvocation.parseAgents(message);
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if (agentHandles.length > 0) return true;
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return false;
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}
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}
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const EventEmitter = require("node:events");
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const { writeResponseChunk } = require("../helpers/chat/responses");
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/**
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* This is a special EventEmitter specifically used in the Aibitat agent handler
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* that enables us to use HTTP to relay all .introspect and .send events back to an
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* http handler instead of websockets, like we do on the frontend. This interface is meant to
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* mock a websocket interface for the methods used and bind them to an HTTP method so that the developer
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* API can invoke agent calls.
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*/
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class EphemeralEventListener extends EventEmitter {
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messages = [];
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constructor() {
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super();
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}
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send(jsonData) {
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const data = JSON.parse(jsonData);
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this.messages.push(data);
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this.emit("chunk", data);
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}
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close() {
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this.emit("closed");
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}
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/**
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* Compacts all messages in class and returns them in a condensed format.
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* @returns {{thoughts: string[], textResponse: string}}
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*/
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packMessages() {
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const thoughts = [];
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let textResponse = null;
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for (let msg of this.messages) {
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if (msg.type !== "statusResponse") {
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textResponse = msg.content;
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} else {
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thoughts.push(msg.content);
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}
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}
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return { thoughts, textResponse };
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}
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/**
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* Waits on the HTTP plugin to emit the 'closed' event from the agentHandler
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* so that we can compact and return all the messages in the current queue.
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* @returns {Promise<{thoughts: string[], textResponse: string}>}
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*/
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async waitForClose() {
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return new Promise((resolve) => {
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this.once("closed", () => resolve(this.packMessages()));
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});
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}
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/**
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* Streams the events with `writeResponseChunk` over HTTP chunked encoding
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* and returns on the close event emission.
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* ----------
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* DevNote: Agents do not stream so in here we are simply
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* emitting the thoughts and text response as soon as we get them.
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* @param {import("express").Response} response
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* @param {string} uuid - Unique identifier that is the same across chunks.
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* @returns {Promise<{thoughts: string[], textResponse: string}>}
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*/
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async streamAgentEvents(response, uuid) {
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const onChunkHandler = (data) => {
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if (data.type === "statusResponse") {
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return writeResponseChunk(response, {
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id: uuid,
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type: "agentThought",
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thought: data.content,
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sources: [],
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attachments: [],
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close: false,
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error: null,
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});
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}
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return writeResponseChunk(response, {
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id: uuid,
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type: "textResponse",
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textResponse: data.content,
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sources: [],
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attachments: [],
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close: true,
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error: null,
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});
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};
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this.on("chunk", onChunkHandler);
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// Wait for close and after remove chunk listener
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return this.waitForClose().then((closedResponse) => {
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this.removeListener("chunk", onChunkHandler);
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return closedResponse;
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});
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}
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}
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module.exports = { EphemeralAgentHandler, EphemeralEventListener };
|
@ -10,7 +10,7 @@ const { USER_AGENT, WORKSPACE_AGENT } = require("./defaults");
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class AgentHandler {
|
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#invocationUUID;
|
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#funcsToLoad = [];
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#noProviderModelDefault = {
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noProviderModelDefault = {
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azure: "OPEN_MODEL_PREF",
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lmstudio: "LMSTUDIO_MODEL_PREF",
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textgenwebui: null, // does not even use `model` in API req
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@ -74,7 +74,7 @@ class AgentHandler {
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}
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}
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#checkSetup() {
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checkSetup() {
|
||||
switch (this.provider) {
|
||||
case "openai":
|
||||
if (!process.env.OPEN_AI_KEY)
|
||||
@ -163,7 +163,7 @@ class AgentHandler {
|
||||
}
|
||||
}
|
||||
|
||||
#providerDefault() {
|
||||
providerDefault() {
|
||||
switch (this.provider) {
|
||||
case "openai":
|
||||
return "gpt-4o";
|
||||
@ -210,24 +210,24 @@ class AgentHandler {
|
||||
* @returns {string} the model preference value to use in API calls
|
||||
*/
|
||||
#fetchModel() {
|
||||
if (!Object.keys(this.#noProviderModelDefault).includes(this.provider))
|
||||
return this.invocation.workspace.agentModel || this.#providerDefault();
|
||||
if (!Object.keys(this.noProviderModelDefault).includes(this.provider))
|
||||
return this.invocation.workspace.agentModel || this.providerDefault();
|
||||
|
||||
// Provider has no reliable default (cant load many models) - so we need to look at system
|
||||
// for the model param.
|
||||
const sysModelKey = this.#noProviderModelDefault[this.provider];
|
||||
const sysModelKey = this.noProviderModelDefault[this.provider];
|
||||
if (!!sysModelKey)
|
||||
return process.env[sysModelKey] ?? this.#providerDefault();
|
||||
return process.env[sysModelKey] ?? this.providerDefault();
|
||||
|
||||
// If all else fails - look at the provider default list
|
||||
return this.#providerDefault();
|
||||
return this.providerDefault();
|
||||
}
|
||||
|
||||
#providerSetupAndCheck() {
|
||||
this.provider = this.invocation.workspace.agentProvider;
|
||||
this.model = this.#fetchModel();
|
||||
this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`);
|
||||
this.#checkSetup();
|
||||
this.checkSetup();
|
||||
}
|
||||
|
||||
async #validInvocation() {
|
||||
@ -239,7 +239,7 @@ class AgentHandler {
|
||||
this.invocation = invocation ?? null;
|
||||
}
|
||||
|
||||
#parseCallOptions(args, config = {}, pluginName) {
|
||||
parseCallOptions(args, config = {}, pluginName) {
|
||||
const callOpts = {};
|
||||
for (const [param, definition] of Object.entries(config)) {
|
||||
if (
|
||||
@ -280,7 +280,7 @@ class AgentHandler {
|
||||
continue;
|
||||
}
|
||||
|
||||
const callOpts = this.#parseCallOptions(
|
||||
const callOpts = this.parseCallOptions(
|
||||
args,
|
||||
childPlugin?.startupConfig?.params,
|
||||
name
|
||||
@ -300,7 +300,7 @@ class AgentHandler {
|
||||
continue;
|
||||
}
|
||||
|
||||
const callOpts = this.#parseCallOptions(
|
||||
const callOpts = this.parseCallOptions(
|
||||
args,
|
||||
AgentPlugins[name].startupConfig.params
|
||||
);
|
||||
|
@ -4,6 +4,11 @@ const { WorkspaceChats } = require("../../models/workspaceChats");
|
||||
const { getVectorDbClass, getLLMProvider } = require("../helpers");
|
||||
const { writeResponseChunk } = require("../helpers/chat/responses");
|
||||
const { chatPrompt, sourceIdentifier, recentChatHistory } = require("./index");
|
||||
const {
|
||||
EphemeralAgentHandler,
|
||||
EphemeralEventListener,
|
||||
} = require("../agents/ephemeral");
|
||||
const { Telemetry } = require("../../models/telemetry");
|
||||
|
||||
/**
|
||||
* @typedef ResponseObject
|
||||
@ -37,6 +42,59 @@ async function chatSync({
|
||||
}) {
|
||||
const uuid = uuidv4();
|
||||
const chatMode = mode ?? "chat";
|
||||
|
||||
if (EphemeralAgentHandler.isAgentInvocation({ message })) {
|
||||
await Telemetry.sendTelemetry("agent_chat_started");
|
||||
|
||||
// Initialize the EphemeralAgentHandler to handle non-continuous
|
||||
// conversations with agents since this is over REST.
|
||||
const agentHandler = new EphemeralAgentHandler({
|
||||
uuid,
|
||||
workspace,
|
||||
prompt: message,
|
||||
userId: user?.id || null,
|
||||
threadId: thread?.id || null,
|
||||
sessionId,
|
||||
});
|
||||
|
||||
// Establish event listener that emulates websocket calls
|
||||
// in Aibitat so that we can keep the same interface in Aibitat
|
||||
// but use HTTP.
|
||||
const eventListener = new EphemeralEventListener();
|
||||
await agentHandler.init();
|
||||
await agentHandler.createAIbitat({ handler: eventListener });
|
||||
agentHandler.startAgentCluster();
|
||||
|
||||
// The cluster has started and now we wait for close event since
|
||||
// this is a synchronous call for an agent, so we return everything at once.
|
||||
// After this, we conclude the call as we normally do.
|
||||
return await eventListener
|
||||
.waitForClose()
|
||||
.then(async ({ thoughts, textResponse }) => {
|
||||
await WorkspaceChats.new({
|
||||
workspaceId: workspace.id,
|
||||
prompt: String(message),
|
||||
response: {
|
||||
text: textResponse,
|
||||
sources: [],
|
||||
type: chatMode,
|
||||
thoughts,
|
||||
},
|
||||
include: false,
|
||||
apiSessionId: sessionId,
|
||||
});
|
||||
return {
|
||||
id: uuid,
|
||||
type: "textResponse",
|
||||
sources: [],
|
||||
close: true,
|
||||
error: null,
|
||||
textResponse,
|
||||
thoughts,
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
const LLMConnector = getLLMProvider({
|
||||
provider: workspace?.chatProvider,
|
||||
model: workspace?.chatModel,
|
||||
@ -257,6 +315,58 @@ async function streamChat({
|
||||
}) {
|
||||
const uuid = uuidv4();
|
||||
const chatMode = mode ?? "chat";
|
||||
|
||||
if (EphemeralAgentHandler.isAgentInvocation({ message })) {
|
||||
await Telemetry.sendTelemetry("agent_chat_started");
|
||||
|
||||
// Initialize the EphemeralAgentHandler to handle non-continuous
|
||||
// conversations with agents since this is over REST.
|
||||
const agentHandler = new EphemeralAgentHandler({
|
||||
uuid,
|
||||
workspace,
|
||||
prompt: message,
|
||||
userId: user?.id || null,
|
||||
threadId: thread?.id || null,
|
||||
sessionId,
|
||||
});
|
||||
|
||||
// Establish event listener that emulates websocket calls
|
||||
// in Aibitat so that we can keep the same interface in Aibitat
|
||||
// but use HTTP.
|
||||
const eventListener = new EphemeralEventListener();
|
||||
await agentHandler.init();
|
||||
await agentHandler.createAIbitat({ handler: eventListener });
|
||||
agentHandler.startAgentCluster();
|
||||
|
||||
// The cluster has started and now we wait for close event since
|
||||
// and stream back any results we get from agents as they come in.
|
||||
return eventListener
|
||||
.streamAgentEvents(response, uuid)
|
||||
.then(async ({ thoughts, textResponse }) => {
|
||||
console.log({ thoughts, textResponse });
|
||||
await WorkspaceChats.new({
|
||||
workspaceId: workspace.id,
|
||||
prompt: String(message),
|
||||
response: {
|
||||
text: textResponse,
|
||||
sources: [],
|
||||
type: chatMode,
|
||||
thoughts,
|
||||
},
|
||||
include: false,
|
||||
apiSessionId: sessionId,
|
||||
});
|
||||
writeResponseChunk(response, {
|
||||
uuid,
|
||||
type: "finalizeResponseStream",
|
||||
textResponse,
|
||||
thoughts,
|
||||
close: true,
|
||||
error: false,
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
const LLMConnector = getLLMProvider({
|
||||
provider: workspace?.chatProvider,
|
||||
model: workspace?.chatModel,
|
||||
|
Loading…
Reference in New Issue
Block a user