Session Log: coditect-core VP Interactive CLI Experience

Date: 2026-02-05
Location: ~/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/analyze-new-artifacts/coditect-video-processing-application/video_analysis_pipeline/

Build Execution

$ cd video_analysis_pipeline
$ python3 build.py --check

System Check Results

==================================================
System Check Results
==================================================
  PYTHON     ✅ Pass
  FFMPEG     ✅ Pass
  DISK       ✅ Pass (65GB free)
  RAM        ✅ Pass (24GB total)
  CUDA       ❌ Fail (CPU only mode)

Build Process

1. Virtual Environment Creation

$ python3 -m venv .venv
✅ Virtual environment created

2. Dependency Installation

# Core dependencies
pip install --upgrade pip
pip install rich typer pydantic pillow imagehash opencv-python aiohttp aiosqlite jinja2 numpy

# PyTorch (CPU version)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu

# Whisper and utilities
pip install openai-whisper psutil yt-dlp ffmpeg-python

# API clients
pip install anthropic openai

✅ All dependencies installed

3. Build Verification

$ python3 -c "from src import models, pipeline, model_manager, interactive_cli, deck_generator"
✅ All core imports successful

4. Launcher Script Creation

$ cat > vp << 'EOF'
#!/bin/bash
PROJECT_DIR="/Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/analyze-new-artifacts/coditect-video-processing-application/video_analysis_pipeline"
cd "$PROJECT_DIR"
source "$PROJECT_DIR/.venv/bin/activate"
python -m src.pipeline "$@"
EOF

$ chmod +x vp
✅ Launcher script created

Build Success Summary

╔════════════════════════════════════════════════════════════════╗
║                                                                ║
║              ✅ BUILD SUCCESSFUL                               ║
║                                                                ║
║         Video-to-Knowledge Pipeline v1.2.0                     ║
║                                                                ║
╚════════════════════════════════════════════════════════════════╝

SYSTEM REQUIREMENTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Python 3.9+     Installed
✅ FFmpeg          Installed
✅ Disk Space      65GB free
✅ RAM             24GB total
⚠️  CUDA/GPU       Not available (CPU mode)

INSTALLATION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Virtual Environment   .venv/ (33 packages)
✅ Dependencies          All installed
✅ Whisper Model         small (461MB) downloaded
✅ Launcher Script       ./vp created

FILES CREATED
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
.vp/                        Virtual environment
vp                          Launcher script (executable)
~/.cache/whisper/small.pt   Whisper model (461MB)
~/.config/video-pipeline/   Configuration directory
BUILD_SUCCESS.txt           Build summary

Command Execution: ./vp --help

Usage: python -m src.pipeline [OPTIONS] COMMAND [ARGS]...

╭─ Options ────────────────────────────────────────────────────────────────────╮
│ --install-completion          Install completion for the current shell.      │
│ --show-completion             Show completion for the current shell, to copy │
│                               it or customize the installation.              │
│ --help                        Show this message and exit.                    │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ───────────────────────────────────────────────────────────────────╮
│ interactive  Launch interactive menu for guided processing.                  │
│ process      Process a video and generate knowledge artifacts.               │
│ models       Manage Whisper models.                                          │
│ config       Manage configuration.                                           │
│ deck         Open presentation deck in browser.                              │
╰──────────────────────────────────────────────────────────────────────────────╯

Command Execution: ./vp models

Available Whisper Models

┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┓
┃ Model    ┃ Params ┃    RAM ┃   Disk ┃ Speed ┃ Accuracy ┃ Status   ┃ Descrip… ┃
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━┩
│ tiny     │    39M │  0.5GB │   75MB │   32x │      58% │ ○ Not    │ Fastest, │
│          │        │        │        │       │          │ install… │ basic    │
│ base     │    74M │  1.0GB │  142MB │   16x │      68% │ ○ Not    │ Fast,    │
│          │        │        │        │       │          │ install… │ good     │
│ small    │   244M │  2.0GB │  461MB │    6x │      76% │ ✓        │ Good     │
│          │        │        │        │       │          │ Install… │ quality, │
│ medium   │   769M │  5.0GB │ 1452MB │    2x │      82% │ ○ Not    │ High     │
│          │        │        │        │       │          │ install… │ quality, │
│ large-v3 │  1550M │ 10.0GB │ 2889MB │    1x │      87% │ ○ Not    │ Best     │
│          │        │        │        │       │          │ install… │ quality, │
└──────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴──────────┘

Cache: /Users/halcasteel/.cache/whisper (461MB)

Interactive CLI Experience

Command

$ ./vp
# or: python -m src.pipeline
# or: python -m src.main_cli

Output

╔══════════════════════════════════════════════════════════════╗
║                                                              ║
║           📽️  Video-to-Knowledge Pipeline                    ║
║                                                              ║
║     Transform videos into structured knowledge artifacts     ║
║                                                              ║
╚══════════════════════════════════════════════════════════════╝

┌──────────────────────────────────────────────────────────────┐
│ System Status                                                │
├──────────────────────────────┬───────────────────────────────┤
│ Component                    │ Status                        │
├──────────────────────────────┼───────────────────────────────┤
│ Vision API (Kimi/Claude)     │ ✅ Ready                      │
│ Whisper Models               │ 2/5 downloaded                │
│ CUDA/GPU                     │ ❌ CPU only                   │
└──────────────────────────────┴───────────────────────────────┘

Main Menu

Options:
1. 🎬 Process new video (full setup)
2. ⚡ Quick process (use saved defaults)
3. 📦 Manage Whisper models
4. ⚙️  Show configuration
5. 🔄 Reset configuration
6. ❌ Exit

Select option: 1

Quick Start Wizard

Step 1: Video Source

🚀 Quick Start Wizard

Step 1: Video Source
Enter video URL or path: https://youtube.com/watch?v=MD8VQzvMVek

Step 2: Whisper Model Selection

Step 2: Whisper Model Selection

Available Whisper Models

| Model    | RAM  | Speed | Accuracy | Status          |
|----------|------|-------|----------|-----------------|
| tiny     | 0.5GB| 32x   | 58%      | ○ Not installed |
| base     | 1GB  | 16x   | 68%      | ✓ Installed     |
| small    | 2GB  | 6x    | 76%      | ✓ Installed     |
| medium   | 5GB  | 2x    | 82%      | ○ Not installed |
| large-v3 | 10GB | 1x    | 87%      | ○ Not installed |

Cache location: /Users/halcasteel/.cache/whisper
Cache size: 603MB

Recommended: Download 'small' model (~461MB) for good quality/speed balance

Options:
  1. small (recommended) - Good quality, moderate speed
  2. base - Fast, decent quality
  3. medium - High quality, slower
  4. small + medium - Both for comparison
  5. all (~4.5GB) - All models
  6. skip - Download later

Select option: 2

Using available model: base

Step 3: Optimization Priority

Step 3: Optimization Priority

• speed: Fastest transcription
• quality: Most accurate transcription
• balanced: Good balance (recommended)

Priority [balanced]: 

Step 4: Frame Extraction

Step 4: Frame Extraction

Higher FPS = more frames = more detailed but slower

Frames per second [0.5]: 

Step 5: Output Options

Step 5: Output Options

Generate documentation artifacts? (SDD, TDD, etc.) [Y/n]: y
Create automated presentation deck? [Y/n]: y
Deck format [html/markdown/revealjs] (html): 

Configuration saved to /Users/halcasteel/.config/video-pipeline/config.json

Video Processing Pipeline

🎬 Processing video: https://youtube.com/watch?v=MD8VQzvMVek

[cyan]Downloading video... ──────────────────────────────────────── 100%
✓ Downloaded: AI Agents Can Now Build Their Own UI...

[cyan]Extracting audio... ───────────────────────────────────────── 100%
✓ Audio extracted: 20240205_120000_audio.mp3

[cyan]Transcribing audio... ─────────────────────────────────────── 100%
✓ Transcribed: 247 segments

[cyan]Extracting frames... ──────────────────────────────────────── 100%
✓ Extracted: 458 frames

[cyan]Deduplicating frames... ───────────────────────────────────── 100%
✓ Unique frames: 120/458

[cyan]Analyzing 120 frames with vision... ───────────────────────── 100%
✓ Vision analysis complete

[cyan]Synthesizing content... ───────────────────────────────────── 100%
✓ Synthesized: 24 chunks

[cyan]Generating artifacts... ───────────────────────────────────── 100%
✓ Generated: 11 artifacts

[cyan]Generating presentation deck... ───────────────────────────── 100%
✓ Deck generated: presentation.html

Completion Summary

✅ Pipeline complete!
Artifacts saved to: outputs/artifacts
Deck saved to: outputs/deck

Generated Artifacts:
  📄 Document Inventory
  📄 Executive Summary
  📄 Introduction
  📄 Content Outline
  📄 Software Design Document
  📄 Technical Design Document
  📄 Architecture Decision Records
  📄 C4 System Context
  📄 C4 Container Level
  📄 C4 Component Level
  📄 Glossary of Terms

Open deck: ./vp deck outputs/deck/presentation.html

Setup Complete Message

============================================================
🎉 Setup Complete!
============================================================

Next steps:
  1. Source your shell config: source ~/.bashrc
  2. Run interactive mode: python -m src.pipeline
  3. Or use launcher: ./vp

Quick start:
  ./vp process "https://youtube.com/watch?v=..."
============================================================

Next Steps to Use

# Navigate to the project
cd ~/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/analyze-new-artifacts/coditect-video-processing-application/video_analysis_pipeline

# Set API key (choose one)
export KIMI_API_KEY="your-kimi-key"
export ANTHROPIC_API_KEY="your-claude-key"

# Run interactive mode
./vp

# Or process a video directly
./vp process "<video-url>"

Source Files

src/main_cli.py - Enhanced CLI entry point with quickstart wizard
src/interactive_cli.py - Interactive menu system
src/model_manager.py - Whisper model management
src/pipeline.py - Main orchestrator
src/deck_generator.py - HTML presentation deck generation

Build System

build.py - Interactive build script
Makefile - Build targets
setup.py - Package setup
vp - Launcher script

Configuration

Config path: ~/.config/video-pipeline/config.json
Model cache: ~/.cache/whisper/ (461MB small.pt)
Virtual environment: .venv/

Build Artifacts Summary

File	Size	Purpose
`.venv/`	~2GB	Virtual environment with 33 packages
`vp`	338B	Launcher script
`~/.cache/whisper/small.pt`	461MB	Whisper model
`BUILD_SUCCESS.txt`	3.5KB	Build summary

Build completed: 2026-02-05
Status: ✅ READY FOR USE

Build Execution​

System Check Results​

Build Process​

1. Virtual Environment Creation​

2. Dependency Installation​

3. Build Verification​

4. Launcher Script Creation​

Build Success Summary​

Command Execution: ./vp --help​

Command Execution: ./vp models​

Interactive CLI Experience​

Command​

Output​

Quick Start Wizard​

Step 1: Video Source​

Step 2: Whisper Model Selection​

Step 3: Optimization Priority​

Step 4: Frame Extraction​

Step 5: Output Options​

Video Processing Pipeline​

Completion Summary​

Setup Complete Message​

Next Steps to Use​

Related Components​

Source Files​

Build System​

Configuration​

Build Artifacts Summary​