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Gramps
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# Directory Layout
This page describes the structure of the Llama Chile Shop video automation project as implemented on the NAS mount (`Z:\`). This layout ensures a predictable, scalable structure for stream session content and pipeline assets.
## Root Structure (`Z:\`)
```
Z:\
├── YYYY.MM.DD/ # Session folder (e.g., 2025.06.20)
│ ├── hits/ # Raw clips of eliminations
│ ├── misses/ # Raw clips of deaths
│ ├── montages/ # Precompiled montage reels
│ ├── outtakes/ # Manually tagged moments for postprocessing
│ └── rendered/ # Final output videos (1:1 clip-to-video mapping)
├── assets/ # Branding assets
│ ├── intro-wide.mp4
│ ├── intro-vertical.mp4
│ ├── outro-wide.mp4
│ ├── outro-vertical.mp4
│ ├── BurbankBigCondensed-Black.otf # Fortnite font
│ └── LlamaLlama.png
├── modules/ # Helper modules (Python)
├── logs/ # Diagnostic/debug output
├── .env # API credentials (loaded via dotenv)
├── main.py # Main pipeline for daily clip automation
├── upload_youtube_montage.py # Standalone test harness for YouTube flow
├── README.md
```
## Naming Conventions
* Session folders follow: `YYYY.MM.DD` or `YYYY.MM.DD.N`
* Rendered videos retain input name, with `-vert` or `-vertical` denoting vertical orientation
* All `notes.*` files in subfolders are used to seed OpenAI-based descriptions (except for `montages/`, which has none)
## Example
Given a stream session folder `Z:\2025.07.04`:
```
Z:\2025.07.04
├── montages\
│ └── Fortnite-montage-20250704.mp4
├── hits\
│ └── 001_hit.mp4
│ └── 001_hit_notes.txt
├── rendered\
│ └── Fortnite-montage-20250704.mp4
```
This structure allows the pipeline to:
1. Detect input type
2. Generate and overlay titles
3. Call OpenAI if a `notes.*` file is present
4. Upload to YouTube/PeerTube as applicable
5. Optionally toot/post to social media
---
Next: [[Module Index](https://chatgpt.com/c/687fcbf3-b2b4-8010-911e-601ae3b70980#)](#)