node-agency
Version:
A node package for building AI agents
379 lines • 19.6 kB
JavaScript
"use strict";
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());
});
};
var __asyncValues = (this && this.__asyncValues) || function (o) {
if (!Symbol.asyncIterator) throw new TypeError("Symbol.asyncIterator is not defined.");
var m = o[Symbol.asyncIterator], i;
return m ? m.call(o) : (o = typeof __values === "function" ? __values(o) : o[Symbol.iterator](), i = {}, verb("next"), verb("throw"), verb("return"), i[Symbol.asyncIterator] = function () { return this; }, i);
function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }
function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }
};
var __importDefault = (this && this.__importDefault) || function (mod) {
return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.Model = void 0;
const openai_1 = __importDefault(require("openai"));
const utils_1 = require("../utils");
const logger_1 = require("../logger");
function isParseableJson(str) {
try {
return JSON.parse(str);
}
catch (e) {
return null;
}
}
class Model {
constructor(options) {
this.history = [];
this.selfReflected = 0;
this.parallelToolCalls = false;
this.isManager = false;
this.model = "gpt-3.5-turbo";
this.selfReflect = true;
const { parallelToolCalls, OPENAI_API_KEY, model, selfReflect } = options || {};
const openai = new openai_1.default({
apiKey: OPENAI_API_KEY || process.env.OPENAI_API_KEY,
});
this.openai = openai;
this.parallelToolCalls = parallelToolCalls || false;
this.model = model || this.model;
this.selfReflect = selfReflect !== null && selfReflect !== void 0 ? selfReflect : true;
}
call(systemMessage, prompt, tools, context) {
return __awaiter(this, void 0, void 0, function* () {
prompt.content =
prompt.content +
(context
? "\n\n## This is results from your coworkers to help you with your task:\n" +
context
: "");
// console.log("-----------------");
// console.log("Prompt: ", prompt.content);
// console.log("-----------------");
// debugger;
this.history.push(prompt);
const messages = [
{
role: "system",
content: systemMessage,
},
...this.history,
];
try {
const message = yield this.callGPT(messages, tools);
this.history.push({
role: "assistant",
content: message.content,
tool_calls: message.tool_calls,
});
if (message.tool_calls) {
if (message.content) {
(0, logger_1.Logger)({
type: "info",
payload: "\n\n" + message.content + "\n\n",
});
}
const { tool_calls } = message;
const toolMessagesResolved = [];
const coWorkerCalls = tool_calls.filter((tool_call) => {
return (tool_call.function.name === "delegate_task" ||
tool_call.function.name === "ask_question");
});
if (this.parallelToolCalls && !this.isManager) {
const filteredCalls = tool_calls.filter((tool_call) => {
return (tool_call.function.name !== "delegate_task" &&
tool_call.function.name !== "ask_question");
});
const toolMessagePromises = filteredCalls.map((tool_call) => __awaiter(this, void 0, void 0, function* () {
return this.processingToolCall(tool_call);
}));
const toolMessagesSettled = yield Promise.allSettled(toolMessagePromises);
for (const toolMessage of toolMessagesSettled) {
if (toolMessage.status === "fulfilled") {
toolMessagesResolved.push(toolMessage.value);
}
}
for (const tool_call of coWorkerCalls) {
const toolMessage = yield this.processingToolCall(tool_call);
toolMessagesResolved.push(toolMessage);
}
}
else {
for (const tool_call of tool_calls) {
const toolMessage = yield this.processingToolCall(tool_call);
toolMessagesResolved.push(toolMessage);
}
}
const allMessagesHasResvoled = tool_calls.every((message) => {
return toolMessagesResolved.find((toolMessage) => toolMessage.tool_call_id === message.id);
});
if (!allMessagesHasResvoled) {
const missingToolCalls = tool_calls.filter((message) => {
return !toolMessagesResolved.find((toolMessage) => {
toolMessage.tool_call_id === message.id;
});
});
throw new Error("Failed to resolve all tool calls Missing: " +
missingToolCalls
.map((message) => `Name: '${message.function.name}', ID:${message.id}`)
.join(", "));
}
const lastMessage = toolMessagesResolved[toolMessagesResolved.length - 1];
const allButLastMessage = toolMessagesResolved.slice(0, toolMessagesResolved.length - 1);
this.history.push(...allButLastMessage);
return this.call(systemMessage, lastMessage, tools);
}
// if (message.content && !message.content.includes("<CONTINUE>")) {
// const maxRuntime = new Date().getTime() + 1000 * 60 * 5;
// let currentTime = new Date().getTime();
// let currentStep = "plan";
// while (currentStep === "plan" && currentTime < maxRuntime) {
// const plan = await this.call(
// systemMessage,
// {
// role: "user",
// content:
// "Plan your next steps, when you are ready, if there are no more steps to take then indicate you are done with <CONTINUE> at the very end of your response.",
// },
// tools
// );
// if (!plan.includes("<CONTINUE>")) {
// message.content = plan;
// currentTime = new Date().getTime();
// } else {
// message.content = plan.replace("<CONTINUE>", "");
// currentStep = "execute";
// }
// }
// }
return message.content || "Unknown Error Occurred, Please try again.";
}
catch (error) {
console.error(error);
throw new Error("Failed to call GPT-3");
}
});
}
callStream(systemMessage, prompt, callback, tools, context) {
return __awaiter(this, void 0, void 0, function* () {
prompt.content =
prompt.content +
(context
? "\n\nHere is further context to help you with your task:\n" + context
: "");
this.history.push(prompt);
const messages = [
{
role: "system",
content: systemMessage,
},
...this.history,
];
try {
const message = yield this.callGPTStream(messages, callback, tools);
return message;
}
catch (error) {
console.error(error);
throw new Error("Failed to call GPT-3");
}
});
}
processingToolCall(tool_call) {
return __awaiter(this, void 0, void 0, function* () {
const { name, arguments: args } = tool_call.function;
(0, logger_1.Logger)({
type: "function",
payload: JSON.stringify({
name,
params: args,
}),
});
const result = yield (0, utils_1.callFunction)(name, args);
const toolMessage = {
role: "tool",
tool_call_id: tool_call.id,
content: JSON.stringify({ result }),
};
return toolMessage;
});
}
callGPT(messages_1, tools_1) {
return __awaiter(this, arguments, void 0, function* (messages, tools, reflected = false) {
try {
const gptResponse = yield this.openai.chat.completions.create({
model: this.model,
messages,
tools: tools,
stream: false,
});
const { choices: [reply], usage, } = gptResponse;
const { message } = reply;
if (this.selfReflect && reflected && this.selfReflected >= 3) {
(0, logger_1.Logger)({ type: "warn", payload: "Self-Reflection Limit Reached\n\n" });
}
if (this.selfReflect &&
!reflected &&
message.content &&
this.selfReflected < 3 &&
!message.tool_calls) {
(0, logger_1.Logger)({
type: "info",
payload: `Self-Reflecting On Output (${this.selfReflected})...\n\n`,
});
this.selfReflected++;
return this.callGPT([
...messages,
message,
{
role: "user",
content: "Reflect on your response, find ways to improve it, respond with only the improved version, with no mention of the reflection process, or changes made.",
},
], tools, true);
}
return message;
}
catch (error) {
console.error(error);
console.debug("History: ", this.history);
throw new Error("Failed to call GPT-3");
}
});
}
callGPTStream(messages, callback, tools) {
return __awaiter(this, void 0, void 0, function* () {
const gptResponse = yield this.openai.chat.completions.create({
model: this.model,
messages,
tools: tools,
stream: true,
});
const _this = this;
const toolCalls = [];
const toolMessages = [];
const stream = new ReadableStream({
start(controller) {
return __awaiter(this, void 0, void 0, function* () {
var _a, e_1, _b, _c, _d, e_2, _e, _f;
var _g, _h, _j, _k, _l, _m, _o;
let currentMessage = "";
try {
for (var _p = true, gptResponse_1 = __asyncValues(gptResponse), gptResponse_1_1; gptResponse_1_1 = yield gptResponse_1.next(), _a = gptResponse_1_1.done, !_a; _p = true) {
_c = gptResponse_1_1.value;
_p = false;
const value = _c;
const choice = value.choices[0];
const delta = choice.delta;
if (delta.tool_calls != null) {
for (const toolCallDelta of delta.tool_calls) {
const index = toolCallDelta.index;
if (toolCalls[index] == null) {
if (toolCallDelta.type !== "function") {
continue;
}
if (toolCallDelta.id == null) {
continue;
}
if (((_g = toolCallDelta.function) === null || _g === void 0 ? void 0 : _g.name) == null) {
continue;
}
if (toolCallDelta.function &&
toolCallDelta.id &&
toolCallDelta.function.name) {
toolCalls[index] = {
id: toolCallDelta.id,
type: "function",
function: {
name: toolCallDelta.function.name,
arguments: (_h = toolCallDelta.function.arguments) !== null && _h !== void 0 ? _h : "",
},
};
}
continue;
}
const toolCall = toolCalls[index];
if (((_j = toolCallDelta.function) === null || _j === void 0 ? void 0 : _j.arguments) != null) {
toolCall.function.arguments +=
(_l = (_k = toolCallDelta.function) === null || _k === void 0 ? void 0 : _k.arguments) !== null && _l !== void 0 ? _l : "";
}
// check if tool call is complete
if (((_m = toolCall.function) === null || _m === void 0 ? void 0 : _m.name) == null ||
((_o = toolCall.function) === null || _o === void 0 ? void 0 : _o.arguments) == null ||
!isParseableJson(toolCall.function.arguments)) {
continue;
}
(0, logger_1.Logger)({
type: "function",
payload: JSON.stringify({
name: toolCall.function.name,
params: toolCall.function.arguments,
}),
});
const toolMessage = yield _this.processingToolCall(toolCall);
const toolRequestMessage = {
role: "assistant",
content: null,
tool_calls: [toolCall],
};
toolMessages.push(toolRequestMessage, toolMessage);
continue;
}
}
else if (delta.content != null) {
controller.enqueue(value.choices[0].delta.content);
currentMessage += value.choices[0].delta.content;
}
}
}
catch (e_1_1) { e_1 = { error: e_1_1 }; }
finally {
try {
if (!_p && !_a && (_b = gptResponse_1.return)) yield _b.call(gptResponse_1);
}
finally { if (e_1) throw e_1.error; }
}
if (currentMessage && !toolMessages.length) {
_this.history.push({
role: "assistant",
content: currentMessage,
});
callback(currentMessage);
}
if (toolMessages.length) {
_this.history.push(...toolMessages);
const newStream = yield _this.callGPTStream(_this.history, callback, tools);
try {
for (var _q = true, newStream_1 = __asyncValues(newStream), newStream_1_1; newStream_1_1 = yield newStream_1.next(), _d = newStream_1_1.done, !_d; _q = true) {
_f = newStream_1_1.value;
_q = false;
const newPart = _f;
controller.enqueue(newPart);
}
}
catch (e_2_1) { e_2 = { error: e_2_1 }; }
finally {
try {
if (!_q && !_d && (_e = newStream_1.return)) yield _e.call(newStream_1);
}
finally { if (e_2) throw e_2.error; }
}
}
controller.close();
});
},
});
return (0, utils_1.readableStreamAsyncIterable)(stream);
});
}
}
exports.Model = Model;
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