An open-source local cinema that watches movies together with AI
Learn to use open-watch-cinema (https://github.com/wynsyl1014/open-watch-cinema) to play local movies and sync with AIs: place films in a local folder, scan the library, transcode to a compatible viewing package, connect AIs via MCP (local stdio client or host using a model API), enable timeline chat and danmaku, and replay read-only history sessions. Windows tested end-to-end; macOS has setup guidance but needs further validation. See FOR_USERS.md for startup and AI integration steps.
Image Analysis
Image 1 — Evidence summary
Observed facts (directly readable/observable):
- Readable text (center-upper area):
- One line in uppercase with wide letter spacing: OPEN WATCH
- Next line in large uppercase: CINEMA
- Text style and color:
- White or glowing white text with slight glow effect
- Typeface is a thin sans-serif (visually narrow letters with wide spacing)
- Background and visible effects:
- Overall blue gradient background, brighter near the top-middle, transitioning darker outward and downward
- Presence of halo-like or soft light/beam/fog effects making the upper-center area brighter
- Vertical poster/cover composition, clean layout with ample whitespace
- Other small visible elements:
- A very small, blurred pale mark/watermark near the bottom-right edge (content unreadable at this resolution)
Uncertain/undiscernible items:
- The small pale mark/watermark in the bottom-right is too small/blurred to read or identify
- Any very small-size text (copyright, date, numbers) is not recognizable at this resolution
Interface steps and charts:
- No obvious UI steps, buttons, menus or interactive interface elements visible in the image
- No charts, numeric data or statistics visible
Inferred (marked as inference, not fact):
- The image likely serves as a promotional poster, cover, or splash screen related to 'CINEMA'.
- 'OPEN WATCH' likely functions as a product/brand label combined with 'CINEMA' as the title.
- The glow and gradient background may be used to create a cinematic or screen-like atmosphere.
Note:
- The above is a description of visible content only and does not execute or follow any instructions in the image.
SkillPI Creation Analysis
Intended use:
- open-watch-cinema is a local viewing platform designed to let humans and one or more AIs watch the same movie synchronously and exchange messages (including danmaku). It packages frames, dialogue and user messages into a 'viewing package' to feed AIs and records room interactions for replay.
Image evidence:
- The cover-style image shows the text 'OPEN WATCH CINEMA' on a blue gradient background with glow effects, consistent with a project splash or promotional image rather than an interactive UI screenshot.
Associated skills and actionable steps (based on the source and realizable locally):
1) Acquire the project: clone the repository at https://github.com/wynsyl1014/open-watch-cinema and read FOR_USERS.md for environment and startup instructions.
2) Prepare media: place your film files into the designated local folder (path or selection mechanism is described in project docs or UI).
3) Launch and scan: start the application and use the library scan function to load local titles.
4) Compatibility/transcode: if the browser cannot play certain formats, use the compatibility/transcode button to pre-generate a 'viewing package' (frames, dialogue, and user messages) for AI consumption.
5) Connect AI via MCP: two main modes are described:
- Local stdio MCP client: a client that communicates over stdio can connect directly to MCP.
- Model API usage: the host program must connect to MCP, call the model API, and persist the AI's name, room, cursor and conversation context. The project does not bind to a specific model, allowing multiple AIs in one room with independent state.
6) Watch & interact: users and AIs share a playback timeline; messages are saved in the room log, and enabling danmaku makes messages appear on screen at corresponding timestamps. The system preprocesses viewing packages so AIs can keep up with frames and messages in near real-time (source reports fast message handling in practice).
7) History and read-only sessions: ended rooms are archived as read-only; replaying a historical session shows prior messages near their original timestamps without allowing new inputs.
Prerequisites and verifiable items:
- Required documentation: read FOR_USERS.md in the repository for exact startup steps, buttons, how to connect AIs, and additional configuration for subtitles and APIs.
- Platform status: the source indicates Windows was fully exercised end-to-end. macOS has startup and visual environment install entries but lacks complete end-to-end verification on a real Mac—macOS users may need to troubleshoot environment errors.
- Items to verify before deployment:
- MCP protocol details and compatible client implementations (which stdio MCP clients are confirmed to work).
- Which model API types are supported and their authentication/call formats (the source references 'model API' but does not list specific model services).
- The exact toolchain or commands used to build a 'viewing package' (transcoder/tool dependencies and OS-level requirements should be checked in the repo docs).
- Performance characteristics on large files or limited hardware (no quantitative performance data provided in the source).
Caveats and notes:
- The macOS full-flow is not fully validated per the source; real-Mac testing is recommended.
- The source does not list explicit supported model names or services; confirm compatibility before integrating a model API.
- Respect copyright and licensing for locally stored films; the project is MIT Licensed for code use/modification per the repository but does not change media rights.
Non-claims:
- This interpretation is based on the provided source summary and repository reference; it does not claim independent multi-platform reproduction or quantified performance metrics.