https://github.com/jbilcke-hf/ai-tube-clap-exporter

API service used to convert a .clap file (complete will all its assets) to a video file
https://github.com/jbilcke-hf/ai-tube-clap-exporter

ai-cinema ai-exchange-file-format ai-filmmaking ai-filmmaking-file-format ai-movie-industry ai-movie-standard ai-tool-interoperability aitube clap-file-format openclap

Last synced: 2 months ago
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API service used to convert a .clap file (complete will all its assets) to a video file

• Host: GitHub
• URL: https://github.com/jbilcke-hf/ai-tube-clap-exporter
• Owner: jbilcke-hf
• License: apache-2.0
• Created: 2024-04-24T15:30:09.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-07-24T14:34:03.000Z (6 months ago)
• Last Synced: 2024-07-24T16:55:20.520Z (6 months ago)
• Topics: ai-cinema, ai-exchange-file-format, ai-filmmaking, ai-filmmaking-file-format, ai-movie-industry, ai-movie-standard, ai-tool-interoperability, aitube, clap-file-format, openclap
• Language: TypeScript
• Homepage: https://aitube.at
• Size: 521 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
---

title: AI Tube Clap Exporter API

emoji: 🍿🤖

colorFrom: red

colorTo: blue

sdk: docker

pinned: false

app_port: 3000

---

Export a full .clap (with all its assets already in) to a video

# Installation

It is important that you make sure to use the correct version of Node (Node 20)

1. `nvm use`

2. `npm i`

3. clone `.env` to `.env.local`

4. edit `.env.local` to define the secrets / api access keys

5. `npm run start`

# Testing the Docker image

Note: you need to install Docker, and it needs to be already running.

You will also need to build it for *your* architecture.

```bash

docker build --platform linux/arm64 -t ai-tube-clap-exporter .

docker run -it -p 7860:7860 ai-tube-clap-exporter

```

# Architecture

AI Channels are just Hugging Face datasets.

For now, we keep everything into one big JSON index, but don't worry we can migrate this to something more efficient, such as Redis (eg. using Upstash for convenience).