Updated Architecture Overview (markdown)
Gramps
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# Architecture Overview
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<!--StartFragment--><html><head></head><body><h2>🧱 Architecture Overview</h2>
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<p>This page provides a high-level technical map of the LCS Pipeline — from input detection to final video upload. It outlines how the system is structured, modularized, and designed for hands-free content generation.</p>
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<hr>
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<h3>🎯 Primary Goal</h3>
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<p>To automate livestream clip creation, formatting, titling, thumbnail generation, and publishing across multiple platforms with minimal user input.</p>
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<hr>
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<h3>🗂️ Core Workflow (Pipeline Phases)</h3>
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<ol>
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<li>
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<p><strong>Session Discovery</strong><br>
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Scans for new <code inline="">YYYY.MM.DD</code> folders on startup. Multiple sessions per day supported (<code inline="">.2</code>, <code inline="">.3</code>, etc.).</p>
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</li>
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<li>
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<p><strong>Clip Classification</strong><br>
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Reads each subfolder (<code inline="">hits/</code>, <code inline="">misses/</code>, <code inline="">montages/</code>, etc.) and classifies by:</p>
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<ul>
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<li>
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<p>Folder name</p>
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</li>
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<p>Filename suffix (<code inline="">-vert</code> for vertical)</p>
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</li>
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</ul>
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</li>
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<li>
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<p><strong>Metadata Injection</strong><br>
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Loads <code inline="">notes.json</code> (if present) or prompts user for:</p>
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<ul>
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<li>
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<p><code inline="">highlight</code> (required)</p>
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</li>
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<li>
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<p><code inline="">tags</code>, <code inline="">gag_name</code> (optional)</p>
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</li>
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</ul>
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</li>
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<li>
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<p><strong>Title + Description Generation</strong><br>
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Uses OpenAI to create:</p>
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<p>Dynamic video titles (based on folder + metadata)</p>
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</li>
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<li>
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<p>Social-ready video descriptions</p>
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</li>
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</ul>
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</li>
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<li>
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<p><strong>Intro/Outro Assembly</strong></p>
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<p>Concatenates intro + title card + clip + outro</p>
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</li>
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<p>Uses branding assets in <code inline="">assets/</code></p>
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</li>
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</ul>
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<p><strong>Thumbnail Generation</strong><br>
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Creates stylized Fortnite-style thumbnails under 2MB</p>
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</li>
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<p><strong>Upload</strong></p>
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<p>Vertical → YouTube Shorts</p>
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<p>Widescreen → YouTube Clips (and PeerTube, if enabled)</p>
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</li>
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</ul>
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</li>
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<li>
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<p><strong>Archive & Cleanup</strong></p>
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<p>Metadata written to <code inline="">metadata/history/<date>/<slug>.json</code></p>
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<p>Original clip folder optionally deleted (unless <code inline="">DEBUG=True</code>)</p>
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</li>
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</ul>
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</li>
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</ol>
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<hr>
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<h3>📁 Key Components</h3>
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This page provides an overview of the internal structure of the LCS Pipeline.
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Module | Role
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-- | --
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main.py | Pipeline launcher and orchestrator
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render_engine.py | Handles stitching + export
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title_utils.py | Generates title screens
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yt_poster.py | YouTube upload logic
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pt_poster.py | PeerTube upload logic (optional)
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thumbnail_utils.py | Builds and validates thumbnails
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metadata_utils.py | Normalizes and stores clip metadata
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## Modules
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- `main.py`: Central orchestration logic
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- `modules/`: Reusable utilities for title cards, thumbnails, uploads
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- `assets/`: Contains branding videos and fonts
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## Flow
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<hr>
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1. Detect new video sessions
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<h3>📦 Folder Independence</h3>
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2. Generate metadata, titles, overlays
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<p>Each session folder is processed atomically — no cross-folder dependencies.</p>
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3. Render videos with intro/title/outro
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<ul>
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4. Upload to YouTube and optionally PeerTube
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5. Auto-publish wiki and social metadata
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<p>Safe to rerun on failed or partially processed sessions</p>
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<p>Idempotent if <code inline="">rendered/</code> and history already exist</p>
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</li>
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</ul>
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<hr>
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<h3>🔧 Exception Paths</h3>
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<ul>
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<li>
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<p><code inline="">timelapses/</code> are handled via custom renderer (future logic)</p>
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</li>
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<li>
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<p><code inline="">outtakes/</code> require manual metadata and never auto-upload</p>
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</li>
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</ul>
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<hr>
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<p>See also: <a href="https://chatgpt.com/c/Clip-Handling-Logic"><code inline="">Clip Handling Logic</code></a>, <a href="https://chatgpt.com/c/File-Naming-&-Directory-Conventions"><code inline="">File Naming</code></a>, <a href="https://chatgpt.com/c/Metadata-Extraction"><code inline="">Metadata Extraction</code></a></p></body></html><!--EndFragment-->
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</body>
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</html>## 🧱 Architecture Overview
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This page provides a high-level technical map of the LCS Pipeline — from input detection to final video upload. It outlines how the system is structured, modularized, and designed for hands-free content generation.
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---
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### 🎯 Primary Goal
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To automate livestream clip creation, formatting, titling, thumbnail generation, and publishing across multiple platforms with minimal user input.
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---
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### 🗂️ Core Workflow (Pipeline Phases)
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|
|
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1. **Session Discovery**
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Scans for new `YYYY.MM.DD` folders on startup. Multiple sessions per day supported (`.2`, `.3`, etc.).
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2. **Clip Classification**
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Reads each subfolder (`hits/`, `misses/`, `montages/`, etc.) and classifies by:
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* Folder name
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* Filename suffix (`-vert` for vertical)
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3. **Metadata Injection**
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Loads `notes.json` (if present) or prompts user for:
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|
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* `highlight` (required)
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* `tags`, `gag_name` (optional)
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4. **Title + Description Generation**
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Uses OpenAI to create:
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* Dynamic video titles (based on folder + metadata)
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* Social-ready video descriptions
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5. **Intro/Outro Assembly**
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* Concatenates intro + title card + clip + outro
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* Uses branding assets in `assets/`
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6. **Thumbnail Generation**
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Creates stylized Fortnite-style thumbnails under 2MB
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7. **Upload**
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* Vertical → YouTube Shorts
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* Widescreen → YouTube Clips (and PeerTube, if enabled)
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8. **Archive & Cleanup**
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* Metadata written to `metadata/history/<date>/<slug>.json`
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* Original clip folder optionally deleted (unless `DEBUG=True`)
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---
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### 📁 Key Components
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| Module | Role |
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| -------------------- | ----------------------------------- |
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| `main.py` | Pipeline launcher and orchestrator |
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| `render_engine.py` | Handles stitching + export |
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| `title_utils.py` | Generates title screens |
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| `yt_poster.py` | YouTube upload logic |
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| `pt_poster.py` | PeerTube upload logic (optional) |
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| `thumbnail_utils.py` | Builds and validates thumbnails |
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| `metadata_utils.py` | Normalizes and stores clip metadata |
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---
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### 📦 Folder Independence
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||||||
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Each session folder is processed atomically — no cross-folder dependencies.
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||||||
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|
||||||
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* Safe to rerun on failed or partially processed sessions
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* Idempotent if `rendered/` and history already exist
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---
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### 🔧 Exception Paths
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* `timelapses/` are handled via custom renderer (future logic)
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* `outtakes/` require manual metadata and never auto-upload
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---
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See also: [`[Clip Handling Logic](https://chatgpt.com/c/Clip-Handling-Logic)`](./Clip-Handling-Logic), [`[File Naming](https://chatgpt.com/c/File-Naming-&-Directory-Conventions)`](./File-Naming-&-Directory-Conventions), [`[Metadata Extraction](https://chatgpt.com/c/Metadata-Extraction)`](./Metadata-Extraction)
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Reference in New Issue
Block a user