auto-gpt-ts
Version:
my take of Auto-GPT in typescript
70 lines • 3.3 kB
JavaScript
;
var __decorate = (this && this.__decorate) || function (decorators, target, key, desc) {
var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;
if (typeof Reflect === "object" && typeof Reflect.decorate === "function") r = Reflect.decorate(decorators, target, key, desc);
else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;
return c > 3 && r && Object.defineProperty(target, key, r), r;
};
var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
return new (P || (P = Promise))(function (resolve, reject) {
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
step((generator = generator.apply(thisArg, _arguments || [])).next());
});
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.AgentManager = void 0;
const config_1 = require("../config/config");
const llm_utils_1 = require("../llm/llm-utils");
const singelton_1 = require("../singelton");
let AgentManager = class AgentManager {
constructor() {
this.nextKey = 0;
this.agents = {};
this.cfg = new config_1.Config();
}
// Create new GPT agent
// TODO: Centralise use of create_chat_completion() to globally enforce token limit
createAgent(task, prompt, model) {
return __awaiter(this, void 0, void 0, function* () {
const messages = [{ role: "user", content: prompt }];
// Start GPT instance
let agentReply = yield (0, llm_utils_1.createChatCompletion)(messages, model);
messages.push({ role: "assistant", content: agentReply });
const key = this.nextKey;
this.nextKey += 1;
this.agents[key] = [task, messages, model];
return [key, agentReply];
});
}
messageAgent(key, message) {
return __awaiter(this, void 0, void 0, function* () {
const [_, messages, model] = this.agents[Number(key)];
// Add user message to message history before sending to agent
messages.push({ role: "user", content: message });
// Start GPT instance
let agentReply = yield (0, llm_utils_1.createChatCompletion)(messages, model);
messages.push({ role: "assistant", content: agentReply });
return agentReply;
});
}
listAgents() {
return Object.entries(this.agents).map(([key, [task]]) => [key, task]);
}
deleteAgent(key) {
try {
delete this.agents[Number(key)];
return true;
}
catch (_a) {
return false;
}
}
};
AgentManager = __decorate([
singelton_1.Singleton
], AgentManager);
exports.AgentManager = AgentManager;
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