Workflow on Ghafoor's Personal Blog

Step-by-Step Vocabulary Extraction Guide

noreply@example.com (AG Sayyed) — Fri, 08 May 2026 00:00:00 +0000

Dictionary Vocabulary Extraction - Step-by-Step Guide

🚨 IMPORTANT: Environment Setup

For AI Agents / Automated Commands

Before running any Python-based transcript extraction commands, you MUST:

Run conda-bash alias to ensure python commands work in scripts
Once python profile is read, base environment will be activated. Now you can run the conda commands, then you can activate ags-dictionary environment

Activate conda bash profile:

1source ~/miniconda3/etc/profile.d/conda.sh

Activate the Python environment:
```
1conda activate ags-dictionary
```
Then run your commands:

Workflows

noreply@example.com (AG Sayyed) — Fri, 08 May 2026 00:00:00 +0000

Workflows

Complete step-by-step processes for extracting and managing vocabulary.

📖 Documentation in This Section

Step-by-Step Guide ⭐ START HERE - Complete 7-step workflow with detailed explanations
Quick Reference - Quick command reference
Copilot Integration - Using Copilot for vocabulary extraction

🎯 Main Workflow: Video to Vocabulary

The 7-Step Process

Extract Transcript - Automated YouTube transcript download
Extract Vocabulary - Use Copilot to find challenging words
Save YAML File - Store vocabulary data
Validate YAML - Ensure proper formatting
Create Hugo Page - Generate content page
Test Locally - View and verify in browser
Review & Commit - Final check and git commit

⚡ Quick Start Workflow

1# Step 1: Extract transcript
2./scripts/dictionary/dict-step1-transcript.sh "https://youtube.com/watch?v=VIDEO_ID" topic_name
3
4# Step 2: Use Copilot (manual process - see guide)
5# Copy transcript and use the Copilot prompt
6
7# Step 3-7: Follow the Step-by-Step Guide

📚 Different Paths

For Content Creators

Read Step-by-Step Guide
Follow each step in order
Use Quick Reference for commands

For Developers

Read Step-by-Step Guide for overview
Check Copilot Integration for AI setup
Review Quick Reference for commands

For Automation Users

Refer to Quick Reference for all commands
Use scripts/dictionary/dict-step1-transcript.sh for automation
See Copilot Integration for AI setup

Getting Started - Setup instructions
Guides - Detailed how-to guides
Reference - Technical reference

Dictionary Workflow Improvements - Implementation Summary

noreply@example.com (AG Sayyed) — Tue, 05 May 2026 00:00:00 +0000

Dictionary Workflow Improvements - Summary

✅ What’s Been Done

I’ve analyzed your dictionary system and created a comprehensive automation workflow for extracting vocabulary from videos. Here’s what’s now available:

📚 New Documentation (4 files)

workflow-improvements.md
- Complete analysis of current system
- Proposed multi-stage automation pipeline
- Enhanced data structure with video metadata
- Implementation phases (MVP → Semi-automated → Fully automated)
- LLM integration strategy
- Time savings: From 2-4 hours → 15-30 minutes per video
video-to-vocab-howto.md

Dictionary Workflow Improvements - Video to Vocabulary Automation

noreply@example.com (AG Sayyed) — Tue, 05 May 2026 00:00:00 +0000

Dictionary Workflow Improvements

📊 Current State Analysis

✅ Strengths

Well-structured data model: YAML format is clean and maintainable
Dual rendering options: Accordion and table views work well
Good separation of concerns: Data (YAML) separate from presentation (Hugo shortcodes)
Urdu support: Font and RTL text handling is solid
Documentation: Comprehensive guides exist

❌ Pain Points

Manual vocabulary extraction: No automated way to extract words from videos
Time-consuming data entry: Each word requires multiple fields to be filled manually
No video metadata tracking: Source video links not tracked in data structure
Missing translation support: No automated English-to-Urdu translation
No difficulty assessment: Can’t automatically identify “difficult” words
No batch processing: Can’t handle multiple videos at once

🎯 Proposed Improvements

1. Enhanced Data Structure

Update YAML schema to include video metadata:

Agents Revisited

noreply@example.com (AG Sayyed) — Tue, 29 Jul 2025 00:00:00 +0000

This document provides a clear, practical overview of AI agents, explaining their core functions, how they differ from general AI, their workflow, and the massive impact they are expected to have on business and daily life. Readers will understand the agent paradigm and its real-world applications.

Introduction

AI agents are poised to become as ubiquitous as apps, with the potential for billions of agents operating worldwide. These digital assistants are expected to outnumber people and transform industries by automating tasks and enabling new skills.

Anki Workflow Verification

noreply@example.com (AG Sayyed) — Mon, 01 Jan 0001 00:00:00 +0000

Anki Workflow Verification

Date: 2 May 2026
Status: ✅ Verified and Working

Current Working Workflow

1. Card Creation (Manual)

JSON files are manually created in: data/course/{course}/{unit}/{module}/{lesson}/anki/*.json
Each JSON contains metadata + flashcards array
Example: data/course/psychology-l2/01/01m/001/anki/01-counselling-skills.json

2. Card Generation (Automatic)

JSON File → apkg_generator.py → .apkg Package → Anki Desktop

Key Scripts:

✅ apkg_generator.py - Main generator (reads JSON, creates APKG)
✅ generate_unit_apkg.py - Creates unit-level APKG files
✅ rebuild_all_apkgs.py - Rebuilds all APKG files

NOT Used in Production:

Workflow on Ghafoor's Personal Blog

Step-by-Step Vocabulary Extraction Guide

Dictionary Vocabulary Extraction - Step-by-Step Guide

🚨 IMPORTANT: Environment Setup

For AI Agents / Automated Commands

Workflows

Workflows

📖 Documentation in This Section

🎯 Main Workflow: Video to Vocabulary

The 7-Step Process

⚡ Quick Start Workflow

📚 Different Paths

For Content Creators

For Developers

For Automation Users

🔗 Related Sections

Dictionary Workflow Improvements - Implementation Summary

Dictionary Workflow Improvements - Summary

✅ What’s Been Done

📚 New Documentation (4 files)

Dictionary Workflow Improvements - Video to Vocabulary Automation

Dictionary Workflow Improvements

📊 Current State Analysis

✅ Strengths

❌ Pain Points

🎯 Proposed Improvements

1. Enhanced Data Structure

Agents Revisited

Introduction

Anki Workflow Verification

Anki Workflow Verification

Current Working Workflow

1. Card Creation (Manual)

2. Card Generation (Automatic)