ponzischeme89
101 lines
2.2 KiB
Markdown
101 lines
2.2 KiB
Markdown
# Sublogue
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Sublogue is a lightweight tool for adding plot summaries and metadata to subtitle files.
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It takes an existing .srt, pulls data from OMDb, TMDb, and TVMaze, and inserts a short plot block at the start of the file — without altering any existing timings or dialogue.
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If you’ve ever opened a movie or episode and thought “wait… what was this again?”, Sublogue quietly solves that.
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## Features
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- Inserts a plot summary at the beginning of an existing `.srt`
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- Automatically fetches metadata (OMDb, TMDb, TVMaze fallback)
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- Never alters existing dialogue timing
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- Handles long plots without breaking readability
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- Clean web UI (Svelte + Vite)
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- Fast Python backend (Flask + aiohttp)
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- Docker image available through GHCR
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## Deployment
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<details>
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<summary>Docker Compose</summary>
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Create `data/` and `media/` folders next to the compose file, then run:
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```yaml
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version: "3.9"
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services:
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sublogue:
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image: ponzischeme89/sublogue:latest
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container_name: sublogue
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restart: unless-stopped
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environment:
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- TZ=Etc/UTC
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- PUID=1000
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- PGID=1000
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volumes:
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- ./data:/config
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- ./media:/media
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ports:
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- "5000:5000"
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```
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Then start it with:
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```bash
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docker compose up -d
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```
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</details>
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<details>
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<summary>Unraid</summary>
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Sublogue includes an Unraid template at `unraid-sublogue.xml`. Import it in Unraid's Docker UI, then map:
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- `/mnt/user/appdata/sublogue` -> `/config`
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- `/mnt/user/appdata/sublogue/media` -> `/media`
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Start the container and open `http://<UNRAID-IP>:5000`.
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</details>
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<details>
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<summary>Komodo</summary>
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Create a new stack in Komodo and paste a template like this (example format below):
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```yaml
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version: "3.9"
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services:
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shelfarr:
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image: ghcr.io/ponzischeme89/sublogue:latest
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container_name: sublogue
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ports:
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- "5055:5055"
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environment:
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- TZ=Pacific/Auckland
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- PORT=5055
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volumes:
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- /volume1/Docker/sublogue/data:/data
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- /share/subtitles:/audiobooks
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restart: unless-stopped
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networks:
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- npm_network
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networks:
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npm_network:
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external: true
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```
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</details>
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## Acknowledgements
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- Svelte for the frontend UI.
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- Flask for the backend API.
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- asyncio for async metadata fetching.
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