mirror of
https://github.com/kamranahmedse/developer-roadmap.git
synced 2025-08-24 09:55:57 +02:00
538 lines
16 KiB
JavaScript
538 lines
16 KiB
JavaScript
import OpenAI from 'openai';
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import path from 'path';
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import fs from 'fs';
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import { fileURLToPath } from 'url';
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import { dirname } from 'path';
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const __filename = fileURLToPath(import.meta.url);
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const __dirname = dirname(__filename);
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/**
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* @typedef {Object} Node
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* @property {string} id - The unique identifier for the node
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* @property {string} text - The text content of the node
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*/
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const roadmapId = 'ai-agents';
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/** @type {Node[]} */
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const nodes = [
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{
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id: 'ZF5_5Y5zqa75Ov22JACX6',
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text: 'AI Agents > Transformer Models and LLMs',
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},
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{
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id: 'GAjuWyJl9CI1nqXBp6XCf',
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text: 'AI Agents > LLM Fundamentals > Model Mechanis > Tokenization',
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},
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{
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id: 'dyn1LSioema-Bf9lLTgUZ',
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text: 'AI Agents > LLM Fundamentals > Model Mechanis > Context Windows',
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},
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{
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id: '1fiWPBV99E2YncqdCgUw2',
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text: 'AI Agents > LLM Fundamentals > Model Mechanis > Token Based Pricing',
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},
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{
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id: 'L1zL1GzqjSAjF06pIIXhy',
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text: 'AI Agents > LLM Fundamentals > Generation Controls > Temperature',
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},
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{
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id: 'icbp1NjurQfdM0dHnz6v2',
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text: 'AI Agents > LLM Fundamentals > Generation Controls > Top-p',
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},
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{
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id: 'z_N-Y0zGkv8_qHPuVtimL',
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text: 'AI Agents > LLM Fundamentals > Generation Controls > Frequency Penalty',
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},
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{
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id: 'Vd8ycw8pW-ZKvg5WYFtoh',
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text: 'AI Agents > LLM Fundamentals > Generation Controls > Presence Penalty',
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},
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{
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id: 'K0G-Lw069jXUJwZqHtybd',
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text: 'AI Agents > LLM Fundamentals > Generation Controls > Stopping Criteria',
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},
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{
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id: 'Bn_BkthrVX_vOuwQzvPZa',
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text: 'AI Agents > LLM Fundamentals > Generation Controls > Max Length',
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},
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{
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id: 'DSJAhQhc1dQmBHQ8ZkTau',
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text: 'AI Agents > Model Families and Licences > Open Weight Models',
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},
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{
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id: 'tJYmEDDwK0LtEux-kwp9B',
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text: 'AI Agents > Model Families and Licences > Closed Weight Models',
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},
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{
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id: 'i2NE6haX9-7mdoV5LQ3Ah',
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text: 'AI Agents > Understand the Basics > Streamed vs Unstreamed Responses',
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},
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{
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id: 'N3yZfUxphxjiupqGpyaS9',
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text: 'AI Agents > Understand the Basics > Reasoning vs Standard Models',
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},
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{
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id: '5OW_6o286mj470ElFyJ_5',
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text: 'AI Agents > Understand the Basics > Fine-tuning vs Prompt Engineering',
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},
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{
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id: 'UIm54UmICKgep6s8Itcyv',
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text: 'AI Agents > Understand the Basics > Embeddings and Vector Search',
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},
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{
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id: 'qwVQOwBTLA2yUgRISzC8k',
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text: 'AI Agents > Understand the Basics > Understand the Basics of RAG',
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},
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{
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id: 'B8dzg61TGaknuruBgkEJd',
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text: 'AI Agents > Understand the Basics > Pricing of Common Models',
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},
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{
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id: 'aFZAm44nP5NefX_9TpT0A',
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text: 'AI Agents > AI Agents 101 > What are AI Agents?',
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},
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{
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id: '2zsOUWJQ8e7wnoHmq1icG',
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text: 'AI Agents > AI Agents 101 > What are Tools?',
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},
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{
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id: 'Eih4eybuYB3C2So8K0AT3',
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text: 'AI Agents > AI Agents 101 > Agent Loop',
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},
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{
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id: 'LU76AhCYDjxdBhpMQ4eMU',
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text: 'AI Agents > AI Agents 101 > Agent Loop > Perception / User Input',
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},
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{
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id: 'ycPRgRYR4lEBQr_xxHKnM',
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text: 'AI Agents > AI Agents 101 > Agent Loop > Reason and Plan',
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},
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{
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id: 'sHYd4KsKlmw5Im3nQ19W8',
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text: 'AI Agents > AI Agents 101 > Agent Loop > Acting / Tool Invocation',
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},
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{
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id: 'ZJTrun3jK3zBGOTm1jdMI',
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text: 'AI Agents > AI Agents 101 > Agent Loop > Observation & Reflection',
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},
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{
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id: 'PPdAutqJF5G60Eg9lYBND',
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text: 'AI Agents > AI Agents 101 > Example Usecases > Personal assistant',
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},
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{
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id: 'PK8w31GlvtmAuU92sHaqr',
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text: 'AI Agents > AI Agents 101 > Example Usecases > Code generation',
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},
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{
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id: 'wKYEaPWNsR30TIpHaxSsq',
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text: 'AI Agents > AI Agents 101 > Example Usecases > Data analysis',
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},
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{
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id: '5oLc-235bvKhApxzYFkEc',
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text: 'AI Agents > AI Agents 101 > Example Usecases > Web Scraping / Crawling',
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},
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{
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id: 'ok8vN7VtCgyef5x6aoQaL',
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text: 'AI Agents > AI Agents 101 > Example Usecases > NPC / Game AI',
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},
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{
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id: 'Y8EqzFx3qxtrSh7bWbbV8',
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text: 'AI Agents > Prompt Engineering > What is Prompt Engineering',
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},
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{
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id: 'qFKFM2qNPEN7EoD0V-1SM',
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text: 'AI Agents > Prompt Engineering > Writing Good Prompts > Be specific in what you want',
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},
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{
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id: '6I42CoeWX-kkFXTKAY7rw',
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text: 'AI Agents > Prompt Engineering > Writing Good Prompts > Provide additional context',
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},
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{
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id: 'sUwdtOX550tSdceaeFPmF',
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text: 'AI Agents > Prompt Engineering > Writing Good Prompts > Use relevant technical terms',
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},
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{
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id: 'yulzE4ZNLhXOgHhG7BtZQ',
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text: 'AI Agents > Prompt Engineering > Writing Good Prompts > Use Examples in your Prompt',
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},
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{
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id: 'noTuUFnHSBzn7GKG9UZEi',
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text: 'AI Agents > Prompt Engineering > Writing Good Prompts > Iterate and Test your Prompts',
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},
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{
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id: 'wwHHlEoPAx0TLxbtY6nMA',
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text: 'AI Agents > Prompt Engineering > Writing Good Prompts > Specify Length, format etc',
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},
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{
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id: 'qakbxB8xe7Y8gejC5cZnK',
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text: 'AI Agents > AI Agents 101 > Tools / Actions > Tool Definition',
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},
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{
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id: 'kBtqT8AduLoYDWopj-V9_',
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text: 'AI Agents > Tools / Actions > Examples of Tools > Web Search',
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},
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{
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id: 'mS0EVCkWuPN_GkVPng4A2',
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text: 'AI Agents > Tools / Actions > Examples of Tools > Code Execution / REPL',
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},
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{
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id: 'sV1BnA2-qBnXoKpUn-8Ub',
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text: 'AI Agents > Tools / Actions > Examples of Tools > Database Queries',
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},
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{
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id: '52qxjZILV-X1isup6dazC',
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text: 'AI Agents > Tools / Actions > Examples of Tools > API Requests > Tools / Actions > Examples of Tools > API Requests',
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},
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{
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id: 'qaNr5I-NQPnfrRH7ynGTl',
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text: 'AI Agents > Tools / Actions > Examples of Tools > Email / Slack / SMS',
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},
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{
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id: 'BoJqZvdGam4cd6G6yK2IV',
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text: 'AI Agents > Tools / Actions > Examples of Tools > File System Access',
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},
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{
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id: '1B0IqRNYdtbHDi1jHSXuI',
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text: 'AI Agents > Model Context Protocol (MCP)',
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},
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{
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id: '9FryAIrWRHh8YlzKX3et5',
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text: 'AI Agents > Model Context Protocol (MCP) > Core Components > MCP Hosts',
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},
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{
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id: 'CGVstUxVXLJcYZrwk3iNQ',
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text: 'AI Agents > Model Context Protocol (MCP) > Core Components > MCP Client',
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},
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{
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id: 'yv_-87FVM7WKn5iv6LW9q',
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text: 'AI Agents > Model Context Protocol (MCP) > Core Components > MCP Servers',
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},
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{
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id: '1NXIN-Hbjl5rPy_mqxQYW',
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text: 'AI Agents > Model Context Protocol (MCP) > Creating MCP Servers',
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},
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{
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id: 'iBtJp24F_kJE3YlBsW60s',
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text: 'AI Agents > Model Context Protocol (MCP) > Creating MCP Servers > Deployment Modes > Local Desktop',
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},
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{
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id: 'dHNMX3_t1KSDdAWqgdJXv',
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text: 'AI Agents > Model Context Protocol (MCP) > Creating MCP Servers > Deployment Modes > Remote / Cloud',
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},
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{
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id: 'TBH_DZTAfR8Daoh-njNFC',
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text: 'AI Agents > Agent Memory > What is Agent Memory?',
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},
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{
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id: 'M3U6RfIqaiut2nuOibY8W',
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text: 'AI Agents > Agent Memory > Short Term Memory',
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},
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{
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id: 'Ue633fz6Xu2wa2-KOAtdP',
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text: 'AI Agents > Agent Memory > What is Agent Memory? > Long Term Memory',
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},
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{
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id: 'EfCCNqLMJpWKKtamUa5gK',
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text: 'AI Agents > Agent Memory > What is Agent Memory? > Episodic vs Semantic Memory',
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},
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{
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id: 'wkS4yOJ3JdZQE_yBID8K7',
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text: 'AI Agents > Agent Memory > What is Agent Memory? > Maintaining Memory > RAG and Vector Databases',
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},
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{
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id: 'QJqXHV8VHPTnfYfmKPzW7',
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text: 'AI Agents > Agent Memory > What is Agent Memory? > Maintaining Memory > User Profile Storage',
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},
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{
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id: 'jTDC19BTWCqxqMizrIJHr',
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text: 'AI Agents > Agent Memory > Maintaining Memory > Summarization / Compression',
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},
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{
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id: 'm-97m7SI0XpBnhEE8-_1S',
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text: 'AI Agents > Agent Memory > Maintaining Memory > Forgetting / Aging Strategies',
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},
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{
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id: 'cW8O4vLLKEG-Q0dE8E5Zp',
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text: 'AI Agents > Agent Architectures > Common Architectures > RAG Agent',
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},
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{
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id: '53xDks6JQ33fHMa3XcuCd',
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text: 'AI Agents > Agent Architectures > Common Architectures > ReAct (Reason + Act)',
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},
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{
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id: 'qwdh5pkBbrF8LKPxbZp4F',
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text: 'AI Agents > Agent Architectures > Common Architectures > Chain of Thought (CoT)',
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},
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{
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id: '6YLCMWzystao6byCYCTPO',
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text: 'AI Agents > Agent Architectures > Common Architectures > Planner Executor',
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},
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{
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id: 'Ep8RoZSy_Iq_zWXlGQLZo',
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text: 'AI Agents > Agent Architectures > Common Architectures > DAG Agents',
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},
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{
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id: 'Nmy1PoB32DcWZnPM8l8jT',
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text: 'AI Agents > Agent Architectures > Common Architectures > Tree-of-Thought',
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},
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{
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id: 'hj1adjkG9nalXKZ-Youn0',
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text: 'AI Agents > Agent Architectures > Common Architectures > Tree-of-Thought',
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},
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{
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id: 'US6T5dXM8IY9V2qZnTOFW',
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text: 'AI Agents > Building Agents > Manual (from scratch)',
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},
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{
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id: 'aafZxtjxiwzJH1lwHBODi',
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text: 'AI Agents > Building Agents > LLM Native "Function Calling"',
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},
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{
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id: 'AQtxTTxmBpfl8BMgJbGzc',
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text: 'AI Agents > Building Agents > LLM Native "Function Calling" > OpenAI Functions Calling',
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},
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{
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id: '37GBFVZ2J2d5r8bd1ViHq',
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text: 'AI Agents > Building Agents > LLM Native "Function Calling" > OpenAI Assistant API',
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},
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{
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id: '_iIsBJTVS6OBf_dsdmbVO',
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text: 'AI Agents > Building Agents > LLM Native "Function Calling" > Gemini Function Calling',
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},
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{
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id: '1EZFbDHA5J5_5BPMLMxXb',
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text: 'AI Agents > Building Agents > LLM Native "Function Calling" > Anthropic Tool Use',
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},
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{
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id: 'Ka6VpCEnqABvwiF9vba7t',
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text: 'AI Agents > Building Agents > Building Using Frameworks > Langchain',
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},
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{
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id: 'iEHF-Jm3ck-Iu85EbCoDi',
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text: 'AI Agents > Building Agents > Building Using Frameworks > LlamaIndex',
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},
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{
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id: 'XS-FsvtrXGZ8DPrwOsnlI',
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text: 'AI Agents > Building Agents > Building Using Frameworks > Haystack',
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},
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{
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id: '7YtnQ9-KIvGPSpDzEDexl',
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text: 'AI Agents > Building Agents > Building Using Frameworks > AutoGen',
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},
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{
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id: 'uFPJqgU4qGvZyxTv-osZA',
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text: 'AI Agents > Building Agents > Building Using Frameworks > CrewAI',
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},
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{
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id: 'eWxQiBrxIUG2JNcrdfIHS',
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text: 'AI Agents > Building Agents > Building Using Frameworks > Smol Depot',
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},
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{
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id: 'v8qLnyFRnEumodBYxQSXQ',
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text: 'AI Agents > Building Agents > Evaluation and Testing > Metrics to Track',
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},
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{
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id: 'qo_O4YAe4-MTP_ZJoXJHR',
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text: 'AI Agents > Evaluation and Testing > Unit Testing for Individual Tools',
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},
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{
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id: 'P9-SiIda3TSjHsfkI5OUV',
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text: 'AI Agents > Evaluation and Testing > Integration Testing for Flows',
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},
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{
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id: 'rHxdxN97ZcU7MPl8L1jzN',
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text: 'AI Agents > Evaluation and Testing > Human in the Loop Evaluation',
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},
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{
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id: 'xp7TCTRE9HP60_rGzTUF6',
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text: 'AI Agents > Evaluation and Testing > Frameworks > LangSmith',
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},
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{
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id: '0924QUH1wV7Mp-Xu0FAhF',
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text: 'AI Agents > Evaluation and Testing > Frameworks > DeepEval',
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},
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{
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id: 'YzEDtGEaMaMWVt0W03HRt',
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text: 'AI Agents > Evaluation and Testing > Frameworks > Ragas',
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},
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{
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id: 'zs6LM8WEnb0ERWpiaQCgc',
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text: 'AI Agents > Debugging and Monitoring > Structured logging & tracing',
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},
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{
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id: 'zs6LM8WEnb0ERWpiaQCgc',
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text: 'AI Agents > Debugging and Monitoring > Structured logging & tracing',
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},
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{
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id: 'SS8mGqf9wfrNqenIWvN8Z',
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text: 'AI Agents > Observability Tools > LangSmith',
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},
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{
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id: 'MLxP5N0Vrmwh-kyvNeGXn',
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text: 'AI Agents > Observability Tools > Helicone',
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},
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{
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id: 'UoIheaJlShiceafrWALEH',
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text: 'AI Agents > Observability Tools > LangFuse',
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},
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{
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id: '7UqPXUzqKYXklnB3x-tsv',
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text: 'AI Agents > Observability Tools > openllmetry',
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},
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{
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id: 'SU2RuicMUo8tiAsQtDI1k',
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text: 'AI Agents > Security & Ethics > Prompt Injection / Jailbreaks',
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},
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{
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id: 'UVzLGXG6K7HQVHmw8ZAv2',
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text: 'AI Agents > Security & Ethics > Tool sandboxing / Permissioning',
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},
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{
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id: 'rdlYBJNNyZUshzsJawME4',
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text: 'AI Agents > Security & Ethics > Data Privacy + PII Redaction',
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},
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{
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id: 'EyLo2j8IQsIK91SKaXkmK',
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text: 'AI Agents > Security & Ethics > Bias & Toxicity Guardrails',
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},
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{
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id: '63nsfJFO1BwjLX_ZVaPFC',
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text: 'AI Agents > Security & Ethics > Safety + Red Team Testing',
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},
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];
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const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
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if (!OPENAI_API_KEY) {
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console.error('OPENAI_API_KEY is not set');
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process.exit(1);
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}
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const openai = new OpenAI({
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apiKey: OPENAI_API_KEY,
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});
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const prompt = `
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You are a helpful assistant that can help me generate content for a roadmap tree.
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You will be given a roadmap topic in the form of "Parent > Child > Leaf". You need
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to generate a single paragraph explaining the topic.
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Also, I hate it when you say "In the realm of..."
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or "In the context of..." or "..in the context of..." or "when we talk about..." or something
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similar.
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IMPORTANT: Use simple and clear English. Avoid complex words and jargon when possible.
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Write in a way that is easy to understand. Use short sentences and common words.
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`;
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/**
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* Generates content for a given node using OpenAI's GPT model
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* @param {Node} node - The node to generate content for
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* @returns {Promise<string>} The generated content
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*/
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const generateContent = async (node) => {
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try {
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const content = await openai.chat.completions.create({
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model: 'o3',
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messages: [
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{ role: 'system', content: prompt },
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{
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role: 'user',
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content: `Node: ${node.text}`,
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},
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],
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});
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return content.choices[0].message.content;
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} catch (error) {
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console.error(
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`Error generating content for node ${node.id}:`,
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error.message,
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);
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throw error;
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}
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};
|
|
|
|
const roadmapContentDir = path.join(
|
|
__dirname,
|
|
`../src/data/roadmaps/${roadmapId}/content`,
|
|
);
|
|
const contentFiles = fs.readdirSync(roadmapContentDir);
|
|
|
|
/**
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* Processes a single node by generating content and writing to file
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* @param {Node} node - The node to process
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* @param {string} roadmapContentDir - Directory path for content files
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* @param {string[]} contentFiles - List of existing content files
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* @returns {Promise<void>}
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*/
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const processNode = async (node, roadmapContentDir, contentFiles) => {
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try {
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const nodeId = node.id;
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const relevantFileName = contentFiles.find((file) =>
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file.endsWith(`${nodeId}.md`),
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);
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if (!relevantFileName) {
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console.warn(`No matching file found for node ${nodeId}`);
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return;
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}
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const fileTitle = node.text
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.replace(/\s+>\s+/g, '>')
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.split('>')
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.pop();
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const content = await generateContent(node);
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const filePath = path.join(roadmapContentDir, relevantFileName);
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await fs.promises.writeFile(filePath, `# ${fileTitle}\n\n${content}`);
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console.log(`Successfully processed node ${nodeId}`);
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} catch (error) {
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console.error(`Failed to process node ${node.id}:`, error.message);
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}
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};
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/**
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* Main function to run the content generation
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* @returns {Promise<void>}
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*/
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const main = async () => {
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try {
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// Process nodes in parallel with concurrency limit
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const BATCH_SIZE = 20; // Adjust based on API rate limits
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for (let i = 0; i < nodes.length; i += BATCH_SIZE) {
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const batch = nodes.slice(i, i + BATCH_SIZE);
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const promises = batch.map((node) =>
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processNode(node, roadmapContentDir, contentFiles),
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);
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await Promise.allSettled(promises);
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// Add a small delay between batches to avoid rate limiting
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if (i + BATCH_SIZE < nodes.length) {
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await new Promise((resolve) => setTimeout(resolve, 1000));
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}
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}
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console.log('Content generation completed');
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} catch (error) {
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console.error('Fatal error in main process:', error);
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process.exit(1);
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}
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};
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// Add error handling for uncaught exceptions
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process.on('uncaughtException', (error) => {
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console.error('Uncaught Exception:', error);
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process.exit(1);
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});
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process.on('unhandledRejection', (error) => {
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console.error('Unhandled Rejection:', error);
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process.exit(1);
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});
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main();
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